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\n \n\n \n \n \n \n \n Association Between Vascular NOTCH3 Aggregation and Disease Severity in a CADASIL Cohort - Implications for NOTCH3 Variant-Specific Disease Prediction.\n \n \n \n\n\n \n Cerfontaine, M. N.; Gravesteijn, G.; Hack, R. J.; Dijkstra, K. L.; Rodríguez-Girondo, M.; Gesierich, B.; Witjes-Ané, M. W.; van Doorn, R.; Duering, M.; Rutten, J. W.; and Lesnik Oberstein, S. A. J.\n\n\n \n\n\n\n Ann Neurol. April 2025.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{cerfontaine_association_2025,\n\ttitle = {Association {Between} {Vascular} {NOTCH3} {Aggregation} and {Disease} {Severity} in a {CADASIL} {Cohort} - {Implications} for {NOTCH3} {Variant}-{Specific} {Disease} {Prediction}},\n\tissn = {1531-8249},\n\tdoi = {10.1002/ana.27240},\n\tabstract = {OBJECTIVE: Vascular NOTCH3 protein ectodomain aggregation is a pathological hallmark of cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL), a monogenic small vessel disease typically caused by cysteine-altering variants in NOTCH3. Given their high population frequency, these NOTCH3 variants are an important genetic contributor to stroke and vascular dementia worldwide. Disease severity in CADASIL is highly variable and is mainly determined by the position of the pathogenic NOTCH3 variant in the NOTCH3 ectodomain. Here, we aimed to investigate the association between NOTCH3 aggregation load in skin vessels, cysteine-altering NOTCH3 variants, and disease severity in a prospective cohort study of 212 patients with CADASIL with 39 distinct cysteine-altering NOTCH3 variants.\nMETHODS: NOTCH3 aggregation load in skin vessels was determined by calculating the NOTCH3 score; the fraction of skin vessel wall area positive for NOTCH3 staining. Variant-specific NOTCH3 scores were calculated for variants present in 10 or more participants, by averaging the NOTCH3 scores of individuals with that distinct variant. The associations between the NOTCH3 score, NOTCH3 variants, and neuroimaging and clinical outcomes were investigated using multivariable linear mixed models, Cox regression, and mediation analyses.\nRESULTS: The NOTCH3 score was significantly associated with lifetime stroke probability and small vessel disease neuroimaging outcomes, but not with age. Variant-specific NOTCH3 scores reflected differences in disease severity associated with distinct NOTCH3 variants.\nINTERPRETATION: These findings suggest that differences in NOTCH3 aggregation propensity underlie the differences in disease severity associated with NOTCH3 cysteine-altering variants, and show that NOTCH3-variant specific NOTCH3 scores can contribute to improved individualized disease prediction in CADASIL. ANN NEUROL 2025.},\n\tlanguage = {eng},\n\tjournal = {Ann Neurol},\n\tauthor = {Cerfontaine, Minne N. and Gravesteijn, Gido and Hack, Remco J. and Dijkstra, Kyra L. and Rodríguez-Girondo, Mar and Gesierich, Benno and Witjes-Ané, Marie-Noëlle W. and van Doorn, Remco and Duering, Marco and Rutten, Julie W. and Lesnik Oberstein, Saskia A. J.},\n\tmonth = apr,\n\tyear = {2025},\n\tpmid = {40265482},\n}\n\n

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\n \n\n \n \n \n \n \n Reduced myelin contributes to cognitive impairment in patients with monogenic small vessel disease.\n \n \n \n\n\n \n Denecke, J.; Dewenter, A.; Lee, J.; Franzmeier, N.; Valentim, C.; Kopczak, A.; Dichgans, M.; Pirpamer, L.; Gesierich, B.; Duering, M.; and Ewers, M.\n\n\n \n\n\n\n Alzheimers Dement, 21(5): e70127. May 2025.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{denecke_reduced_2025,\n\ttitle = {Reduced myelin contributes to cognitive impairment in patients with monogenic small vessel disease},\n\tvolume = {21},\n\tissn = {1552-5279},\n\tdoi = {10.1002/alz.70127},\n\tabstract = {INTRODUCTION: Myelin is pivotal for signal transfer and thus cognition. Cerebral small vessel disease (cSVD) is primarily associated with white matter (WM) lesions and diffusion changes; however, myelin alterations and related cognitive impairments in cSVD remain unclear.\nMETHODS: We included 64 patients with familial cSVD (i.e., cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy [CADASIL]) and 20 cognitively unimpaired individuals. χ separation applied to susceptibility weighted imaging was used to assess myelin and iron within WM hyperintensities, normal appearing WM, and two strategic fiber tracts. Diffusion-based mean diffusivity and free water were analyzed for comparisons. Cognitive impairment was assessed by the Trail Making Test.\nRESULTS: CADASIL patients showed reduced myelin within WM hyperintensities and its penumbra in the normal appearing WM. Myelin was moderately correlated with diffusion and iron changes and associated with slower processing speed controlled for diffusion and iron alterations.\nDISCUSSION: Myelin constitutes WM alterations distinct from diffusion changes and substantially contributes to explaining cognitive impairment in cSVD.\nHIGHLIGHTS: χ-negative magnetic resonance signal was reduced within white matter hyperintensities and normal appearing white matter in patients with cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy, suggesting widespread myelin decreases due to cerebral small vessel disease (cSVD). χ-negative values were only moderately associated with diffusion tensor imaging derived indices including free water and mean diffusivity, suggesting that χ separation depicts distinct microstructural changes in cSVD. Alterations in χ-negative values made a unique contribution to explain processing speed impairment, even when controlled for diffusion and iron changes.},\n\tlanguage = {eng},\n\tnumber = {5},\n\tjournal = {Alzheimers Dement},\n\tauthor = {Denecke, Jannis and Dewenter, Anna and Lee, Jongho and Franzmeier, Nicolai and Valentim, Carolina and Kopczak, Anna and Dichgans, Martin and Pirpamer, Lukas and Gesierich, Benno and Duering, Marco and Ewers, Michael},\n\tmonth = may,\n\tyear = {2025},\n\tpmid = {40317599},\n\tpmcid = {PMC12046978},\n\tkeywords = {Aged, CADASIL, cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy, Cerebral Small Vessel Diseases, chi separation, Cognitive Dysfunction, diffusion magnetic resonance imaging, Diffusion Tensor Imaging, Female, Humans, Magnetic Resonance Imaging, Male, Middle Aged, Myelin Sheath, Neuropsychological Tests, susceptibility mapping, White Matter, white matter hyperintensities},\n\tpages = {e70127},\n}\n\n

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\n \n\n \n \n \n \n \n Topographic Localization of Chronic Cerebellar Ischemic Lesions: Implications for Underlying Cause.\n \n \n \n\n\n \n Kneihsl, M.; Hakim, A.; Goeldlin, M. B.; Branca, M.; Fenzl, S.; Abend, S.; Gattringer, T.; Enzinger, C.; Dawson, J.; Gesierich, B.; Kopczak, A.; Hack, R. J.; Cerfontaine, M. N.; Rutten, J. W.; Lesnik Oberstein, S. A. J.; Pasi, M.; Fischer, U.; Duering, M.; and Meinel, T. R.\n\n\n \n\n\n\n Stroke. April 2025.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{kneihsl_topographic_2025,\n\ttitle = {Topographic {Localization} of {Chronic} {Cerebellar} {Ischemic} {Lesions}: {Implications} for {Underlying} {Cause}},\n\tissn = {1524-4628},\n\tshorttitle = {Topographic {Localization} of {Chronic} {Cerebellar} {Ischemic} {Lesions}},\n\tdoi = {10.1161/STROKEAHA.124.049337},\n\tabstract = {BACKGROUND: Chronic cerebellar lesions of presumed ischemic origin are frequently found in patients with ischemic stroke and as incidental findings. However, the differentiation of embolic lesions from lesions caused by cerebral small vessel disease (SVD) is unclear. We aimed to investigate whether the location of chronic cerebellar ischemic lesions (deep versus cortical) indicates the underlying cause (embolic versus SVD).\nMETHODS: This study was a post hoc data analysis from the multinational ELAN trial (Early Versus Late Initiation of Direct Oral Anticoagulants in Patients With Postischemic Stroke With Atrial Fibrillation), which included patients with acute ischemic stroke and atrial fibrillation cohort between 2017 and 2022. For comparison, data from 2 cohorts (DiViNAS [Disease Variability in NOTCH3-Associated SVD] and VASCAMY [Vascular and Amyloid Predictors of Neurodegeneration and Cognitive Decline in Nondemented Subjects]) consisting of participants with hereditary cerebral SVD (ie, Cerebral Autosomal Dominant Arteriopathy With Subcortical Infarcts and Leukoencephalopathy) were analyzed (Cerebral Autosomal Dominant Arteriopathy With Subcortical Infarcts and Leukoencephalopathy cohort). Brain magnetic resonance imaging scans were evaluated for presence and location of chronic cerebellar ischemic lesions. The association between these lesions and the severity of supratentorial SVD was analyzed using univariable and multivariable models, adjusting for key covariables.\nRESULTS: In the atrial fibrillation cohort (N=790), 278 (35\\%) patients had chronic cerebellar ischemic lesions (cortical: n=242; deep: n=36). In multivariable analyses, features of cerebral SVD were associated with deep cerebellar ischemic lesions (summary SVD score; odds ratio per point, 2.5 [95\\% CI, 1.5-3.5]; P{\\textless}0.001), while there was no association of SVD markers and cortical cerebellar ischemic lesions (summary SVD score; odds ratio per point, 1.1 [95\\% CI, 0.9-1.3]; P=0.107). In the Cerebral Autosomal Dominant Arteriopathy With Subcortical Infarcts and Leukoencephalopathy cohort (N=257), chronic cerebellar ischemic lesions (n=108 [42\\%]) were almost exclusively identified in deep cerebellar regions (n=101, 94\\%).\nCONCLUSIONS: Chronic cerebellar ischemic lesions in deep but not cortical regions were associated with supratentorial cerebral SVD. Therefore, cerebral SVD is likely the primary cause of chronic ischemic lesions in deep cerebellar regions, while cortical cerebellar lesions are more likely attributable to embolic etiologies.\nREGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT03148457.},\n\tlanguage = {eng},\n\tjournal = {Stroke},\n\tauthor = {Kneihsl, Markus and Hakim, Arsany and Goeldlin, Martina B. and Branca, Mattia and Fenzl, Sabine and Abend, Stefanie and Gattringer, Thomas and Enzinger, Christian and Dawson, Jesse and Gesierich, Benno and Kopczak, Anna and Hack, Remco J. and Cerfontaine, Minne N. and Rutten, Julie W. and Lesnik Oberstein, Saskia A. J. and Pasi, Marco and Fischer, Urs and Duering, Marco and Meinel, Thomas R.},\n\tmonth = apr,\n\tyear = {2025},\n\tpmid = {40177749},\n\tkeywords = {atrial fibrillation, brain, cerebral infarction, ischemic stroke, magnetic resonance imaging},\n}\n\n

\n\n\n

\n BACKGROUND: Chronic cerebellar lesions of presumed ischemic origin are frequently found in patients with ischemic stroke and as incidental findings. However, the differentiation of embolic lesions from lesions caused by cerebral small vessel disease (SVD) is unclear. We aimed to investigate whether the location of chronic cerebellar ischemic lesions (deep versus cortical) indicates the underlying cause (embolic versus SVD). METHODS: This study was a post hoc data analysis from the multinational ELAN trial (Early Versus Late Initiation of Direct Oral Anticoagulants in Patients With Postischemic Stroke With Atrial Fibrillation), which included patients with acute ischemic stroke and atrial fibrillation cohort between 2017 and 2022. For comparison, data from 2 cohorts (DiViNAS [Disease Variability in NOTCH3-Associated SVD] and VASCAMY [Vascular and Amyloid Predictors of Neurodegeneration and Cognitive Decline in Nondemented Subjects]) consisting of participants with hereditary cerebral SVD (ie, Cerebral Autosomal Dominant Arteriopathy With Subcortical Infarcts and Leukoencephalopathy) were analyzed (Cerebral Autosomal Dominant Arteriopathy With Subcortical Infarcts and Leukoencephalopathy cohort). Brain magnetic resonance imaging scans were evaluated for presence and location of chronic cerebellar ischemic lesions. The association between these lesions and the severity of supratentorial SVD was analyzed using univariable and multivariable models, adjusting for key covariables. RESULTS: In the atrial fibrillation cohort (N=790), 278 (35%) patients had chronic cerebellar ischemic lesions (cortical: n=242; deep: n=36). In multivariable analyses, features of cerebral SVD were associated with deep cerebellar ischemic lesions (summary SVD score; odds ratio per point, 2.5 [95% CI, 1.5-3.5]; P\\textless0.001), while there was no association of SVD markers and cortical cerebellar ischemic lesions (summary SVD score; odds ratio per point, 1.1 [95% CI, 0.9-1.3]; P=0.107). In the Cerebral Autosomal Dominant Arteriopathy With Subcortical Infarcts and Leukoencephalopathy cohort (N=257), chronic cerebellar ischemic lesions (n=108 [42%]) were almost exclusively identified in deep cerebellar regions (n=101, 94%). CONCLUSIONS: Chronic cerebellar ischemic lesions in deep but not cortical regions were associated with supratentorial cerebral SVD. Therefore, cerebral SVD is likely the primary cause of chronic ischemic lesions in deep cerebellar regions, while cortical cerebellar lesions are more likely attributable to embolic etiologies. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT03148457.\n

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\n \n\n \n \n \n \n \n The relation between cerebral small vessel function and white matter microstructure in monogenic and sporadic small vessel disease - the ZOOM@SVDs study.\n \n \n \n\n\n \n Vlegels, N.; van den Brink, H.; Kopczak, A.; Arts, T.; Pham, S. D. T.; Siero, J. C. W.; Gesierich, B.; De Luca, A.; Duering, M.; Zwanenburg, J. J. M.; Dichgans, M.; and Biessels, G. J.\n\n\n \n\n\n\n Cereb Circ Cogn Behav, 8: 100383. 2025.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{vlegels_relation_2025,\n\ttitle = {The relation between cerebral small vessel function and white matter microstructure in monogenic and sporadic small vessel disease - the {ZOOM}@{SVDs} study},\n\tvolume = {8},\n\tissn = {2666-2450},\n\tdoi = {10.1016/j.cccb.2025.100383},\n\tabstract = {In cerebral small vessel disease (cSVD), vascular dysfunction has been associated with cSVD-lesions across the brain. Here we further explore the relation between vascular dysfunction and cSVD-related brain injury. We tested two hypotheses: (1) that complementary measures of abnormal small vessel function relate to decreased white matter integrity, and (2) that local variance in vascular dysfunction relates to local variance in white matter integrity within individual patients. We included 23 patients with monogenic cSVD (i.e. CADASIL) and 46 patients with sporadic cSVD. With whole-brain analyses, we tested if small vessel flow velocity and reactivity measures from 7T-MRI were associated with global peak-width-of-skeletonized-mean-diffusivity (PSMD). We also tested voxel-wise correlations between reactivity to hypercapnia and mean diffusivity (MD) in white matter. Whole-brain analyses showed a negative association between blood flow velocity and PSMD for the perforating arteries in the centrum semiovale in CADASIL (p = 0.04) and in the basal ganglia in sporadic cSVD (p = 0.002). Global white matter reactivity to hypercapnia was not associated with PSMD. Within patients, both in CADASIL and sporadic cSVD, we observed significant voxel-wise negative correlations for endothelial-independent vascular reactivity and MD in the white matter. These findings confirm our hypothesis that small vessel dysfunction in patients with cSVD is associated with microstructural white matter alterations, also at voxel level. The latter may reflect a direct relationship between local small vessel dysfunction and tissue injury.},\n\tlanguage = {eng},\n\tjournal = {Cereb Circ Cogn Behav},\n\tauthor = {Vlegels, Naomi and van den Brink, Hilde and Kopczak, Anna and Arts, Tine and Pham, Stanley D. T. and Siero, Jeroen C. W. and Gesierich, Benno and De Luca, Alberto and Duering, Marco and Zwanenburg, Jaco J. M. and Dichgans, Martin and Biessels, Geert Jan},\n\tyear = {2025},\n\tpmid = {40230817},\n\tpmcid = {PMC11994352},\n\tkeywords = {CADASIL, Cerebral small vessel disease, Small vessel function, Ultra-high field strength MRI, White matter microstructure},\n\tpages = {100383},\n}\n\n

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\n \n\n \n \n \n \n \n Cerebrovascular Function in Sporadic and Genetic Cerebral Small Vessel Disease.\n \n \n \n\n\n \n Stringer, M. S.; Blair, G. W.; Kopczak, A.; Kerkhofs, D.; Thrippleton, M. J.; Chappell, F. M.; Maniega, S. M.; Brown, R.; Shuler, K.; Hamilton, I.; Garcia, D. J.; Doubal, F. N.; Clancy, U.; Sakka, E.; Poliakova, T.; Janssen, E.; Duering, M.; Ingrisch, M.; Staals, J.; Backes, W. H.; van Oostenbrugge, R.; Biessels, G. J.; Dichgans, M.; Wardlaw, J. M.; and SVDs@target consortium\n\n\n \n\n\n\n Ann Neurol, 97(3): 483–498. March 2025.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{stringer_cerebrovascular_2025,\n\ttitle = {Cerebrovascular {Function} in {Sporadic} and {Genetic} {Cerebral} {Small} {Vessel} {Disease}},\n\tvolume = {97},\n\tissn = {1531-8249},\n\tdoi = {10.1002/ana.27136},\n\tabstract = {OBJECTIVE: Cerebral small vessel diseases (SVDs) are associated with cerebrovascular dysfunction, such as increased blood-brain barrier leakage (permeability surface area product), vascular pulsatility, and decreased cerebrovascular reactivity (CVR). No studies assessed all 3 functions concurrently. We assessed 3 key vascular functions in sporadic and genetic SVD to determine associations with SVD severity, subtype, and interrelations.\nMETHODS: In this prospective, cross-sectional, multicenter INVESTIGATE-SVDs study, we acquired brain magnetic resonance imaging in patients with sporadic SVD/cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL), including structural, quantitative microstructural, permeability surface area product, blood plasma volume fraction, vascular pulsatility, and CVR (in response to CO2) scans. We determined vascular function and white matter hyperintensity (WMH) associations, using covariate-adjusted linear regression; normal-appearing white matter and WMH differences, interrelationships between vascular functions, using linear mixed models; and major sources of variance using principal component analyses.\nRESULTS: We recruited 77 patients (45 sporadic/32 CADASIL) at 3 sites. In adjusted analyses, patients with worse WMH had lower CVR (B = -1.78, 95\\% CI -3.30, -0.27) and blood plasma volume fraction (B = -0.594, 95\\% CI -0.987, -0.202). CVR was worse in WMH than normal-appearing white matter (eg, CVR: B = -0.048, 95\\% CI -0.079, -0.017). Adjusting for WMH severity, SVD subtype had minimal influence on vascular function (eg, CVR in CADASIL vs sporadic: B = 0.0169, 95\\% CI -0.0247, 0.0584). Different vascular function mechanisms were not generally interrelated (eg, permeability surface area product{\\textasciitilde}CVR: B = -0.85, 95\\% CI -4.72, 3.02). Principal component analyses identified WMH volume/quantitative microstructural metrics explained most variance in CADASIL and arterial pulsatility in sporadic SVD, but similar main variance sources.\nINTERPRETATION: Vascular function was worse with higher WMH, and in WMH than normal-appearing white matter. Sporadic SVD-CADASIL differences largely reflect disease severity. Limited vascular function interrelations may suggest disease stage-specific differences. ANN NEUROL 2025;97:483-498.},\n\tlanguage = {eng},\n\tnumber = {3},\n\tjournal = {Ann Neurol},\n\tauthor = {Stringer, Michael S. and Blair, Gordon W. and Kopczak, Anna and Kerkhofs, Danielle and Thrippleton, Michael J. and Chappell, Francesca M. and Maniega, Susana Muñoz and Brown, Rosalind and Shuler, Kirsten and Hamilton, Iona and Garcia, Daniela Jaime and Doubal, Fergus N. and Clancy, Una and Sakka, Eleni and Poliakova, Tetiana and Janssen, Esther and Duering, Marco and Ingrisch, Michael and Staals, Julie and Backes, Walter H. and van Oostenbrugge, Robert and Biessels, Geert Jan and Dichgans, Martin and Wardlaw, Joanna M. and {SVDs@target consortium}},\n\tmonth = mar,\n\tyear = {2025},\n\tpmid = {39552538},\n\tpmcid = {PMC11831873},\n\tkeywords = {Adult, Aged, Blood-Brain Barrier, Brain, CADASIL, Cerebral Small Vessel Diseases, Cerebrovascular Circulation, Cross-Sectional Studies, Female, Humans, Magnetic Resonance Imaging, Male, Middle Aged, Prospective Studies, White Matter},\n\tpages = {483--498},\n}\n\n

\n\n\n

\n OBJECTIVE: Cerebral small vessel diseases (SVDs) are associated with cerebrovascular dysfunction, such as increased blood-brain barrier leakage (permeability surface area product), vascular pulsatility, and decreased cerebrovascular reactivity (CVR). No studies assessed all 3 functions concurrently. We assessed 3 key vascular functions in sporadic and genetic SVD to determine associations with SVD severity, subtype, and interrelations. METHODS: In this prospective, cross-sectional, multicenter INVESTIGATE-SVDs study, we acquired brain magnetic resonance imaging in patients with sporadic SVD/cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL), including structural, quantitative microstructural, permeability surface area product, blood plasma volume fraction, vascular pulsatility, and CVR (in response to CO2) scans. We determined vascular function and white matter hyperintensity (WMH) associations, using covariate-adjusted linear regression; normal-appearing white matter and WMH differences, interrelationships between vascular functions, using linear mixed models; and major sources of variance using principal component analyses. RESULTS: We recruited 77 patients (45 sporadic/32 CADASIL) at 3 sites. In adjusted analyses, patients with worse WMH had lower CVR (B = -1.78, 95% CI -3.30, -0.27) and blood plasma volume fraction (B = -0.594, 95% CI -0.987, -0.202). CVR was worse in WMH than normal-appearing white matter (eg, CVR: B = -0.048, 95% CI -0.079, -0.017). Adjusting for WMH severity, SVD subtype had minimal influence on vascular function (eg, CVR in CADASIL vs sporadic: B = 0.0169, 95% CI -0.0247, 0.0584). Different vascular function mechanisms were not generally interrelated (eg, permeability surface area product~CVR: B = -0.85, 95% CI -4.72, 3.02). Principal component analyses identified WMH volume/quantitative microstructural metrics explained most variance in CADASIL and arterial pulsatility in sporadic SVD, but similar main variance sources. INTERPRETATION: Vascular function was worse with higher WMH, and in WMH than normal-appearing white matter. Sporadic SVD-CADASIL differences largely reflect disease severity. Limited vascular function interrelations may suggest disease stage-specific differences. ANN NEUROL 2025;97:483-498.\n

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\n \n\n \n \n \n \n \n Extended Technical and Clinical Validation of Deep Learning-Based Brainstem Segmentation for Application in Neurodegenerative Diseases.\n \n \n \n\n\n \n Gesierich, B.; Sander, L.; Pirpamer, L.; Meier, D. S.; Ruberte, E.; Amann, M.; Sinnecker, T.; Huck, A.; de Leeuw, F.; Maillard, P.; Moy, S.; Helmer, K. G.; MarkVCID Consortium; Levin, J.; Höglinger, G. U.; PROMESA Study Group; Kühne, M.; Bonati, L. H.; Kuhle, J.; Cattin, P.; Granziera, C.; Schlaeger, R.; and Duering, M.\n\n\n \n\n\n\n Hum Brain Mapp, 46(3): e70141. February 2025.\n \n\n\n\n
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@article{gesierich_extended_2025,\n\ttitle = {Extended {Technical} and {Clinical} {Validation} of {Deep} {Learning}-{Based} {Brainstem} {Segmentation} for {Application} in {Neurodegenerative} {Diseases}},\n\tvolume = {46},\n\tissn = {1097-0193},\n\tdoi = {10.1002/hbm.70141},\n\tabstract = {Disorders of the central nervous system, including neurodegenerative diseases, frequently affect the brainstem and can present with focal atrophy. This study aimed to (1) optimize deep learning-based brainstem segmentation for a wide range of pathologies and T1-weighted image acquisition parameters, (2) conduct a systematic technical and clinical validation, (3) improve segmentation quality in the presence of brainstem lesions, and (4) make an optimized brainstem segmentation tool available for public use. An intentionally heterogeneous ground truth dataset (n = 257) was employed in the training of deep learning models based on multi-dimensional gated recurrent units (MD-GRU) or the nnU-Net method. Segmentation performance was evaluated against ground truth labels. FreeSurfer was used for benchmarking in subsequent validation. Technical validation, including scan-rescan repeatability (n = 46) and inter-scanner reproducibility (n = 20, 3 different scanners) in unseen data, was conducted in patients with cerebral small vessel disease. Clinical validation in unseen data was performed in 1-year follow-up data of 16 patients with multiple system atrophy, evaluating the annual percentage volume change. Two lesion filling algorithms were investigated to improve segmentation performance in 23 patients with multiple sclerosis. The MD-GRU and nnU-Net models demonstrated very good segmentation performance (median Dice coefficients ≥ 0.95 each) and outperformed a previously published model trained on a narrower dataset. Scan-rescan repeatability and inter-scanner reproducibility yielded similar Bland-Altman derived limits of agreement for longitudinal FreeSurfer (total brainstem volume repeatability/reproducibility 0.68/1.85), MD-GRU (0.72/1.46), and nnU-Net (0.48/1.52). All methods showed comparable performance in the detection of atrophy in the total brainstem (atrophy detected in 100\\% of patients) and its substructures. In patients with multiple sclerosis, lesion filling further improved the accuracy of brainstem segmentation. We enhanced and systematically validated two fully automated deep learning brainstem segmentation methods and released them publicly. This enables a broader evaluation of brainstem volume as a candidate biomarker for neurodegeneration.},\n\tlanguage = {eng},\n\tnumber = {3},\n\tjournal = {Hum Brain Mapp},\n\tauthor = {Gesierich, Benno and Sander, Laura and Pirpamer, Lukas and Meier, Dominik S. and Ruberte, Esther and Amann, Michael and Sinnecker, Tim and Huck, Antal and de Leeuw, Frank-Erik and Maillard, Pauline and Moy, Sue and Helmer, Karl G. and {MarkVCID Consortium} and Levin, Johannes and Höglinger, Günter U. and {PROMESA Study Group} and Kühne, Michael and Bonati, Leo H. and Kuhle, Jens and Cattin, Philippe and Granziera, Cristina and Schlaeger, Regina and Duering, Marco},\n\tmonth = feb,\n\tyear = {2025},\n\tpmid = {39936343},\n\tpmcid = {PMC11815323},\n\tkeywords = {Adult, Aged, atrophy, Brain Stem, brainstem, Cerebral Small Vessel Diseases, deep learning, Deep Learning, Female, Humans, Image Interpretation, Computer-Assisted, Magnetic Resonance Imaging, Male, Middle Aged, Multiple Sclerosis, Multiple System Atrophy, neurodegeneration, Neurodegenerative Diseases, Neuroimaging, Reproducibility of Results, segmentation},\n\tpages = {e70141},\n}\n\n

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\n Disorders of the central nervous system, including neurodegenerative diseases, frequently affect the brainstem and can present with focal atrophy. This study aimed to (1) optimize deep learning-based brainstem segmentation for a wide range of pathologies and T1-weighted image acquisition parameters, (2) conduct a systematic technical and clinical validation, (3) improve segmentation quality in the presence of brainstem lesions, and (4) make an optimized brainstem segmentation tool available for public use. An intentionally heterogeneous ground truth dataset (n = 257) was employed in the training of deep learning models based on multi-dimensional gated recurrent units (MD-GRU) or the nnU-Net method. Segmentation performance was evaluated against ground truth labels. FreeSurfer was used for benchmarking in subsequent validation. Technical validation, including scan-rescan repeatability (n = 46) and inter-scanner reproducibility (n = 20, 3 different scanners) in unseen data, was conducted in patients with cerebral small vessel disease. Clinical validation in unseen data was performed in 1-year follow-up data of 16 patients with multiple system atrophy, evaluating the annual percentage volume change. Two lesion filling algorithms were investigated to improve segmentation performance in 23 patients with multiple sclerosis. The MD-GRU and nnU-Net models demonstrated very good segmentation performance (median Dice coefficients ≥ 0.95 each) and outperformed a previously published model trained on a narrower dataset. Scan-rescan repeatability and inter-scanner reproducibility yielded similar Bland-Altman derived limits of agreement for longitudinal FreeSurfer (total brainstem volume repeatability/reproducibility 0.68/1.85), MD-GRU (0.72/1.46), and nnU-Net (0.48/1.52). All methods showed comparable performance in the detection of atrophy in the total brainstem (atrophy detected in 100% of patients) and its substructures. In patients with multiple sclerosis, lesion filling further improved the accuracy of brainstem segmentation. We enhanced and systematically validated two fully automated deep learning brainstem segmentation methods and released them publicly. This enables a broader evaluation of brainstem volume as a candidate biomarker for neurodegeneration.\n

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\n \n\n \n \n \n \n \n Tract-specific white matter hyperintensities and neuropsychiatric syndromes: a multicentre memory clinic study.\n \n \n \n\n\n \n Kan, C. N.; Coenen, M.; Xu, X.; Hilal, S.; Barkhof, F.; Benke, T.; Dal-Bianco, P.; DeCarli, C.; Duering, M.; Enzinger, C.; Exalto, L. G.; Fletcher, E. F.; Hofer, E.; Koek, H. L.; Kuijf, H. J.; Maillard, P. M.; Moonen, J. E. F.; Papma, J. M.; Pijnenburg, Y. A. L.; Schmidt, R.; Steketee, R. M. E.; van den Berg, E.; van der Flier, W. M.; Venketasubramanian, N.; Vernooij, M. W.; Wolters, F. J.; Biessels, G. J.; Chen, C. L.; Biesbroek, J. M.; Tan, C. H.; and Alzheimer’s Disease Neuroimaging Initiative\n\n\n \n\n\n\n J Neurol Neurosurg Psychiatry,jnnp–2024–334264. January 2025.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{kan_tract-specific_2025,\n\ttitle = {Tract-specific white matter hyperintensities and neuropsychiatric syndromes: a multicentre memory clinic study},\n\tissn = {1468-330X},\n\tshorttitle = {Tract-specific white matter hyperintensities and neuropsychiatric syndromes},\n\tdoi = {10.1136/jnnp-2024-334264},\n\tabstract = {BACKGROUND: White matter hyperintensities (WMH) have been implicated in the pathogenesis of neuropsychiatric symptoms of dementia but the functional significance of WMH in specific white matter (WM) tracts is unclear. We investigate whether WMH burden within major WM fibre classes and individual WM tracts are differentially associated with different neuropsychiatric syndromes in a large multicentre study.\nMETHOD: Neuroimaging and neuropsychiatric data of seven memory clinic cohorts through the Meta VCI Map consortium were harmonised. Class-based analyses of major WM fibres (association, commissural and projection) and region-of-interest-based analyses on 11 individual WM tracts were used to evaluate associations of WMH volume with severity of hyperactivity, psychosis, affective and apathy syndromes.\nRESULTS: Among 2935 patients (50.4\\% women; mean age=72.2 years; 19.8\\% subjective cognitive impairment, 39.8\\% mild cognitive impairment, and 40.4\\% dementia), larger WMH volume within projection fibres (B=0.24, SE=0.10, p=0.013) was associated with greater apathy. Larger WMH volume within association (B=0.31, SE=0.12, p=0.009), commissural (B=0.47, SE=0.17, p=0.006) and projection (B=0.39, SE=0.16, p=0.016) fibres was associated with greater hyperactivity, driven by the inferior fronto-occipital fasciculus (B=0.50, SE=0.18, p=0.006), forceps major (B=0.48, SE=0.18, p=0.009) and anterior thalamic radiation (B=0.49, SE=0.19, p=0.011), respectively. Larger WMH volume in the uncinate fasciculus (B=1.82, SE=0.67, p=0.005) and forceps minor (B=0.61, SE=0.19, p=0.001) were additionally associated with greater apathy. No associations with affective and psychosis were observed.\nCONCLUSIONS: Tract-syndrome specificity of WMH burden with apathy and hyperactivity suggests that disruption of strategic neuronal pathways may be a potential mechanism through which small vessel disease affects emotional and behavioural regulation in memory clinic patients.},\n\tlanguage = {eng},\n\tjournal = {J Neurol Neurosurg Psychiatry},\n\tauthor = {Kan, Cheuk Ni and Coenen, Mirthe and Xu, Xin and Hilal, Saima and Barkhof, Frederik and Benke, Thomas and Dal-Bianco, Peter and DeCarli, Charles and Duering, Marco and Enzinger, Christian and Exalto, Lieza G. and Fletcher, Evan F. and Hofer, Edith and Koek, Huiberdina L. and Kuijf, Hugo J. and Maillard, Pauline M. and Moonen, Justine E. F. and Papma, Janne M. and Pijnenburg, Yolande A. L. and Schmidt, Reinhold and Steketee, Rebecca M. E. and van den Berg, Esther and van der Flier, Wiesje M. and Venketasubramanian, Narayanaswamy and Vernooij, Meike W. and Wolters, Frank J. and Biessels, Geert Jan and Chen, Christopher Li-Hsian and Biesbroek, J. Matthijs and Tan, Chin Hong and {Alzheimer’s Disease Neuroimaging Initiative}},\n\tmonth = jan,\n\tyear = {2025},\n\tpmid = {39761997},\n\tkeywords = {CEREBROVASCULAR DISEASE, CLINICAL NEUROLOGY, DEMENTIA, PSYCHIATRY},\n\tpages = {jnnp--2024--334264},\n}\n\n

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\n \n\n \n \n \n \n \n Disease Severity Staging System for NOTCH3-Associated Small Vessel Disease, Including CADASIL.\n \n \n \n\n\n \n Gravesteijn, G.; Rutten, J. W.; Cerfontaine, M. N.; Hack, R. J.; Liao, Y.; Jolly, A. A.; Guey, S.; Hsu, S.; Park, J.; Yuan, Y.; Kopczak, A.; Rifino, N.; Neilson, S. J.; Poggesi, A.; Shourav, M. M. I.; Saito, S.; Ishiyama, H.; Domínguez Mayoral, A.; Nogueira, R.; Muiño, E.; Andersen, P.; De Stefano, N.; Santo, G.; Sukhonpanich, N.; Mele, F.; Park, A.; Lee, J. S.; Rodríguez-Girondo, M.; Vonk, S. J. J.; Brodtmann, A.; Börjesson-Hanson, A.; Pantoni, L.; Fernández-Cadenas, I.; Silva, A. R.; Montanaro, V. V. A.; Kalaria, R. N.; Lopergolo, D.; Ihara, M.; Meschia, J. F.; Muir, K. W.; Bersano, A.; Pescini, F.; Duering, M.; Choi, J. C.; Ling, C.; Kim, H.; Markus, H. S.; Chabriat, H.; Lee, Y.; and Lesnik Oberstein, S. A. J.\n\n\n \n\n\n\n JAMA Neurol, 82(1): 49–60. January 2025.\n \n\n\n\n
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@article{gravesteijn_disease_2025,\n\ttitle = {Disease {Severity} {Staging} {System} for {NOTCH3}-{Associated} {Small} {Vessel} {Disease}, {Including} {CADASIL}},\n\tvolume = {82},\n\tissn = {2168-6157},\n\tdoi = {10.1001/jamaneurol.2024.4487},\n\tabstract = {IMPORTANCE: Typical cysteine-altering NOTCH3 (NOTCH3cys) variants are highly prevalent (approximately 1 in 300 individuals) and are associated with a broad spectrum of small vessel disease (SVD), ranging from early-onset stroke and dementia (cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy [CADASIL]) to nonpenetrance. A staging system that captures the full NOTCH3-SVD severity spectrum is needed and currently lacking.\nOBJECTIVE: To design a simple disease severity staging system that captures the broad clinicoradiological NOTCH3-SVD severity spectrum.\nDESIGN, SETTING, AND PARTICIPANTS: A cohort study was performed in which the NOTCH3-SVD severity staging system was developed using a discovery cohort (2019-2020) and validated in independent international CADASIL cohorts (1999-2023) and the UK Biobank. Clinical and imaging data were collected from participants originating from 23 international CADASIL cohorts and from the UK Biobank. Eligibility criteria were presence of a NOTCH3cys variant, availability of brain magnetic resonance imaging, and modified Rankin Scale score. The discovery cohort consisted of 195 NOTCH3cys-positive cases from families with CADASIL; the validation set included 1713 NOTCH3cys-positive cases from 15 countries. The UK Biobank cohort consisted of 101 NOTCH3cys-positive individuals. Data from 2-year (2019-2023) and 18-year (1999-2017) follow-up studies were also analyzed. Data analysis was performed from July 2023 to August 2024.\nMAIN OUTCOMES AND MEASURES: Percentage of cases following the sequence of events of the NOTCH3-SVD stages, and the association between the stages and ischemic stroke, intracerebral hemorrhage, global cognition, processing speed, brain volume, brain microstructural damage, and serum neurofilament light chain (NfL) level.\nRESULTS: The NOTCH3-SVD staging system encompasses 9 disease stages or substages, ranging from stage 0 (premanifest stage) to stage 4B (end stage). Of all 1908 cases, which included 195 in the discovery cohort (mean [SD] age, 52.4 [12.2] years) and 1713 in the validation cohorts (mean [SD] age, 53.1 [13.0] years), 1789 (94\\%) followed the sequence of events defined by the NOTCH3-SVD staging system. The NOTCH3-SVD stages were associated with neuroimaging outcomes in the NOTCH3cys-positive cases in the CADASIL cohorts and in the UK Biobank and with cognitive outcomes and serum NfL level in cases from the CADASIL cohorts. The NOTCH3-SVD staging system captured disease progression and was associated with 18-year survival.\nCONCLUSIONS AND RELEVANCE: The NOTCH3-SVD staging system captures the full disease spectrum, from asymptomatic individuals with a NOTCH3cys variant to patients with end-stage disease. The NOTCH3-SVD staging system is a simple but effective tool for uniform disease staging in the clinic and in research.},\n\tlanguage = {eng},\n\tnumber = {1},\n\tjournal = {JAMA Neurol},\n\tauthor = {Gravesteijn, Gido and Rutten, Julie W. and Cerfontaine, Minne N. and Hack, Remco J. and Liao, Yi-Chu and Jolly, Amy A. and Guey, Stéphanie and Hsu, Shao-Lun and Park, Jae-Young and Yuan, Yun and Kopczak, Anna and Rifino, Nicola and Neilson, Sam J. and Poggesi, Anna and Shourav, Md Manjurul Islam and Saito, Satoshi and Ishiyama, Hiroyuki and Domínguez Mayoral, Ana and Nogueira, Renata and Muiño, Elena and Andersen, Pia and De Stefano, Nicola and Santo, Gustavo and Sukhonpanich, Nontapat and Mele, Francesco and Park, Ashley and Lee, Jung Seok and Rodríguez-Girondo, Mar and Vonk, Sebastiaan J. J. and Brodtmann, Amy and Börjesson-Hanson, Anne and Pantoni, Leonardo and Fernández-Cadenas, Israel and Silva, Ana Rita and Montanaro, Vinícus V. A. and Kalaria, Rajesh N. and Lopergolo, Diego and Ihara, Masafumi and Meschia, James F. and Muir, Keith W. and Bersano, Anna and Pescini, Francesca and Duering, Marco and Choi, Jay Chol and Ling, Chen and Kim, Hyunjin and Markus, Hugh S. and Chabriat, Hugues and Lee, Yi-Chung and Lesnik Oberstein, Saskia A. J.},\n\tmonth = jan,\n\tyear = {2025},\n\tpmid = {39610302},\n\tkeywords = {Adult, Aged, CADASIL, Cerebral Small Vessel Diseases, Cohort Studies, Female, Humans, Magnetic Resonance Imaging, Male, Middle Aged, Receptor, Notch3, Severity of Illness Index},\n\tpages = {49--60},\n}\n\n

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\n IMPORTANCE: Typical cysteine-altering NOTCH3 (NOTCH3cys) variants are highly prevalent (approximately 1 in 300 individuals) and are associated with a broad spectrum of small vessel disease (SVD), ranging from early-onset stroke and dementia (cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy [CADASIL]) to nonpenetrance. A staging system that captures the full NOTCH3-SVD severity spectrum is needed and currently lacking. OBJECTIVE: To design a simple disease severity staging system that captures the broad clinicoradiological NOTCH3-SVD severity spectrum. DESIGN, SETTING, AND PARTICIPANTS: A cohort study was performed in which the NOTCH3-SVD severity staging system was developed using a discovery cohort (2019-2020) and validated in independent international CADASIL cohorts (1999-2023) and the UK Biobank. Clinical and imaging data were collected from participants originating from 23 international CADASIL cohorts and from the UK Biobank. Eligibility criteria were presence of a NOTCH3cys variant, availability of brain magnetic resonance imaging, and modified Rankin Scale score. The discovery cohort consisted of 195 NOTCH3cys-positive cases from families with CADASIL; the validation set included 1713 NOTCH3cys-positive cases from 15 countries. The UK Biobank cohort consisted of 101 NOTCH3cys-positive individuals. Data from 2-year (2019-2023) and 18-year (1999-2017) follow-up studies were also analyzed. Data analysis was performed from July 2023 to August 2024. MAIN OUTCOMES AND MEASURES: Percentage of cases following the sequence of events of the NOTCH3-SVD stages, and the association between the stages and ischemic stroke, intracerebral hemorrhage, global cognition, processing speed, brain volume, brain microstructural damage, and serum neurofilament light chain (NfL) level. RESULTS: The NOTCH3-SVD staging system encompasses 9 disease stages or substages, ranging from stage 0 (premanifest stage) to stage 4B (end stage). Of all 1908 cases, which included 195 in the discovery cohort (mean [SD] age, 52.4 [12.2] years) and 1713 in the validation cohorts (mean [SD] age, 53.1 [13.0] years), 1789 (94%) followed the sequence of events defined by the NOTCH3-SVD staging system. The NOTCH3-SVD stages were associated with neuroimaging outcomes in the NOTCH3cys-positive cases in the CADASIL cohorts and in the UK Biobank and with cognitive outcomes and serum NfL level in cases from the CADASIL cohorts. The NOTCH3-SVD staging system captured disease progression and was associated with 18-year survival. CONCLUSIONS AND RELEVANCE: The NOTCH3-SVD staging system captures the full disease spectrum, from asymptomatic individuals with a NOTCH3cys variant to patients with end-stage disease. The NOTCH3-SVD staging system is a simple but effective tool for uniform disease staging in the clinic and in research.\n

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\n \n\n \n \n \n \n \n Heterogeneity and Penumbra of White Matter Hyperintensities in Small Vessel Diseases Determined by Quantitative MRI.\n \n \n \n\n\n \n Voorter, P. H. M.; Stringer, M. S.; van Dinther, M.; Kerkhofs, D.; Dewenter, A.; Blair, G. W.; Thrippleton, M. J.; Jaime Garcia, D.; Chappell, F. M.; Janssen, E.; Kopczak, A.; Staals, J.; Ingrisch, M.; Duering, M.; Doubal, F. N.; Dichgans, M.; van Oostenbrugge, R. J.; Jansen, J. F. A.; Wardlaw, J. M.; Backes, W. H.; and SVDs@target Consortium\n\n\n \n\n\n\n Stroke, 56(1): 128–137. January 2025.\n \n\n\n\n
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@article{voorter_heterogeneity_2025,\n\ttitle = {Heterogeneity and {Penumbra} of {White} {Matter} {Hyperintensities} in {Small} {Vessel} {Diseases} {Determined} by {Quantitative} {MRI}},\n\tvolume = {56},\n\tissn = {1524-4628},\n\tdoi = {10.1161/STROKEAHA.124.047910},\n\tabstract = {BACKGROUND: White matter hyperintensities (WMHs) are established structural imaging markers of cerebral small vessel disease. The pathophysiologic condition of brain tissue varies over the core, the vicinity, and the subtypes of WMH and cannot be interpreted from conventional magnetic resonance imaging. We aim to improve our pathophysiologic understanding of WMHs and the adjacently injured normal-appearing white matter in terms of microstructural and microvascular alterations using quantitative magnetic resonance imaging in patients with sporadic and genetic cerebral small vessel disease.\nMETHODS: Structural T2-weighted imaging, multishell diffusion imaging, and dynamic contrast-enhanced magnetic resonance imaging were performed at 3T in 44 participants with sporadic cerebral small vessel disease and 32 participants with monogenic cerebral small vessel disease (cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy; 59±12 years, 41 males) between June 2017 and May 2020 as part of the prospective, multicenter (Edinburgh, the United Kingdom; Maastricht, the Netherlands; and Munich, Germany), observational INVESTIGATE-SVDs study (Imaging Neurovascular, Endothelial and Structural Integrity in Preparation to Treat Small Vessel Diseases). The mean diffusivity, free water content, and perfusion (all derived from multishell diffusion imaging), as well as the blood-brain barrier leakage and plasma volume fraction (derived from dynamic contrast-enhanced magnetic resonance imaging), were compared between deep and periventricular WMH types using paired t tests. Additional spatial analyses were performed inside and outside the WMH types to determine the internal heterogeneity and the extent of the penumbras, that is, adjacent white matter at risk for conversion to WMH.\nRESULTS: Periventricular WMH had higher mean diffusivity, higher free water content, and more plasma volume compared with deep WMH (P{\\textless}0.001, P=0.01, and P{\\textless}0.001, respectively). No differences were observed in perfusion (P=0.94) and blood-brain barrier leakage (P=0.65) between periventricular and deep WMHs. The spatial analyses inside WMH and the adjacent white matter revealed a gradual gradient in white matter microstructure, free water content, perfusion, and plasma volume but not in blood-brain barrier leakage.\nCONCLUSIONS: We showed different pathophysiological heterogeneity of the 2 WMH types. Periventricular WMHs display more severe damage and fluid accumulation compared with deep WMH, whereas deep WMHs reflect stronger hypoperfusion in the lesion's core.\nREGISTRATION: URL: https://www.isrctn.com; Unique identifier: ISRCTN10514229.},\n\tlanguage = {eng},\n\tnumber = {1},\n\tjournal = {Stroke},\n\tauthor = {Voorter, Paulien H. M. and Stringer, Michael S. and van Dinther, Maud and Kerkhofs, Daniëlle and Dewenter, Anna and Blair, Gordon W. and Thrippleton, Michael J. and Jaime Garcia, Daniela and Chappell, Francesca M. and Janssen, Esther and Kopczak, Anna and Staals, Julie and Ingrisch, Michael and Duering, Marco and Doubal, Fergus N. and Dichgans, Martin and van Oostenbrugge, Robert J. and Jansen, Jacobus F. A. and Wardlaw, Joanna M. and Backes, Walter H. and {SVDs@target Consortium}},\n\tmonth = jan,\n\tyear = {2025},\n\tpmid = {39648904},\n\tkeywords = {Aged, blood-brain barrier, Blood-Brain Barrier, cerebral small vessel diseases, Cerebral Small Vessel Diseases, diffusion, Diffusion Magnetic Resonance Imaging, Female, Humans, magnetic resonance imaging, Magnetic Resonance Imaging, Male, Middle Aged, perfusion, Prospective Studies, White Matter},\n\tpages = {128--137},\n}\n\n

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\n BACKGROUND: White matter hyperintensities (WMHs) are established structural imaging markers of cerebral small vessel disease. The pathophysiologic condition of brain tissue varies over the core, the vicinity, and the subtypes of WMH and cannot be interpreted from conventional magnetic resonance imaging. We aim to improve our pathophysiologic understanding of WMHs and the adjacently injured normal-appearing white matter in terms of microstructural and microvascular alterations using quantitative magnetic resonance imaging in patients with sporadic and genetic cerebral small vessel disease. METHODS: Structural T2-weighted imaging, multishell diffusion imaging, and dynamic contrast-enhanced magnetic resonance imaging were performed at 3T in 44 participants with sporadic cerebral small vessel disease and 32 participants with monogenic cerebral small vessel disease (cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy; 59±12 years, 41 males) between June 2017 and May 2020 as part of the prospective, multicenter (Edinburgh, the United Kingdom; Maastricht, the Netherlands; and Munich, Germany), observational INVESTIGATE-SVDs study (Imaging Neurovascular, Endothelial and Structural Integrity in Preparation to Treat Small Vessel Diseases). The mean diffusivity, free water content, and perfusion (all derived from multishell diffusion imaging), as well as the blood-brain barrier leakage and plasma volume fraction (derived from dynamic contrast-enhanced magnetic resonance imaging), were compared between deep and periventricular WMH types using paired t tests. Additional spatial analyses were performed inside and outside the WMH types to determine the internal heterogeneity and the extent of the penumbras, that is, adjacent white matter at risk for conversion to WMH. RESULTS: Periventricular WMH had higher mean diffusivity, higher free water content, and more plasma volume compared with deep WMH (P\\textless0.001, P=0.01, and P\\textless0.001, respectively). No differences were observed in perfusion (P=0.94) and blood-brain barrier leakage (P=0.65) between periventricular and deep WMHs. The spatial analyses inside WMH and the adjacent white matter revealed a gradual gradient in white matter microstructure, free water content, perfusion, and plasma volume but not in blood-brain barrier leakage. CONCLUSIONS: We showed different pathophysiological heterogeneity of the 2 WMH types. Periventricular WMHs display more severe damage and fluid accumulation compared with deep WMH, whereas deep WMHs reflect stronger hypoperfusion in the lesion's core. REGISTRATION: URL: https://www.isrctn.com; Unique identifier: ISRCTN10514229.\n

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\n \n\n \n \n \n \n \n Baseline and Longitudinal MRI Markers Associated With 16-Year Mortality in Patients With Cerebral Small Vessel Disease.\n \n \n \n\n\n \n Yi, F.; Jacob, M. A.; Verhoeven, J. I.; Cai, M.; Duering, M.; Tuladhar, A. M.; and De Leeuw, F.\n\n\n \n\n\n\n Neurology, 103(6): e209701. September 2024.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{yi_baseline_2024,\n\ttitle = {Baseline and {Longitudinal} {MRI} {Markers} {Associated} {With} 16-{Year} {Mortality} in {Patients} {With} {Cerebral} {Small} {Vessel} {Disease}},\n\tvolume = {103},\n\tissn = {1526-632X},\n\tdoi = {10.1212/WNL.0000000000209701},\n\tabstract = {BACKGROUND AND OBJECTIVES: Information on whether small vessel disease (SVD) reduces life expectancy is limited. Moreover, the excess mortality risk attributed specifically to SVD compared with controls from the general population has not been evaluated. This study aimed to investigate the baseline and progression of MRI markers of SVD associated with mortality in a 16-year follow-up cohort study and to determine the excess long-term mortality risk of patients with SVD.\nMETHODS: Participants with SVD from the Radboud University Nijmegen Diffusion Tensor and Magnetic Resonance Imaging Cohort (RUN DMC) study (with MRI assessments in 2006, 2011, 2015, and 2020) were followed until their death or December 1, 2021. Adjusted Cox regression analyses and linear mixed-effect regression models were used to investigate the association between MRI markers of SVD and mortality. The excess mortality risk of SVD was calculated by comparing mortality data of the RUN DMC study with the general population matched by sex, age, and calendar year.\nRESULTS: 200 of 503 (39.9\\%) participants died during a follow-up period of 15.9 years. Cause of death was available for 182 (91\\%) participants. Baseline white matter hyperintensity volume (HR 1.3 per 1-SD increase [95\\% CI 1.1-1.5], p = 0.010), presence of lacunes (1.5 [95\\% CI 1.1-2.0], p = 0.008), mean diffusivity (HR 1.1 per 1-SD increase [95\\% CI 1.1-1.2], p = 0.001), and total brain volume (HR 1.5 per 1-SD decrease [95\\% CI 1.3-1.9], p {\\textless} 0.001) were associated with all-cause mortality after adjusting for age, sex, and vascular risk factors. Total brain volume decrease over time was associated with all-cause mortality after adjusting for age, sex, and vascular risk factors (HR 1.3 per 1-SD decrease [95\\% CI 1.1-1.7], p = 0.035), and gray matter volume decrease remained significant after additionally adjusting for its baseline volume (1.3 per 1-SD decrease [1.1-1.6], p = 0.019). Participants with a Fazekas score of 3, presence of lacunes, or lower microstructural integrity had an excess long-term mortality risk (21.8, 15.7, 10.1 per 1,000 person-years, respectively) compared with the general population.\nDISCUSSION: Excess long-term mortality risk only exists in patients with severe SVD (Fazekas score of 3, presence of lacunes, or lower microstructural integrity). This could help in assisting clinicians to predict the clinical outcomes of patients with SVD by severity.},\n\tlanguage = {eng},\n\tnumber = {6},\n\tjournal = {Neurology},\n\tauthor = {Yi, Fang and Jacob, Mina A. and Verhoeven, Jamie I. and Cai, Mengfei and Duering, Marco and Tuladhar, Anil Man and De Leeuw, Frank-Erik},\n\tmonth = sep,\n\tyear = {2024},\n\tpmid = {39167750},\n\tpmcid = {PMC11379354},\n\tkeywords = {Aged, Diffusion Tensor Imaging, Female, Humans, Male, Middle Aged, Aged, 80 and over, Follow-Up Studies, Magnetic Resonance Imaging, Cohort Studies, Longitudinal Studies, White Matter, Cerebral Small Vessel Diseases},\n\tpages = {e209701},\n}\n\n

\n\n\n

\n BACKGROUND AND OBJECTIVES: Information on whether small vessel disease (SVD) reduces life expectancy is limited. Moreover, the excess mortality risk attributed specifically to SVD compared with controls from the general population has not been evaluated. This study aimed to investigate the baseline and progression of MRI markers of SVD associated with mortality in a 16-year follow-up cohort study and to determine the excess long-term mortality risk of patients with SVD. METHODS: Participants with SVD from the Radboud University Nijmegen Diffusion Tensor and Magnetic Resonance Imaging Cohort (RUN DMC) study (with MRI assessments in 2006, 2011, 2015, and 2020) were followed until their death or December 1, 2021. Adjusted Cox regression analyses and linear mixed-effect regression models were used to investigate the association between MRI markers of SVD and mortality. The excess mortality risk of SVD was calculated by comparing mortality data of the RUN DMC study with the general population matched by sex, age, and calendar year. RESULTS: 200 of 503 (39.9%) participants died during a follow-up period of 15.9 years. Cause of death was available for 182 (91%) participants. Baseline white matter hyperintensity volume (HR 1.3 per 1-SD increase [95% CI 1.1-1.5], p = 0.010), presence of lacunes (1.5 [95% CI 1.1-2.0], p = 0.008), mean diffusivity (HR 1.1 per 1-SD increase [95% CI 1.1-1.2], p = 0.001), and total brain volume (HR 1.5 per 1-SD decrease [95% CI 1.3-1.9], p \\textless 0.001) were associated with all-cause mortality after adjusting for age, sex, and vascular risk factors. Total brain volume decrease over time was associated with all-cause mortality after adjusting for age, sex, and vascular risk factors (HR 1.3 per 1-SD decrease [95% CI 1.1-1.7], p = 0.035), and gray matter volume decrease remained significant after additionally adjusting for its baseline volume (1.3 per 1-SD decrease [1.1-1.6], p = 0.019). Participants with a Fazekas score of 3, presence of lacunes, or lower microstructural integrity had an excess long-term mortality risk (21.8, 15.7, 10.1 per 1,000 person-years, respectively) compared with the general population. DISCUSSION: Excess long-term mortality risk only exists in patients with severe SVD (Fazekas score of 3, presence of lacunes, or lower microstructural integrity). This could help in assisting clinicians to predict the clinical outcomes of patients with SVD by severity.\n

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\n \n\n \n \n \n \n \n Association of NOTCH3 Variant Risk Category With 2-Year Clinical and Radiologic Small Vessel Disease Progression in Patients With CADASIL.\n \n \n \n\n\n \n Cerfontaine, M. N.; Hack, R. J.; Gesierich, B.; Duering, M.; Witjes-Ané, M. W.; Rodríguez-Girondo, M.; Gravesteijn, G.; Rutten, J.; and Lesnik Oberstein, S. A. J.\n\n\n \n\n\n\n Neurology, 102(10): e209310. May 2024.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{cerfontaine_association_2024,\n\ttitle = {Association of {NOTCH3} {Variant} {Risk} {Category} {With} 2-{Year} {Clinical} and {Radiologic} {Small} {Vessel} {Disease} {Progression} in {Patients} {With} {CADASIL}},\n\tvolume = {102},\n\tissn = {1526-632X},\n\tdoi = {10.1212/WNL.0000000000209310},\n\tabstract = {BACKGROUND AND OBJECTIVES: Pathogenic variants in NOTCH3 are the main cause of hereditary cerebral small vessel disease (SVD). SVD-associated NOTCH3 variants have recently been categorized into high risk (HR), moderate risk (MR), or low risk (LR) for developing early-onset severe SVD. The most severe NOTCH3-associated SVD phenotype is also known as cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL). We aimed to investigate whether NOTCH3 variant risk category is associated with 2-year progression rate of SVD clinical and neuroimaging outcomes in CADASIL.\nMETHODS: A single-center prospective 2-year follow-up study was performed of patients with CADASIL. Clinical outcomes were incident stroke, disability (modified Rankin Scale), and executive function (Trail Making Test B given A t-scores). Neuroimaging outcomes were mean skeletonized mean diffusivity (MSMD), normalized white matter hyperintensity volume (nWMHv), normalized lacune volume (nLV), and brain parenchymal fraction (BPF). Cox regression and mixed-effect models, adjusted for age, sex, and cardiovascular risk factors, were used to study 2-year changes in outcomes and differences in disease progression between patients with HR-NOTCH3 and MR-NOTCH3 variants.\nRESULTS: One hundred sixty-two patients with HR (n = 90), MR (n = 67), and LR (n = 5) NOTCH3 variants were included. For the entire cohort, there was 2-year mean progression for MSMD (β = 0.20, 95\\% CI 0.17-0.23, p = 7.0 × 10-24), nLV (β = 0.13, 95\\% CI 0.080-0.19, p = 2.1 × 10-6), nWMHv (β = 0.092, 95\\% CI 0.075-0.11, p = 8.8 × 10-20), and BPF (β = -0.22, 95\\% CI -0.26 to -0.19, p = 3.2 × 10-22), as well as an increase in disability (p = 0.002) and decline of executive function (β = -0.15, 95\\% CI -0.30 to -3.4 × 10-5, p = 0.05). The HR-NOTCH3 group had a higher probability of 2-year incident stroke (hazard ratio 4.3, 95\\% CI 1.4-13.5, p = 0.011), and a higher increase in MSMD (β = 0.074, 95\\% CI 0.013-0.14, p = 0.017) and nLV (β = 0.14, 95\\% CI 0.034-0.24, p = 0.0089) than the MR-NOTCH3 group. Subgroup analyses showed significant 2-year progression of MSMD in young (n = 17, β = 0.014, 95\\% CI 0.0093-0.019, p = 1.4 × 10-5) and premanifest (n = 24, β = 0.012, 95\\% CI 0.0082-0.016, p = 1.1 × 10-6) individuals.\nDISCUSSION: In a trial-sensitive time span of 2 years, we found that patients with HR-NOTCH3 variants have a significantly faster progression of major clinical and neuroimaging outcomes, compared with patients with MR-NOTCH3 variants. This has important implications for clinical trial design and disease prediction and monitoring in the clinic. Moreover, we show that MSMD is a promising outcome measure for trials enrolling premanifest individuals.},\n\tlanguage = {eng},\n\tnumber = {10},\n\tjournal = {Neurology},\n\tauthor = {Cerfontaine, Minne N. and Hack, Remco J. and Gesierich, Benno and Duering, Marco and Witjes-Ané, Marie-Noëlle W. and Rodríguez-Girondo, Mar and Gravesteijn, Gido and Rutten, Julie and Lesnik Oberstein, Saskia A. J.},\n\tmonth = may,\n\tyear = {2024},\n\tpmid = {38713890},\n\tpmcid = {PMC11177591},\n\tkeywords = {Disease Progression, Female, Humans, Male, Prospective Studies, Follow-Up Studies, Magnetic Resonance Imaging, Risk Factors, Receptor, Notch3, Executive Function, Cerebral Small Vessel Diseases, CADASIL},\n\tpages = {e209310},\n}\n\n

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\n BACKGROUND AND OBJECTIVES: Pathogenic variants in NOTCH3 are the main cause of hereditary cerebral small vessel disease (SVD). SVD-associated NOTCH3 variants have recently been categorized into high risk (HR), moderate risk (MR), or low risk (LR) for developing early-onset severe SVD. The most severe NOTCH3-associated SVD phenotype is also known as cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL). We aimed to investigate whether NOTCH3 variant risk category is associated with 2-year progression rate of SVD clinical and neuroimaging outcomes in CADASIL. METHODS: A single-center prospective 2-year follow-up study was performed of patients with CADASIL. Clinical outcomes were incident stroke, disability (modified Rankin Scale), and executive function (Trail Making Test B given A t-scores). Neuroimaging outcomes were mean skeletonized mean diffusivity (MSMD), normalized white matter hyperintensity volume (nWMHv), normalized lacune volume (nLV), and brain parenchymal fraction (BPF). Cox regression and mixed-effect models, adjusted for age, sex, and cardiovascular risk factors, were used to study 2-year changes in outcomes and differences in disease progression between patients with HR-NOTCH3 and MR-NOTCH3 variants. RESULTS: One hundred sixty-two patients with HR (n = 90), MR (n = 67), and LR (n = 5) NOTCH3 variants were included. For the entire cohort, there was 2-year mean progression for MSMD (β = 0.20, 95% CI 0.17-0.23, p = 7.0 × 10-24), nLV (β = 0.13, 95% CI 0.080-0.19, p = 2.1 × 10-6), nWMHv (β = 0.092, 95% CI 0.075-0.11, p = 8.8 × 10-20), and BPF (β = -0.22, 95% CI -0.26 to -0.19, p = 3.2 × 10-22), as well as an increase in disability (p = 0.002) and decline of executive function (β = -0.15, 95% CI -0.30 to -3.4 × 10-5, p = 0.05). The HR-NOTCH3 group had a higher probability of 2-year incident stroke (hazard ratio 4.3, 95% CI 1.4-13.5, p = 0.011), and a higher increase in MSMD (β = 0.074, 95% CI 0.013-0.14, p = 0.017) and nLV (β = 0.14, 95% CI 0.034-0.24, p = 0.0089) than the MR-NOTCH3 group. Subgroup analyses showed significant 2-year progression of MSMD in young (n = 17, β = 0.014, 95% CI 0.0093-0.019, p = 1.4 × 10-5) and premanifest (n = 24, β = 0.012, 95% CI 0.0082-0.016, p = 1.1 × 10-6) individuals. DISCUSSION: In a trial-sensitive time span of 2 years, we found that patients with HR-NOTCH3 variants have a significantly faster progression of major clinical and neuroimaging outcomes, compared with patients with MR-NOTCH3 variants. This has important implications for clinical trial design and disease prediction and monitoring in the clinic. Moreover, we show that MSMD is a promising outcome measure for trials enrolling premanifest individuals.\n

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\n \n\n \n \n \n \n \n Meso-cortical pathway damage in cognition, apathy and gait in cerebral small vessel disease.\n \n \n \n\n\n \n Li, H.; Jacob, M. A.; Cai, M.; Kessels, R. P. C.; Norris, D. G.; Duering, M.; de Leeuw, F.; and Tuladhar, A. M.\n\n\n \n\n\n\n Brain,awae145. May 2024.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{li_meso-cortical_2024,\n\ttitle = {Meso-cortical pathway damage in cognition, apathy and gait in cerebral small vessel disease},\n\tissn = {1460-2156},\n\tdoi = {10.1093/brain/awae145},\n\tabstract = {Cerebral small vessel disease (SVD) is known to contribute to cognitive impairment, apathy, and gait dysfunction. Although associations between cognitive impairment and either apathy or gait dysfunction have been shown in SVD, the inter-relations among these three clinical features and their potential common neural basis remains unexplored. The dopaminergic meso-cortical and meso-limbic pathways have been known as the important brain circuits for both cognitive control, emotion regulation and motor function. Here, we investigated the potential inter-relations between cognitive impairment, apathy, and gait dysfunction, with a specific focus on determining whether these clinical features are associated with damage to the meso-cortical and meso-limbic pathways in SVD. In this cross-sectional study, we included 213 participants with SVD in whom MRI scans and comprehensive neurobehavioral assessments were administered. These assessments comprised of six clinical measures: processing speed, executive function, memory, apathy (based on the Apathy Evaluation Scale), and gait function (based on the time and steps in Timed Up and Go test). We reconstructed five tracts connecting ventral tegmental area (VTA) and the dorsolateral prefrontal cortex (dlPFC), ventral lateral PFC (vlPFC), medial orbitofrontal cortex (mOFC), anterior cingulate cortex (ACC) and nucleus accumbens (NAc) within meso-cortical and meso-limbic pathways using diffusion weighted imaging. The damage along the five tracts was quantified using the free water (FW) and FW-corrected mean diffusivity (MD-t) indices. Furthermore, we explored the inter-correlations among the six clinical measures and identified their common components using principal component analysis (PCA). Linear regression analyses showed that higher FW values of tracts within meso-cortical pathways were related to these clinical measures in cognition, apathy, and gait (all P-corrected values {\\textless} 0.05). PCA showed strong inter-associations among these clinical measures and identified a common component wherein all six clinical measures loaded on. Higher FW values of tracts within meso-cortical pathways were related to the PCA-derived common component (all P-corrected values {\\textless} 0.05). Moreover, FW values of VTA-ACC tract showed the strongest contribution to the PCA-derived common component over all other neuroimaging features. In conclusion, our study showed that the three clinical features (cognitive impairment, apathy, and gait dysfunction) of SVD are strongly inter-related and that the damage in meso-cortical pathway could be the common neural basis underlying the three features in SVD. These findings advance our understanding of the mechanisms behind these clinical features of SVD and have the potential to inform novel management and intervention strategies for SVD.},\n\tlanguage = {eng},\n\tjournal = {Brain},\n\tauthor = {Li, Hao and Jacob, Mina A. and Cai, Mengfei and Kessels, Roy P. C. and Norris, David G. and Duering, Marco and de Leeuw, Frank-Erik and Tuladhar, Anil M.},\n\tmonth = may,\n\tyear = {2024},\n\tpmid = {38709856},\n\tkeywords = {Aged, Aged, 80 and over, apathy, Apathy, Cerebral Cortex, cerebral small vessel disease, Cerebral Small Vessel Diseases, Cognition, Cognitive Dysfunction, cognitive impairment, Cross-Sectional Studies, Female, Gait, Gait Disorders, Neurologic, gait dysfunction, Humans, Magnetic Resonance Imaging, Male, meso-cortico-limbic system, Middle Aged, Neural Pathways, Neuropsychological Tests},\n\tpages = {awae145},\n}\n\n

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\n Cerebral small vessel disease (SVD) is known to contribute to cognitive impairment, apathy, and gait dysfunction. Although associations between cognitive impairment and either apathy or gait dysfunction have been shown in SVD, the inter-relations among these three clinical features and their potential common neural basis remains unexplored. The dopaminergic meso-cortical and meso-limbic pathways have been known as the important brain circuits for both cognitive control, emotion regulation and motor function. Here, we investigated the potential inter-relations between cognitive impairment, apathy, and gait dysfunction, with a specific focus on determining whether these clinical features are associated with damage to the meso-cortical and meso-limbic pathways in SVD. In this cross-sectional study, we included 213 participants with SVD in whom MRI scans and comprehensive neurobehavioral assessments were administered. These assessments comprised of six clinical measures: processing speed, executive function, memory, apathy (based on the Apathy Evaluation Scale), and gait function (based on the time and steps in Timed Up and Go test). We reconstructed five tracts connecting ventral tegmental area (VTA) and the dorsolateral prefrontal cortex (dlPFC), ventral lateral PFC (vlPFC), medial orbitofrontal cortex (mOFC), anterior cingulate cortex (ACC) and nucleus accumbens (NAc) within meso-cortical and meso-limbic pathways using diffusion weighted imaging. The damage along the five tracts was quantified using the free water (FW) and FW-corrected mean diffusivity (MD-t) indices. Furthermore, we explored the inter-correlations among the six clinical measures and identified their common components using principal component analysis (PCA). Linear regression analyses showed that higher FW values of tracts within meso-cortical pathways were related to these clinical measures in cognition, apathy, and gait (all P-corrected values \\textless 0.05). PCA showed strong inter-associations among these clinical measures and identified a common component wherein all six clinical measures loaded on. Higher FW values of tracts within meso-cortical pathways were related to the PCA-derived common component (all P-corrected values \\textless 0.05). Moreover, FW values of VTA-ACC tract showed the strongest contribution to the PCA-derived common component over all other neuroimaging features. In conclusion, our study showed that the three clinical features (cognitive impairment, apathy, and gait dysfunction) of SVD are strongly inter-related and that the damage in meso-cortical pathway could be the common neural basis underlying the three features in SVD. These findings advance our understanding of the mechanisms behind these clinical features of SVD and have the potential to inform novel management and intervention strategies for SVD.\n

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\n \n\n \n \n \n \n \n Strategic white matter hyperintensity locations associated with post-stroke cognitive impairment: A multicenter study in 1568 stroke patients.\n \n \n \n\n\n \n Coenen, M.; de Kort, F. A.; Weaver, N. A.; Kuijf, H. J.; Aben, H. P.; Bae, H.; Bordet, R.; Chen, C. P.; Dewenter, A.; Doeven, T.; Dondaine, T.; Duering, M.; Fang, R.; van der Giessen, R. S.; Kim, J.; Kim, B. J.; de Kort, P. L.; Koudstaal, P. J.; Lee, M.; Lim, J.; Lopes, R.; van Oostenbrugge, R. J.; Staals, J.; Yu, K.; Biessels, G. J.; and Biesbroek, J. M.\n\n\n \n\n\n\n Int J Stroke,17474930241252530. June 2024.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n\n\n\n

@article{coenen_strategic_2024,\n\ttitle = {Strategic white matter hyperintensity locations associated with post-stroke cognitive impairment: {A} multicenter study in 1568 stroke patients},\n\tissn = {1747-4949},\n\tshorttitle = {Strategic white matter hyperintensity locations associated with post-stroke cognitive impairment},\n\tdoi = {10.1177/17474930241252530},\n\tabstract = {BACKGROUND: Post-stroke cognitive impairment (PSCI) occurs in up to 50\\% of stroke survivors. Presence of pre-existing vascular brain injury, in particular the extent of white matter hyperintensities (WMH), is associated with worse cognitive outcome after stroke, but the role of WMH location in this association is unclear.\nAIMS: We determined if WMH in strategic white matter tracts explain cognitive performance after stroke.\nMETHODS: Individual patient data from nine ischemic stroke cohorts with magnetic resonance imaging (MRI) were harmonized through the Meta VCI Map consortium. The association between WMH volumes in strategic tracts and domain-specific cognitive functioning (attention and executive functioning, information processing speed, language and verbal memory) was assessed using linear mixed models and lasso regression. We used a hypothesis-driven design, primarily addressing four white matter tracts known to be strategic in memory clinic patients: the left and right anterior thalamic radiation, forceps major, and left inferior fronto-occipital fasciculus.\nRESULTS: The total study sample consisted of 1568 patients (39.9\\% female, mean age = 67.3 years). Total WMH volume was strongly related to cognitive performance on all four cognitive domains. WMH volume in the left anterior thalamic radiation was significantly associated with cognitive performance on attention and executive functioning and information processing speed and WMH volume in the forceps major with information processing speed. The multivariable lasso regression showed that these associations were independent of age, sex, education, and total infarct volume and had larger coefficients than total WMH volume.\nCONCLUSION: These results show tract-specific relations between WMH volume and cognitive performance after ischemic stroke, independent of total WMH volume. This implies that the concept of strategic lesions in PSCI extends beyond acute infarcts and also involves pre-existing WMH.\nDATA ACCESS STATEMENT: The Meta VCI Map consortium is dedicated to data sharing, following our guidelines.},\n\tlanguage = {eng},\n\tjournal = {Int J Stroke},\n\tauthor = {Coenen, Mirthe and de Kort, Floor As and Weaver, Nick A. and Kuijf, Hugo J. and Aben, Hugo P. and Bae, Hee-Joon and Bordet, Régis and Chen, Christopher Plh and Dewenter, Anna and Doeven, Thomas and Dondaine, Thibaut and Duering, Marco and Fang, Rong and van der Giessen, Ruben S. and Kim, Jonguk and Kim, Beom Joon and de Kort, Paul Lm and Koudstaal, Peter J. and Lee, Minwoo and Lim, Jae-Sung and Lopes, Renaud and van Oostenbrugge, Robert J. and Staals, Julie and Yu, Kyung-Ho and Biessels, Geert Jan and Biesbroek, J. Matthijs},\n\tmonth = jun,\n\tyear = {2024},\n\tpmid = {38651756},\n\tkeywords = {White matter hyperintensities, post-stroke cognition, strategic lesion location},\n\tpages = {17474930241252530},\n}\n\n

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\n BACKGROUND: Post-stroke cognitive impairment (PSCI) occurs in up to 50% of stroke survivors. Presence of pre-existing vascular brain injury, in particular the extent of white matter hyperintensities (WMH), is associated with worse cognitive outcome after stroke, but the role of WMH location in this association is unclear. AIMS: We determined if WMH in strategic white matter tracts explain cognitive performance after stroke. METHODS: Individual patient data from nine ischemic stroke cohorts with magnetic resonance imaging (MRI) were harmonized through the Meta VCI Map consortium. The association between WMH volumes in strategic tracts and domain-specific cognitive functioning (attention and executive functioning, information processing speed, language and verbal memory) was assessed using linear mixed models and lasso regression. We used a hypothesis-driven design, primarily addressing four white matter tracts known to be strategic in memory clinic patients: the left and right anterior thalamic radiation, forceps major, and left inferior fronto-occipital fasciculus. RESULTS: The total study sample consisted of 1568 patients (39.9% female, mean age = 67.3 years). Total WMH volume was strongly related to cognitive performance on all four cognitive domains. WMH volume in the left anterior thalamic radiation was significantly associated with cognitive performance on attention and executive functioning and information processing speed and WMH volume in the forceps major with information processing speed. The multivariable lasso regression showed that these associations were independent of age, sex, education, and total infarct volume and had larger coefficients than total WMH volume. CONCLUSION: These results show tract-specific relations between WMH volume and cognitive performance after ischemic stroke, independent of total WMH volume. This implies that the concept of strategic lesions in PSCI extends beyond acute infarcts and also involves pre-existing WMH. DATA ACCESS STATEMENT: The Meta VCI Map consortium is dedicated to data sharing, following our guidelines.\n

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\n \n\n \n \n \n \n \n Perivascular Spaces, Diffusivity Along Perivascular Spaces, and Free Water in Cerebral Small Vessel Disease.\n \n \n \n\n\n \n Li, H.; Jacob, M. A.; Cai, M.; Kessels, R. P. C.; Norris, D. G.; Duering, M.; De Leeuw, F.; and Tuladhar, A. M.\n\n\n \n\n\n\n Neurology, 102(9): e209306. May 2024.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{li_perivascular_2024,\n\ttitle = {Perivascular {Spaces}, {Diffusivity} {Along} {Perivascular} {Spaces}, and {Free} {Water} in {Cerebral} {Small} {Vessel} {Disease}},\n\tvolume = {102},\n\tissn = {1526-632X},\n\tdoi = {10.1212/WNL.0000000000209306},\n\tabstract = {BACKGROUND AND OBJECTIVES: Previous studies have linked the MRI measures of perivascular spaces (PVSs), diffusivity along the perivascular spaces (DTI-ALPS), and free water (FW) to cerebral small vessel disease (SVD) and SVD-related cognitive impairments. However, studies on the longitudinal associations between the three MRI measures, SVD progression, and cognitive decline are lacking. This study aimed to explore how PVS, DTI-ALPS, and FW contribute to SVD progression and cognitive decline.\nMETHODS: This is a cohort study that included participants with SVD who underwent neuroimaging and cognitive assessment, specifically measuring Mini-Mental State Examination (MMSE), cognitive index, and processing speed, at 2 time points. Three MRI measures were quantified: PVS in basal ganglia (BG-PVS) volumes, FW fraction, and DTI-ALPS. We performed a latent change score model to test inter-relations between the 3 MRI measures and linear regression mixed models to test their longitudinal associations with the changes of other SVD MRI markers and cognitive performances.\nRESULTS: In baseline assessment, we included 289 participants with SVD, characterized by a median age of 67.0 years and 42.9\\% women. Of which, 220 participants underwent the follow-up assessment, with a median follow-up time of 3.4 years. Baseline DTI-ALPS was associated with changes in BG-PVS volumes (β = -0.09, p = 0.030), but not vice versa (β = -0.08, p = 0.110). Baseline BG-PVS volumes were associated with changes in white matter hyperintensity (WMH) volumes (β = 0.33, p-corrected {\\textless} 0.001) and lacune numbers (β = 0.28, p-corrected {\\textless} 0.001); FW fraction was associated with changes in WMH volumes (β = 0.30, p-corrected {\\textless} 0.001), lacune numbers (β = 0.28, p-corrected {\\textless} 0.001), and brain volumes (β = -0.45, p-corrected {\\textless} 0.001); DTI-ALPS was associated with changes in WMH volumes (β = -0.20, p-corrected = 0.002) and brain volumes (β = 0.23, p-corrected {\\textless} 0.001). Furthermore, baseline FW fraction was associated with decline in MMSE score (β = -0.17, p-corrected = 0.006); baseline FW fraction and DTI-ALPS were associated with changes in cognitive index (FW fraction: β = -0.25, p-corrected {\\textless} 0.001; DTI-ALPS: β = 0.20, p-corrected = 0.001) and processing speed over time (FW fraction: β = -0.29, p-corrected {\\textless} 0.001; DTI-ALPS: β = 0.21, p-corrected {\\textless} 0.001).\nDISCUSSION: Our results showed that increased BG-PVS volumes, increased FW fraction, and decreased DTI-ALPS are related to progression of MRI markers of SVD, along with SVD-related cognitive decline over time. These findings may suggest that the glymphatic dysfunction is related to SVD progression, but further studies are needed.},\n\tlanguage = {eng},\n\tnumber = {9},\n\tjournal = {Neurology},\n\tauthor = {Li, Hao and Jacob, Mina A. and Cai, Mengfei and Kessels, Roy P. C. and Norris, David G. and Duering, Marco and De Leeuw, Frank-Erik and Tuladhar, Anil Man},\n\tmonth = may,\n\tyear = {2024},\n\tpmid = {38626373},\n\tkeywords = {Aged, Female, Humans, Male, Magnetic Resonance Imaging, Cohort Studies, Cerebral Small Vessel Diseases, Water, Cognitive Dysfunction},\n\tpages = {e209306},\n}\n\n

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\n BACKGROUND AND OBJECTIVES: Previous studies have linked the MRI measures of perivascular spaces (PVSs), diffusivity along the perivascular spaces (DTI-ALPS), and free water (FW) to cerebral small vessel disease (SVD) and SVD-related cognitive impairments. However, studies on the longitudinal associations between the three MRI measures, SVD progression, and cognitive decline are lacking. This study aimed to explore how PVS, DTI-ALPS, and FW contribute to SVD progression and cognitive decline. METHODS: This is a cohort study that included participants with SVD who underwent neuroimaging and cognitive assessment, specifically measuring Mini-Mental State Examination (MMSE), cognitive index, and processing speed, at 2 time points. Three MRI measures were quantified: PVS in basal ganglia (BG-PVS) volumes, FW fraction, and DTI-ALPS. We performed a latent change score model to test inter-relations between the 3 MRI measures and linear regression mixed models to test their longitudinal associations with the changes of other SVD MRI markers and cognitive performances. RESULTS: In baseline assessment, we included 289 participants with SVD, characterized by a median age of 67.0 years and 42.9% women. Of which, 220 participants underwent the follow-up assessment, with a median follow-up time of 3.4 years. Baseline DTI-ALPS was associated with changes in BG-PVS volumes (β = -0.09, p = 0.030), but not vice versa (β = -0.08, p = 0.110). Baseline BG-PVS volumes were associated with changes in white matter hyperintensity (WMH) volumes (β = 0.33, p-corrected \\textless 0.001) and lacune numbers (β = 0.28, p-corrected \\textless 0.001); FW fraction was associated with changes in WMH volumes (β = 0.30, p-corrected \\textless 0.001), lacune numbers (β = 0.28, p-corrected \\textless 0.001), and brain volumes (β = -0.45, p-corrected \\textless 0.001); DTI-ALPS was associated with changes in WMH volumes (β = -0.20, p-corrected = 0.002) and brain volumes (β = 0.23, p-corrected \\textless 0.001). Furthermore, baseline FW fraction was associated with decline in MMSE score (β = -0.17, p-corrected = 0.006); baseline FW fraction and DTI-ALPS were associated with changes in cognitive index (FW fraction: β = -0.25, p-corrected \\textless 0.001; DTI-ALPS: β = 0.20, p-corrected = 0.001) and processing speed over time (FW fraction: β = -0.29, p-corrected \\textless 0.001; DTI-ALPS: β = 0.21, p-corrected \\textless 0.001). DISCUSSION: Our results showed that increased BG-PVS volumes, increased FW fraction, and decreased DTI-ALPS are related to progression of MRI markers of SVD, along with SVD-related cognitive decline over time. These findings may suggest that the glymphatic dysfunction is related to SVD progression, but further studies are needed.\n

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\n \n\n \n \n \n \n \n Enhancing Cognitive Performance Prediction through White Matter Hyperintensity Connectivity Assessment: A Multicenter Lesion Network Mapping Analysis of 3,485 Memory Clinic Patients.\n \n \n \n\n\n \n Petersen, M.; Coenen, M.; DeCarli, C.; De Luca, A.; van der Lelij, E.; Alzheimer’s Disease Neuroimaging Initiative; Barkhof, F.; Benke, T.; Chen, C. P. L. H.; Dal-Bianco, P.; Dewenter, A.; Duering, M.; Enzinger, C.; Ewers, M.; Exalto, L. G.; Fletcher, E. F.; Franzmeier, N.; Hilal, S.; Hofer, E.; Koek, H. L.; Maier, A. B.; Maillard, P. M.; McCreary, C. R.; Papma, J. M.; Pijnenburg, Y. A. L.; Schmidt, R.; Smith, E. E.; Steketee, R. M. E.; van den Berg, E.; van der Flier, W. M.; Venkatraghavan, V.; Venketasubramanian, N.; Vernooij, M. W.; Wolters, F. J.; Xu, X.; Horn, A.; Patil, K. R.; Eickhoff, S. B.; Thomalla, G.; Biesbroek, J. M.; Biessels, G. J.; and Cheng, B.\n\n\n \n\n\n\n medRxiv,2024.03.28.24305007. April 2024.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{petersen_enhancing_2024,\n\ttitle = {Enhancing {Cognitive} {Performance} {Prediction} through {White} {Matter} {Hyperintensity} {Connectivity} {Assessment}: {A} {Multicenter} {Lesion} {Network} {Mapping} {Analysis} of 3,485 {Memory} {Clinic} {Patients}},\n\tshorttitle = {Enhancing {Cognitive} {Performance} {Prediction} through {White} {Matter} {Hyperintensity} {Connectivity} {Assessment}},\n\tdoi = {10.1101/2024.03.28.24305007},\n\tabstract = {INTRODUCTION: White matter hyperintensities of presumed vascular origin (WMH) are associated with cognitive impairment and are a key imaging marker in evaluating cognitive health. However, WMH volume alone does not fully account for the extent of cognitive deficits and the mechanisms linking WMH to these deficits remain unclear. We propose that lesion network mapping (LNM), enables to infer if brain networks are connected to lesions, and could be a promising technique for enhancing our understanding of the role of WMH in cognitive disorders. Our study employed this approach to test the following hypotheses: (1) LNM-informed markers surpass WMH volumes in predicting cognitive performance, and (2) WMH contributing to cognitive impairment map to specific brain networks.\nMETHODS \\& RESULTS: We analyzed cross-sectional data of 3,485 patients from 10 memory clinic cohorts within the Meta VCI Map Consortium, using harmonized test results in 4 cognitive domains and WMH segmentations. WMH segmentations were registered to a standard space and mapped onto existing normative structural and functional brain connectome data. We employed LNM to quantify WMH connectivity across 480 atlas-based gray and white matter regions of interest (ROI), resulting in ROI-level structural and functional LNM scores. The capacity of total and regional WMH volumes and LNM scores in predicting cognitive function was compared using ridge regression models in a nested cross-validation. LNM scores predicted performance in three cognitive domains (attention and executive function, information processing speed, and verbal memory) significantly better than WMH volumes. LNM scores did not improve prediction for language functions. ROI-level analysis revealed that higher LNM scores, representing greater disruptive effects of WMH on regional connectivity, in gray and white matter regions of the dorsal and ventral attention networks were associated with lower cognitive performance.\nCONCLUSION: Measures of WMH-related brain network connectivity significantly improve the prediction of current cognitive performance in memory clinic patients compared to WMH volume as a traditional imaging marker of cerebrovascular disease. This highlights the crucial role of network effects, particularly in attentionrelated brain regions, improving our understanding of vascular contributions to cognitive impairment. Moving forward, refining WMH information with connectivity data could contribute to patient-tailored therapeutic interventions and facilitate the identification of subgroups at risk of cognitive disorders.},\n\tlanguage = {eng},\n\tjournal = {medRxiv},\n\tauthor = {Petersen, Marvin and Coenen, Mirthe and DeCarli, Charles and De Luca, Alberto and van der Lelij, Ewoud and {Alzheimer’s Disease Neuroimaging Initiative} and Barkhof, Frederik and Benke, Thomas and Chen, Christopher P. L. H. and Dal-Bianco, Peter and Dewenter, Anna and Duering, Marco and Enzinger, Christian and Ewers, Michael and Exalto, Lieza G. and Fletcher, Evan F. and Franzmeier, Nicolai and Hilal, Saima and Hofer, Edith and Koek, Huiberdina L. and Maier, Andrea B. and Maillard, Pauline M. and McCreary, Cheryl R. and Papma, Janne M. and Pijnenburg, Yolande A. L. and Schmidt, Reinhold and Smith, Eric E. and Steketee, Rebecca M. E. and van den Berg, Esther and van der Flier, Wiesje M. and Venkatraghavan, Vikram and Venketasubramanian, Narayanaswamy and Vernooij, Meike W. and Wolters, Frank J. and Xu, Xin and Horn, Andreas and Patil, Kaustubh R. and Eickhoff, Simon B. and Thomalla, Götz and Biesbroek, J. Matthijs and Biessels, Geert Jan and Cheng, Bastian},\n\tmonth = apr,\n\tyear = {2024},\n\tpmid = {38586023},\n\tpmcid = {PMC10996741},\n\tpages = {2024.03.28.24305007},\n}\n\n

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\n INTRODUCTION: White matter hyperintensities of presumed vascular origin (WMH) are associated with cognitive impairment and are a key imaging marker in evaluating cognitive health. However, WMH volume alone does not fully account for the extent of cognitive deficits and the mechanisms linking WMH to these deficits remain unclear. We propose that lesion network mapping (LNM), enables to infer if brain networks are connected to lesions, and could be a promising technique for enhancing our understanding of the role of WMH in cognitive disorders. Our study employed this approach to test the following hypotheses: (1) LNM-informed markers surpass WMH volumes in predicting cognitive performance, and (2) WMH contributing to cognitive impairment map to specific brain networks. METHODS & RESULTS: We analyzed cross-sectional data of 3,485 patients from 10 memory clinic cohorts within the Meta VCI Map Consortium, using harmonized test results in 4 cognitive domains and WMH segmentations. WMH segmentations were registered to a standard space and mapped onto existing normative structural and functional brain connectome data. We employed LNM to quantify WMH connectivity across 480 atlas-based gray and white matter regions of interest (ROI), resulting in ROI-level structural and functional LNM scores. The capacity of total and regional WMH volumes and LNM scores in predicting cognitive function was compared using ridge regression models in a nested cross-validation. LNM scores predicted performance in three cognitive domains (attention and executive function, information processing speed, and verbal memory) significantly better than WMH volumes. LNM scores did not improve prediction for language functions. ROI-level analysis revealed that higher LNM scores, representing greater disruptive effects of WMH on regional connectivity, in gray and white matter regions of the dorsal and ventral attention networks were associated with lower cognitive performance. CONCLUSION: Measures of WMH-related brain network connectivity significantly improve the prediction of current cognitive performance in memory clinic patients compared to WMH volume as a traditional imaging marker of cerebrovascular disease. This highlights the crucial role of network effects, particularly in attentionrelated brain regions, improving our understanding of vascular contributions to cognitive impairment. Moving forward, refining WMH information with connectivity data could contribute to patient-tailored therapeutic interventions and facilitate the identification of subgroups at risk of cognitive disorders.\n

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\n \n\n \n \n \n \n \n Amyloid pathology and vascular risk are associated with distinct patterns of cerebral white matter hyperintensities: A multicenter study in 3132 memory clinic patients.\n \n \n \n\n\n \n Biesbroek, J. M.; Coenen, M.; DeCarli, C.; Fletcher, E. M.; Maillard, P. M.; Alzheimer's Disease Neuroimaging Initiative; Barkhof, F.; Barnes, J.; Benke, T.; Chen, C. P. L. H.; Dal-Bianco, P.; Dewenter, A.; Duering, M.; Enzinger, C.; Ewers, M.; Exalto, L. G.; Franzmeier, N.; Hilal, S.; Hofer, E.; Koek, H. L.; Maier, A. B.; McCreary, C. R.; Papma, J. M.; Paterson, R. W.; Pijnenburg, Y. A. L.; Rubinski, A.; Schmidt, R.; Schott, J. M.; Slattery, C. F.; Smith, E. E.; Sudre, C. H.; Steketee, R. M. E.; Teunissen, C. E.; van den Berg, E.; van der Flier, W. M.; Venketasubramanian, N.; Venkatraghavan, V.; Vernooij, M. W.; Wolters, F. J.; Xin, X.; Kuijf, H. J.; and Biessels, G. J.\n\n\n \n\n\n\n Alzheimers Dement, 20(4): 2980–2989. April 2024.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{biesbroek_amyloid_2024,\n\ttitle = {Amyloid pathology and vascular risk are associated with distinct patterns of cerebral white matter hyperintensities: {A} multicenter study in 3132 memory clinic patients},\n\tvolume = {20},\n\tissn = {1552-5279},\n\tshorttitle = {Amyloid pathology and vascular risk are associated with distinct patterns of cerebral white matter hyperintensities},\n\tdoi = {10.1002/alz.13765},\n\tabstract = {INTRODUCTION: White matter hyperintensities (WMH) are associated with key dementia etiologies, in particular arteriolosclerosis and amyloid pathology. We aimed to identify WMH locations associated with vascular risk or cerebral amyloid-β1-42 (Aβ42)-positive status.\nMETHODS: Individual patient data (n = 3,132; mean age 71.5 ± 9 years; 49.3\\% female) from 11 memory clinic cohorts were harmonized. WMH volumes in 28 regions were related to a vascular risk compound score (VRCS) and Aß42 status (based on cerebrospinal fluid or amyloid positron emission tomography), correcting for age, sex, study site, and total WMH volume.\nRESULTS: VRCS was associated with WMH in anterior/superior corona radiata (B = 0.034/0.038, p {\\textless} 0.001), external capsule (B = 0.052, p {\\textless} 0.001), and middle cerebellar peduncle (B = 0.067, p {\\textless} 0.001), and Aß42-positive status with WMH in posterior thalamic radiation (B = 0.097, p {\\textless} 0.001) and splenium (B = 0.103, p {\\textless} 0.001).\nDISCUSSION: Vascular risk factors and Aß42 pathology have distinct signature WMH patterns. This regional vulnerability may incite future studies into how arteriolosclerosis and Aß42 pathology affect the brain's white matter.\nHIGHLIGHTS: Key dementia etiologies may be associated with specific patterns of white matter hyperintensities (WMH). We related WMH locations to vascular risk and cerebral Aβ42 status in 11 memory clinic cohorts. Aβ42 positive status was associated with posterior WMH in splenium and posterior thalamic radiation. Vascular risk was associated with anterior and infratentorial WMH. Amyloid pathology and vascular risk have distinct signature WMH patterns.},\n\tlanguage = {eng},\n\tnumber = {4},\n\tjournal = {Alzheimers Dement},\n\tauthor = {Biesbroek, J. Matthijs and Coenen, Mirthe and DeCarli, Charles and Fletcher, Evan M. and Maillard, Pauline M. and {Alzheimer's Disease Neuroimaging Initiative} and Barkhof, Frederik and Barnes, Josephine and Benke, Thomas and Chen, Christopher P. L. H. and Dal-Bianco, Peter and Dewenter, Anna and Duering, Marco and Enzinger, Christian and Ewers, Michael and Exalto, Lieza G. and Franzmeier, Nicolai and Hilal, Saima and Hofer, Edith and Koek, Huiberdina L. and Maier, Andrea B. and McCreary, Cheryl R. and Papma, Janne M. and Paterson, Ross W. and Pijnenburg, Yolande A. L. and Rubinski, Anna and Schmidt, Reinhold and Schott, Jonathan M. and Slattery, Catherine F. and Smith, Eric E. and Sudre, Carole H. and Steketee, Rebecca M. E. and Teunissen, Charlotte E. and van den Berg, Esther and van der Flier, Wiesje M. and Venketasubramanian, Narayanaswamy and Venkatraghavan, Vikram and Vernooij, Meike W. and Wolters, Frank J. and Xin, Xu and Kuijf, Hugo J. and Biessels, Geert Jan},\n\tmonth = apr,\n\tyear = {2024},\n\tpmid = {38477469},\n\tpmcid = {PMC11032573},\n\tkeywords = {dementia, Aged, Female, Humans, Male, Middle Aged, Aged, 80 and over, Magnetic Resonance Imaging, white matter hyperintensities, Dementia, Amyloid beta-Peptides, White Matter, amyloid pathology, arteriolosclerosis, Arteriolosclerosis, lesion pattern},\n\tpages = {2980--2989},\n}\n\n

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\n \n\n \n \n \n \n \n Visit-to-visit blood pressure variability and progression of white matter hyperintensities over 14 years.\n \n \n \n\n\n \n Janssen, E.; van Dalen, J. W.; Cai, M.; Jacob, M. A.; Marques, J.; Duering, M.; Richard, E.; Tuladhar, A. M.; de Leeuw, F.; and Hilkens, N.\n\n\n \n\n\n\n Blood Press, 33(1): 2314498. December 2024.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{janssen_visit--visit_2024,\n\ttitle = {Visit-to-visit blood pressure variability and progression of white matter hyperintensities over 14 years},\n\tvolume = {33},\n\tissn = {1651-1999},\n\tdoi = {10.1080/08037051.2024.2314498},\n\tabstract = {Purpose: There is evidence that blood pressure variability (BPV) is associated with cerebral small vessel disease (SVD) and may therefore increase the risk of stroke and dementia. It remains unclear if BPV is associated with SVD progression over years. We examined whether visit-to-visit BPV is associated with white matter hyperintensity (WMH) progression over 14 years and MRI markers after 14 years. Materials and methods: We included participants with SVD from the Radboud University Nijmegen Diffusion tensor Magnetic resonance-imaging Cohort (RUNDMC) who underwent baseline assessment in 2006 and follow-up in 2011, 2015 and 2020. BPV was calculated as coefficient of variation (CV) of BP at all visits. Association between WMH progression rates over 14 years and BPV was examined using linear-mixed effects (LME) model. Regression models were used to examine association between BPV and MRI markers at final visit in participants. Results: A total of 199 participants (60.5 SD 6.6 years) who underwent four MRI scans and BP measurements were included, with mean follow-up of 13.7 (SD 0.5) years. Systolic BPV was associated with higher progression of WMH (β = 0.013, 95\\% CI 0.005 - 0.022) and higher risk of incident lacunes (OR: 1.10, 95\\% CI 1.01-1.21). There was no association between systolic BPV and grey and white matter volumes, Peak Skeleton of Mean Diffusivity (PSMD) or microbleed count after 13.7 years. Conclusions: Visit-to-visit systolic BPV is associated with increased progression of WMH volumes and higher risk of incident lacunes over 14 years in participants with SVD. Future studies are needed to examine causality of this association.},\n\tlanguage = {eng},\n\tnumber = {1},\n\tjournal = {Blood Press},\n\tauthor = {Janssen, Esther and van Dalen, Jan Willem and Cai, Mengfei and Jacob, Mina A. and Marques, José and Duering, Marco and Richard, Edo and Tuladhar, Anil M. and de Leeuw, Frank-Erik and Hilkens, Nina},\n\tmonth = dec,\n\tyear = {2024},\n\tpmid = {38477113},\n\tkeywords = {Blood Pressure, Blood Pressure Determination, blood pressure variability, Cerebral small vessel disease, Disease Progression, Humans, hypertension, magnetic resonance imaging, Magnetic Resonance Imaging, Stroke, White Matter, white matter hyperintensity},\n\tpages = {2314498},\n}\n\n

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\n \n\n \n \n \n \n \n Association of Long-Term Blood Pressure Variability with Cerebral Amyloid Angiopathy-related Brain Injury and Cognitive Decline.\n \n \n \n\n\n \n Sveikata, L.; Zotin, M. C. Z.; Schoemaker, D.; Ma, Y.; Perosa, V.; Chokesuwattanaskul, A.; Charidimou, A.; Duering, M.; Gurol, E. M.; Assal, F.; Greenberg, S. M.; and Viswanathan, A.\n\n\n \n\n\n\n medRxiv,2024.02.24.24303071. February 2024.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{sveikata_association_2024,\n\ttitle = {Association of {Long}-{Term} {Blood} {Pressure} {Variability} with {Cerebral} {Amyloid} {Angiopathy}-related {Brain} {Injury} and {Cognitive} {Decline}},\n\tdoi = {10.1101/2024.02.24.24303071},\n\tabstract = {INTRODUCTION: Long-term systolic blood pressure variability (BPV) has been proposed as a novel risk factor for dementia, but the underlying mechanisms are largely unknown. We aimed to investigate the association between long-term blood pressure variability (BPV), brain injury, and cognitive decline in patients with mild cognitive symptoms and cerebral amyloid angiopathy (CAA), a well-characterized small-vessel disease that causes cognitive decline in older adults.\nMETHODS: Using a prospective memory clinic cohort, we enrolled 102 participants, of whom 52 with probable CAA. All underwent a 3-tesla research MRI at baseline and annual neuropsychological evaluation over 2 years, for which standardized z-scores for four cognitive domains were calculated. BPV was assessed using a coefficient of variation derived from serial outpatient BP measurements (median 12) over five years. We measured the peak width of skeletonized mean diffusivity (PSMD) as a marker of white matter integrity, and other neuroimaging markers of CAA, including lacunes and cortical cerebral microinfarcts. Using regression models, we evaluated the association of BPV with microstructural brain injury and whether CAA modified this association. We also examined the association of BPV with subsequent cognitive decline.\nRESULTS: Systolic BPV was dose-dependently associated with PSMD (estimate=0.22, 95\\% CI: 0.06, 0.39, p=0.010), independent of age, sex, mean BP, common vascular risk factors, brain atrophy, and CAA severity. The presence of probable CAA strengthened the association between BPV and PSMD (estimate=9.33, 95\\% CI: 1.32, 17.34, p for interaction = 0.023). Higher BPV correlated with greater ischemic injury (lobar lacunes and cortical cerebral microinfarcts) and a decline in global cognition and processing speed (estimate=-0.30, 95\\% CI: -0.55, -0.04, p=0.022).\nDISCUSSION: Long-term BPV has a dose-dependent association with alterations in white matter integrity, lobar lacunes, and cortical cerebral microinfarcts, and predicts cognitive decline. Controlling BPV is a potential strategic approach to prevent cognitive decline, especially in early-stage CAA.},\n\tlanguage = {eng},\n\tjournal = {medRxiv},\n\tauthor = {Sveikata, Lukas and Zotin, Maria Clara Zanon and Schoemaker, Dorothee and Ma, Yuan and Perosa, Valentina and Chokesuwattanaskul, Anthipa and Charidimou, Andreas and Duering, Marco and Gurol, Edip M. and Assal, Frédéric and Greenberg, Steven M. and Viswanathan, Anand},\n\tmonth = feb,\n\tyear = {2024},\n\tpmid = {38464316},\n\tpmcid = {PMC10925352},\n\tkeywords = {Alzheimer’s Disease, Blood pressure variability, Cerebral amyloid angiopathy, Cerebrovascular disease/Stroke, MCI (mild cognitive impairment), Vascular Dementia},\n\tpages = {2024.02.24.24303071},\n}\n\n

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\n INTRODUCTION: Long-term systolic blood pressure variability (BPV) has been proposed as a novel risk factor for dementia, but the underlying mechanisms are largely unknown. We aimed to investigate the association between long-term blood pressure variability (BPV), brain injury, and cognitive decline in patients with mild cognitive symptoms and cerebral amyloid angiopathy (CAA), a well-characterized small-vessel disease that causes cognitive decline in older adults. METHODS: Using a prospective memory clinic cohort, we enrolled 102 participants, of whom 52 with probable CAA. All underwent a 3-tesla research MRI at baseline and annual neuropsychological evaluation over 2 years, for which standardized z-scores for four cognitive domains were calculated. BPV was assessed using a coefficient of variation derived from serial outpatient BP measurements (median 12) over five years. We measured the peak width of skeletonized mean diffusivity (PSMD) as a marker of white matter integrity, and other neuroimaging markers of CAA, including lacunes and cortical cerebral microinfarcts. Using regression models, we evaluated the association of BPV with microstructural brain injury and whether CAA modified this association. We also examined the association of BPV with subsequent cognitive decline. RESULTS: Systolic BPV was dose-dependently associated with PSMD (estimate=0.22, 95% CI: 0.06, 0.39, p=0.010), independent of age, sex, mean BP, common vascular risk factors, brain atrophy, and CAA severity. The presence of probable CAA strengthened the association between BPV and PSMD (estimate=9.33, 95% CI: 1.32, 17.34, p for interaction = 0.023). Higher BPV correlated with greater ischemic injury (lobar lacunes and cortical cerebral microinfarcts) and a decline in global cognition and processing speed (estimate=-0.30, 95% CI: -0.55, -0.04, p=0.022). DISCUSSION: Long-term BPV has a dose-dependent association with alterations in white matter integrity, lobar lacunes, and cortical cerebral microinfarcts, and predicts cognitive decline. Controlling BPV is a potential strategic approach to prevent cognitive decline, especially in early-stage CAA.\n

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\n \n\n \n \n \n \n \n Long-Term Brain Structure and Cognition Following Bariatric Surgery.\n \n \n \n\n\n \n Custers, E.; Vreeken, D.; Kleemann, R.; Kessels, R. P. C.; Duering, M.; Brouwer, J.; Aufenacker, T. J.; Witteman, B. P. L.; Snabel, J.; Gart, E.; Mutsaerts, H. J. M. M.; Wiesmann, M.; Hazebroek, E. J.; and Kiliaan, A. J.\n\n\n \n\n\n\n JAMA Netw Open, 7(2): e2355380. February 2024.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{custers_long-term_2024,\n\ttitle = {Long-{Term} {Brain} {Structure} and {Cognition} {Following} {Bariatric} {Surgery}},\n\tvolume = {7},\n\tissn = {2574-3805},\n\tdoi = {10.1001/jamanetworkopen.2023.55380},\n\tabstract = {IMPORTANCE: Weight loss induced by bariatric surgery (BS) is associated with improved cognition and changed brain structure; however, previous studies on the association have used small cohorts and short follow-up periods, making it difficult to determine long-term neurological outcomes associated with BS.\nOBJECTIVE: To investigate long-term associations of weight loss after BS with cognition and brain structure and perfusion.\nDESIGN, SETTING, AND PARTICIPANTS: This cohort study included participants from the Bariatric Surgery Rijnstate and Radboudumc Neuroimaging and Cognition in Obesity study. Data from participants with severe obesity (body mass index [BMI; calculated as weight in kilograms divided by height in meters squared] {\\textgreater}40, or BMI {\\textgreater}35 with comorbidities) eligible for Roux-en-Y gastric bypass and aged 35 to 55 years were enrolled from a hospital specialized in BS (Rijnstate Hospital, Arnhem, the Netherlands). Participants were recruited between September 2018 and December 2020 with follow-up till March 2023. Data were collected before BS and at 6 and 24 months after BS. Data were analyzed from March to November 2023.\nEXPOSURE: Roux-en-Y gastric bypass.\nMAIN OUTCOMES AND MEASURES: Primary outcomes included body weight, BMI, waist circumference, blood pressure, medication use, cognitive performance (20\\% change index of compound z-score), brain volumes, cortical thickness, cerebral blood flow (CBF), and spatial coefficient of variation (sCOV). Secondary outcomes include cytokines, adipokines, depressive symptoms (assessed using the Beck Depression Inventory), and physical activity (assessed using the Baecke Questionnaire).\nRESULTS: A total of 133 participants (mean [SD] age, 46.8 [5.7] years; 112 [84.2\\%] female) were included. Global cognition was at least 20\\% higher in 52 participants (42.9\\%) at 24 months after BS. Compared with baseline, at 24 months, inflammatory markers were lower (mean [SD] high-sensitivity C-reactive protein: 4.77 [5.80] μg/mL vs 0.80 [1.09] μg/mL; P {\\textless} .001), fewer patients used antihypertensives (48 patients [36.1\\%] vs 22 patients [16.7\\%]), and patients had lower depressive symptoms (median [IQR] BDI score: 9.0 [5.0-13.0] vs 3.0 [1.0-6.0]; P {\\textless} .001) and greater physical activity (mean [SD] Baecke score: 7.64 [1.29] vs 8.19 [1.35]; P {\\textless} .001). After BS, brain structure and perfusion were lower in most brain regions, while hippocampal and white matter volume remained stable. CBF and sCOV did not change in nucleus accumbens and parietal cortex. The temporal cortex showed a greater thickness (mean [SD] thickness: 2.724 [0.101] mm vs 2.761 [0.007] mm; P = .007) and lower sCOV (median [IQR] sCOV: 4.41\\% [3.83\\%-5.18\\%] vs 3.97\\% [3.71\\%-4.59\\%]; P = .02) after BS.\nCONCLUSIONS AND RELEVANCE: These findings suggest that BS was associated with health benefits 2 years after surgery. BS was associated with improved cognition and general health and changed blood vessel efficiency and cortical thickness of the temporal cortex. These results may improve treatment options for patients with obesity and dementia.},\n\tlanguage = {eng},\n\tnumber = {2},\n\tjournal = {JAMA Netw Open},\n\tauthor = {Custers, Emma and Vreeken, Debby and Kleemann, Robert and Kessels, Roy P. C. and Duering, Marco and Brouwer, Jonna and Aufenacker, Theo J. and Witteman, Bart P. L. and Snabel, Jessica and Gart, Eveline and Mutsaerts, Henk J. M. M. and Wiesmann, Maximilian and Hazebroek, Eric J. and Kiliaan, Amanda J.},\n\tmonth = feb,\n\tyear = {2024},\n\tpmid = {38334996},\n\tpmcid = {PMC10858407},\n\tkeywords = {Cognition, Female, Humans, Male, Middle Aged, Cohort Studies, Brain, Obesity, Bariatric Surgery, Weight Loss},\n\tpages = {e2355380},\n}\n\n

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\n IMPORTANCE: Weight loss induced by bariatric surgery (BS) is associated with improved cognition and changed brain structure; however, previous studies on the association have used small cohorts and short follow-up periods, making it difficult to determine long-term neurological outcomes associated with BS. OBJECTIVE: To investigate long-term associations of weight loss after BS with cognition and brain structure and perfusion. DESIGN, SETTING, AND PARTICIPANTS: This cohort study included participants from the Bariatric Surgery Rijnstate and Radboudumc Neuroimaging and Cognition in Obesity study. Data from participants with severe obesity (body mass index [BMI; calculated as weight in kilograms divided by height in meters squared] \\textgreater40, or BMI \\textgreater35 with comorbidities) eligible for Roux-en-Y gastric bypass and aged 35 to 55 years were enrolled from a hospital specialized in BS (Rijnstate Hospital, Arnhem, the Netherlands). Participants were recruited between September 2018 and December 2020 with follow-up till March 2023. Data were collected before BS and at 6 and 24 months after BS. Data were analyzed from March to November 2023. EXPOSURE: Roux-en-Y gastric bypass. MAIN OUTCOMES AND MEASURES: Primary outcomes included body weight, BMI, waist circumference, blood pressure, medication use, cognitive performance (20% change index of compound z-score), brain volumes, cortical thickness, cerebral blood flow (CBF), and spatial coefficient of variation (sCOV). Secondary outcomes include cytokines, adipokines, depressive symptoms (assessed using the Beck Depression Inventory), and physical activity (assessed using the Baecke Questionnaire). RESULTS: A total of 133 participants (mean [SD] age, 46.8 [5.7] years; 112 [84.2%] female) were included. Global cognition was at least 20% higher in 52 participants (42.9%) at 24 months after BS. Compared with baseline, at 24 months, inflammatory markers were lower (mean [SD] high-sensitivity C-reactive protein: 4.77 [5.80] μg/mL vs 0.80 [1.09] μg/mL; P \\textless .001), fewer patients used antihypertensives (48 patients [36.1%] vs 22 patients [16.7%]), and patients had lower depressive symptoms (median [IQR] BDI score: 9.0 [5.0-13.0] vs 3.0 [1.0-6.0]; P \\textless .001) and greater physical activity (mean [SD] Baecke score: 7.64 [1.29] vs 8.19 [1.35]; P \\textless .001). After BS, brain structure and perfusion were lower in most brain regions, while hippocampal and white matter volume remained stable. CBF and sCOV did not change in nucleus accumbens and parietal cortex. The temporal cortex showed a greater thickness (mean [SD] thickness: 2.724 [0.101] mm vs 2.761 [0.007] mm; P = .007) and lower sCOV (median [IQR] sCOV: 4.41% [3.83%-5.18%] vs 3.97% [3.71%-4.59%]; P = .02) after BS. CONCLUSIONS AND RELEVANCE: These findings suggest that BS was associated with health benefits 2 years after surgery. BS was associated with improved cognition and general health and changed blood vessel efficiency and cortical thickness of the temporal cortex. These results may improve treatment options for patients with obesity and dementia.\n

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\n \n\n \n \n \n \n \n Cerebral Small Vessel Disease: Advancing Knowledge With Neuroimaging.\n \n \n \n\n\n \n Ter Telgte, A.; and Duering, M.\n\n\n \n\n\n\n Stroke, 55(6): 1686–1688. June 2024.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{ter_telgte_cerebral_2024,\n\ttitle = {Cerebral {Small} {Vessel} {Disease}: {Advancing} {Knowledge} {With} {Neuroimaging}},\n\tvolume = {55},\n\tissn = {1524-4628},\n\tshorttitle = {Cerebral {Small} {Vessel} {Disease}},\n\tdoi = {10.1161/STROKEAHA.123.044294},\n\tlanguage = {eng},\n\tnumber = {6},\n\tjournal = {Stroke},\n\tauthor = {Ter Telgte, Annemieke and Duering, Marco},\n\tmonth = jun,\n\tyear = {2024},\n\tpmid = {38328947},\n\tkeywords = {Humans, cognition, Neuroimaging, Magnetic Resonance Imaging, neuroimaging, magnetic resonance imaging, cerebral small vessel diseases, Cerebral Small Vessel Diseases, brain},\n\tpages = {1686--1688},\n}\n\n

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\n \n\n \n \n \n \n \n Enhancing cognitive performance prediction by white matter hyperintensity connectivity assessment.\n \n \n \n\n\n \n Petersen, M.; Coenen, M.; DeCarli, C.; De Luca, A.; van der Lelij, E.; Alzheimer’s Disease Neuroimaging Initiative; Barkhof, F.; Benke, T.; Chen, C. P. L. H.; Dal-Bianco, P.; Dewenter, A.; Duering, M.; Enzinger, C.; Ewers, M.; Exalto, L. G.; Fletcher, E. M.; Franzmeier, N.; Hilal, S.; Hofer, E.; Koek, H. L.; Maier, A. B.; Maillard, P. M.; McCreary, C. R.; Papma, J. M.; Pijnenburg, Y. A. L.; Schmidt, R.; Smith, E. E.; Steketee, R. M. E.; van den Berg, E.; van der Flier, W. M.; Venkatraghavan, V.; Venketasubramanian, N.; Vernooij, M. W.; Wolters, F. J.; Xu, X.; Horn, A.; Patil, K. R.; Eickhoff, S. B.; Thomalla, G.; Biesbroek, J. M.; Biessels, G. J.; and Cheng, B.\n\n\n \n\n\n\n Brain, 147(12): 4265–4279. December 2024.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{petersen_enhancing_2024-1,\n\ttitle = {Enhancing cognitive performance prediction by white matter hyperintensity connectivity assessment},\n\tvolume = {147},\n\tissn = {1460-2156},\n\tdoi = {10.1093/brain/awae315},\n\tabstract = {White matter hyperintensities of presumed vascular origin (WMH) are associated with cognitive impairment and are a key imaging marker in evaluating brain health. However, WMH volume alone does not fully account for the extent of cognitive deficits and the mechanisms linking WMH to these deficits remain unclear. Lesion network mapping (LNM) enables us to infer if brain networks are connected to lesions and could be a promising technique for enhancing our understanding of the role of WMH in cognitive disorders. Our study employed LNM to test the following hypotheses: (i) LNM-informed markers surpass WMH volumes in predicting cognitive performance; and (ii) WMH contributing to cognitive impairment map to specific brain networks. We analysed cross-sectional data of 3485 patients from 10 memory clinic cohorts within the Meta VCI Map Consortium, using harmonized test results in four cognitive domains and WMH segmentations. WMH segmentations were registered to a standard space and mapped onto existing normative structural and functional brain connectome data. We employed LNM to quantify WMH connectivity to 480 atlas-based grey and white matter regions of interest (ROI), resulting in ROI-level structural and functional LNM scores. We compared the capacity of total and regional WMH volumes and LNM scores in predicting cognitive function using ridge regression models in a nested cross-validation. LNM scores predicted performance in three cognitive domains (attention/executive function, information processing speed, and verbal memory) significantly better than WMH volumes. LNM scores did not improve prediction for language functions. ROI-level analysis revealed that higher LNM scores, representing greater connectivity to WMH, in grey and white matter regions of the dorsal and ventral attention networks were associated with lower cognitive performance. Measures of WMH-related brain network connectivity significantly improve the prediction of current cognitive performance in memory clinic patients compared to WMH volume as a traditional imaging marker of cerebrovascular disease. This highlights the crucial role of network integrity, particularly in attention-related brain regions, improving our understanding of vascular contributions to cognitive impairment. Moving forward, refining WMH information with connectivity data could contribute to patient-tailored therapeutic interventions and facilitate the identification of subgroups at risk of cognitive disorders.},\n\tlanguage = {eng},\n\tnumber = {12},\n\tjournal = {Brain},\n\tauthor = {Petersen, Marvin and Coenen, Mirthe and DeCarli, Charles and De Luca, Alberto and van der Lelij, Ewoud and {Alzheimer’s Disease Neuroimaging Initiative} and Barkhof, Frederik and Benke, Thomas and Chen, Christopher P. L. H. and Dal-Bianco, Peter and Dewenter, Anna and Duering, Marco and Enzinger, Christian and Ewers, Michael and Exalto, Lieza G. and Fletcher, Evan M. and Franzmeier, Nicolai and Hilal, Saima and Hofer, Edith and Koek, Huiberdina L. and Maier, Andrea B. and Maillard, Pauline M. and McCreary, Cheryl R. and Papma, Janne M. and Pijnenburg, Yolande A. L. and Schmidt, Reinhold and Smith, Eric E. and Steketee, Rebecca M. E. and van den Berg, Esther and van der Flier, Wiesje M. and Venkatraghavan, Vikram and Venketasubramanian, Narayanaswamy and Vernooij, Meike W. and Wolters, Frank J. and Xu, Xin and Horn, Andreas and Patil, Kaustubh R. and Eickhoff, Simon B. and Thomalla, Götz and Biesbroek, J. Matthijs and Biessels, Geert Jan and Cheng, Bastian},\n\tmonth = dec,\n\tyear = {2024},\n\tpmid = {39400198},\n\tpmcid = {PMC11629703},\n\tkeywords = {Aged, Brain, cerebral small vessel disease, Cognition, Cognitive Dysfunction, Connectome, Cross-Sectional Studies, dementia, Female, Humans, lesion network mapping, magnetic resonance imaging, Magnetic Resonance Imaging, Male, Middle Aged, Neuropsychological Tests, vascular cognitive impairment, White Matter, white matter hyperintensities},\n\tpages = {4265--4279},\n}\n\n

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\n White matter hyperintensities of presumed vascular origin (WMH) are associated with cognitive impairment and are a key imaging marker in evaluating brain health. However, WMH volume alone does not fully account for the extent of cognitive deficits and the mechanisms linking WMH to these deficits remain unclear. Lesion network mapping (LNM) enables us to infer if brain networks are connected to lesions and could be a promising technique for enhancing our understanding of the role of WMH in cognitive disorders. Our study employed LNM to test the following hypotheses: (i) LNM-informed markers surpass WMH volumes in predicting cognitive performance; and (ii) WMH contributing to cognitive impairment map to specific brain networks. We analysed cross-sectional data of 3485 patients from 10 memory clinic cohorts within the Meta VCI Map Consortium, using harmonized test results in four cognitive domains and WMH segmentations. WMH segmentations were registered to a standard space and mapped onto existing normative structural and functional brain connectome data. We employed LNM to quantify WMH connectivity to 480 atlas-based grey and white matter regions of interest (ROI), resulting in ROI-level structural and functional LNM scores. We compared the capacity of total and regional WMH volumes and LNM scores in predicting cognitive function using ridge regression models in a nested cross-validation. LNM scores predicted performance in three cognitive domains (attention/executive function, information processing speed, and verbal memory) significantly better than WMH volumes. LNM scores did not improve prediction for language functions. ROI-level analysis revealed that higher LNM scores, representing greater connectivity to WMH, in grey and white matter regions of the dorsal and ventral attention networks were associated with lower cognitive performance. Measures of WMH-related brain network connectivity significantly improve the prediction of current cognitive performance in memory clinic patients compared to WMH volume as a traditional imaging marker of cerebrovascular disease. This highlights the crucial role of network integrity, particularly in attention-related brain regions, improving our understanding of vascular contributions to cognitive impairment. Moving forward, refining WMH information with connectivity data could contribute to patient-tailored therapeutic interventions and facilitate the identification of subgroups at risk of cognitive disorders.\n

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\n \n\n \n \n \n \n \n Risk factors and clinical significance of post-stroke incident ischemic lesions.\n \n \n \n\n\n \n Fang, R.; Duering, M.; Bode, F. J.; Stösser, S.; Meißner, J. N.; Hermann, P.; Liman, T. G.; Nolte, C. H.; Kerti, L.; Ikenberg, B.; Bernkopf, K.; Glanz, W.; Janowitz, D.; Wagner, M.; Neumann, K.; Speck, O.; Düzel, E.; Gesierich, B.; Dewenter, A.; Spottke, A.; Waegemann, K.; Görtler, M.; Wunderlich, S.; Zerr, I.; Petzold, G. C.; Endres, M.; Georgakis, M. K.; Dichgans, M.; and DEMDAS investigators\n\n\n \n\n\n\n Alzheimers Dement, 20(12): 8412–8428. December 2024.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{fang_risk_2024,\n\ttitle = {Risk factors and clinical significance of post-stroke incident ischemic lesions},\n\tvolume = {20},\n\tissn = {1552-5279},\n\tdoi = {10.1002/alz.14274},\n\tabstract = {INTRODUCTION: While incident ischemic lesions (IILs) are not unusual on follow-up magnetic resonance imaging (MRI) following stroke, their risk factors and prognostic significance remain unknown.\nMETHODS: In a prospective multicenter study of 503 acute stroke patients, we assessed IILs on registered MRI images at baseline and 6 months, analyzing risk factors and clinical outcomes across 36 months.\nRESULTS: At 6 months, 78 patients (15.5\\%) had IILs, mostly diffusion-weighted imaging-positive (72\\%) and clinically covert (91\\%). Older age and small vessel disease (SVD) lesions were baseline risk factors for IILs. IILs were associated with worse cognitive (beta for global cognition: -0.31, 95\\% confidence interval [CI]: -0.48 to -0.14) and functional outcomes (beta for modified Rankin scale [mRS]: 0.36, 95\\% CI: 0.14 to 0.58), and higher recurrent stroke risk (hazard ratio: 3.81, 95\\% CI: 1.35 to 10.69). IILs partially explained the relationship between SVD and poor cognition.\nDISCUSSION: IILs are common and are associated with worse cognitive and functional outcomes and stroke recurrence risk. Assessing IILs following stroke might aid prognostication.\nHIGHLIGHTS: Incident ischemic lesions (IILs) were assessed with registered baseline and 6-month magnetic resonance imaging (MRI) scans in a stroke cohort. IILs 6 months after stroke are present in one-sixth of patients and are mostly clinically silent. Small vessel disease burden is the main baseline risk factor for IILs. IILs are associated with cognitive and functional impairment and stroke recurrence. Assessing IILs by follow-up MRI aids long-term prognostication for stroke patients.},\n\tlanguage = {eng},\n\tnumber = {12},\n\tjournal = {Alzheimers Dement},\n\tauthor = {Fang, Rong and Duering, Marco and Bode, Felix J. and Stösser, Sebastian and Meißner, Julius N. and Hermann, Peter and Liman, Thomas G. and Nolte, Christian H. and Kerti, Lucia and Ikenberg, Benno and Bernkopf, Kathleen and Glanz, Wenzel and Janowitz, Daniel and Wagner, Michael and Neumann, Katja and Speck, Oliver and Düzel, Emrah and Gesierich, Benno and Dewenter, Anna and Spottke, Annika and Waegemann, Karin and Görtler, Michael and Wunderlich, Silke and Zerr, Inga and Petzold, Gabor C. and Endres, Matthias and Georgakis, Marios K. and Dichgans, Martin and {DEMDAS investigators}},\n\tmonth = dec,\n\tyear = {2024},\n\tpmid = {39417418},\n\tpmcid = {PMC11667539},\n\tkeywords = {Aged, Brain, Brain Ischemia, cerebral small vessel disease, Clinical Relevance, cognitive impairment, Diffusion Magnetic Resonance Imaging, Female, functional outcome, Humans, incident ischemic lesions, Ischemic Stroke, Magnetic Resonance Imaging, Male, Middle Aged, Prognosis, Prospective Studies, recurrent stroke, Risk Factors, stroke, Stroke},\n\tpages = {8412--8428},\n}\n\n

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\n \n\n \n \n \n \n \n Metabolic dysfunction-associated steatotic liver disease is associated with effects on cerebral perfusion and white matter integrity.\n \n \n \n\n\n \n Seidel, F.; Vreeken, D.; Custers, E.; Wiesmann, M.; Özsezen, S.; van Duyvenvoorde, W.; Caspers, M.; Menke, A.; Morrison, M. C.; Verschuren, L.; Duering, M.; Hazebroek, E. J.; Kiliaan, A. J.; and Kleemann, R.\n\n\n \n\n\n\n Heliyon, 10(19): e38516. October 2024.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{seidel_metabolic_2024,\n\ttitle = {Metabolic dysfunction-associated steatotic liver disease is associated with effects on cerebral perfusion and white matter integrity},\n\tvolume = {10},\n\tissn = {2405-8440},\n\tdoi = {10.1016/j.heliyon.2024.e38516},\n\tabstract = {It is unclear whether early metabolic and inflammatory aberrations in the liver are associated with detrimental changes in brain structure and cognitive function. This cross-sectional study examines putative associations between metabolic dysfunction-associated steatotic liver disease (MASLD) and brain health in 36-55 year-old participants with obesity (n = 70) from the BARICO study (BAriatric surgery Rijnstate and Radboudumc neuroImaging and Cognition in Obesity). The participants underwent brain magnetic resonance imaging to study brain volumes and cortical thickness (3T MRI including T1-weighted magnetization-prepared rapid gradient-echo sequence), cerebral blood perfusion (arterial spin labeling) and white matter integrity (diffusion weighted imaging to assess mean-skeletonized mean diffusivity and fluid-attenuated inversion recovery to detect the presence of white matter hyperintensities (WMH)). The participants additionally performed neuropsychological tests to assess global cognition, working and episodic memory, verbal fluency and the ability to shift attention. Liver biopsies were collected and liver dysfunction was examined with histopathological, biochemical, and gene expression analyses. Linear regression analyses were performed between liver and brain parameters and the influence of body-mass index, diabetes and hypertension was explored. Early stages of liver disease were not associated with cognitive status but with cerebrovascular changes independently of age, sex, BMI, diabetes and hypertension: hepatic fibrosis development was associated with higher spatial coefficient of variation (sCoV) in the nucleus accumbens (NAcc), reflecting greater variations in cerebral perfusion and reduced vascular efficiency. Elevated hepatic levels of free cholesterol and cholesteryl esters were associated with increased WMH, indicating cerebral small vessel disease. RNA-seq and pathway analyses identified associations between sCoV in NAcc and WMH and the expression of hepatic genes involved in inflammation and cellular stress. Additionally, sCoV in NAcc correlated with plasma IL-6 levels suggesting that systemic-low grade inflammation may, at least partly, mediate this relationship. In conclusion, this study demonstrates that specific features of liver dysfunction (e.g. free cholesterol, onset of fibrosis) are associated with subtle cerebrovascular impairments, when changes in cognitive performance are not yet noticeable. These findings highlight the need for future research on therapeutic strategies that normalize metabolic-inflammatory aberrations in the liver to reduce the risk of cognitive decline.},\n\tlanguage = {eng},\n\tnumber = {19},\n\tjournal = {Heliyon},\n\tauthor = {Seidel, Florine and Vreeken, Debby and Custers, Emma and Wiesmann, Maximilian and Özsezen, Serdar and van Duyvenvoorde, Wim and Caspers, Martien and Menke, Aswin and Morrison, Martine C. and Verschuren, Lars and Duering, Marco and Hazebroek, Eric J. and Kiliaan, Amanda J. and Kleemann, Robert},\n\tmonth = oct,\n\tyear = {2024},\n\tpmid = {39391513},\n\tpmcid = {PMC11466594},\n\tkeywords = {Brain health, MASLD, Metabolism, Systemic inflammation},\n\tpages = {e38516},\n}\n\n

\n\n\n

\n It is unclear whether early metabolic and inflammatory aberrations in the liver are associated with detrimental changes in brain structure and cognitive function. This cross-sectional study examines putative associations between metabolic dysfunction-associated steatotic liver disease (MASLD) and brain health in 36-55 year-old participants with obesity (n = 70) from the BARICO study (BAriatric surgery Rijnstate and Radboudumc neuroImaging and Cognition in Obesity). The participants underwent brain magnetic resonance imaging to study brain volumes and cortical thickness (3T MRI including T1-weighted magnetization-prepared rapid gradient-echo sequence), cerebral blood perfusion (arterial spin labeling) and white matter integrity (diffusion weighted imaging to assess mean-skeletonized mean diffusivity and fluid-attenuated inversion recovery to detect the presence of white matter hyperintensities (WMH)). The participants additionally performed neuropsychological tests to assess global cognition, working and episodic memory, verbal fluency and the ability to shift attention. Liver biopsies were collected and liver dysfunction was examined with histopathological, biochemical, and gene expression analyses. Linear regression analyses were performed between liver and brain parameters and the influence of body-mass index, diabetes and hypertension was explored. Early stages of liver disease were not associated with cognitive status but with cerebrovascular changes independently of age, sex, BMI, diabetes and hypertension: hepatic fibrosis development was associated with higher spatial coefficient of variation (sCoV) in the nucleus accumbens (NAcc), reflecting greater variations in cerebral perfusion and reduced vascular efficiency. Elevated hepatic levels of free cholesterol and cholesteryl esters were associated with increased WMH, indicating cerebral small vessel disease. RNA-seq and pathway analyses identified associations between sCoV in NAcc and WMH and the expression of hepatic genes involved in inflammation and cellular stress. Additionally, sCoV in NAcc correlated with plasma IL-6 levels suggesting that systemic-low grade inflammation may, at least partly, mediate this relationship. In conclusion, this study demonstrates that specific features of liver dysfunction (e.g. free cholesterol, onset of fibrosis) are associated with subtle cerebrovascular impairments, when changes in cognitive performance are not yet noticeable. These findings highlight the need for future research on therapeutic strategies that normalize metabolic-inflammatory aberrations in the liver to reduce the risk of cognitive decline.\n

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\n \n\n \n \n \n \n \n Temporal evolution of microstructural integrity in cerebellar peduncles in Parkinson's disease: Stage-specific patterns and dopaminergic correlates.\n \n \n \n\n\n \n He, C.; Yang, R.; Rong, S.; Zhang, P.; Chen, X.; Qi, Q.; Gao, Z.; Li, Y.; Li, H.; de Leeuw, F.; Tuladhar, A. M.; Duering, M.; Helmich, R. C.; van der Vliet, R.; Darweesh, S. K. L.; Liu, Z.; Wang, L.; Cai, M.; and Zhang, Y.\n\n\n \n\n\n\n Neuroimage Clin, 44: 103679. 2024.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{he_temporal_2024,\n\ttitle = {Temporal evolution of microstructural integrity in cerebellar peduncles in {Parkinson}'s disease: {Stage}-specific patterns and dopaminergic correlates},\n\tvolume = {44},\n\tissn = {2213-1582},\n\tshorttitle = {Temporal evolution of microstructural integrity in cerebellar peduncles in {Parkinson}'s disease},\n\tdoi = {10.1016/j.nicl.2024.103679},\n\tabstract = {BACKGROUND: Previous research revealed differences in cerebellar white matter integrity by disease stages, indicating a compensatory role in Parkinson's disease (PD). However, the temporal evolution of cerebellar white matter microstructure in patients with PD (PwPD) remains unclear.\nOBJECTIVE: To unravel temporal evolution of cerebellar white matter and its dopaminergic correlates in PD.\nMETHODS: We recruited 124 PwPD from the PPMI study. The participants were divided into two subsets: Subset 1 (n = 41) had three MRI scans (baseline, 2 years, and 4 years), and Subset 2 (n = 106) had at least two MRI scans at baseline, 1 year, and/or 2 years. Free water-corrected diffusion metrics were used to measure the microstructural integrity in cerebellar peduncles (CP), the main white matter tracts connecting to and from the cerebellum. The ACAPULCO processing pipeline was used to assess cerebellar lobules volumes. Linear mixed-effect models were used to study longitudinal changes. We also examined the relationships between microstructural integrity in CP, striatal dopamine transporter specific binding ratio (SBR), and clinical symptoms.\nRESULTS: Microstructural changes in CP showed a non-linear pattern in PwPD. Free water-corrected fractional anisotropy (FAt) increased in the first two years but declined from 2 to 4 years, while free water-corrected mean diffusivity exhibited the opposite trend. The initial increased FAt in CP correlated with cerebellar regional volume atrophy, striatal dopaminergic SBR decline, and worsening clinical symptoms, but this correlation varied across disease stages.\nCONCLUSIONS: Our findings suggest a non-linear evolution of microstructural integrity in CP throughout the course of PD, indicating the adaptive structural reorganization of the cerebellum simultaneously with progressive striatal dopaminergic degeneration in PD.},\n\tlanguage = {eng},\n\tjournal = {Neuroimage Clin},\n\tauthor = {He, Chentao and Yang, Rui and Rong, Siming and Zhang, Piao and Chen, Xi and Qi, Qi and Gao, Ziqi and Li, Yan and Li, Hao and de Leeuw, Frank-Erik and Tuladhar, Anil M. and Duering, Marco and Helmich, Rick C. and van der Vliet, Rick and Darweesh, Sirwan K. L. and Liu, Zaiyi and Wang, Lijuan and Cai, Mengfei and Zhang, Yuhu},\n\tyear = {2024},\n\tpmid = {39366283},\n\tpmcid = {PMC11489329},\n\tkeywords = {Aged, Cerebellar peduncles, Cerebellum, Compensation, Diffusion Tensor Imaging, Disease Progression, Dopamine, Dopaminergic degeneration, Female, Humans, Longitudinal Studies, Magnetic Resonance Imaging, Male, Microstructural integrity, Middle Aged, Parkinson Disease, Parkinson’s disease, White Matter},\n\tpages = {103679},\n}\n\n

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\n \n\n \n \n \n \n \n High-Sensitivity Cardiac Troponin T and Cognitive Function Over 12 Months After Stroke-Results of the DEMDAS Study.\n \n \n \n\n\n \n von Rennenberg, R.; Nolte, C. H.; Liman, T. G.; Hellwig, S.; Riegler, C.; Scheitz, J. F.; Georgakis, M. K.; Fang, R.; Bode, F. J.; Petzold, G. C.; Hermann, P.; Zerr, I.; Goertler, M.; Bernkopf, K.; Wunderlich, S.; Dichgans, M.; Endres, M.; and DEMDAS investigators *\n\n\n \n\n\n\n J Am Heart Assoc, 13(6): e033439. March 2024.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{von_rennenberg_high-sensitivity_2024,\n\ttitle = {High-{Sensitivity} {Cardiac} {Troponin} {T} and {Cognitive} {Function} {Over} 12 {Months} {After} {Stroke}-{Results} of the {DEMDAS} {Study}},\n\tvolume = {13},\n\tissn = {2047-9980},\n\tdoi = {10.1161/JAHA.123.033439},\n\tabstract = {BACKGROUND: Subclinical myocardial injury in form of hs-cTn (high-sensitivity cardiac troponin)  levels has been associated with cognitive impairment and imaging markers of cerebral small vessel disease (SVD) in population-based and cardiovascular cohorts. Whether hs-cTn is associated with domain-specific cognitive decline and SVD burden in patients with stroke remains unknown.\nMETHODS AND RESULTS: We analyzed patients with acute stroke without premorbid dementia from the prospective multicenter DEMDAS (DZNE [German Center for Neurodegenerative Disease]-Mechanisms of Dementia after Stroke) study. Patients underwent neuropsychological testing 6 and 12 months after the index event. Test results were classified into 5 cognitive domains (language, memory, executive function, attention, and visuospatial function). SVD markers (lacunes, cerebral microbleeds, white matter hyperintensities, and enlarged perivascular spaces) were assessed on cranial magnetic resonance imaging to constitute a global SVD score. We examined the association between hs-cTnT (hs-cTn T levels) and cognitive domains as well as the global SVD score and individual SVD markers, respectively. Measurement of cognitive and SVD-marker analyses were performed in 385 and 466 patients with available hs-cTnT levels, respectively. In analyses adjusted for demographic characteristics, cardiovascular risk factors, and cognitive status at baseline, higher hs-cTnT was negatively associated with the cognitive domains "attention" up to 12 months of follow-up (beta-coefficient, -0.273 [95\\% CI, -0.436 to -0.109]) and "executive function" after 12 months. Higher hs-cTnT was associated with the global SVD score (adjusted odds ratio, 1.95 [95\\% CI, 1.27-3.00]) and the white matter hyperintensities and lacune subscores.\nCONCLUSIONS: In patients with stroke, hs-cTnT is associated with a higher burden of SVD markers and cognitive function in domains linked to vascular cognitive impairment.\nREGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT01334749.},\n\tlanguage = {eng},\n\tnumber = {6},\n\tjournal = {J Am Heart Assoc},\n\tauthor = {von Rennenberg, Regina and Nolte, Christian H. and Liman, Thomas G. and Hellwig, Simon and Riegler, Christoph and Scheitz, Jan F. and Georgakis, Marios K. and Fang, Rong and Bode, Felix J. and Petzold, Gabor C. and Hermann, Peter and Zerr, Inga and Goertler, Michael and Bernkopf, Kathleen and Wunderlich, Silke and Dichgans, Martin and Endres, Matthias and {DEMDAS investigators *}},\n\tmonth = mar,\n\tyear = {2024},\n\tpmid = {38456438},\n\tpmcid = {PMC11010029},\n\tkeywords = {acute stroke, cardiac troponin, Cerebral Small Vessel Diseases, Cognition, Cognitive Dysfunction, cognitive impairment, Dementia, heart and brain axis, Humans, Magnetic Resonance Imaging, Neurodegenerative Diseases, Prospective Studies, Stroke, Troponin T},\n\tpages = {e033439},\n}\n\n

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\n BACKGROUND: Subclinical myocardial injury in form of hs-cTn (high-sensitivity cardiac troponin) levels has been associated with cognitive impairment and imaging markers of cerebral small vessel disease (SVD) in population-based and cardiovascular cohorts. Whether hs-cTn is associated with domain-specific cognitive decline and SVD burden in patients with stroke remains unknown. METHODS AND RESULTS: We analyzed patients with acute stroke without premorbid dementia from the prospective multicenter DEMDAS (DZNE [German Center for Neurodegenerative Disease]-Mechanisms of Dementia after Stroke) study. Patients underwent neuropsychological testing 6 and 12 months after the index event. Test results were classified into 5 cognitive domains (language, memory, executive function, attention, and visuospatial function). SVD markers (lacunes, cerebral microbleeds, white matter hyperintensities, and enlarged perivascular spaces) were assessed on cranial magnetic resonance imaging to constitute a global SVD score. We examined the association between hs-cTnT (hs-cTn T levels) and cognitive domains as well as the global SVD score and individual SVD markers, respectively. Measurement of cognitive and SVD-marker analyses were performed in 385 and 466 patients with available hs-cTnT levels, respectively. In analyses adjusted for demographic characteristics, cardiovascular risk factors, and cognitive status at baseline, higher hs-cTnT was negatively associated with the cognitive domains \"attention\" up to 12 months of follow-up (beta-coefficient, -0.273 [95% CI, -0.436 to -0.109]) and \"executive function\" after 12 months. Higher hs-cTnT was associated with the global SVD score (adjusted odds ratio, 1.95 [95% CI, 1.27-3.00]) and the white matter hyperintensities and lacune subscores. CONCLUSIONS: In patients with stroke, hs-cTnT is associated with a higher burden of SVD markers and cognitive function in domains linked to vascular cognitive impairment. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT01334749.\n

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\n \n\n \n \n \n \n \n Similarity between structural and proxy estimates of brain connectivity.\n \n \n \n\n\n \n Lizarraga, A.; Ripp, I.; Sala, A.; Shi, K.; Düring, M.; Koch, K.; and Yakushev, I.\n\n\n \n\n\n\n J Cereb Blood Flow Metab, 44(2): 284–295. February 2024.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{lizarraga_similarity_2024,\n\ttitle = {Similarity between structural and proxy estimates of brain connectivity},\n\tvolume = {44},\n\tissn = {1559-7016},\n\tdoi = {10.1177/0271678X231204769},\n\tabstract = {Functional magnetic resonance and diffusion weighted imaging have so far made a major contribution to delineation of the brain connectome at the macroscale. While functional connectivity (FC) was shown to be related to structural connectivity (SC) to a certain degree, their spatial overlap is unknown. Even less clear are relations of SC with estimates of connectivity from inter-subject covariance of regional F18-fluorodeoxyglucose uptake (FDGcov) and grey matter volume (GMVcov). Here, we asked to what extent SC underlies three proxy estimates of brain connectivity: FC, FDGcov and GMVcov. Simultaneous PET/MR acquisitions were performed in 56 healthy middle-aged individuals. Similarity between four networks was assessed using Spearman correlation and convergence ratio (CR), a measure of spatial overlap. Spearman correlation coefficient was 0.27 for SC-FC, 0.40 for SC-FDGcov, and 0.15 for SC-GMVcov. Mean CRs were 51\\% for SC-FC, 48\\% for SC-FDGcov, and 37\\% for SC-GMVcov. These results proved to be reproducible and robust against image processing steps. In sum, we found a relevant similarity of SC with FC and FDGcov, while GMVcov consistently showed the weakest similarity. These findings indicate that white matter tracts underlie FDGcov to a similar degree as FC, supporting FDGcov as estimate of functional brain connectivity.},\n\tlanguage = {eng},\n\tnumber = {2},\n\tjournal = {J Cereb Blood Flow Metab},\n\tauthor = {Lizarraga, Aldana and Ripp, Isabelle and Sala, Arianna and Shi, Kuangyu and Düring, Marco and Koch, Kathrin and Yakushev, Igor},\n\tmonth = feb,\n\tyear = {2024},\n\tpmid = {37773727},\n\tpmcid = {PMC10993877},\n\tkeywords = {Brain, Brain Mapping, Connectome, Diffusion Magnetic Resonance Imaging, Diffusion Tensor Imaging, DWI, Fluorodeoxyglucose F18, fMRI, functional connectivity, Humans, Magnetic Resonance Imaging, Middle Aged, molecular connectivity, multimodal imaging},\n\tpages = {284--295},\n}\n

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\n \n\n \n \n \n \n \n Advanced MRI in cerebral small vessel disease.\n \n \n \n\n\n \n van den Brink, H.; Doubal, F. N.; and Duering, M.\n\n\n \n\n\n\n Int J Stroke, 18(1): 28–35. January 2023.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{van_den_brink_advanced_2023,\n\ttitle = {Advanced {MRI} in cerebral small vessel disease},\n\tvolume = {18},\n\tissn = {1747-4949},\n\tdoi = {10.1177/17474930221091879},\n\tabstract = {Cerebral small vessel disease (cSVD) is a major cause of stroke and dementia. This review summarizes recent developments in advanced neuroimaging of cSVD with a focus on clinical and research applications. In the first section, we highlight how advanced structural imaging techniques, including diffusion magnetic resonance imaging (MRI), enable improved detection of tissue damage, including characterization of tissue appearing normal on conventional MRI. These techniques enable progression to be monitored and may be useful as surrogate endpoint in clinical trials. Quantitative MRI, including iron and myelin imaging, provides insights into tissue composition on the molecular level. In the second section, we cover how advanced MRI techniques can demonstrate functional or dynamic abnormalities of the blood vessels, which could be targeted in mechanistic research and early-stage intervention trials. Such techniques include the use of dynamic contrast enhanced MRI to measure blood-brain barrier permeability, and MRI methods to assess cerebrovascular reactivity. In the third section, we discuss how the increased spatial resolution provided by ultrahigh field MRI at 7 T allows imaging of perforating arteries, and flow velocity and pulsatility within them. The advanced MRI techniques we describe are providing novel pathophysiological insights in cSVD and allow improved quantification of disease burden and progression. They have application in clinical trials, both in assessing novel therapeutic mechanisms, and as a sensitive endpoint to assess efficacy of interventions on parenchymal tissue damage. We also discuss challenges of these advanced techniques and suggest future directions for research.},\n\tlanguage = {eng},\n\tnumber = {1},\n\tjournal = {Int J Stroke},\n\tauthor = {van den Brink, Hilde and Doubal, Fergus N. and Duering, Marco},\n\tmonth = jan,\n\tyear = {2023},\n\tpmid = {35311609},\n\tpmcid = {PMC9806457},\n\tkeywords = {Stroke, Diffusion Magnetic Resonance Imaging, Humans, diffusion tensor imaging, Magnetic Resonance Imaging, quantitative MRI, Cerebral Small Vessel Diseases, MRI, Blood-Brain Barrier, blood–brain barrier, Cerebral small vessel disease, cerebrovascular reactivity, ultrahigh field MRI},\n\tpages = {28--35},\n\tfile = {Full Text:/Users/mduering/Zotero/storage/2FF5DNS2/van den Brink et al. - 2023 - Advanced MRI in cerebral small vessel disease.pdf:application/pdf},\n}\n\n

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\n \n\n \n \n \n \n \n Neuroimaging standards for research into small vessel disease-advances since 2013.\n \n \n \n\n\n \n Duering, M.; Biessels, G. J.; Brodtmann, A.; Chen, C.; Cordonnier, C.; de Leeuw, F.; Debette, S.; Frayne, R.; Jouvent, E.; Rost, N. S.; Ter Telgte, A.; Al-Shahi Salman, R.; Backes, W. H.; Bae, H.; Brown, R.; Chabriat, H.; De Luca, A.; deCarli , C.; Dewenter, A.; Doubal, F. N.; Ewers, M.; Field, T. S.; Ganesh, A.; Greenberg, S.; Helmer, K. G.; Hilal, S.; Jochems, A. C. C.; Jokinen, H.; Kuijf, H.; Lam, B. Y. K.; Lebenberg, J.; MacIntosh, B. J.; Maillard, P.; Mok, V. C. T.; Pantoni, L.; Rudilosso, S.; Satizabal, C. L.; Schirmer, M. D.; Schmidt, R.; Smith, C.; Staals, J.; Thrippleton, M. J.; van Veluw, S. J.; Vemuri, P.; Wang, Y.; Werring, D.; Zedde, M.; Akinyemi, R. O.; Del Brutto, O. H.; Markus, H. S.; Zhu, Y.; Smith, E. E.; Dichgans, M.; and Wardlaw, J. M.\n\n\n \n\n\n\n Lancet Neurol, 22(7): 602–618. July 2023.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{duering_neuroimaging_2023,\n\ttitle = {Neuroimaging standards for research into small vessel disease-advances since 2013},\n\tvolume = {22},\n\tcopyright = {All rights reserved},\n\tissn = {1474-4465},\n\tdoi = {10.1016/S1474-4422(23)00131-X},\n\tabstract = {Cerebral small vessel disease (SVD) is common during ageing and can present as stroke, cognitive decline, neurobehavioural symptoms, or functional impairment. SVD frequently coexists with neurodegenerative disease, and can exacerbate cognitive and other symptoms and affect activities of daily living. Standards for Reporting Vascular Changes on Neuroimaging 1 (STRIVE-1) categorised and standardised the diverse features of SVD that are visible on structural MRI. Since then, new information on these established SVD markers and novel MRI sequences and imaging features have emerged. As the effect of combined SVD imaging features becomes clearer, a key role for quantitative imaging biomarkers to determine sub-visible tissue damage, subtle abnormalities visible at high-field strength MRI, and lesion-symptom patterns, is also apparent. Together with rapidly emerging machine learning methods, these metrics can more comprehensively capture the effect of SVD on the brain than the structural MRI features alone and serve as intermediary outcomes in clinical trials and future routine practice. Using a similar approach to that adopted in STRIVE-1, we updated the guidance on neuroimaging of vascular changes in studies of ageing and neurodegeneration to create STRIVE-2.},\n\tlanguage = {eng},\n\tnumber = {7},\n\tjournal = {Lancet Neurol},\n\tauthor = {Duering, Marco and Biessels, Geert Jan and Brodtmann, Amy and Chen, Christopher and Cordonnier, Charlotte and de Leeuw, Frank-Erik and Debette, Stéphanie and Frayne, Richard and Jouvent, Eric and Rost, Natalia S. and Ter Telgte, Annemieke and Al-Shahi Salman, Rustam and Backes, Walter H. and Bae, Hee-Joon and Brown, Rosalind and Chabriat, Hugues and De Luca, Alberto and deCarli, Charles and Dewenter, Anna and Doubal, Fergus N. and Ewers, Michael and Field, Thalia S. and Ganesh, Aravind and Greenberg, Steven and Helmer, Karl G. and Hilal, Saima and Jochems, Angela C. C. and Jokinen, Hanna and Kuijf, Hugo and Lam, Bonnie Y. K. and Lebenberg, Jessica and MacIntosh, Bradley J. and Maillard, Pauline and Mok, Vincent C. T. and Pantoni, Leonardo and Rudilosso, Salvatore and Satizabal, Claudia L. and Schirmer, Markus D. and Schmidt, Reinhold and Smith, Colin and Staals, Julie and Thrippleton, Michael J. and van Veluw, Susanne J. and Vemuri, Prashanthi and Wang, Yilong and Werring, David and Zedde, Marialuisa and Akinyemi, Rufus O. and Del Brutto, Oscar H. and Markus, Hugh S. and Zhu, Yi-Cheng and Smith, Eric E. and Dichgans, Martin and Wardlaw, Joanna M.},\n\tmonth = jul,\n\tyear = {2023},\n\tpmid = {37236211},\n\tkeywords = {Humans, Neuroimaging, Magnetic Resonance Imaging, Brain, Cerebral Small Vessel Diseases, Cognitive Dysfunction, Neurodegenerative Diseases, Activities of Daily Living},\n\tpages = {602--618},\n}\n\n

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\n \n\n \n \n \n \n \n Disentangling the effects of Alzheimer's and small vessel disease on white matter fibre tracts.\n \n \n \n\n\n \n Dewenter, A.; Jacob, M. A.; Cai, M.; Gesierich, B.; Hager, P.; Kopczak, A.; Biel, D.; Ewers, M.; Tuladhar, A. M.; de Leeuw, F.; Dichgans, M.; Franzmeier, N.; Duering, M.; SVDs@target Consortium; and (ADNI), A. D. N. I.\n\n\n \n\n\n\n Brain, 146(2): 678–689. February 2023.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{dewenter_disentangling_2023,\n\ttitle = {Disentangling the effects of {Alzheimer}'s and small vessel disease on white matter fibre tracts},\n\tvolume = {146},\n\tissn = {1460-2156},\n\tdoi = {10.1093/brain/awac265},\n\tabstract = {Alzheimer's disease and cerebral small vessel disease are the two leading causes of cognitive decline and dementia and coexist in most memory clinic patients. White matter damage as assessed by diffusion MRI is a key feature in both Alzheimer's and cerebral small vessel disease. However, disease-specific biomarkers of white matter alterations are missing. Recent advances in diffusion MRI operating on the fixel level (fibre population within a voxel) promise to advance our understanding of disease-related white matter alterations. Fixel-based analysis allows derivation of measures of both white matter microstructure, measured by fibre density, and macrostructure, measured by fibre-bundle cross-section. Here, we evaluated the capacity of these state-of-the-art fixel metrics to disentangle the effects of cerebral small vessel disease and Alzheimer's disease on white matter integrity. We included three independent samples (total n = 387) covering genetically defined cerebral small vessel disease and age-matched controls, the full spectrum of biomarker-confirmed Alzheimer's disease including amyloid- and tau-PET negative controls and a validation sample with presumed mixed pathology. In this cross-sectional analysis, we performed group comparisons between patients and controls and assessed associations between fixel metrics within main white matter tracts and imaging hallmarks of cerebral small vessel disease (white matter hyperintensity volume, lacune and cerebral microbleed count) and Alzheimer's disease (amyloid- and tau-PET), age and a measure of neurodegeneration (brain volume). Our results showed that (i) fibre density was reduced in genetically defined cerebral small vessel disease and strongly associated with cerebral small vessel disease imaging hallmarks; (ii) fibre-bundle cross-section was mainly associated with brain volume; and (iii) both fibre density and fibre-bundle cross-section were reduced in the presence of amyloid, but not further exacerbated by abnormal tau deposition. Fixel metrics were only weakly associated with amyloid- and tau-PET. Taken together, our results in three independent samples suggest that fibre density captures the effect of cerebral small vessel disease, while fibre-bundle cross-section is largely determined by neurodegeneration. The ability of fixel-based imaging markers to capture distinct effects on white matter integrity can propel future applications in the context of precision medicine.},\n\tlanguage = {eng},\n\tnumber = {2},\n\tjournal = {Brain},\n\tauthor = {Dewenter, Anna and Jacob, Mina A. and Cai, Mengfei and Gesierich, Benno and Hager, Paul and Kopczak, Anna and Biel, Davina and Ewers, Michael and Tuladhar, Anil M. and de Leeuw, Frank-Erik and Dichgans, Martin and Franzmeier, Nicolai and Duering, Marco and {SVDs@target Consortium and Alzheimer’s Disease Neuroimaging Initiative (ADNI)}},\n\tmonth = feb,\n\tyear = {2023},\n\tpmid = {35859352},\n\tpmcid = {PMC9924910},\n\tkeywords = {Diffusion Magnetic Resonance Imaging, Humans, cerebral small vessel disease, Cross-Sectional Studies, Brain, White Matter, Alzheimer Disease, Alzheimer’s disease, Cerebral Small Vessel Diseases, CADASIL, diffusion magnetic resonance imaging, Amyloidogenic Proteins, fixel-based analysis, Vascular Diseases},\n\tpages = {678--689},\n\tfile = {Full Text:/Users/mduering/Zotero/storage/7ZEUXJLZ/Dewenter et al. - 2023 - Disentangling the effects of Alzheimer's and small.pdf:application/pdf},\n}\n\n

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\n Alzheimer's disease and cerebral small vessel disease are the two leading causes of cognitive decline and dementia and coexist in most memory clinic patients. White matter damage as assessed by diffusion MRI is a key feature in both Alzheimer's and cerebral small vessel disease. However, disease-specific biomarkers of white matter alterations are missing. Recent advances in diffusion MRI operating on the fixel level (fibre population within a voxel) promise to advance our understanding of disease-related white matter alterations. Fixel-based analysis allows derivation of measures of both white matter microstructure, measured by fibre density, and macrostructure, measured by fibre-bundle cross-section. Here, we evaluated the capacity of these state-of-the-art fixel metrics to disentangle the effects of cerebral small vessel disease and Alzheimer's disease on white matter integrity. We included three independent samples (total n = 387) covering genetically defined cerebral small vessel disease and age-matched controls, the full spectrum of biomarker-confirmed Alzheimer's disease including amyloid- and tau-PET negative controls and a validation sample with presumed mixed pathology. In this cross-sectional analysis, we performed group comparisons between patients and controls and assessed associations between fixel metrics within main white matter tracts and imaging hallmarks of cerebral small vessel disease (white matter hyperintensity volume, lacune and cerebral microbleed count) and Alzheimer's disease (amyloid- and tau-PET), age and a measure of neurodegeneration (brain volume). Our results showed that (i) fibre density was reduced in genetically defined cerebral small vessel disease and strongly associated with cerebral small vessel disease imaging hallmarks; (ii) fibre-bundle cross-section was mainly associated with brain volume; and (iii) both fibre density and fibre-bundle cross-section were reduced in the presence of amyloid, but not further exacerbated by abnormal tau deposition. Fixel metrics were only weakly associated with amyloid- and tau-PET. Taken together, our results in three independent samples suggest that fibre density captures the effect of cerebral small vessel disease, while fibre-bundle cross-section is largely determined by neurodegeneration. The ability of fixel-based imaging markers to capture distinct effects on white matter integrity can propel future applications in the context of precision medicine.\n

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\n \n\n \n \n \n \n \n Characterization of Vasogenic and Cytotoxic Brain Edema Formation after experimental TBI by Free Water Diffusion MRI.\n \n \n \n\n\n \n Hu, S.; Exner, C.; Sienel, R. I.; Wehn, A.; Seker, B.; Magdane Boldoczki, F.; Guo, Y.; Duering, M.; Pasternak, O.; Plesnila, N.; and Schwarzmaier, S. M.\n\n\n \n\n\n\n J Neurotrauma. September 2023.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{hu_characterization_2023,\n\ttitle = {Characterization of {Vasogenic} and {Cytotoxic} {Brain} {Edema} {Formation} after experimental {TBI} by {Free} {Water} {Diffusion} {MRI}},\n\tissn = {1557-9042},\n\tdoi = {10.1089/neu.2023.0222},\n\tabstract = {Brain edema formation is a key factor for secondary tissue damage after traumatic brain injury (TBI). While vasogenic brain edema (VBE) is caused by blood brain barrier disruption, cytotoxic edema (CBE) is caused by astrocytic swelling. However, the type of brain edema and the time course of edema formation remain unclear. We performed free water imaging, a bi-tensor model based diffusion MRI analysis, to characterize VBE and CBE formation up to 7 days following experimental TBI. Male C57/Bl6 mice were subjected to Controlled Cortical Impact (CCI) or sham surgery and investigated by MRI 4 hours, 1, 2, 3, 5 and 7 days thereafter (n=8/group). We determined Mean Diffusivity (MD) and Free Water (FW) in contusion, peri-contusional area, ipsi- and contralateral brain tissue. Free, i.e. non-restricted, water was interpreted as VBE, restricted water as CBE. To verify the results, VBE formation was investigated by in-vivo 2-Photon Microscopy (2-PM) 48 hours after surgery. We found that MD and FW values decreased for 48 hours within the contusion, indicating the occurrence of CBE. In peri-contusional tissue MD and FW indices were increased at all time-points, suggesting the formation of VBE. This was consistent with our results obtained by 2-PM. Taken together, CBE formation occurs for 48 hours after trauma and is restricted to the contusion, while VBE forms in peri-contusional tissue up to 7 days after TBI. Our results indicate that free water MR imaging may represent a promising tool to investigate vasogenic and cytotoxic brain edema in the laboratory and in patients.},\n\tlanguage = {eng},\n\tjournal = {J Neurotrauma},\n\tauthor = {Hu, Senbin and Exner, Carina and Sienel, Rebecca Isabella and Wehn, Antonia and Seker, Burcu and Magdane Boldoczki, Fanni and Guo, Yinghuimin and Duering, Marco and Pasternak, Ofer and Plesnila, Nikolaus and Schwarzmaier, Susanne M.},\n\tmonth = sep,\n\tyear = {2023},\n\tpmid = {37776177},\n\tkeywords = {Diffusion Tensor Imaging, MRI, Brain Edema, controlled cortical impact, IN VIVO STUDIES},\n}\n\n

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\n \n\n \n \n \n \n \n Structural network efficiency predicts conversion to incident parkinsonism in patients with cerebral small vessel disease.\n \n \n \n\n\n \n Cai, M.; Jacob, M. A.; Marques, J.; Norris, D. G.; Duering, M.; Esselink, R. A. J.; Zhang, Y.; de Leeuw, F.; and Tuladhar, A. M.\n\n\n \n\n\n\n J Gerontol A Biol Sci Med Sci,glad182. August 2023.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{cai_structural_2023,\n\ttitle = {Structural network efficiency predicts conversion to incident parkinsonism in patients with cerebral small vessel disease},\n\tissn = {1758-535X},\n\tdoi = {10.1093/gerona/glad182},\n\tabstract = {BACKGROUND: To investigate whether structural network disconnectivity is associated with parkinsonian signs and their progression, as well as with an increased risk of incident parkinsonism.\nMETHODS: In a prospective cohort (RUN DMC study) consisting of 293 participants with small vessel disease (SVD), we assessed parkinsonian signs and incident parkinsonism over an 8-year follow-up. In addition, we reconstructed the white matter network followed by graph-theoretical analyses to compute the network metrics. Conventional MRI markers for SVD were assessed.\nRESULTS: We included 293 patients free of parkinsonism at baseline (2011), with a mean age 68.8 (SD 8.4) years, and 130 (44.4\\%) were men. 19 participants (6.5\\%) developed parkinsonism during a median (SD) follow-up time of 8.3 years. Compared with participants without parkinsonism, those with all-cause parkinsonism had higher UPDRS scores and lower global efficiency at baseline. Baseline global efficiency was associated with UPDRS motor scores in 2011 (β=-0.047, p{\\textless}0.001) and 2015 (β=-0.84, p{\\textless}0.001), as well as with the changes in UPDRS scores during the 4-year follow-up (β=-0.63, p=0.004). In addition, at the regional level, we identified an inter-hemispheric disconnected network associated with increased UPDRS motor score. Besides, lower global efficiency was associated with an increased risk of all-cause and vascular parkinsonism independent of SVD markers.\nCONCLUSIONS: Our findings suggest that global network efficiency is associated with a gradual decline in motor performance, ultimately leading to incident parkinsonism in the elderly with SVD. Global network efficiency may have the added value to serve as a useful marker to capture changes of motor signs.},\n\tlanguage = {eng},\n\tjournal = {J Gerontol A Biol Sci Med Sci},\n\tauthor = {Cai, Mengfei and Jacob, Mina A. and Marques, José and Norris, David G. and Duering, Marco and Esselink, Rianne A. J. and Zhang, Yuhu and de Leeuw, Frank-Erik and Tuladhar, Anil M.},\n\tmonth = aug,\n\tyear = {2023},\n\tpmid = {37527837},\n\tkeywords = {Small vessel disease, motor disturbance, network efficiency, parkinsonism},\n\tpages = {glad182},\n\tfile = {Full Text:/Users/mduering/Zotero/storage/57DYBR4W/Cai et al. - 2023 - Structural network efficiency predicts conversion .pdf:application/pdf},\n}\n\n

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\n \n\n \n \n \n \n \n Regional cortical thinning, demyelination, and iron loss in cerebral small vessel disease.\n \n \n \n\n\n \n Li, H.; Jacob, M. A.; Cai, M.; Duering, M.; Chamberland, M.; Norris, D. G.; Kessels, R. P. C.; de Leeuw, F.; Marques, J. P.; and Tuladhar, A. M.\n\n\n \n\n\n\n Brain,awad220. June 2023.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{li_regional_2023,\n\ttitle = {Regional cortical thinning, demyelination, and iron loss in cerebral small vessel disease},\n\tissn = {1460-2156},\n\tdoi = {10.1093/brain/awad220},\n\tabstract = {The link between white matter hyperintensities (WMH) and cortical thinning is thought to be an important pathway by which WMH contributes to cognitive deficits in cerebral small vessel disease (SVD). However, the mechanism behind this association and the underlying tissue composition abnormalities are unclear. The objective of this study is to determine the association between WMH and cortical thickness, and the in-vivo tissue composition abnormalities in the WMH-connected cortical regions. In this cross-sectional study, we included 213 participants with SVD who underwent standardized protocol including multimodal neuroimaging scans and cognitive assessment (i.e., processing speed, executive function, and memory). We identified the cortex connected to WMH using probabilistic tractography starting from the WMH and defined the WMH-connected regions at three connectivity levels (low, medium, and high connectivity level). We calculated the cortical thickness, myelin and iron of the cortex based on T1-weighted, quantitative R1, R2*, and susceptibility maps. We used diffusion-weighted imaging to estimate the mean diffusivity (MD) of the connecting white matter tracts. We found that cortical thickness, R1, R2*, and susceptibility values in the WMH-connected regions were significantly lower than in the WMH-unconnected regions (all p-corrected{\\textless}0.001). Linear regression analyses showed that higher MD of the connecting white matter tracts were related to lower thickness (β=-0.30, p-corrected{\\textless}0.001), R1 (β=-0.26, p-corrected=0.001), R2* (β=-0.32, p-corrected{\\textless}0.001) and susceptibility values (β=-0.39, p-corrected{\\textless}0.001) of WMH-connected cortical regions at high connectivity level. In addition, lower scores on processing speed were significantly related to lower cortical thickness (β=0.20, p-corrected=0.030), lower R1 values (β=0.20, p-corrected=0.006), lower R2* values (β=0.29, p-corrected=0.006), and lower susceptibility values (β=0.19, p-corrected=0.024) of the WMH-connected regions at high connectivity level, independent of WMH volumes and the cortical measures of WMH-unconnected regions. Together, our study demonstrated that the microstructural integrity of white matter tracts passing through WMH is related to the regional cortical abnormalities as measured by thickness, R1, R2* and susceptibility values in the connected cortical regions. These findings are indicative of cortical thinning, demyelination and iron loss in the cortex, which is most likely through the disruption of the connecting white matter tracts and may contribute to processing speed impairment in SVD, a key clinical feature of SVD. These findings may have implications for finding intervention targets for the treatment of cognitive impairment in SVD by preventing secondary degeneration.},\n\tlanguage = {eng},\n\tjournal = {Brain},\n\tauthor = {Li, Hao and Jacob, Mina A. and Cai, Mengfei and Duering, Marco and Chamberland, Maxime and Norris, David G. and Kessels, Roy P. C. and de Leeuw, Frank-Erik and Marques, José P. and Tuladhar, Anil M.},\n\tmonth = jun,\n\tyear = {2023},\n\tpmid = {37366338},\n\tkeywords = {white matter hyperintensities, cortical thickness, iron, myelination, secondary degeneration, biosketch},\n\tpages = {awad220},\n\tfile = {Full Text:/Users/mduering/Zotero/storage/N33FMISG/Li et al. - 2023 - Regional cortical thinning, demyelination, and iro.pdf:application/pdf},\n}\n\n

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\n The link between white matter hyperintensities (WMH) and cortical thinning is thought to be an important pathway by which WMH contributes to cognitive deficits in cerebral small vessel disease (SVD). However, the mechanism behind this association and the underlying tissue composition abnormalities are unclear. The objective of this study is to determine the association between WMH and cortical thickness, and the in-vivo tissue composition abnormalities in the WMH-connected cortical regions. In this cross-sectional study, we included 213 participants with SVD who underwent standardized protocol including multimodal neuroimaging scans and cognitive assessment (i.e., processing speed, executive function, and memory). We identified the cortex connected to WMH using probabilistic tractography starting from the WMH and defined the WMH-connected regions at three connectivity levels (low, medium, and high connectivity level). We calculated the cortical thickness, myelin and iron of the cortex based on T1-weighted, quantitative R1, R2*, and susceptibility maps. We used diffusion-weighted imaging to estimate the mean diffusivity (MD) of the connecting white matter tracts. We found that cortical thickness, R1, R2*, and susceptibility values in the WMH-connected regions were significantly lower than in the WMH-unconnected regions (all p-corrected\\textless0.001). Linear regression analyses showed that higher MD of the connecting white matter tracts were related to lower thickness (β=-0.30, p-corrected\\textless0.001), R1 (β=-0.26, p-corrected=0.001), R2* (β=-0.32, p-corrected\\textless0.001) and susceptibility values (β=-0.39, p-corrected\\textless0.001) of WMH-connected cortical regions at high connectivity level. In addition, lower scores on processing speed were significantly related to lower cortical thickness (β=0.20, p-corrected=0.030), lower R1 values (β=0.20, p-corrected=0.006), lower R2* values (β=0.29, p-corrected=0.006), and lower susceptibility values (β=0.19, p-corrected=0.024) of the WMH-connected regions at high connectivity level, independent of WMH volumes and the cortical measures of WMH-unconnected regions. Together, our study demonstrated that the microstructural integrity of white matter tracts passing through WMH is related to the regional cortical abnormalities as measured by thickness, R1, R2* and susceptibility values in the connected cortical regions. These findings are indicative of cortical thinning, demyelination and iron loss in the cortex, which is most likely through the disruption of the connecting white matter tracts and may contribute to processing speed impairment in SVD, a key clinical feature of SVD. These findings may have implications for finding intervention targets for the treatment of cognitive impairment in SVD by preventing secondary degeneration.\n

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\n \n\n \n \n \n \n \n Blood-brain barrier leakage hotspots collocating with brain lesions due to sporadic and monogenic small vessel disease.\n \n \n \n\n\n \n Rudilosso, S.; Stringer, M. S.; Thrippleton, M.; Chappell, F.; Blair, G. W.; Jaime Garcia, D.; Doubal, F.; Hamilton, I.; Janssen, E.; Kopczak, A.; Ingrisch, M.; Kerkhofs, D.; Backes, W. H.; Staals, J.; Duering, M.; Dichgans, M.; Wardlaw, J. M.; and SVDs@target consortium\n\n\n \n\n\n\n J Cereb Blood Flow Metab, 43(9): 1490–1502. September 2023.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{rudilosso_blood-brain_2023,\n\ttitle = {Blood-brain barrier leakage hotspots collocating with brain lesions due to sporadic and monogenic small vessel disease},\n\tvolume = {43},\n\tissn = {1559-7016},\n\tdoi = {10.1177/0271678X231173444},\n\tabstract = {Blood-brain barrier (BBB) is known to be impaired in cerebral small vessel disease (SVD), and is measurable by dynamic-contrast enhancement (DCE)-MRI. In a cohort of 69 patients (42 sporadic, 27 monogenic SVD), who underwent 3T MRI, including DCE and cerebrovascular reactivity (CVR) sequences, we assessed the relationship of BBB-leakage hotspots to SVD lesions (lacunes, white matter hyperintensities (WMH), and microbleeds). We defined as hotspots the regions with permeability surface area product highest decile on DCE-derived maps within the white matter. We assessed factors associated with the presence and number of hotspots corresponding to SVD lesions in multivariable regression models adjusted for age, WMH volume, number of lacunes, and SVD type. We identified hotspots at lacune edges in 29/46 (63\\%) patients with lacunes, within WMH in 26/60 (43\\%) and at the WMH edges in 34/60 (57\\%) patients with WMH, and microbleed edges in 4/11 (36\\%) patients with microbleeds. In adjusted analysis, lower WMH-CVR was associated with presence and number of hotspots at lacune edges, and higher WMH volume with hotspots within WMH and at WMH edges, independently of the SVD type. In conclusion, SVD lesions frequently collocate with high BBB-leakage in patients with sporadic and monogenic forms of SVD.},\n\tlanguage = {eng},\n\tnumber = {9},\n\tjournal = {J Cereb Blood Flow Metab},\n\tauthor = {Rudilosso, Salvatore and Stringer, Michael S. and Thrippleton, Michael and Chappell, Francesca and Blair, Gordon W. and Jaime Garcia, Daniela and Doubal, Fergus and Hamilton, Iona and Janssen, Esther and Kopczak, Anna and Ingrisch, Michael and Kerkhofs, Danielle and Backes, Walter H. and Staals, Julie and Duering, Marco and Dichgans, Martin and Wardlaw, Joanna M. and {SVDs@target consortium}},\n\tmonth = sep,\n\tyear = {2023},\n\tpmid = {37132279},\n\tpmcid = {PMC10414006},\n\tkeywords = {Humans, cerebral small vessel disease, Magnetic Resonance Imaging, white matter hyperintensities, Blood-brain barrier, White Matter, Cerebral Hemorrhage, Cerebral Small Vessel Diseases, Blood-Brain Barrier, dynamic-contrast enhanced imaging, lacunar},\n\tpages = {1490--1502},\n\tfile = {Full Text:/Users/mduering/Zotero/storage/Q7JWHXJ5/Rudilosso et al. - 2023 - Blood-brain barrier leakage hotspots collocating w.pdf:application/pdf},\n}\n\n

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\n \n\n \n \n \n \n \n Peak width of skeletonized mean diffusivity and cognitive performance in cerebral amyloid angiopathy.\n \n \n \n\n\n \n Horn, M. J.; Gokcal, E.; Becker, J. A.; Das, A. S.; Schwab, K.; Zanon Zotin, M. C.; Goldstein, J. N.; Rosand, J.; Viswanathan, A.; Polimeni, J. R.; Duering, M.; Greenberg, S. M.; and Gurol, M. E.\n\n\n \n\n\n\n Front Neurosci, 17: 1141007. 2023.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{horn_peak_2023,\n\ttitle = {Peak width of skeletonized mean diffusivity and cognitive performance in cerebral amyloid angiopathy},\n\tvolume = {17},\n\tissn = {1662-4548},\n\tdoi = {10.3389/fnins.2023.1141007},\n\tabstract = {BACKGROUND: Cerebral Amyloid Angiopathy (CAA) is a cerebral small vessel disease that can lead to microstructural disruption of white matter (WM), which can be measured by the Peak Width of Skeletonized Mean Diffusivity (PSMD). We hypothesized that PSMD measures would be increased in patients with CAA compared to healthy controls (HC), and increased PSMD is associated with lower cognitive scores in patients with CAA.\nMETHODS: Eighty-one probable CAA patients without cognitive impairment who were diagnosed with Boston criteria and 23 HCs were included. All subjects underwent an advanced brain MRI with high-resolution diffusion-weighted imaging (DWI). PSMD scores were quantified from a probabilistic skeleton of the WM tracts in the mean diffusivity (MD) image using a combination of fractional anisotropy (FA) and the FSL Tract-Based Spatial Statistics (TBSS) algorithm (www.psmd-marker.com). Within CAA cohort, standardized z-scores of processing speed, executive functioning and memory were obtained.\nRESULTS: The mean of age and sex were similar between CAA patients (69.6 ± 7.3, 59.3\\% male) and HCs (70.6 ± 8.5, 56.5\\% male) (p = 0.581 and p = 0.814). PSMD was higher in the CAA group [(4.13 ± 0.94) × 10-4 mm2/s] compared to HCs [(3.28 ± 0.51) × 10-4 mm2/s] (p {\\textless} 0.001). In a linear regression model corrected for relevant variables, diagnosis of CAA was independently associated with increased PSMD compared to HCs (ß = 0.45, 95\\% CI 0.13-0.76, p = 0.006). Within CAA cohort, higher PSMD was associated with lower scores in processing speed (p {\\textless} 0.001), executive functioning (p = 0.004), and memory (0.047). Finally, PSMD outperformed all other MRI markers of CAA by explaining most of the variance in models predicting lower scores in each cognitive domain.\nDISCUSSION: Peak Width of Skeletonized Mean Diffusivity is increased in CAA, and it is associated with worse cognitive scores supporting the view that disruption of white matter has a significant role in cognitive impairment in CAA. As a robust marker, PSMD can be used in clinical trials or practice.},\n\tlanguage = {eng},\n\tjournal = {Front Neurosci},\n\tauthor = {Horn, Mitchell J. and Gokcal, Elif and Becker, J. Alex and Das, Alvin S. and Schwab, Kristin and Zanon Zotin, Maria Clara and Goldstein, Joshua N. and Rosand, Jonathan and Viswanathan, Anand and Polimeni, Jonathan R. and Duering, Marco and Greenberg, Steven M. and Gurol, M. Edip},\n\tyear = {2023},\n\tpmid = {37077322},\n\tpmcid = {PMC10106761},\n\tkeywords = {cerebral small vessel disease, cerebral amyloid angiopathy (CAA), cognitive functions, diffusion-weighted imaging, peak width of skeletonized mean diffusivity (PSMD)},\n\tpages = {1141007},\n\tfile = {Full Text:/Users/mduering/Zotero/storage/HLXL3TP5/Horn et al. - 2023 - Peak width of skeletonized mean diffusivity and co.pdf:application/pdf},\n}\n\n

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\n BACKGROUND: Cerebral Amyloid Angiopathy (CAA) is a cerebral small vessel disease that can lead to microstructural disruption of white matter (WM), which can be measured by the Peak Width of Skeletonized Mean Diffusivity (PSMD). We hypothesized that PSMD measures would be increased in patients with CAA compared to healthy controls (HC), and increased PSMD is associated with lower cognitive scores in patients with CAA. METHODS: Eighty-one probable CAA patients without cognitive impairment who were diagnosed with Boston criteria and 23 HCs were included. All subjects underwent an advanced brain MRI with high-resolution diffusion-weighted imaging (DWI). PSMD scores were quantified from a probabilistic skeleton of the WM tracts in the mean diffusivity (MD) image using a combination of fractional anisotropy (FA) and the FSL Tract-Based Spatial Statistics (TBSS) algorithm (www.psmd-marker.com). Within CAA cohort, standardized z-scores of processing speed, executive functioning and memory were obtained. RESULTS: The mean of age and sex were similar between CAA patients (69.6 ± 7.3, 59.3% male) and HCs (70.6 ± 8.5, 56.5% male) (p = 0.581 and p = 0.814). PSMD was higher in the CAA group [(4.13 ± 0.94) × 10-4 mm2/s] compared to HCs [(3.28 ± 0.51) × 10-4 mm2/s] (p \\textless 0.001). In a linear regression model corrected for relevant variables, diagnosis of CAA was independently associated with increased PSMD compared to HCs (ß = 0.45, 95% CI 0.13-0.76, p = 0.006). Within CAA cohort, higher PSMD was associated with lower scores in processing speed (p \\textless 0.001), executive functioning (p = 0.004), and memory (0.047). Finally, PSMD outperformed all other MRI markers of CAA by explaining most of the variance in models predicting lower scores in each cognitive domain. DISCUSSION: Peak Width of Skeletonized Mean Diffusivity is increased in CAA, and it is associated with worse cognitive scores supporting the view that disruption of white matter has a significant role in cognitive impairment in CAA. As a robust marker, PSMD can be used in clinical trials or practice.\n

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\n \n\n \n \n \n \n \n Cerebral Small Vessel Disease Progression and the Risk of Dementia: A 14-Year Follow-Up Study.\n \n \n \n\n\n \n Jacob, M. A.; Cai, M.; van de Donk, V.; Bergkamp, M.; Marques, J.; Norris, D. G.; Kessels, R. P. C.; Claassen, J. A. H. R.; Duering, M.; Tuladhar, A. M.; and Leeuw, F. d.\n\n\n \n\n\n\n Am J Psychiatry, 180(7): 508–518. July 2023.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{jacob_cerebral_2023,\n\ttitle = {Cerebral {Small} {Vessel} {Disease} {Progression} and the {Risk} of {Dementia}: {A} 14-{Year} {Follow}-{Up} {Study}},\n\tvolume = {180},\n\tissn = {1535-7228},\n\tshorttitle = {Cerebral {Small} {Vessel} {Disease} {Progression} and the {Risk} of {Dementia}},\n\tdoi = {10.1176/appi.ajp.20220380},\n\tabstract = {OBJECTIVE: Cerebral small vessel disease (SVD) is considered the most important vascular contributor to cognitive decline and dementia, although a causal relation between its MRI markers and dementia still needs to be established. The authors investigated the relation between baseline SVD severity as well as SVD progression on MRI markers and incident dementia, by subtype, in individuals with sporadic SVD over a follow-up period of 14 years.\nMETHODS: The study included 503 participants with sporadic SVD, and without dementia, from the prospective Radboud University Nijmegen Diffusion Tensor and Magnetic Resonance Cohort (RUN DMC) study, with screening for baseline inclusion conducted in 2006. Follow-ups in 2011, 2015, and 2020 included cognitive assessments and MRI scans. Dementia was diagnosed according to DSM-5 criteria and stratified into Alzheimer's dementia and vascular dementia.\nRESULTS: Dementia as an endpoint was available for 498 participants (99.0\\%) and occurred in 108 participants (21.5\\%) (Alzheimer's dementia, N=38; vascular dementia, N=34; mixed-etiology Alzheimer's dementia/vascular dementia, N=26), with a median follow-up time of 13.2 years (interquartile range, 8.8-13.8). Higher baseline white matter hyperintensity (WMH) volume (hazard ratio=1.31 per 1-SD increase, 95\\% CI=1.02-1.67), presence of diffusion-weighted-imaging-positive lesions (hazard ratio=2.03, 95\\% CI=1.01-4.04), and higher peak width of skeletonized mean diffusivity (hazard ratio=1.24 per 1-SD increase, 95\\% CI=1.02-1.51) were independently associated with all-cause dementia and vascular dementia. WMH progression predicted incident all-cause dementia (hazard ratio=1.76 per 1-SD increase, 95\\% CI=1.18-2.63).\nCONCLUSIONS: Both baseline SVD severity and SVD progression were independently associated with an increase in risk of all-cause dementia over a follow-up of 14 years. The results suggest that SVD progression precedes dementia and may causally contribute to its development. Slowing SVD progression may delay dementia onset.},\n\tlanguage = {eng},\n\tnumber = {7},\n\tjournal = {Am J Psychiatry},\n\tauthor = {Jacob, Mina A. and Cai, Mengfei and van de Donk, Vera and Bergkamp, Mayra and Marques, José and Norris, David G. and Kessels, Roy P. C. and Claassen, Jurgen A. H. R. and Duering, Marco and Tuladhar, Anil M. and Leeuw, Frank-Erik de},\n\tmonth = jul,\n\tyear = {2023},\n\tpmid = {37073486},\n\tkeywords = {Disease Progression, Humans, Prospective Studies, Neuroimaging, Follow-Up Studies, Magnetic Resonance Imaging, Dementia, Dementia, Vascular, Alzheimer Disease, Cerebral Small Vessel Diseases, MRI, Alzheimer’s Disease, Cognitive Decline, Small Vessel Disease},\n\tpages = {508--518},\n}\n\n

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\n OBJECTIVE: Cerebral small vessel disease (SVD) is considered the most important vascular contributor to cognitive decline and dementia, although a causal relation between its MRI markers and dementia still needs to be established. The authors investigated the relation between baseline SVD severity as well as SVD progression on MRI markers and incident dementia, by subtype, in individuals with sporadic SVD over a follow-up period of 14 years. METHODS: The study included 503 participants with sporadic SVD, and without dementia, from the prospective Radboud University Nijmegen Diffusion Tensor and Magnetic Resonance Cohort (RUN DMC) study, with screening for baseline inclusion conducted in 2006. Follow-ups in 2011, 2015, and 2020 included cognitive assessments and MRI scans. Dementia was diagnosed according to DSM-5 criteria and stratified into Alzheimer's dementia and vascular dementia. RESULTS: Dementia as an endpoint was available for 498 participants (99.0%) and occurred in 108 participants (21.5%) (Alzheimer's dementia, N=38; vascular dementia, N=34; mixed-etiology Alzheimer's dementia/vascular dementia, N=26), with a median follow-up time of 13.2 years (interquartile range, 8.8-13.8). Higher baseline white matter hyperintensity (WMH) volume (hazard ratio=1.31 per 1-SD increase, 95% CI=1.02-1.67), presence of diffusion-weighted-imaging-positive lesions (hazard ratio=2.03, 95% CI=1.01-4.04), and higher peak width of skeletonized mean diffusivity (hazard ratio=1.24 per 1-SD increase, 95% CI=1.02-1.51) were independently associated with all-cause dementia and vascular dementia. WMH progression predicted incident all-cause dementia (hazard ratio=1.76 per 1-SD increase, 95% CI=1.18-2.63). CONCLUSIONS: Both baseline SVD severity and SVD progression were independently associated with an increase in risk of all-cause dementia over a follow-up of 14 years. The results suggest that SVD progression precedes dementia and may causally contribute to its development. Slowing SVD progression may delay dementia onset.\n

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\n \n\n \n \n \n \n \n The EffecTs of Amlodipine and other Blood PREssure Lowering Agents on Microvascular FuncTion in Small Vessel Diseases (TREAT-SVDs) trial: Study protocol for a randomised crossover trial.\n \n \n \n\n\n \n Kopczak, A.; S Stringer, M.; van den Brink, H.; Kerkhofs, D.; W Blair, G.; van Dinther, M.; Onkenhout, L.; A Wartolowska, K.; Thrippleton, M. J.; Duering, M.; Staals, J.; Middeke, M.; André, E.; Norrving, B.; Bousser, M.; Mansmann, U.; Rothwell, P. M.; N Doubal, F.; van Oostenbrugge, R.; Biessels, G. J.; Webb, A. J.; Wardlaw, J. M.; and Dichgans, M.\n\n\n \n\n\n\n Eur Stroke J, 8(1): 387–397. March 2023.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{kopczak_effects_2023,\n\ttitle = {The {EffecTs} of {Amlodipine} and other {Blood} {PREssure} {Lowering} {Agents} on {Microvascular} {FuncTion} in {Small} {Vessel} {Diseases} ({TREAT}-{SVDs}) trial: {Study} protocol for a randomised crossover trial},\n\tvolume = {8},\n\tissn = {2396-9881},\n\tshorttitle = {The {EffecTs} of {Amlodipine} and other {Blood} {PREssure} {Lowering} {Agents} on {Microvascular} {FuncTion} in {Small} {Vessel} {Diseases} ({TREAT}-{SVDs}) trial},\n\tdoi = {10.1177/23969873221143570},\n\tabstract = {BACKGROUND: Hypertension is the leading modifiable risk factor for cerebral small vessel diseases (SVDs). Yet, it is unknown whether antihypertensive drug classes differentially affect microvascular function in SVDs.\nAIMS: To test whether amlodipine has a beneficial effect on microvascular function when compared to either losartan or atenolol, and whether losartan has a beneficial effect when compared to atenolol in patients with symptomatic SVDs.\nDESIGN: TREAT-SVDs is an investigator-led, prospective, open-label, randomised crossover trial with blinded endpoint assessment (PROBE design) conducted at five study sites across Europe. Patients aged 18 years or older with symptomatic SVD who have an indication for antihypertensive treatment and are suffering from either sporadic SVD and a history of lacunar stroke or vascular cognitive impairment (group A) or CADASIL (group B) are randomly allocated 1:1:1 to one of three sequences of antihypertensive treatment. Patients stop their regular antihypertensive medication for a 2-week run-in period followed by 4-week periods of monotherapy with amlodipine, losartan and atenolol in random order as open-label medication in standard dose.\nOUTCOMES: The primary outcome measure is cerebrovascular reactivity (CVR) as determined by blood oxygen level dependent brain MRI signal response to hypercapnic challenge with change in CVR in normal appearing white matter as primary endpoint. Secondary outcome measures are mean systolic blood pressure (BP) and BP variability (BPv).\nDISCUSSION: TREAT-SVDs will provide insights into the effects of different antihypertensive drugs on CVR, BP, and BPv in patients with symptomatic sporadic and hereditary SVDs.\nFUNDING: European Union's Horizon 2020 programme.\nTRIAL REGISTRATION: NCT03082014.},\n\tlanguage = {eng},\n\tnumber = {1},\n\tjournal = {Eur Stroke J},\n\tauthor = {Kopczak, Anna and S Stringer, Michael and van den Brink, Hilde and Kerkhofs, Danielle and W Blair, Gordon and van Dinther, Maud and Onkenhout, Laurien and A Wartolowska, Karolina and Thrippleton, Michael J. and Duering, Marco and Staals, Julie and Middeke, Martin and André, Elisabeth and Norrving, Bo and Bousser, Marie-Germaine and Mansmann, Ulrich and Rothwell, Peter M. and N Doubal, Fergus and van Oostenbrugge, Robert and Biessels, Geert Jan and Webb, Alastair Js and Wardlaw, Joanna M. and Dichgans, Martin},\n\tmonth = mar,\n\tyear = {2023},\n\tpmid = {37021189},\n\tpmcid = {PMC10069218},\n\tkeywords = {Humans, Prospective Studies, Small vessel diseases, vascular cognitive impairment, magnetic resonance imaging, CADASIL, cerebrovascular reactivity, amlodipine, Amlodipine, Antihypertensive Agents, antihypertensive drug classes, Atenolol, Blood Pressure, blood pressure variability, Cross-Over Studies, lacunar stroke, Losartan, randomised clinical trial, Randomized Controlled Trials as Topic},\n\tpages = {387--397},\n\tfile = {Full Text:/Users/mduering/Zotero/storage/JVLQXZEG/Kopczak et al. - 2023 - The EffecTs of Amlodipine and other Blood PREssure.pdf:application/pdf},\n}\n\n

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\n \n\n \n \n \n \n \n Dissociable Contributions of Thalamic-Subregions to Cognitive Impairment in Small Vessel Disease.\n \n \n \n\n\n \n Li, H.; Cai, M.; Jacob, M. A.; Norris, D. G.; Marques, J. P.; Chamberland, M.; Duering, M.; Kessels, R. P. C.; de Leeuw, F.; and Tuladhar, A. M.\n\n\n \n\n\n\n Stroke, 54(5): 1367–1376. May 2023.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{li_dissociable_2023,\n\ttitle = {Dissociable {Contributions} of {Thalamic}-{Subregions} to {Cognitive} {Impairment} in {Small} {Vessel} {Disease}},\n\tvolume = {54},\n\tissn = {1524-4628},\n\tdoi = {10.1161/STROKEAHA.122.041687},\n\tabstract = {BACKGROUND: Structural network damage is a potentially important mechanism by which cerebral small vessel disease (SVD) can cause cognitive impairment. As a central hub of the structural network, the role of thalamus in SVD-related cognitive impairments remains unclear. We aimed to determine the associations between the structural alterations of thalamic subregions and cognitive impairments in SVD.\nMETHODS: In this cross-sectional study, 205 SVD participants without thalamic lacunes from the third follow-up (2020) of the prospective RUN DMC study (Radboud University Nijmegen Diffusion Tensor and Magnetic Resonance Cohort), which was initiated in 2006, Nijmegen, were included. Cognitive functions included processing speed, executive function, and memory. Probabilistic tractography was performed from thalamus to 6 cortical regions, followed by connectivity-based thalamic segmentation to assess each thalamic subregion volume and connectivity (measured by mean diffusivity [MD] of the connecting white matter tracts) with the cortex. Least absolute shrinkage and selection operator regression analysis was conducted to identify the volumes or connectivity of the total thalamus and 6 thalamic subregions that have the strongest association with cognitive performance. Linear regression and mediation analyses were performed to test the association of least absolute shrinkage and selection operator-selected thalamic subregion volume or MD with cognitive performance, while adjusting for age and education.\nRESULTS: We found that higher MD of the thalamic-motor tract was associated with worse processing speed (β=-0.27; P{\\textless}0.001), higher MD of the thalamic-frontal tract was associated with worse executive function (β=-0.24; P=0.001), and memory (β=-0.28; P{\\textless}0.001), respectively. The mediation analysis showed that MD of thalamocortical tracts mediated the association between corresponding thalamic subregion volumes and the cognitive performances in 3 domains.\nCONCLUSIONS: Our results suggest that the structural alterations of thalamus are linked to cognitive impairment in SVD, largely depending on the damage pattern of the white matter tracts connecting specific thalamic subregions and cortical regions.},\n\tlanguage = {eng},\n\tnumber = {5},\n\tjournal = {Stroke},\n\tauthor = {Li, Hao and Cai, Mengfei and Jacob, Mina A. and Norris, David G. and Marques, José P. and Chamberland, Maxime and Duering, Marco and Kessels, Roy P. C. and de Leeuw, Frank-Erik and Tuladhar, Anil M.},\n\tmonth = may,\n\tyear = {2023},\n\tpmid = {36912138},\n\tpmcid = {PMC10121245},\n\tkeywords = {Diffusion Tensor Imaging, Humans, cerebral small vessel disease, white matter, Prospective Studies, Magnetic Resonance Imaging, Cross-Sectional Studies, White Matter, Cerebral Small Vessel Diseases, thalamus, Cognitive Dysfunction, cognitive impairments, cortical regions, Thalamus},\n\tpages = {1367--1376},\n\tfile = {Full Text:/Users/mduering/Zotero/storage/HLDK9WTE/Li et al. - 2023 - Dissociable Contributions of Thalamic-Subregions t.pdf:application/pdf},\n}\n\n

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\n BACKGROUND: Structural network damage is a potentially important mechanism by which cerebral small vessel disease (SVD) can cause cognitive impairment. As a central hub of the structural network, the role of thalamus in SVD-related cognitive impairments remains unclear. We aimed to determine the associations between the structural alterations of thalamic subregions and cognitive impairments in SVD. METHODS: In this cross-sectional study, 205 SVD participants without thalamic lacunes from the third follow-up (2020) of the prospective RUN DMC study (Radboud University Nijmegen Diffusion Tensor and Magnetic Resonance Cohort), which was initiated in 2006, Nijmegen, were included. Cognitive functions included processing speed, executive function, and memory. Probabilistic tractography was performed from thalamus to 6 cortical regions, followed by connectivity-based thalamic segmentation to assess each thalamic subregion volume and connectivity (measured by mean diffusivity [MD] of the connecting white matter tracts) with the cortex. Least absolute shrinkage and selection operator regression analysis was conducted to identify the volumes or connectivity of the total thalamus and 6 thalamic subregions that have the strongest association with cognitive performance. Linear regression and mediation analyses were performed to test the association of least absolute shrinkage and selection operator-selected thalamic subregion volume or MD with cognitive performance, while adjusting for age and education. RESULTS: We found that higher MD of the thalamic-motor tract was associated with worse processing speed (β=-0.27; P\\textless0.001), higher MD of the thalamic-frontal tract was associated with worse executive function (β=-0.24; P=0.001), and memory (β=-0.28; P\\textless0.001), respectively. The mediation analysis showed that MD of thalamocortical tracts mediated the association between corresponding thalamic subregion volumes and the cognitive performances in 3 domains. CONCLUSIONS: Our results suggest that the structural alterations of thalamus are linked to cognitive impairment in SVD, largely depending on the damage pattern of the white matter tracts connecting specific thalamic subregions and cortical regions.\n

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\n \n\n \n \n \n \n \n Cerebral Small Vessel Disease Progression Increases Risk of Incident Parkinsonism.\n \n \n \n\n\n \n Jacob, M. A.; Cai, M.; Bergkamp, M.; Darweesh, S. K. L.; Gelissen, L. M. Y.; Marques, J.; Norris, D. G.; Duering, M.; Esselink, R. A. J.; Tuladhar, A. M.; and de Leeuw, F.\n\n\n \n\n\n\n Ann Neurol, 93(6): 1130–1141. June 2023.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{jacob_cerebral_2023-1,\n\ttitle = {Cerebral {Small} {Vessel} {Disease} {Progression} {Increases} {Risk} of {Incident} {Parkinsonism}},\n\tvolume = {93},\n\tissn = {1531-8249},\n\tdoi = {10.1002/ana.26615},\n\tabstract = {OBJECTIVE: Cerebral small vessel disease (SVD) is associated with motor impairments and parkinsonian signs cross-sectionally, however, there are little longitudinal data on whether SVD increases risk of incident parkinsonism itself. We investigated the relation between baseline SVD severity as well as SVD progression, and incident parkinsonism over a follow-up of 14 years.\nMETHODS: This study included 503 participants with SVD, and without parkinsonism at baseline, from the RUN DMC prospective cohort study. Baseline inclusion was performed in 2006 and follow-up took place in 2011, 2015, and 2020, including magnetic resonance imaging (MRI) and motor assessments. Parkinsonism was diagnosed according to the UK Brain Bank criteria, and stratified into vascular parkinsonism (VaP) and idiopathic Parkinson's disease (IPD). Linear mixed-effect models were constructed to estimate individual rate changes of MRI-characteristics.\nRESULTS: Follow-up for incident parkinsonism was near-complete (99\\%). In total, 51 (10.2\\%) participants developed parkinsonism (33 VaP, 17 IPD, and 1 progressive supranuclear palsy). Patients with incident VaP had higher SVD burden compared with patients with IPD. Higher baseline white matter hyperintensities (hazard ratio [HR] = 1.46 per 1-SD increase, 95\\% confidence interval [CI] = 1.21-1.78), peak width of skeletonized mean diffusivity (HR = 1.66 per 1-SD increase, 95\\% CI = 1.34-2.05), and presence of lacunes (HR = 1.84, 95\\% CI = 0.99-3.42) were associated with increased risk of all-cause parkinsonism. Incident lacunes were associated with incident VaP (HR = 4.64, 95\\% CI = 1.32-16.32).\nINTERPRETATION: Both baseline SVD severity and SVD progression are independently associated with long-term parkinsonism. Our findings indicate a causal role of SVD in parkinsonism. Future studies are needed to examine the underlying pathophysiology of this relation. ANN NEUROL 2023;93:1130-1141.},\n\tlanguage = {eng},\n\tnumber = {6},\n\tjournal = {Ann Neurol},\n\tauthor = {Jacob, Mina A. and Cai, Mengfei and Bergkamp, Mayra and Darweesh, Sirwan K. L. and Gelissen, Liza M. Y. and Marques, José and Norris, David G. and Duering, Marco and Esselink, Rianne A. J. and Tuladhar, Anil M. and de Leeuw, Frank-Erik},\n\tmonth = jun,\n\tyear = {2023},\n\tpmid = {36762437},\n\tkeywords = {Disease Progression, Humans, Prospective Studies, Magnetic Resonance Imaging, Brain, Parkinson Disease, Cerebral Small Vessel Diseases, Parkinsonian Disorders},\n\tpages = {1130--1141},\n\tfile = {Full Text:/Users/mduering/Zotero/storage/VQMILT4F/Jacob et al. - 2023 - Cerebral Small Vessel Disease Progression Increase.pdf:application/pdf},\n}\n\n

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\n \n\n \n \n \n \n \n Decreased Cerebrospinal Fluid Amyloid β 38, 40, 42, and 43 Levels in Sporadic and Hereditary Cerebral Amyloid Angiopathy.\n \n \n \n\n\n \n De Kort, A. M.; Kuiperij, H. B.; Marques, T. M.; Jäkel, L.; van den Berg, E.; Kersten, I.; van Berckel-Smit, H. E. P.; Duering, M.; Stoops, E.; Abdo, W. F.; Rasing, I.; Voigt, S.; Koemans, E. A.; Kaushik, K.; Warren, A. D.; Greenberg, S. M.; Brinkmalm, G.; Terwindt, G. M.; Wermer, M. J. H.; Schreuder, F. H. B. M.; Klijn, C. J. M.; and Verbeek, M. M.\n\n\n \n\n\n\n Ann Neurol, 93(6): 1173–1186. June 2023.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{de_kort_decreased_2023,\n\ttitle = {Decreased {Cerebrospinal} {Fluid} {Amyloid} β 38, 40, 42, and 43 {Levels} in {Sporadic} and {Hereditary} {Cerebral} {Amyloid} {Angiopathy}},\n\tvolume = {93},\n\tissn = {1531-8249},\n\tdoi = {10.1002/ana.26610},\n\tabstract = {OBJECTIVE: Vascular amyloid β (Aβ) accumulation is the hallmark of cerebral amyloid angiopathy (CAA). The composition of cerebrospinal fluid (CSF) of CAA patients may serve as a diagnostic biomarker of CAA. We studied the diagnostic potential of the peptides Aβ38, Aβ40, Aβ42, and Aβ43 in patients with sporadic CAA (sCAA), hereditary Dutch-type CAA (D-CAA), and Alzheimer disease (AD).\nMETHODS: Aβ peptides were quantified by immunoassays in a discovery group (26 patients with sCAA and 40 controls), a validation group (40 patients with sCAA, 40 patients with AD, and 37 controls), and a group of 22 patients with D-CAA and 54 controls. To determine the diagnostic accuracy, the area under the curve (AUC) was calculated using a receiver operating characteristic curve with 95\\% confidence interval (CI).\nRESULTS: We found decreased levels of all Aβ peptides in sCAA patients and D-CAA patients compared to controls. The difference was most prominent for Aβ42 (AUC of sCAA vs controls for discovery: 0.90, 95\\% CI = 0.82-0.99; for validation: 0.94, 95\\% CI = 0.89-0.99) and Aβ43 (AUC of sCAA vs controls for discovery: 0.95, 95\\% CI = 0.88-1.00; for validation: 0.91, 95\\% CI = 0.83-1.0). All Aβ peptides except Aβ43 were also decreased in sCAA compared to AD (CSF Aβ38: AUC = 0.82, 95\\% CI = 0.71-0.93; CSF Aβ40: AUC = 0.88, 95\\% CI = 0.80-0.96; CSF Aβ42: AUC = 0.79, 95\\% CI = 0.66-0.92).\nINTERPRETATION: A combined biomarker panel of CSF Aβ38, Aβ40, Aβ42, and Aβ43 has potential to differentiate sCAA from AD and controls, and D-CAA from controls. ANN NEUROL 2023;93:1173-1186.},\n\tlanguage = {eng},\n\tnumber = {6},\n\tjournal = {Ann Neurol},\n\tauthor = {De Kort, Anna M. and Kuiperij, H. Bea and Marques, Tainá M. and Jäkel, Lieke and van den Berg, Emma and Kersten, Iris and van Berckel-Smit, Hugo E. P. and Duering, Marco and Stoops, Erik and Abdo, Wilson F. and Rasing, Ingeborg and Voigt, Sabine and Koemans, Emma A. and Kaushik, Kanishk and Warren, Andrew Davock and Greenberg, Steven M. and Brinkmalm, Gunnar and Terwindt, Gisela M. and Wermer, Marieke J. H. and Schreuder, Floris H. B. M. and Klijn, Catharina J. M. and Verbeek, Marcel M.},\n\tmonth = jun,\n\tyear = {2023},\n\tpmid = {36707720},\n\tpmcid = {PMC10238617},\n\tkeywords = {Humans, Biomarkers, Amyloid beta-Peptides, Alzheimer Disease, Cerebral Amyloid Angiopathy, Cerebral Amyloid Angiopathy, Familial, Peptide Fragments},\n\tpages = {1173--1186},\n\tfile = {Full Text:/Users/mduering/Zotero/storage/9EEKEXCZ/De Kort et al. - 2023 - Decreased Cerebrospinal Fluid Amyloid β 38, 40, 42.pdf:application/pdf},\n}\n\n

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\n \n\n \n \n \n \n \n Peak Width of Skeletonized Mean Diffusivity: A Neuroimaging Marker for White Matter Injury.\n \n \n \n\n\n \n Zanon Zotin, M. C.; Yilmaz, P.; Sveikata, L.; Schoemaker, D.; van Veluw, S. J.; Etherton, M. R.; Charidimou, A.; Greenberg, S. M.; Duering, M.; and Viswanathan, A.\n\n\n \n\n\n\n Radiology, 306(3): e212780. March 2023.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{zanon_zotin_peak_2023,\n\ttitle = {Peak {Width} of {Skeletonized} {Mean} {Diffusivity}: {A} {Neuroimaging} {Marker} for {White} {Matter} {Injury}},\n\tvolume = {306},\n\tissn = {1527-1315},\n\tshorttitle = {Peak {Width} of {Skeletonized} {Mean} {Diffusivity}},\n\tdoi = {10.1148/radiol.212780},\n\tabstract = {A leading cause of white matter (WM) injury in older individuals is cerebral small vessel disease (SVD). Cerebral SVD is the most prevalent vascular contributor to cognitive impairment and dementia. Therapeutic progress for cerebral SVD and other WM disorders depends on the development and validation of neuroimaging markers suitable as outcome measures in future interventional trials. Diffusion-tensor imaging (DTI) is one of the best-suited MRI techniques for assessing the extent of WM damage in the brain. But the optimal method to analyze individual DTI data remains hindered by labor-intensive and time-consuming processes. Peak width of skeletonized mean diffusivity (PSMD), a recently developed fast, fully automated DTI marker, was designed to quantify the WM damage secondary to cerebral SVD and reflect related cognitive impairment. Despite its promising results, knowledge about PSMD is still limited in the radiologic community. This focused review provides an overview of the technical details of PSMD while synthesizing the available data on its clinical and neuroimaging associations. From a critical expert viewpoint, the authors discuss the limitations of PSMD and its current validation status as a neuroimaging marker for vascular cognitive impairment. Finally, they point out the gaps to be addressed to further advance the field.},\n\tlanguage = {eng},\n\tnumber = {3},\n\tjournal = {Radiology},\n\tauthor = {Zanon Zotin, Maria Clara and Yilmaz, Pinar and Sveikata, Lukas and Schoemaker, Dorothee and van Veluw, Susanne J. and Etherton, Mark R. and Charidimou, Andreas and Greenberg, Steven M. and Duering, Marco and Viswanathan, Anand},\n\tmonth = mar,\n\tyear = {2023},\n\tpmid = {36692402},\n\tpmcid = {PMC9968775},\n\tkeywords = {Aged, Diffusion Magnetic Resonance Imaging, Diffusion Tensor Imaging, Humans, Neuroimaging, Magnetic Resonance Imaging, White Matter, Cerebral Small Vessel Diseases, Cognitive Dysfunction, biosketch},\n\tpages = {e212780},\n}\n\n

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\n \n\n \n \n \n \n \n Machine learning-based approach reveals essential features for simplified TSPO PET quantification in ischemic stroke patients.\n \n \n \n\n\n \n Zatcepin, A.; Kopczak, A.; Holzgreve, A.; Hein, S.; Schindler, A.; Duering, M.; Kaiser, L.; Lindner, S.; Schidlowski, M.; Bartenstein, P.; Albert, N.; Brendel, M.; and Ziegler, S. I.\n\n\n \n\n\n\n Z Med Phys,S0939–3889(22)00128–3. January 2023.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{zatcepin_machine_2023,\n\ttitle = {Machine learning-based approach reveals essential features for simplified {TSPO} {PET} quantification in ischemic stroke patients},\n\tissn = {1876-4436},\n\tdoi = {10.1016/j.zemedi.2022.11.008},\n\tabstract = {INTRODUCTION: Neuroinflammation evaluation after acute ischemic stroke is a promising option for selecting an appropriate post-stroke treatment strategy. To assess neuroinflammation in vivo, translocator protein PET (TSPO PET) can be used. However, the gold standard TSPO PET quantification method includes a 90 min scan and continuous arterial blood sampling, which is challenging to perform on a routine basis. In this work, we determine what information is required for a simplified quantification approach using a machine learning algorithm.\nMATERIALS AND METHODS: We analyzed data from 18 patients with ischemic stroke who received 0-90 min [18F]GE-180 PET as well as T1-weigted (T1w), FLAIR, and arterial spin labeling (ASL) MRI scans. During PET scans, five manual venous blood samples at 5, 15, 30, 60, and 85 min post injection (p.i.) were drawn, and plasma activity concentration was measured. Total distribution volume (VT) was calculated using Logan plot with the full dynamic PET and an image-derived input function (IDIF) from the carotid arteries. IDIF was scaled by a calibration factor derived from all the measured plasma activity concentrations. The calculated VT values were used for training a random forest regressor. As input features for the model, we used three late PET frames (60-70, 70-80, and 80-90 min p.i.), the ASL image reflecting perfusion, the voxel coordinates, the lesion mask, and the five plasma activity concentrations. The algorithm was validated with the leave-one-out approach. To estimate the impact of the individual features on the algorithm's performance, we used Shapley Additive Explanations (SHAP). Having determined that the three late PET frames and the plasma activity concentrations were the most important features, we tested a simplified quantification approach consisting of dividing a late PET frame by a plasma activity concentration. All the combinations of frames/samples were compared by means of concordance correlation coefficient and Bland-Altman plots.\nRESULTS: When using all the input features, the algorithm predicted VT values with high accuracy (87.8 ± 8.3\\%) for both lesion and non-lesion voxels. The SHAP values demonstrated high impact of the late PET frames (60-70, 70-80, and 80-90 min p.i.) and plasma activity concentrations on the VT prediction, while the influence of the ASL-derived perfusion, voxel coordinates, and the lesion mask was low. Among all the combinations of the late PET frames and plasma activity concentrations, the 70-80 min p.i. frame divided by the 30 min p.i. plasma sample produced the closest VT estimate in the ischemic lesion.\nCONCLUSION: Reliable TSPO PET quantification is achievable by using a single late PET frame divided by a late blood sample activity concentration.},\n\tlanguage = {eng},\n\tjournal = {Z Med Phys},\n\tauthor = {Zatcepin, Artem and Kopczak, Anna and Holzgreve, Adrien and Hein, Sandra and Schindler, Andreas and Duering, Marco and Kaiser, Lena and Lindner, Simon and Schidlowski, Martin and Bartenstein, Peter and Albert, Nathalie and Brendel, Matthias and Ziegler, Sibylle I.},\n\tmonth = jan,\n\tyear = {2023},\n\tpmid = {36682921},\n\tkeywords = {GE180, Image-derived input function, Ischemic stroke, Machine learning, Quantitative PET, TSPO},\n\tpages = {S0939--3889(22)00128--3},\n}\n\n

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\n INTRODUCTION: Neuroinflammation evaluation after acute ischemic stroke is a promising option for selecting an appropriate post-stroke treatment strategy. To assess neuroinflammation in vivo, translocator protein PET (TSPO PET) can be used. However, the gold standard TSPO PET quantification method includes a 90 min scan and continuous arterial blood sampling, which is challenging to perform on a routine basis. In this work, we determine what information is required for a simplified quantification approach using a machine learning algorithm. MATERIALS AND METHODS: We analyzed data from 18 patients with ischemic stroke who received 0-90 min [18F]GE-180 PET as well as T1-weigted (T1w), FLAIR, and arterial spin labeling (ASL) MRI scans. During PET scans, five manual venous blood samples at 5, 15, 30, 60, and 85 min post injection (p.i.) were drawn, and plasma activity concentration was measured. Total distribution volume (VT) was calculated using Logan plot with the full dynamic PET and an image-derived input function (IDIF) from the carotid arteries. IDIF was scaled by a calibration factor derived from all the measured plasma activity concentrations. The calculated VT values were used for training a random forest regressor. As input features for the model, we used three late PET frames (60-70, 70-80, and 80-90 min p.i.), the ASL image reflecting perfusion, the voxel coordinates, the lesion mask, and the five plasma activity concentrations. The algorithm was validated with the leave-one-out approach. To estimate the impact of the individual features on the algorithm's performance, we used Shapley Additive Explanations (SHAP). Having determined that the three late PET frames and the plasma activity concentrations were the most important features, we tested a simplified quantification approach consisting of dividing a late PET frame by a plasma activity concentration. All the combinations of frames/samples were compared by means of concordance correlation coefficient and Bland-Altman plots. RESULTS: When using all the input features, the algorithm predicted VT values with high accuracy (87.8 ± 8.3%) for both lesion and non-lesion voxels. The SHAP values demonstrated high impact of the late PET frames (60-70, 70-80, and 80-90 min p.i.) and plasma activity concentrations on the VT prediction, while the influence of the ASL-derived perfusion, voxel coordinates, and the lesion mask was low. Among all the combinations of the late PET frames and plasma activity concentrations, the 70-80 min p.i. frame divided by the 30 min p.i. plasma sample produced the closest VT estimate in the ischemic lesion. CONCLUSION: Reliable TSPO PET quantification is achievable by using a single late PET frame divided by a late blood sample activity concentration.\n

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\n \n\n \n \n \n \n \n Integrated intravoxel incoherent motion tensor and diffusion tensor brain MRI in a single fast acquisition.\n \n \n \n\n\n \n Dietrich, O.; Cai, M.; Tuladhar, A. M.; Jacob, M. A.; Drenthen, G. S.; Jansen, J. F. A.; Marques, J. P.; Topalis, J.; Ingrisch, M.; Ricke, J.; de Leeuw, F.; Duering, M.; and Backes, W. H.\n\n\n \n\n\n\n NMR Biomed, 36(7): e4905. July 2023.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{dietrich_integrated_2023,\n\ttitle = {Integrated intravoxel incoherent motion tensor and diffusion tensor brain {MRI} in a single fast acquisition},\n\tvolume = {36},\n\tissn = {1099-1492},\n\tdoi = {10.1002/nbm.4905},\n\tabstract = {The acquisition of intravoxel incoherent motion (IVIM) data and diffusion tensor imaging (DTI) data from the brain can be integrated into a single measurement, which offers the possibility to determine orientation-dependent (tensorial) perfusion parameters in addition to established IVIM and DTI parameters. The purpose of this study was to evaluate the feasibility of such a protocol with a clinically feasible scan time below 6 min and to use a model-selection approach to find a set of DTI and IVIM tensor parameters that most adequately describes the acquired data. Diffusion-weighted images of the brain were acquired at 3 T in 20 elderly participants with cerebral small vessel disease using a multiband echoplanar imaging sequence with 15 b-values between 0 and 1000 s/mm2 and six non-collinear diffusion gradient directions for each b-value. Seven different IVIM-diffusion models with 4 to 14 parameters were implemented, which modeled diffusion and pseudo-diffusion as scalar or tensor quantities. The models were compared with respect to their fitting performance based on the goodness of fit (sum of squared fit residuals, chi2 ) and their Akaike weights (calculated from the corrected Akaike information criterion). Lowest chi2 values were found using the model with the largest number of model parameters. However, significantly highest Akaike weights indicating the most appropriate models for the acquired data were found with a nine-parameter IVIM-DTI model (with isotropic perfusion modeling) in normal-appearing white matter (NAWM), and with an 11-parameter model (IVIM-DTI with additional pseudo-diffusion anisotropy) in white matter with hyperintensities (WMH) and in gray matter (GM). The latter model allowed for the additional calculation of the fractional anisotropy of the pseudo-diffusion tensor (with a median value of 0.45 in NAWM, 0.23 in WMH, and 0.36 in GM), which is not accessible with the usually performed IVIM acquisitions based on three orthogonal diffusion-gradient directions.},\n\tlanguage = {eng},\n\tnumber = {7},\n\tjournal = {NMR Biomed},\n\tauthor = {Dietrich, Olaf and Cai, Mengfei and Tuladhar, Anil Man and Jacob, Mina A. and Drenthen, Gerald S. and Jansen, Jacobus F. A. and Marques, José P. and Topalis, Johanna and Ingrisch, Michael and Ricke, Jens and de Leeuw, Frank-Erik and Duering, Marco and Backes, Walter H.},\n\tmonth = jul,\n\tyear = {2023},\n\tpmid = {36637237},\n\tkeywords = {Aged, Diffusion Magnetic Resonance Imaging, Diffusion Tensor Imaging, Humans, cerebral small vessel disease, diffusion tensor imaging, Motion, Brain, White Matter, diffusion-weighted imaging, Akaike information criterion, intravoxel incoherent motion MRI, model selection, Perfusion},\n\tpages = {e4905},\n\tfile = {Full Text:/Users/mduering/Zotero/storage/PXTYPDUF/Dietrich et al. - 2023 - Integrated intravoxel incoherent motion tensor and.pdf:application/pdf},\n}\n\n

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\n The acquisition of intravoxel incoherent motion (IVIM) data and diffusion tensor imaging (DTI) data from the brain can be integrated into a single measurement, which offers the possibility to determine orientation-dependent (tensorial) perfusion parameters in addition to established IVIM and DTI parameters. The purpose of this study was to evaluate the feasibility of such a protocol with a clinically feasible scan time below 6 min and to use a model-selection approach to find a set of DTI and IVIM tensor parameters that most adequately describes the acquired data. Diffusion-weighted images of the brain were acquired at 3 T in 20 elderly participants with cerebral small vessel disease using a multiband echoplanar imaging sequence with 15 b-values between 0 and 1000 s/mm2 and six non-collinear diffusion gradient directions for each b-value. Seven different IVIM-diffusion models with 4 to 14 parameters were implemented, which modeled diffusion and pseudo-diffusion as scalar or tensor quantities. The models were compared with respect to their fitting performance based on the goodness of fit (sum of squared fit residuals, chi2 ) and their Akaike weights (calculated from the corrected Akaike information criterion). Lowest chi2 values were found using the model with the largest number of model parameters. However, significantly highest Akaike weights indicating the most appropriate models for the acquired data were found with a nine-parameter IVIM-DTI model (with isotropic perfusion modeling) in normal-appearing white matter (NAWM), and with an 11-parameter model (IVIM-DTI with additional pseudo-diffusion anisotropy) in white matter with hyperintensities (WMH) and in gray matter (GM). The latter model allowed for the additional calculation of the fractional anisotropy of the pseudo-diffusion tensor (with a median value of 0.45 in NAWM, 0.23 in WMH, and 0.36 in GM), which is not accessible with the usually performed IVIM acquisitions based on three orthogonal diffusion-gradient directions.\n

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\n \n\n \n \n \n \n \n Three-tiered EGFr domain risk stratification for individualized NOTCH3-small vessel disease prediction.\n \n \n \n\n\n \n Hack, R. J.; Gravesteijn, G.; Cerfontaine, M. N.; Santcroos, M. A.; Gatti, L.; Kopczak, A.; Bersano, A.; Duering, M.; Rutten, J. W.; and Lesnik Oberstein, S. A. J.\n\n\n \n\n\n\n Brain, 146(7): 2913–2927. July 2023.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{hack_three-tiered_2023,\n\ttitle = {Three-tiered {EGFr} domain risk stratification for individualized {NOTCH3}-small vessel disease prediction},\n\tvolume = {146},\n\tissn = {1460-2156},\n\tdoi = {10.1093/brain/awac486},\n\tabstract = {Cysteine-altering missense variants (NOTCH3cys) in one of the 34 epidermal growth-factor-like repeat (EGFr) domains of the NOTCH3 protein are the cause of NOTCH3-associated small vessel disease (NOTCH3-SVD). NOTCH3-SVD is highly variable, ranging from cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) at the severe end of the spectrum to non-penetrance. The strongest known NOTCH3-SVD modifier is NOTCH3cys variant position: NOTCH3cys variants located in EGFr domains 1-6 are associated with a more severe phenotype than NOTCH3cys variants located in EGFr domains 7-34. The objective of this study was to further improve NOTCH3-SVD genotype-based risk prediction by using relative differences in NOTCH3cys variant frequencies between large CADASIL and population cohorts as a starting point. Scientific CADASIL literature, cohorts and population databases were queried for NOTCH3cys variants. For each EGFr domain, the relative difference in NOTCH3cys variant frequency (NVFOR) was calculated using genotypes of 2574 CADASIL patients and 1647 individuals from population databases. Based on NVFOR cut-off values, EGFr domains were classified as either low (LR-EGFr), medium (MR-EGFr) or high risk (HR-EGFr). The clinical relevance of this new three-tiered EGFr risk classification was cross-sectionally validated by comparing SVD imaging markers and clinical outcomes between EGFr risk categories using a genotype-phenotype data set of 434 CADASIL patients and 1003 NOTCH3cys positive community-dwelling individuals. CADASIL patients and community-dwelling individuals harboured 379 unique NOTCH3cys variants. Nine EGFr domains were classified as an HR-EGFr, which included EGFr domains 1-6, but additionally also EGFr domains 8, 11 and 26. Ten EGFr domains were classified as MR-EGFr and 11 as LR-EGFr. In the population genotype-phenotype data set, HR-EGFr individuals had the highest risk of stroke [odds ratio (OR) = 10.81, 95\\% confidence interval (CI): 5.46-21.37], followed by MR-EGFr individuals (OR = 1.81, 95\\% CI: 0.84-3.88) and LR-EGFr individuals (OR = 1 [reference]). MR-EGFr individuals had a significantly higher normalized white matter hyperintensity volume (nWMHv; P = 0.005) and peak width of skeletonized mean diffusivity (PSMD; P = 0.035) than LR-EGFr individuals. In the CADASIL genotype-phenotype data set, HR-EGFr domains 8, 11 and 26 patients had a significantly higher risk of stroke (P = 0.002), disability (P = 0.041), nWMHv (P = 1.8 × 10-8), PSMD (P = 2.6 × 10-8) and lacune volume (P = 0.006) than MR-EGFr patients. SVD imaging marker load and clinical outcomes were similar between HR-EGFr 1-6 patients and HR-EGFr 8, 11 and 26 patients. NVFOR was significantly associated with vascular NOTCH3 aggregation load (P = 0.006), but not with NOTCH3 signalling activity (P = 0.88). In conclusion, we identified three clinically distinct NOTCH3-SVD EGFr risk categories based on NFVOR cut-off values, and identified three additional HR-EGFr domains located outside of EGFr domains 1-6. This EGFr risk classification will provide an important key to individualized NOTCH3-SVD disease prediction.},\n\tlanguage = {eng},\n\tnumber = {7},\n\tjournal = {Brain},\n\tauthor = {Hack, Remco J. and Gravesteijn, Gido and Cerfontaine, Minne N. and Santcroos, Mark A. and Gatti, Laura and Kopczak, Anna and Bersano, Anna and Duering, Marco and Rutten, Julie W. and Lesnik Oberstein, Saskia A. J.},\n\tmonth = jul,\n\tyear = {2023},\n\tpmid = {36535904},\n\tpmcid = {PMC10316769},\n\tkeywords = {Stroke, Humans, Magnetic Resonance Imaging, Receptor, Notch3, Mutation, Risk Assessment, CADASIL, Receptors, Notch, EGFr domain, Epidermal Growth Factor, NOTCH3, risk classification, SVD},\n\tpages = {2913--2927},\n\tfile = {Full Text:/Users/mduering/Zotero/storage/JL7N3PLI/Hack et al. - 2023 - Three-tiered EGFr domain risk stratification for i.pdf:application/pdf},\n}\n\n

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\n Cysteine-altering missense variants (NOTCH3cys) in one of the 34 epidermal growth-factor-like repeat (EGFr) domains of the NOTCH3 protein are the cause of NOTCH3-associated small vessel disease (NOTCH3-SVD). NOTCH3-SVD is highly variable, ranging from cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) at the severe end of the spectrum to non-penetrance. The strongest known NOTCH3-SVD modifier is NOTCH3cys variant position: NOTCH3cys variants located in EGFr domains 1-6 are associated with a more severe phenotype than NOTCH3cys variants located in EGFr domains 7-34. The objective of this study was to further improve NOTCH3-SVD genotype-based risk prediction by using relative differences in NOTCH3cys variant frequencies between large CADASIL and population cohorts as a starting point. Scientific CADASIL literature, cohorts and population databases were queried for NOTCH3cys variants. For each EGFr domain, the relative difference in NOTCH3cys variant frequency (NVFOR) was calculated using genotypes of 2574 CADASIL patients and 1647 individuals from population databases. Based on NVFOR cut-off values, EGFr domains were classified as either low (LR-EGFr), medium (MR-EGFr) or high risk (HR-EGFr). The clinical relevance of this new three-tiered EGFr risk classification was cross-sectionally validated by comparing SVD imaging markers and clinical outcomes between EGFr risk categories using a genotype-phenotype data set of 434 CADASIL patients and 1003 NOTCH3cys positive community-dwelling individuals. CADASIL patients and community-dwelling individuals harboured 379 unique NOTCH3cys variants. Nine EGFr domains were classified as an HR-EGFr, which included EGFr domains 1-6, but additionally also EGFr domains 8, 11 and 26. Ten EGFr domains were classified as MR-EGFr and 11 as LR-EGFr. In the population genotype-phenotype data set, HR-EGFr individuals had the highest risk of stroke [odds ratio (OR) = 10.81, 95% confidence interval (CI): 5.46-21.37], followed by MR-EGFr individuals (OR = 1.81, 95% CI: 0.84-3.88) and LR-EGFr individuals (OR = 1 [reference]). MR-EGFr individuals had a significantly higher normalized white matter hyperintensity volume (nWMHv; P = 0.005) and peak width of skeletonized mean diffusivity (PSMD; P = 0.035) than LR-EGFr individuals. In the CADASIL genotype-phenotype data set, HR-EGFr domains 8, 11 and 26 patients had a significantly higher risk of stroke (P = 0.002), disability (P = 0.041), nWMHv (P = 1.8 × 10-8), PSMD (P = 2.6 × 10-8) and lacune volume (P = 0.006) than MR-EGFr patients. SVD imaging marker load and clinical outcomes were similar between HR-EGFr 1-6 patients and HR-EGFr 8, 11 and 26 patients. NVFOR was significantly associated with vascular NOTCH3 aggregation load (P = 0.006), but not with NOTCH3 signalling activity (P = 0.88). In conclusion, we identified three clinically distinct NOTCH3-SVD EGFr risk categories based on NFVOR cut-off values, and identified three additional HR-EGFr domains located outside of EGFr domains 1-6. This EGFr risk classification will provide an important key to individualized NOTCH3-SVD disease prediction.\n

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\n \n\n \n \n \n \n \n Strategic white matter hyperintensity locations for cognitive impairment: A multicenter lesion-symptom mapping study in 3525 memory clinic patients.\n \n \n \n\n\n \n Coenen, M.; Kuijf, H. J.; Huenges Wajer, I. M. C.; Duering, M.; Wolters, F. J.; Fletcher, E. F.; Maillard, P. M.; Alzheimer's Disease Neuroimaging Initiative; Barkhof, F.; Barnes, J.; Benke, T.; Boomsma, J. M. F.; Chen, C. P. L. H.; Dal-Bianco, P.; Dewenter, A.; Enzinger, C.; Ewers, M.; Exalto, L. G.; Franzmeier, N.; Groeneveld, O.; Hilal, S.; Hofer, E.; Koek, D. L.; Maier, A. B.; McCreary, C. R.; Padilla, C. S.; Papma, J. M.; Paterson, R. W.; Pijnenburg, Y. A. L.; Rubinski, A.; Schmidt, R.; Schott, J. M.; Slattery, C. F.; Smith, E. E.; Steketee, R. M. E.; Sudre, C. H.; van den Berg, E.; van der Flier, W. M.; Venketasubramanian, N.; Vernooij, M. W.; Xin, X.; DeCarli, C.; Biessels, G. J.; and Biesbroek, J. M.\n\n\n \n\n\n\n Alzheimers Dement, 19(6): 2420–2432. June 2023.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{coenen_strategic_2023,\n\ttitle = {Strategic white matter hyperintensity locations for cognitive impairment: {A} multicenter lesion-symptom mapping study in 3525 memory clinic patients},\n\tvolume = {19},\n\tissn = {1552-5279},\n\tshorttitle = {Strategic white matter hyperintensity locations for cognitive impairment},\n\tdoi = {10.1002/alz.12827},\n\tabstract = {INTRODUCTION: Impact of white matter hyperintensities (WMH) on cognition likely depends on lesion location, but a comprehensive map of strategic locations is lacking. We aimed to identify these locations in a large multicenter study.\nMETHODS: Individual patient data (n = 3525) from 11 memory clinic cohorts were harmonized. We determined the association of WMH location with attention and executive functioning, information processing speed, language, and verbal memory performance using voxel-based and region of interest tract-based analyses.\nRESULTS: WMH in the left and right anterior thalamic radiation, forceps major, and left inferior fronto-occipital fasciculus were significantly related to domain-specific impairment, independent of total WMH volume and atrophy. A strategic WMH score based on these tracts inversely correlated with performance in all domains.\nDISCUSSION: The data show that the impact of WMH on cognition is location-dependent, primarily involving four strategic white matter tracts. Evaluation of WMH location may support diagnosing vascular cognitive impairment.\nHIGHLIGHTS: We analyzed white matter hyperintensities (WMH) in 3525 memory clinic patients from 11 cohorts The impact of WMH on cognition depends on location We identified four strategic white matter tracts A single strategic WMH score was derived from these four strategic tracts The strategic WMH score was an independent determinant of four cognitive domains.},\n\tlanguage = {eng},\n\tnumber = {6},\n\tjournal = {Alzheimers Dement},\n\tauthor = {Coenen, Mirthe and Kuijf, Hugo J. and Huenges Wajer, Irene M. C. and Duering, Marco and Wolters, Frank J. and Fletcher, Evan F. and Maillard, Pauline M. and {Alzheimer's Disease Neuroimaging Initiative} and Barkhof, Frederik and Barnes, Josephine and Benke, Thomas and Boomsma, Jooske M. F. and Chen, Christopher P. L. H. and Dal-Bianco, Peter and Dewenter, Anna and Enzinger, Christian and Ewers, Michael and Exalto, Lieza G. and Franzmeier, Nicolai and Groeneveld, Onno and Hilal, Saima and Hofer, Edith and Koek, Dineke L. and Maier, Andrea B. and McCreary, Cheryl R. and Padilla, Catarina S. and Papma, Janne M. and Paterson, Ross W. and Pijnenburg, Yolande A. L. and Rubinski, Anna and Schmidt, Reinhold and Schott, Jonathan M. and Slattery, Catherine F. and Smith, Eric E. and Steketee, Rebecca M. E. and Sudre, Carole H. and van den Berg, Esther and van der Flier, Wiesje M. and Venketasubramanian, Narayanaswamy and Vernooij, Meike W. and Xin, Xu and DeCarli, Charles and Biessels, Geert Jan and Biesbroek, J. Matthijs},\n\tmonth = jun,\n\tyear = {2023},\n\tpmid = {36504357},\n\tkeywords = {Cognition, cognitive impairment, Humans, Magnetic Resonance Imaging, white matter hyperintensities, Executive Function, Neuropsychological Tests, White Matter, Cognitive Dysfunction, lesion symptom mapping, location, memory clinic patients},\n\tpages = {2420--2432},\n\tfile = {Full Text:/Users/mduering/Zotero/storage/YPRDUX96/Coenen et al. - 2023 - Strategic white matter hyperintensity locations fo.pdf:application/pdf},\n}\n\n

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\n \n\n \n \n \n \n \n Physical activity and brain health in patients with atrial fibrillation.\n \n \n \n\n\n \n Herber, E.; Aeschbacher, S.; Coslovsky, M.; Schwendinger, F.; Hennings, E.; Gasser, A.; Di Valentino, M.; Rigamonti, E.; Reichlin, T.; Rodondi, N.; Netzer, S.; Beer, J. H.; Stauber, A.; Müller, A.; Ammann, P.; Sinnecker, T.; Duering, M.; Wuerfel, J.; Conen, D.; Kühne, M.; Osswald, S.; Bonati, L. H.; and SWISS-AF Investigators\n\n\n \n\n\n\n Eur J Neurol, 30(3): 567–577. March 2023.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{herber_physical_2023,\n\ttitle = {Physical activity and brain health in patients with atrial fibrillation},\n\tvolume = {30},\n\tissn = {1468-1331},\n\tdoi = {10.1111/ene.15660},\n\tabstract = {BACKGROUND AND PURPOSE: Vascular brain lesions, such as ischemic infarcts, are common among patients with atrial fibrillation (AF) and are associated with impaired cognitive function. The role of physical activity (PA) in the prevalence of brain lesions and cognition in AF has not been investigated.\nMETHODS: Patients from the multicenter Swiss-AF cohort study were included in this cross-sectional analysis. We assessed regular exercise (RE; at least once weekly) and minutes of weekly PA using a validated questionnaire. We studied associations with ischemic infarcts, white matter hyperintensities, cerebral microbleeds, and brain volume on brain magnetic resonance imaging and with global cognition measured with a cognitive construct (CoCo) score.\nRESULTS: Among 1490 participants (mean age = 72 ± 9 years), 730 (49\\%) engaged in RE. In adjusted regression analyses, RE was associated with a lower prevalence of ischemic infarcts (odds ratio [OR] = 0.78, 95\\% confidence interval [CI] = 0.63-0.98, p = 0.03) and of moderate to severe white matter hyperintensities (OR = 0.78, 95\\% CI = 0.62-0.99, p = 0.04), higher brain volume (β-coefficient = 10.73, 95\\% CI = 2.37-19.09, p = 0.01), and higher CoCo score (β-coefficient = 0.08, 95\\% CI = 0.03-0.12, p {\\textless} 0.001). Increasing weekly PA was associated with higher brain volume (β-coefficient = 1.40, 95\\% CI = 0.65-2.15, p {\\textless} 0.001).\nCONCLUSIONS: In AF patients, RE was associated with a lower prevalence of ischemic infarcts and of moderate to severe white matter disease, with larger brain volume, and with better cognitive performance. Prospective studies are needed to investigate whether these associations are causal. Until then, our findings suggest that patients with AF should be encouraged to remain physically active.},\n\tlanguage = {eng},\n\tnumber = {3},\n\tjournal = {Eur J Neurol},\n\tauthor = {Herber, Elena and Aeschbacher, Stefanie and Coslovsky, Michael and Schwendinger, Fabian and Hennings, Elisa and Gasser, Andreas and Di Valentino, Marcello and Rigamonti, Elia and Reichlin, Tobias and Rodondi, Nicolas and Netzer, Seraina and Beer, Juerg H. and Stauber, Annina and Müller, Andreas and Ammann, Peter and Sinnecker, Tim and Duering, Marco and Wuerfel, Jens and Conen, David and Kühne, Michael and Osswald, Stefan and Bonati, Leo H. and {SWISS-AF Investigators}},\n\tmonth = mar,\n\tyear = {2023},\n\tpmid = {36478335},\n\tkeywords = {Aged, Humans, Middle Aged, Aged, 80 and over, Magnetic Resonance Imaging, Cohort Studies, cerebral microbleeds, Infarction, Cross-Sectional Studies, Brain, atrial fibrillation, Atrial Fibrillation, cerebral infarction, cognitive disorders and dementia, neurocognitive function, physical activity, total brain volume, white matter disease},\n\tpages = {567--577},\n}\n\n

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\n \n\n \n \n \n \n \n Free water corrected diffusion tensor imaging discriminates between good and poor outcomes of comatose patients after cardiac arrest.\n \n \n \n\n\n \n Keijzer, H. M.; Duering, M.; Pasternak, O.; Meijer, F. J. A.; Verhulst, M. M. L. H.; Tonino, B. A. R.; Blans, M. J.; Hoedemaekers, C. W. E.; Klijn, C. J. M.; and Hofmeijer, J.\n\n\n \n\n\n\n Eur Radiol, 33(3): 2139–2148. March 2023.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{keijzer_free_2023,\n\ttitle = {Free water corrected diffusion tensor imaging discriminates between good and poor outcomes of comatose patients after cardiac arrest},\n\tvolume = {33},\n\tissn = {1432-1084},\n\tdoi = {10.1007/s00330-022-09245-w},\n\tabstract = {OBJECTIVES: Approximately 50\\% of comatose patients after cardiac arrest never regain consciousness. Cerebral ischaemia may lead to cytotoxic and/or vasogenic oedema, which can be detected by diffusion tensor imaging (DTI). Here, we evaluate the potential value of free water corrected mean diffusivity (MD) and fractional anisotropy (FA) based on DTI, for the prediction of neurological recovery of comatose patients after cardiac arrest.\nMETHODS: A total of 50 patients after cardiac arrest were included in this prospective cohort study in two Dutch hospitals. DTI was obtained 2-4 days after cardiac arrest. Outcome was assessed at 6 months, dichotomised as poor (cerebral performance category 3-5; n = 20) or good (n = 30) neurological outcome. We calculated the whole brain mean MD and FA and compared between patients with good and poor outcomes. In addition, we compared a preliminary prediction model based on clinical parameters with or without the addition of MD and FA.\nRESULTS: We found significant differences between patients with good and poor outcome of mean MD (good: 726 [702-740] × 10-6 mm2/s vs. poor: 663 [575-736] × 10-6 mm2/s; p = 0.01) and mean FA (0.30 ± 0.03 vs. 0.28 ± 0.03; p = 0.03). An exploratory prediction model combining clinical parameters, MD and FA increased the sensitivity for reliable prediction of poor outcome from 60 to 85\\%, compared to the model containing clinical parameters only, but confidence intervals are overlapping.\nCONCLUSIONS: Free water-corrected MD and FA discriminate between patients with good and poor outcomes after cardiac arrest and hold the potential to add to multimodal outcome prediction.\nKEY POINTS: • Whole brain mean MD and FA differ between patients with good and poor outcome after cardiac arrest. • Free water-corrected MD can better discriminate between patients with good and poor outcome than uncorrected MD. • A combination of free water-corrected MD (sensitive to grey matter abnormalities) and FA (sensitive to white matter abnormalities) holds potential to add to the prediction of outcome.},\n\tlanguage = {eng},\n\tnumber = {3},\n\tjournal = {Eur Radiol},\n\tauthor = {Keijzer, Hanneke M. and Duering, Marco and Pasternak, Ofer and Meijer, Frederick J. A. and Verhulst, Marlous M. L. H. and Tonino, Bart A. R. and Blans, Michiel J. and Hoedemaekers, Cornelia W. E. and Klijn, Catharina J. M. and Hofmeijer, Jeannette},\n\tmonth = mar,\n\tyear = {2023},\n\tpmid = {36418623},\n\tpmcid = {PMC9935650},\n\tkeywords = {Diffusion Tensor Imaging, Humans, Prospective Studies, Anisotropy, Brain, Water, MRI, Brain edema, Brain imaging, Brain ischaemia, Cardiac arrest, Coma, Heart Arrest},\n\tpages = {2139--2148},\n\tfile = {Full Text:/Users/mduering/Zotero/storage/PS7AXLN5/Keijzer et al. - 2023 - Free water corrected diffusion tensor imaging disc.pdf:application/pdf},\n}\n\n

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\n OBJECTIVES: Approximately 50% of comatose patients after cardiac arrest never regain consciousness. Cerebral ischaemia may lead to cytotoxic and/or vasogenic oedema, which can be detected by diffusion tensor imaging (DTI). Here, we evaluate the potential value of free water corrected mean diffusivity (MD) and fractional anisotropy (FA) based on DTI, for the prediction of neurological recovery of comatose patients after cardiac arrest. METHODS: A total of 50 patients after cardiac arrest were included in this prospective cohort study in two Dutch hospitals. DTI was obtained 2-4 days after cardiac arrest. Outcome was assessed at 6 months, dichotomised as poor (cerebral performance category 3-5; n = 20) or good (n = 30) neurological outcome. We calculated the whole brain mean MD and FA and compared between patients with good and poor outcomes. In addition, we compared a preliminary prediction model based on clinical parameters with or without the addition of MD and FA. RESULTS: We found significant differences between patients with good and poor outcome of mean MD (good: 726 [702-740] × 10-6 mm2/s vs. poor: 663 [575-736] × 10-6 mm2/s; p = 0.01) and mean FA (0.30 ± 0.03 vs. 0.28 ± 0.03; p = 0.03). An exploratory prediction model combining clinical parameters, MD and FA increased the sensitivity for reliable prediction of poor outcome from 60 to 85%, compared to the model containing clinical parameters only, but confidence intervals are overlapping. CONCLUSIONS: Free water-corrected MD and FA discriminate between patients with good and poor outcomes after cardiac arrest and hold the potential to add to multimodal outcome prediction. KEY POINTS: • Whole brain mean MD and FA differ between patients with good and poor outcome after cardiac arrest. • Free water-corrected MD can better discriminate between patients with good and poor outcome than uncorrected MD. • A combination of free water-corrected MD (sensitive to grey matter abnormalities) and FA (sensitive to white matter abnormalities) holds potential to add to the prediction of outcome.\n

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\n \n\n \n \n \n \n \n Impact of White Adipose Tissue on Brain Structure, Perfusion, and Cognitive Function in Patients With Severe Obesity: The BARICO Study.\n \n \n \n\n\n \n Vreeken, D.; Seidel, F.; de La Roij, G.; Vening, W.; den Hengst, W. A.; Verschuren, L.; Özsezen, S.; Kessels, R. P. C.; Duering, M.; Mutsaerts, H. J. M. M.; Kleemann, R.; Wiesmann, M.; Hazebroek, E. J.; and Kiliaan, A. J.\n\n\n \n\n\n\n Neurology, 100(7): e703–e718. February 2023.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{vreeken_impact_2023,\n\ttitle = {Impact of {White} {Adipose} {Tissue} on {Brain} {Structure}, {Perfusion}, and {Cognitive} {Function} in {Patients} {With} {Severe} {Obesity}: {The} {BARICO} {Study}},\n\tvolume = {100},\n\tissn = {1526-632X},\n\tshorttitle = {Impact of {White} {Adipose} {Tissue} on {Brain} {Structure}, {Perfusion}, and {Cognitive} {Function} in {Patients} {With} {Severe} {Obesity}},\n\tdoi = {10.1212/WNL.0000000000201538},\n\tabstract = {BACKGROUND AND OBJECTIVE: While underlying pathophysiology linking obesity to brain health is not completely understood, white adipose tissue (WAT) is considered a key player. In obesity, WAT becomes dysregulated, showing hyperplasia, hypertrophy, and eventually inflammation. This disbalance leads to dysregulated secretion of adipokines influencing both (cardio)vascular and brain health. Within this study, we investigated the association between omental WAT (oWAT) and subcutaneous WAT (scWAT) with brain structure and perfusion and cognition in adults with severe obesity.\nMETHODS: Within the cross-sectional BARICO study, brain structure and perfusion and cognitive function were measured before bariatric surgery (BS) using MRI and cognitive assessments. During BS, oWAT and scWAT depots were collected and analyzed by histopathology. The number and diameter of adipocytes were quantified together with the amount of crown-like structures (CLS) as an indication of inflammation. Blood samples were collected to analyze adipokines and inflammatory markers. Neuroimaging outcomes included brain volumes, cortical thickness, white matter (WM) integrity, WM hyperintensities, cerebral blood flow using arterial spin labeling (ASL), and the ASL spatial coefficient of variation (sCoV), reflecting cerebrovascular health.\nRESULTS: Seventy-one patients were included (mean age 45.1 ± 5.8 years; 83.1\\% women; mean body mass index 40.8 ± 3.8 kg/m2). scWAT showed more CLS (z = -2.72, p {\\textless} 0.01, r = -0.24) and hypertrophy compared with oWAT (F(1,64) = 3.99, p {\\textless} 0.05, η2 = 0.06). Adiponectin levels were inversely associated with the average diameter of scWAT (β = -0.31, 95\\% CI -0.54 to -0.08) and oWAT (β = -0.33, 95\\% CI -0.55 to -0.09). Furthermore, the adipocyte diameter in oWAT was positively associated with the sCoV in the parietal cortex (β = 0.33, 95\\% CI 0.10-0.60), and the number of adipocytes (per mm2) was positively associated with sCoV in the nucleus accumbens (NAcc) (β = 0.34, 95\\% CI 0.09-0.61). Cognitive function did not correlate with any WAT parameter or plasma marker. These associations were highly influenced by age and sex. sCoV in the NAcc was positively associated with fasting plasma glucose (β = 0.35, 95\\% CI 0.10-0.56).\nDISCUSSION: scWAT and oWAT are different in morphology and in their relationship with plasma markers and cerebrovascular health. Although scWAT showed more CLS and hypertrophy, scWAT was not associated with brain readouts. This study showed, however, important relationships between oWAT morphology and cerebrovascular health in obesity.\nTRIAL REGISTRATION INFORMATION: Trial Registration Number NTR7288 (trialregister.nl/trial/7090).},\n\tlanguage = {eng},\n\tnumber = {7},\n\tjournal = {Neurology},\n\tauthor = {Vreeken, Debby and Seidel, Florine and de La Roij, Guido and Vening, Wouter and den Hengst, Willem A. and Verschuren, Lars and Özsezen, Serdar and Kessels, Roy P. C. and Duering, Marco and Mutsaerts, Henk J. M. M. and Kleemann, Robert and Wiesmann, Maximilian and Hazebroek, Eric J. and Kiliaan, Amanda J.},\n\tmonth = feb,\n\tyear = {2023},\n\tpmid = {36332987},\n\tpmcid = {PMC9969926},\n\tkeywords = {Cognition, Adult, Female, Humans, Male, Middle Aged, Cross-Sectional Studies, Brain, Perfusion, Adipokines, Adipose Tissue, Adipose Tissue, White, Hypertrophy, Inflammation, Obesity, Obesity, Morbid},\n\tpages = {e703--e718},\n\tfile = {Full Text:/Users/mduering/Zotero/storage/M4SMTEKL/Vreeken et al. - 2023 - Impact of White Adipose Tissue on Brain Structure,.pdf:application/pdf},\n}\n\n

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\n BACKGROUND AND OBJECTIVE: While underlying pathophysiology linking obesity to brain health is not completely understood, white adipose tissue (WAT) is considered a key player. In obesity, WAT becomes dysregulated, showing hyperplasia, hypertrophy, and eventually inflammation. This disbalance leads to dysregulated secretion of adipokines influencing both (cardio)vascular and brain health. Within this study, we investigated the association between omental WAT (oWAT) and subcutaneous WAT (scWAT) with brain structure and perfusion and cognition in adults with severe obesity. METHODS: Within the cross-sectional BARICO study, brain structure and perfusion and cognitive function were measured before bariatric surgery (BS) using MRI and cognitive assessments. During BS, oWAT and scWAT depots were collected and analyzed by histopathology. The number and diameter of adipocytes were quantified together with the amount of crown-like structures (CLS) as an indication of inflammation. Blood samples were collected to analyze adipokines and inflammatory markers. Neuroimaging outcomes included brain volumes, cortical thickness, white matter (WM) integrity, WM hyperintensities, cerebral blood flow using arterial spin labeling (ASL), and the ASL spatial coefficient of variation (sCoV), reflecting cerebrovascular health. RESULTS: Seventy-one patients were included (mean age 45.1 ± 5.8 years; 83.1% women; mean body mass index 40.8 ± 3.8 kg/m2). scWAT showed more CLS (z = -2.72, p \\textless 0.01, r = -0.24) and hypertrophy compared with oWAT (F(1,64) = 3.99, p \\textless 0.05, η2 = 0.06). Adiponectin levels were inversely associated with the average diameter of scWAT (β = -0.31, 95% CI -0.54 to -0.08) and oWAT (β = -0.33, 95% CI -0.55 to -0.09). Furthermore, the adipocyte diameter in oWAT was positively associated with the sCoV in the parietal cortex (β = 0.33, 95% CI 0.10-0.60), and the number of adipocytes (per mm2) was positively associated with sCoV in the nucleus accumbens (NAcc) (β = 0.34, 95% CI 0.09-0.61). Cognitive function did not correlate with any WAT parameter or plasma marker. These associations were highly influenced by age and sex. sCoV in the NAcc was positively associated with fasting plasma glucose (β = 0.35, 95% CI 0.10-0.56). DISCUSSION: scWAT and oWAT are different in morphology and in their relationship with plasma markers and cerebrovascular health. Although scWAT showed more CLS and hypertrophy, scWAT was not associated with brain readouts. This study showed, however, important relationships between oWAT morphology and cerebrovascular health in obesity. TRIAL REGISTRATION INFORMATION: Trial Registration Number NTR7288 (trialregister.nl/trial/7090).\n

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\n \n\n \n \n \n \n \n Recent advances in arterial spin labeling perfusion MRI in patients with vascular cognitive impairment.\n \n \n \n\n\n \n Huang, D.; Guo, Y.; Guan, X.; Pan, L.; Zhu, Z.; Chen, Z.; Dijkhuizen, R. M.; Duering, M.; Yu, F.; Boltze, J.; and Li, P.\n\n\n \n\n\n\n J Cereb Blood Flow Metab, 43(2): 173–184. February 2023.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{huang_recent_2023,\n\ttitle = {Recent advances in arterial spin labeling perfusion {MRI} in patients with vascular cognitive impairment},\n\tvolume = {43},\n\tissn = {1559-7016},\n\tdoi = {10.1177/0271678X221135353},\n\tabstract = {Cognitive impairment (CI) is a major health concern in aging populations. It impairs patients' independent life and may progress to dementia. Vascular cognitive impairment (VCI) encompasses all cerebrovascular pathologies that contribute to cognitive impairment (CI). Moreover, the majority of CI subtypes involve various aspects of vascular dysfunction. Recent research highlights the critical role of reduced cerebral blood flow (CBF) in the progress of VCI, and the detection of altered CBF may help to detect or even predict the onset of VCI. Arterial spin labeling (ASL) is a non-invasive, non-ionizing perfusion MRI technique for assessing CBF qualitatively and quantitatively. Recent methodological advances enabling improved signal-to-noise ratio (SNR) and data acquisition have led to an increase in the use of ASL to assess CBF in VCI patients. Combined with other imaging modalities and biomarkers, ASL has great potential for identifying early VCI and guiding prediction and prevention strategies. This review focuses on recent advances in ASL-based perfusion MRI for identifying patients at high risk of VCI.},\n\tlanguage = {eng},\n\tnumber = {2},\n\tjournal = {J Cereb Blood Flow Metab},\n\tauthor = {Huang, Dan and Guo, Yunlu and Guan, Xiaoyu and Pan, Lijun and Zhu, Ziyu and Chen, Zeng'ai and Dijkhuizen, Rick M. and Duering, Marco and Yu, Fang and Boltze, Johannes and Li, Peiying},\n\tmonth = feb,\n\tyear = {2023},\n\tpmid = {36284489},\n\tpmcid = {PMC9903225},\n\tkeywords = {Humans, Magnetic Resonance Imaging, Vascular cognitive impairment, Aging, cerebral blood flow, neuroimaging, Cerebrovascular Circulation, vascular dementia, Cognitive Dysfunction, Perfusion, arterial spin labeling, neurovascular unit, perfusion MRI, Spin Labels},\n\tpages = {173--184},\n\tfile = {Accepted Version:/Users/mduering/Zotero/storage/JTFNQ96H/Huang et al. - 2023 - Recent advances in arterial spin labeling perfusio.pdf:application/pdf},\n}\n\n

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\n \n\n \n \n \n \n \n The global burden of cerebral small vessel disease in low- and middle-income countries: A systematic review and meta-analysis.\n \n \n \n\n\n \n Lam, B. Y. K.; Cai, Y.; Akinyemi, R.; Biessels, G. J.; van den Brink, H.; Chen, C.; Cheung, C. W.; Chow, K. N.; Chung, H. K. H.; Duering, M.; Fu, S. T.; Gustafson, D.; Hilal, S.; Hui, V. M. H.; Kalaria, R.; Kim, S.; Lam, M. L. M.; de Leeuw, F. E.; Li, A. S. M.; Markus, H. S.; Marseglia, A.; Zheng, H.; O'Brien, J.; Pantoni, L.; Sachdev, P. S.; Smith, E. E.; Wardlaw, J.; and Mok, V. C. T.\n\n\n \n\n\n\n Int J Stroke, 18(1): 15–27. January 2023.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{lam_global_2023,\n\ttitle = {The global burden of cerebral small vessel disease in low- and middle-income countries: {A} systematic review and meta-analysis},\n\tvolume = {18},\n\tissn = {1747-4949},\n\tshorttitle = {The global burden of cerebral small vessel disease in low- and middle-income countries},\n\tdoi = {10.1177/17474930221137019},\n\tabstract = {BACKGROUND: Cerebral small vessel disease (cSVD) is a major cause of stroke and dementia. Previous studies on the prevalence of cSVD are mostly based on single geographically defined cohorts in high-income countries. Studies investigating the prevalence of cSVD in low- and middle-income countries (LMICs) are expanding but have not been systematically assessed.\nAIM: This study aims to systematically review the prevalence of cSVD in LMICs.\nRESULTS: Articles were searched from the Ovid MEDLINE and EMBASE databases from 1 January 2000 to 31 March 2022, without language restrictions. Title/abstract screening, full-text review, and data extraction were performed by two to seven independent reviewers. The prevalence of cSVD and study sample size were extracted by pre-defined world regions and health status. The Risk of Bias for Non-randomized Studies tool was used. The protocol was registered on PROSPERO (CRD42022311133). A meta-analysis of proportion was performed to assess the prevalence of different magnetic resonance imaging markers of cSVD, and a meta-regression was performed to investigate associations between cSVD prevalence and type of study, age, and male: female ratio. Of 2743 studies identified, 42 studies spanning 12 global regions were included in the systematic review. Most of the identified studies were from China (n = 23). The median prevalence of moderate-to-severe white matter hyperintensities (WMHs) was 20.5\\%, 40.5\\%, and 58.4\\% in the community, stroke, and dementia groups, respectively. The median prevalence of lacunes was 0.8\\% and 33.5\\% in the community and stroke groups. The median prevalence of cerebral microbleeds (CMBs) was 10.7\\% and 22.4\\% in the community and stroke groups. The median prevalence of moderate-to-severe perivascular spaces was 25.0\\% in the community. Meta-regression analyses showed that the weighted median age (51.4 ± 0.0 years old; range: 36.3-80.2) was a significant predictor of the prevalence of moderate-to-severe WMH and lacunes, while the type of study was a significant predictor of the prevalence of CMB. The heterogeneity of studies was high ({\\textgreater}95\\%). Male participants were overrepresented.\nCONCLUSIONS: This systematic review and meta-analysis provide data on cSVD prevalence in LMICs and demonstrated the high prevalence of the condition. cSVD research in LMICs is being published at an increasing rate, especially between 2010 and 2022. More data are particularly needed from Sub-Saharan Africa and Central Europe, Eastern Europe, and Central Asia.},\n\tlanguage = {eng},\n\tnumber = {1},\n\tjournal = {Int J Stroke},\n\tauthor = {Lam, Bonnie Yin Ka and Cai, Yuan and Akinyemi, Rufus and Biessels, Geert Jan and van den Brink, Hilde and Chen, Christopher and Cheung, Chin Wai and Chow, King Ngai and Chung, Henry Kwun Hang and Duering, Marco and Fu, Siu Ting and Gustafson, Deborah and Hilal, Saima and Hui, Vincent Ming Ho and Kalaria, Rajesh and Kim, SangYun and Lam, Maggie Li Man and de Leeuw, Frank Erik and Li, Ami Sin Man and Markus, Hugh Stephen and Marseglia, Anna and Zheng, Huijing and O'Brien, John and Pantoni, Leonardo and Sachdev, Perminder Singh and Smith, Eric E. and Wardlaw, Joanna and Mok, Vincent Chung Tong},\n\tmonth = jan,\n\tyear = {2023},\n\tpmid = {36282189},\n\tkeywords = {Stroke, Female, Humans, Male, Middle Aged, Magnetic Resonance Imaging, lacunes, white matter hyperintensities, Dementia, Cerebral Small Vessel Diseases, Cerebral small vessel disease, cerebral microbleed, Developing Countries, low- and middle-income countries, meta-analysis, perivascular space, prevalence, systematic review},\n\tpages = {15--27},\n}\n\n

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\n BACKGROUND: Cerebral small vessel disease (cSVD) is a major cause of stroke and dementia. Previous studies on the prevalence of cSVD are mostly based on single geographically defined cohorts in high-income countries. Studies investigating the prevalence of cSVD in low- and middle-income countries (LMICs) are expanding but have not been systematically assessed. AIM: This study aims to systematically review the prevalence of cSVD in LMICs. RESULTS: Articles were searched from the Ovid MEDLINE and EMBASE databases from 1 January 2000 to 31 March 2022, without language restrictions. Title/abstract screening, full-text review, and data extraction were performed by two to seven independent reviewers. The prevalence of cSVD and study sample size were extracted by pre-defined world regions and health status. The Risk of Bias for Non-randomized Studies tool was used. The protocol was registered on PROSPERO (CRD42022311133). A meta-analysis of proportion was performed to assess the prevalence of different magnetic resonance imaging markers of cSVD, and a meta-regression was performed to investigate associations between cSVD prevalence and type of study, age, and male: female ratio. Of 2743 studies identified, 42 studies spanning 12 global regions were included in the systematic review. Most of the identified studies were from China (n = 23). The median prevalence of moderate-to-severe white matter hyperintensities (WMHs) was 20.5%, 40.5%, and 58.4% in the community, stroke, and dementia groups, respectively. The median prevalence of lacunes was 0.8% and 33.5% in the community and stroke groups. The median prevalence of cerebral microbleeds (CMBs) was 10.7% and 22.4% in the community and stroke groups. The median prevalence of moderate-to-severe perivascular spaces was 25.0% in the community. Meta-regression analyses showed that the weighted median age (51.4 ± 0.0 years old; range: 36.3-80.2) was a significant predictor of the prevalence of moderate-to-severe WMH and lacunes, while the type of study was a significant predictor of the prevalence of CMB. The heterogeneity of studies was high (\\textgreater95%). Male participants were overrepresented. CONCLUSIONS: This systematic review and meta-analysis provide data on cSVD prevalence in LMICs and demonstrated the high prevalence of the condition. cSVD research in LMICs is being published at an increasing rate, especially between 2010 and 2022. More data are particularly needed from Sub-Saharan Africa and Central Europe, Eastern Europe, and Central Asia.\n

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\n \n\n \n \n \n \n \n Role of small acute hyperintense lesions in long-term progression of cerebral small vessel disease and clinical outcome: a 14-year follow-up study.\n \n \n \n\n\n \n Verburgt, E.; Janssen, E.; Jacob, M. A.; Cai, M.; Ter Telgte, A.; Wiegertjes, K.; Kessels, R. P. C.; Norris, D. G.; Marques, J.; Duering, M.; Tuladhar, A. M.; and De Leeuw, F.\n\n\n \n\n\n\n J Neurol Neurosurg Psychiatry, 94(2): 144. February 2023.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{verburgt_role_2023,\n\ttitle = {Role of small acute hyperintense lesions in long-term progression of cerebral small vessel disease and clinical outcome: a 14-year follow-up study},\n\tvolume = {94},\n\tissn = {1468-330X},\n\tshorttitle = {Role of small acute hyperintense lesions in long-term progression of cerebral small vessel disease and clinical outcome},\n\tdoi = {10.1136/jnnp-2022-330091},\n\tabstract = {BACKGROUND: Small hyperintense lesions are found on diffusion-weighted imaging (DWI) in patients with sporadic small vessel disease (SVD). Their exact role in SVD progression remains unclear due to their asymptomatic and transient nature. The main objective is to investigate the role of DWI+lesions in the radiological progression of SVD and their relationship with clinical outcomes.\nMETHODS: Participants with SVD were included from the Radboud University Nijmegen Diffusion tensor MRI Cohort. DWI+lesions were assessed on four time points over 14 years. Outcome measures included neuroimaging markers of SVD, cognitive performance and clinical outcomes, including stroke, all-cause dementia and all-cause mortality. Linear mixed-effect models and Cox regression models were used to examine the outcome measures in participants with a DWI+lesion (DWI+) and those without a DWI+lesion (DWI-).\nRESULTS: DWI+lesions were present in 45 out of 503 (8.9\\%) participants (mean age: 66.7 years (SD=8.3)). Participants with DWI+lesions and at least one follow-up (n=33) had higher white matter hyperintensity progression rates (β=0.36, 95\\% CI=0.05 to 0.68, p=0.023), more incident lacunes (incidence rate ratio=2.88, 95\\% CI=1.80 to 4.67, p{\\textless}0.001) and greater cognitive decline (β=-0.03, 95\\% CI=-0.05 to -0.01, p=0.006) during a median follow-up of 13.2 (IQR: 8.8-13.8) years compared with DWI- participants. No differences were found in risk of all-cause mortality, stroke or dementia.\nCONCLUSION: Presence of a DWI+lesion in patients with SVD is associated with greater radiological progression of SVD and cognitive decline compared with patients without DWI+lesions.},\n\tlanguage = {eng},\n\tnumber = {2},\n\tjournal = {J Neurol Neurosurg Psychiatry},\n\tauthor = {Verburgt, Esmée and Janssen, Esther and Jacob, Mina A. and Cai, Mengfei and Ter Telgte, Annemieke and Wiegertjes, Kim and Kessels, Roy P. C. and Norris, David G. and Marques, Jose and Duering, Marco and Tuladhar, Anil M. and De Leeuw, Frank-Erik},\n\tmonth = feb,\n\tyear = {2023},\n\tpmid = {36270793},\n\tkeywords = {Stroke, Aged, Diffusion Magnetic Resonance Imaging, Humans, Follow-Up Studies, Magnetic Resonance Imaging, Dementia, Cerebral Small Vessel Diseases, MRI, CEREBROVASCULAR DISEASE, COGNITION},\n\tpages = {144},\n}\n\n

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\n \n\n \n \n \n \n \n CADASIL Affects Multiple Aspects of Cerebral Small Vessel Function on 7T-MRI.\n \n \n \n\n\n \n van den Brink, H.; Kopczak, A.; Arts, T.; Onkenhout, L.; Siero, J. C. W.; Zwanenburg, J. J. M.; Hein, S.; Hübner, M.; Gesierich, B.; Duering, M.; Stringer, M. S.; Hendrikse, J.; Wardlaw, J. M.; Joutel, A.; Dichgans, M.; Biessels, G. J.; and SVDs@target group\n\n\n \n\n\n\n Ann Neurol, 93(1): 29–39. January 2023.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{van_den_brink_cadasil_2023,\n\ttitle = {{CADASIL} {Affects} {Multiple} {Aspects} of {Cerebral} {Small} {Vessel} {Function} on {7T}-{MRI}},\n\tvolume = {93},\n\tissn = {1531-8249},\n\tdoi = {10.1002/ana.26527},\n\tabstract = {OBJECTIVE: Cerebral small vessel diseases (cSVDs) are a major cause of stroke and dementia. We used cutting-edge 7T-MRI techniques in patients with Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy (CADASIL), to establish which aspects of cerebral small vessel function are affected by this monogenic form of cSVD.\nMETHODS: We recruited 23 CADASIL patients (age 51.1 ± 10.1 years, 52\\% women) and 13 age- and sex-matched controls (46.1 ± 12.6, 46\\% women). Small vessel function measures included: basal ganglia and centrum semiovale perforating artery blood flow velocity and pulsatility, vascular reactivity to a visual stimulus in the occipital cortex and reactivity to hypercapnia in the cortex, subcortical gray matter, white matter, and white matter hyperintensities.\nRESULTS: Compared with controls, CADASIL patients showed lower blood flow velocity and higher pulsatility index within perforating arteries of the centrum semiovale (mean difference - 0.09 cm/s, p = 0.03 and 0.20, p = 0.009) and basal ganglia (mean difference - 0.98 cm/s, p = 0.003 and 0.17, p = 0.06). Small vessel reactivity to a short visual stimulus was decreased (blood-oxygen-level dependent [BOLD] mean difference -0.21\\%, p = 0.04) in patients, while reactivity to hypercapnia was preserved in the cortex, subcortical gray matter, and normal appearing white matter. Among patients, reactivity to hypercapnia was decreased in white matter hyperintensities compared to normal appearing white matter (BOLD mean difference -0.29\\%, p = 0.02).\nINTERPRETATION: Multiple aspects of cerebral small vessel function on 7T-MRI were abnormal in CADASIL patients, indicative of increased arteriolar stiffness and regional abnormalities in reactivity, locally also in relation to white matter injury. These observations provide novel markers of cSVD for mechanistic and intervention studies. ANN NEUROL 2023;93:29-39.},\n\tlanguage = {eng},\n\tnumber = {1},\n\tjournal = {Ann Neurol},\n\tauthor = {van den Brink, Hilde and Kopczak, Anna and Arts, Tine and Onkenhout, Laurien and Siero, Jeroen C. W. and Zwanenburg, Jaco J. M. and Hein, Sandra and Hübner, Mathias and Gesierich, Benno and Duering, Marco and Stringer, Michael S. and Hendrikse, Jeroen and Wardlaw, Joanna M. and Joutel, Anne and Dichgans, Martin and Biessels, Geert Jan and {SVDs@target group}},\n\tmonth = jan,\n\tyear = {2023},\n\tpmid = {36222455},\n\tkeywords = {Adult, Female, Humans, Male, Middle Aged, Magnetic Resonance Imaging, Cerebral Infarction, Cerebral Small Vessel Diseases, CADASIL, Hypercapnia},\n\tpages = {29--39},\n\tfile = {Full Text:/Users/mduering/Zotero/storage/EPMZLE7E/van den Brink et al. - 2023 - CADASIL Affects Multiple Aspects of Cerebral Small.pdf:application/pdf},\n}\n\n

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\n \n\n \n \n \n \n \n Network structure-function coupling and neurocognition in cerebral small vessel disease.\n \n \n \n\n\n \n Tay, J.; Düring, M.; van Leijsen, E. M. C.; Bergkamp, M. I.; Norris, D. G.; de Leeuw, F.; Markus, H. S.; and Tuladhar, A. M.\n\n\n \n\n\n\n Neuroimage Clin, 38: 103421. 2023.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{tay_network_2023,\n\ttitle = {Network structure-function coupling and neurocognition in cerebral small vessel disease},\n\tvolume = {38},\n\tissn = {2213-1582},\n\tdoi = {10.1016/j.nicl.2023.103421},\n\tabstract = {BACKGROUND: Cerebral small vessel disease is a leading cause of cognitive decline and vascular dementia. Small vessel disease pathology changes structural brain networks, but its impact on functional networks remains poorly understood. Structural and functional networks are closely coupled in healthy individuals, and decoupling is associated with clinical symptoms in other neurological conditions. We tested the hypothesis that structural-functional network coupling is related to neurocognitive outcomes in 262 small vessel disease patients.\nMETHODS: Participants underwent multimodal magnetic resonance imaging and cognitive assessment in 2011 and 2015. Structural connectivity networks were reconstructed using probabilistic diffusion tractography, while functional connectivity networks were estimated from resting-state functional magnetic resonance imaging. Structural and functional networks were then correlated to calculate a measure of structural-functional network coupling for each participant.\nRESULTS: Lower whole-brain coupling was associated with reduced processing speed and greater apathy both cross-sectionally and longitudinally. In addition, coupling within the cognitive control network was associated with all cognitive outcomes, suggesting that neurocognitive outcomes in small vessel disease may be related to the functioning of this intrinsic connectivity network.\nCONCLUSIONS: Our work demonstrates the influence of structural-functional connectivity network decoupling in small vessel disease symptomatology. Cognitive control network function may be investigated in future studies.},\n\tlanguage = {eng},\n\tjournal = {Neuroimage Clin},\n\tauthor = {Tay, Jonathan and Düring, Marco and van Leijsen, Esther M. C. and Bergkamp, Mayra I. and Norris, David G. and de Leeuw, Frank-Erik and Markus, Hugh S. and Tuladhar, Anil M.},\n\tyear = {2023},\n\tpmid = {37141644},\n\tpmcid = {PMC10176072},\n\tkeywords = {Cognition, Small vessel disease, Humans, Magnetic Resonance Imaging, Brain, Cerebral Small Vessel Diseases, Cognitive Dysfunction, MRI, Network analysis},\n\tpages = {103421},\n\tfile = {Full Text:/Users/mduering/Zotero/storage/MSYU5584/Tay et al. - 2023 - Network structure-function coupling and neurocogni.pdf:application/pdf},\n}\n\n

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\n \n\n \n \n \n \n \n Cerebral small vessel disease burden and cognitive and functional outcomes after stroke: A multicenter prospective cohort study.\n \n \n \n\n\n \n Georgakis, M. K.; Fang, R.; Düring, M.; Wollenweber, F. A.; Bode, F. J.; Stösser, S.; Kindlein, C.; Hermann, P.; Liman, T. G.; Nolte, C. H.; Kerti, L.; Ikenberg, B.; Bernkopf, K.; Poppert, H.; Glanz, W.; Perosa, V.; Janowitz, D.; Wagner, M.; Neumann, K.; Speck, O.; Dobisch, L.; Düzel, E.; Gesierich, B.; Dewenter, A.; Spottke, A.; Waegemann, K.; Görtler, M.; Wunderlich, S.; Endres, M.; Zerr, I.; Petzold, G.; Dichgans, M.; and DEMDAS Investigators\n\n\n \n\n\n\n Alzheimers Dement, 19(4): 1152–1163. April 2023.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{georgakis_cerebral_2023,\n\ttitle = {Cerebral small vessel disease burden and cognitive and functional outcomes after stroke: {A} multicenter prospective cohort study},\n\tvolume = {19},\n\tissn = {1552-5279},\n\tshorttitle = {Cerebral small vessel disease burden and cognitive and functional outcomes after stroke},\n\tdoi = {10.1002/alz.12744},\n\tabstract = {INTRODUCTION: It remains unknown whether the global small vessel disease (SVD) burden predicts post-stroke outcomes.\nMETHODS: In a prospective multicenter study of 666 ischemic and hemorrhagic stroke patients, we quantified magnetic resonance imaging (MRI)-based SVD markers (lacunes, white matter hyperintensities, microbleeds, perivascular spaces) and explored associations with 6- and 12-month cognitive (battery of 15 neuropsychological tests) and functional (modified Rankin scale) outcomes.\nRESULTS: A global SVD score (range 0-4) was associated with cognitive impairment; worse performance in executive function, attention, language, and visuospatial ability; and worse functional outcome across a 12-month follow-up. Although the global SVD score did not improve prediction, individual SVD markers, assessed across their severity range, improved the calibration, discrimination, and reclassification of predictive models including demographic, clinical, and other imaging factors.\nDISCUSSION: SVD presence and severity are associated with worse cognitive and functional outcomes 12 months after stroke. Assessing SVD severity may aid prognostication for stroke patients.\nHIGHLIGHTS: In a multi-center cohort, we explored associations of small vessel disease (SVD) burden with stroke outcomes. SVD burden associates with post-stroke cognitive and functional outcomes. A currently used score of SVD burden does not improve the prediction of poor outcomes. Assessing the severity of SVD lesions adds predictive value beyond known predictors. To add predictive value in assessing SVD in stroke patients, SVD burden scores should integrate lesion severity.},\n\tlanguage = {eng},\n\tnumber = {4},\n\tjournal = {Alzheimers Dement},\n\tauthor = {Georgakis, Marios K. and Fang, Rong and Düring, Marco and Wollenweber, Frank A. and Bode, Felix J. and Stösser, Sebastian and Kindlein, Christine and Hermann, Peter and Liman, Thomas G. and Nolte, Christian H. and Kerti, Lucia and Ikenberg, Benno and Bernkopf, Kathleen and Poppert, Holger and Glanz, Wenzel and Perosa, Valentina and Janowitz, Daniel and Wagner, Michael and Neumann, Katja and Speck, Oliver and Dobisch, Laura and Düzel, Emrah and Gesierich, Benno and Dewenter, Anna and Spottke, Annika and Waegemann, Karin and Görtler, Michael and Wunderlich, Silke and Endres, Matthias and Zerr, Inga and Petzold, Gabor and Dichgans, Martin and {DEMDAS Investigators}},\n\tmonth = apr,\n\tyear = {2023},\n\tpmid = {35876563},\n\tkeywords = {Cognition, Stroke, cognitive impairment, Humans, cerebral small vessel disease, Prospective Studies, Magnetic Resonance Imaging, stroke, Cerebral Small Vessel Diseases, Cognitive Dysfunction, functional outcome, prediction},\n\tpages = {1152--1163},\n}\n\n

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\n \n\n \n \n \n \n \n Effect of blood pressure-lowering agents on microvascular function in people with small vessel diseases (TREAT-SVDs): a multicentre, open-label, randomised, crossover trial.\n \n \n \n\n\n \n Kopczak, A.; Stringer, M. S.; van den Brink, H.; Kerkhofs, D.; Blair, G. W.; van Dinther, M.; Reyes, C. A.; Garcia, D. J.; Onkenhout, L.; Wartolowska, K. A.; Thrippleton, M. J.; Kampaite, A.; Duering, M.; Staals, J.; Lesnik-Oberstein, S.; Muir, K. W.; Middeke, M.; Norrving, B.; Bousser, M.; Mansmann, U.; Rothwell, P. M.; Doubal, F. N.; van Oostenbrugge, R.; Biessels, G. J.; Webb, A. J. S.; Wardlaw, J. M.; Dichgans, M.; and TREAT-SVDs collaborators\n\n\n \n\n\n\n Lancet Neurol, 22(11): 991–1004. November 2023.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{kopczak_effect_2023,\n\ttitle = {Effect of blood pressure-lowering agents on microvascular function in people with small vessel diseases ({TREAT}-{SVDs}): a multicentre, open-label, randomised, crossover trial},\n\tvolume = {22},\n\tissn = {1474-4465},\n\tshorttitle = {Effect of blood pressure-lowering agents on microvascular function in people with small vessel diseases ({TREAT}-{SVDs})},\n\tdoi = {10.1016/S1474-4422(23)00293-4},\n\tabstract = {BACKGROUND: Hypertension is the leading risk factor for cerebral small vessel disease. We aimed to determine whether antihypertensive drug classes differentially affect microvascular function in people with small vessel disease.\nMETHODS: We did a multicentre, open-label, randomised crossover trial with blinded endpoint assessment at five specialist centres in Europe. We included participants aged 18 years or older with symptomatic sporadic small vessel disease or cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) and an indication for antihypertensive treatment. Participants were randomly assigned (1:1:1) to one of three sequences of antihypertensive treatment using a computer-generated multiblock randomisation, stratified by study site and patient group. A 2-week washout period was followed by three 4-week periods of oral monotherapy with amlodipine, losartan, or atenolol at approved doses. The primary endpoint was change in cerebrovascular reactivity (CVR) determined by blood oxygen level-dependent MRI response to hypercapnic challenge in normal-appearing white matter from the end of washout to the end of each treatment period. Efficacy analyses were done by intention-to-treat principles in all randomly assigned participants who had at least one valid assessment for the primary endpoint, and analyses were done separately for participants with sporadic small vessel disease and CADASIL. This trial is registered at ClinicalTrials.gov, NCT03082014, and EudraCT, 2016-002920-10, and is terminated.\nFINDINGS: Between Feb 22, 2018, and April 28, 2022, 75 participants with sporadic small vessel disease (mean age 64·9 years [SD 9·9]) and 26 with CADASIL (53·1 years [7·0]) were enrolled and randomly assigned to treatment. 79 participants (62 with sporadic small vessel disease and 17 with CADASIL) entered the primary efficacy analysis. Change in CVR did not differ between study drugs in participants with sporadic small vessel disease (mean change in CVR 1·8 × 10-4\\%/mm Hg [SE 20·1; 95\\% CI -37·6 to 41·2] for amlodipine; 16·7 × 10-4\\%/mm Hg [20·0; -22·3 to 55·8] for losartan; -7·1 × 10-4\\%/mm Hg [19·6; -45·5 to 31·1] for atenolol; poverall=0·39) but did differ in patients with CADASIL (15·7 × 10-4\\%/mm Hg [SE 27·5; 95\\% CI -38·3 to 69·7] for amlodipine; 19·4 × 10-4\\%/mm Hg [27·9; -35·3 to 74·2] for losartan; -23·9 × 10-4\\%/mm Hg [27·5; -77·7 to 30·0] for atenolol; poverall=0·019). In patients with CADASIL, pairwise comparisons showed that CVR improved with amlodipine compared with atenolol (-39·6 × 10-4\\%/mm Hg [95\\% CI -72·5 to -6·6; p=0·019) and with losartan compared with atenolol (-43·3 × 10-4\\%/mm Hg [-74·3 to -12·3]; p=0·0061). No deaths occurred. Two serious adverse events were recorded, one while taking amlodipine (diarrhoea with dehydration) and one while taking atenolol (fall with fracture), neither of which was related to study drug intake.\nINTERPRETATION: 4 weeks of treatment with amlodipine, losartan, or atenolol did not differ in their effects on cerebrovascular reactivity in people with sporadic small vessel disease but did result in differential treatment effects in patients with CADASIL. Whether antihypertensive drug classes differentially affect clinical outcomes in people with small vessel diseases requires further research.\nFUNDING: EU Horizon 2020 programme.},\n\tlanguage = {eng},\n\tnumber = {11},\n\tjournal = {Lancet Neurol},\n\tauthor = {Kopczak, Anna and Stringer, Michael S. and van den Brink, Hilde and Kerkhofs, Danielle and Blair, Gordon W. and van Dinther, Maud and Reyes, Carmen Arteaga and Garcia, Daniela Jaime and Onkenhout, Laurien and Wartolowska, Karolina A. and Thrippleton, Michael J. and Kampaite, Agniete and Duering, Marco and Staals, Julie and Lesnik-Oberstein, Saskia and Muir, Keith W. and Middeke, Martin and Norrving, Bo and Bousser, Marie-Germaine and Mansmann, Ulrich and Rothwell, Peter M. and Doubal, Fergus N. and van Oostenbrugge, Robert and Biessels, Geert Jan and Webb, Alastair J. S. and Wardlaw, Joanna M. and Dichgans, Martin and {TREAT-SVDs collaborators}},\n\tmonth = nov,\n\tyear = {2023},\n\tpmid = {37863608},\n\tkeywords = {Aged, Humans, Middle Aged, Treatment Outcome, CADASIL, Double-Blind Method, Amlodipine, Antihypertensive Agents, Atenolol, Blood Pressure, Cross-Over Studies, Losartan, Hypertension},\n\tpages = {991--1004},\n}\n\n

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\n BACKGROUND: Hypertension is the leading risk factor for cerebral small vessel disease. We aimed to determine whether antihypertensive drug classes differentially affect microvascular function in people with small vessel disease. METHODS: We did a multicentre, open-label, randomised crossover trial with blinded endpoint assessment at five specialist centres in Europe. We included participants aged 18 years or older with symptomatic sporadic small vessel disease or cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) and an indication for antihypertensive treatment. Participants were randomly assigned (1:1:1) to one of three sequences of antihypertensive treatment using a computer-generated multiblock randomisation, stratified by study site and patient group. A 2-week washout period was followed by three 4-week periods of oral monotherapy with amlodipine, losartan, or atenolol at approved doses. The primary endpoint was change in cerebrovascular reactivity (CVR) determined by blood oxygen level-dependent MRI response to hypercapnic challenge in normal-appearing white matter from the end of washout to the end of each treatment period. Efficacy analyses were done by intention-to-treat principles in all randomly assigned participants who had at least one valid assessment for the primary endpoint, and analyses were done separately for participants with sporadic small vessel disease and CADASIL. This trial is registered at ClinicalTrials.gov, NCT03082014, and EudraCT, 2016-002920-10, and is terminated. FINDINGS: Between Feb 22, 2018, and April 28, 2022, 75 participants with sporadic small vessel disease (mean age 64·9 years [SD 9·9]) and 26 with CADASIL (53·1 years [7·0]) were enrolled and randomly assigned to treatment. 79 participants (62 with sporadic small vessel disease and 17 with CADASIL) entered the primary efficacy analysis. Change in CVR did not differ between study drugs in participants with sporadic small vessel disease (mean change in CVR 1·8 × 10-4%/mm Hg [SE 20·1; 95% CI -37·6 to 41·2] for amlodipine; 16·7 × 10-4%/mm Hg [20·0; -22·3 to 55·8] for losartan; -7·1 × 10-4%/mm Hg [19·6; -45·5 to 31·1] for atenolol; poverall=0·39) but did differ in patients with CADASIL (15·7 × 10-4%/mm Hg [SE 27·5; 95% CI -38·3 to 69·7] for amlodipine; 19·4 × 10-4%/mm Hg [27·9; -35·3 to 74·2] for losartan; -23·9 × 10-4%/mm Hg [27·5; -77·7 to 30·0] for atenolol; poverall=0·019). In patients with CADASIL, pairwise comparisons showed that CVR improved with amlodipine compared with atenolol (-39·6 × 10-4%/mm Hg [95% CI -72·5 to -6·6; p=0·019) and with losartan compared with atenolol (-43·3 × 10-4%/mm Hg [-74·3 to -12·3]; p=0·0061). No deaths occurred. Two serious adverse events were recorded, one while taking amlodipine (diarrhoea with dehydration) and one while taking atenolol (fall with fracture), neither of which was related to study drug intake. INTERPRETATION: 4 weeks of treatment with amlodipine, losartan, or atenolol did not differ in their effects on cerebrovascular reactivity in people with sporadic small vessel disease but did result in differential treatment effects in patients with CADASIL. Whether antihypertensive drug classes differentially affect clinical outcomes in people with small vessel diseases requires further research. FUNDING: EU Horizon 2020 programme.\n

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\n \n\n \n \n \n \n \n White Matter Hyperintensity Volume and Poststroke Cognition: An Individual Patient Data Pooled Analysis of 9 Ischemic Stroke Cohort Studies.\n \n \n \n\n\n \n de Kort, F. A. S.; Coenen, M.; Weaver, N. A.; Kuijf, H. J.; Aben, H. P.; Bae, H.; Bordet, R.; Cammà, G.; Chen, C. P. L. H.; Dewenter, A.; Duering, M.; Fang, R.; van der Giessen, R. S.; Hamilton, O. K. L.; Hilal, S.; Huenges Wajer, I. M. C.; Kan, C. N.; Kim, J.; Kim, B. J.; Köhler, S.; de Kort, P. L. M.; Koudstaal, P. J.; Lim, J.; Lopes, R.; Mok, V. C. T.; Staals, J.; Venketasubramanian, N.; Verhagen, C. M.; Verhey, F. R. J.; Wardlaw, J. M.; Xu, X.; Yu, K.; Biesbroek, J. M.; and Biessels, G. J.\n\n\n \n\n\n\n Stroke, 54(12): 3021–3029. October 2023.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{de_kort_white_2023,\n\ttitle = {White {Matter} {Hyperintensity} {Volume} and {Poststroke} {Cognition}: {An} {Individual} {Patient} {Data} {Pooled} {Analysis} of 9 {Ischemic} {Stroke} {Cohort} {Studies}},\n\tvolume = {54},\n\tissn = {1524-4628},\n\tshorttitle = {White {Matter} {Hyperintensity} {Volume} and {Poststroke} {Cognition}},\n\tdoi = {10.1161/STROKEAHA.123.044297},\n\tabstract = {BACKGROUND: White matter hyperintensities (WMH) are associated with cognitive dysfunction after ischemic stroke. Yet, uncertainty remains about affected domains, the role of other preexisting brain injury, and infarct types in the relation between WMH burden and poststroke cognition. We aimed to disentangle these factors in a large sample of patients with ischemic stroke from different cohorts.\nMETHODS: We pooled and harmonized individual patient data (n=1568) from 9 cohorts, through the Meta VCI Map consortium (www.metavcimap.org). Included cohorts comprised patients with available magnetic resonance imaging and multidomain cognitive assessment {\\textless}15 months poststroke. In this individual patient data meta-analysis, linear mixed models were used to determine the association between WMH volume and domain-specific cognitive functioning (Z scores; attention and executive functioning, processing speed, language and verbal memory) for the total sample and stratified by infarct type. Preexisting brain injury was accounted for in the multivariable models and all analyses were corrected for the study site as a random effect.\nRESULTS: In the total sample (67 years [SD, 11.5], 40\\% female), we found a dose-dependent inverse relationship between WMH volume and poststroke cognitive functioning across all 4 cognitive domains (coefficients ranging from -0.09 [SE, 0.04, P=0.01] for verbal memory to -0.19 [SE, 0.03, P{\\textless}0.001] for attention and executive functioning). This relation was independent of acute infarct volume and the presence of lacunes and old infarcts. In stratified analyses, the relation between WMH volume and domain-specific functioning was also largely independent of infarct type.\nCONCLUSIONS: In patients with ischemic stroke, increasing WMH volume is independently associated with worse cognitive functioning across all major domains, regardless of old ischemic lesions and infarct type.},\n\tlanguage = {eng},\n\tnumber = {12},\n\tjournal = {Stroke},\n\tauthor = {de Kort, Floor A. S. and Coenen, Mirthe and Weaver, Nick A. and Kuijf, Hugo J. and Aben, Hugo P. and Bae, Hee-Joon and Bordet, Régis and Cammà, Guido and Chen, Christopher P. L. H. and Dewenter, Anna and Duering, Marco and Fang, Rong and van der Giessen, Ruben S. and Hamilton, Olivia K. L. and Hilal, Saima and Huenges Wajer, Irene M. C. and Kan, Cheuk Ni and Kim, Jonguk and Kim, Beom Joon and Köhler, Sebastian and de Kort, Paul L. M. and Koudstaal, Peter J. and Lim, Jae-Sung and Lopes, Renaud and Mok, Vincent C. T. and Staals, Julie and Venketasubramanian, Narayanaswamy and Verhagen, Charlotte M. and Verhey, Frans R. J. and Wardlaw, Joanna M. and Xu, Xin and Yu, Kyung-Ho and Biesbroek, J. Matthijs and Biessels, Geert Jan},\n\tmonth = oct,\n\tyear = {2023},\n\tpmid = {37901947},\n\tpmcid = {PMC10664782},\n\tkeywords = {cognition, neuroimaging, cerebral small vessel diseases, brain, ischemic stroke, infarcts},\n\tpages = {3021--3029},\n}\n\n

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\n \n\n \n \n \n \n \n Florbetapir PET-assessed demyelination is associated with faster tau accumulation in an APOE ε4-dependent manner.\n \n \n \n\n\n \n Rubinski, A.; Dewenter, A.; Zheng, L.; Franzmeier, N.; Stephenson, H.; Deming, Y.; Duering, M.; Gesierich, B.; Denecke, J.; Pham, A.; Bendlin, B.; Ewers, M.; and Alzheimer’s Disease Neuroimaging Initiative\n\n\n \n\n\n\n Eur J Nucl Med Mol Imaging. December 2023.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{rubinski_florbetapir_2023,\n\ttitle = {Florbetapir {PET}-assessed demyelination is associated with faster tau accumulation in an {APOE} ε4-dependent manner},\n\tissn = {1619-7089},\n\tdoi = {10.1007/s00259-023-06530-8},\n\tabstract = {PURPOSE: The main objectives were to test whether (1) a decrease in myelin is associated with enhanced rate of fibrillar tau accumulation and cognitive decline in Alzheimer's disease, and (2) whether apolipoprotein E (APOE) ε4 genotype is associated with worse myelin decrease and thus tau accumulation.\nMETHODS: To address our objectives, we repurposed florbetapir-PET as a marker of myelin in the white matter (WM) based on previous validation studies showing that beta-amyloid (Aβ) PET tracers bind to WM myelin. We assessed 43 Aβ-biomarker negative (Aβ-) cognitively normal participants and 108 Aβ+ participants within the AD spectrum with florbetapir-PET at baseline and longitudinal flortaucipir-PET as a measure of fibrillar tau (tau-PET) over {\\textasciitilde} 2 years. In linear regression analyses, we tested florbetapir-PET in the whole WM and major fiber tracts as predictors of tau-PET accumulation in a priori defined regions of interest (ROIs) and fiber-tract projection areas. In mediation analyses we tested whether tau-PET accumulation mediates the effect of florbetapir-PET in the whole WM on cognition. Finally, we assessed the role of myelin alteration on the association between APOE and tau-PET accumulation.\nRESULTS: Lower florbetapir-PET in the whole WM or at a given fiber tract was predictive of faster tau-PET accumulation in Braak stages or the connected grey matter areas in Aβ+ participants. Faster tau-PET accumulation in higher cortical brain areas mediated the association between a decrease in florbetapir-PET in the WM and a faster rate of decline in global cognition and episodic memory. APOE ε4 genotype was associated with a worse decrease in the whole WM florbetapir-PET and thus enhanced tau-PET accumulation.\nCONCLUSION: Myelin alterations are associated in an APOE ε4 dependent manner with faster tau progression and cognitive decline, and may therefore play a role in the etiology of AD.},\n\tlanguage = {eng},\n\tjournal = {Eur J Nucl Med Mol Imaging},\n\tauthor = {Rubinski, Anna and Dewenter, Anna and Zheng, Lukai and Franzmeier, Nicolai and Stephenson, Henry and Deming, Yuetiva and Duering, Marco and Gesierich, Benno and Denecke, Jannis and Pham, An-Vi and Bendlin, Barbara and Ewers, Michael and {Alzheimer’s Disease Neuroimaging Initiative}},\n\tmonth = dec,\n\tyear = {2023},\n\tpmid = {38049659},\n\tkeywords = {Myelin, Tau, APOE, Florbetapir-PET},\n}\n\n

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\n \n\n \n \n \n \n \n Spatial distributions of white matter hyperintensities on brain MRI: A pooled analysis of individual participant data from 11 memory clinic cohorts.\n \n \n \n\n\n \n Coenen, M.; Biessels, G. J.; DeCarli, C.; Fletcher, E. F.; Maillard, P. M.; Alzheimer's Disease Neuroimaging Initiative; Barkhof, F.; Barnes, J.; Benke, T.; Boomsma, J. M. F.; P L H Chen, C.; Dal-Bianco, P.; Dewenter, A.; Duering, M.; Enzinger, C.; Ewers, M.; Exalto, L. G.; Franzmeier, N.; Groeneveld, O.; Hilal, S.; Hofer, E.; Koek, H. L.; Maier, A. B.; McCreary, C. R.; Papma, J. M.; Paterson, R. W.; Pijnenburg, Y. A. L.; Rubinski, A.; Schmidt, R.; Schott, J. M.; Slattery, C. F.; Smith, E. E.; Sudre, C. H.; Steketee, R. M. E.; van den Berg, E.; van der Flier, W. M.; Venketasubramanian, N.; Vernooij, M. W.; Wolters, F. J.; Xin, X.; Biesbroek, J. M.; and Kuijf, H. J.\n\n\n \n\n\n\n Neuroimage Clin, 40: 103547. 2023.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{coenen_spatial_2023,\n\ttitle = {Spatial distributions of white matter hyperintensities on brain {MRI}: {A} pooled analysis of individual participant data from 11 memory clinic cohorts},\n\tvolume = {40},\n\tissn = {2213-1582},\n\tshorttitle = {Spatial distributions of white matter hyperintensities on brain {MRI}},\n\tdoi = {10.1016/j.nicl.2023.103547},\n\tabstract = {INTRODUCTION: The spatial distribution of white matter hyperintensities (WMH) on MRI is often considered in the diagnostic evaluation of patients with cognitive problems. In some patients, clinicians may classify WMH patterns as "unusual", but this is largely based on expert opinion, because detailed quantitative information about WMH distribution frequencies in a memory clinic setting is lacking. Here we report voxel wise 3D WMH distribution frequencies in a large multicenter dataset and also aimed to identify individuals with unusual WMH patterns.\nMETHODS: Individual participant data (N = 3525, including 777 participants with subjective cognitive decline, 1389 participants with mild cognitive impairment and 1359 patients with dementia) from eleven memory clinic cohorts, recruited through the Meta VCI Map Consortium, were used. WMH segmentations were provided by participating centers or performed in Utrecht and registered to the Montreal Neurological Institute (MNI)-152 brain template for spatial normalization. To determine WMH distribution frequencies, we calculated WMH probability maps at voxel level. To identify individuals with unusual WMH patterns, region-of-interest (ROI) based WMH probability maps, rule-based scores, and a machine learning method (Local Outlier Factor (LOF)), were implemented.\nRESULTS: WMH occurred in 82\\% of voxels from the white matter template with large variation between subjects. Only a small proportion of the white matter (1.7\\%), mainly in the periventricular areas, was affected by WMH in at least 20\\% of participants. A large portion of the total white matter was affected infrequently. Nevertheless, 93.8\\% of individual participants had lesions in voxels that were affected in less than 2\\% of the population, mainly located in subcortical areas. Only the machine learning method effectively identified individuals with unusual patterns, in particular subjects with asymmetric WMH distribution or with WMH at relatively rarely affected locations despite common locations not being affected.\nDISCUSSION: Aggregating data from several memory clinic cohorts, we provide a detailed 3D map of WMH lesion distribution frequencies, that informs on common as well as rare localizations. The use of data-driven analysis with LOF can be used to identify unusual patterns, which might serve as an alert that rare causes of WMH should be considered.},\n\tlanguage = {eng},\n\tjournal = {Neuroimage Clin},\n\tauthor = {Coenen, Mirthe and Biessels, Geert Jan and DeCarli, Charles and Fletcher, Evan F. and Maillard, Pauline M. and {Alzheimer's Disease Neuroimaging Initiative} and Barkhof, Frederik and Barnes, Josephine and Benke, Thomas and Boomsma, Jooske M. F. and P L H Chen, Christopher and Dal-Bianco, Peter and Dewenter, Anna and Duering, Marco and Enzinger, Christian and Ewers, Michael and Exalto, Lieza G. and Franzmeier, Nicolai and Groeneveld, Onno and Hilal, Saima and Hofer, Edith and Koek, Huiberdina L. and Maier, Andrea B. and McCreary, Cheryl R. and Papma, Janne M. and Paterson, Ross W. and Pijnenburg, Yolande A. L. and Rubinski, Anna and Schmidt, Reinhold and Schott, Jonathan M. and Slattery, Catherine F. and Smith, Eric E. and Sudre, Carole H. and Steketee, Rebecca M. E. and van den Berg, Esther and van der Flier, Wiesje M. and Venketasubramanian, Narayanaswamy and Vernooij, Meike W. and Wolters, Frank J. and Xin, Xu and Biesbroek, J. Matthijs and Kuijf, Hugo J.},\n\tyear = {2023},\n\tpmid = {38035457},\n\tpmcid = {PMC10698002},\n\tkeywords = {Humans, Neuroimaging, Magnetic Resonance Imaging, White matter hyperintensities, Lesion location, Brain, White Matter, Cognitive Dysfunction, Multicenter Studies as Topic, Brain MRI, Distribution frequencies},\n\tpages = {103547},\n}\n\n

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\n INTRODUCTION: The spatial distribution of white matter hyperintensities (WMH) on MRI is often considered in the diagnostic evaluation of patients with cognitive problems. In some patients, clinicians may classify WMH patterns as \"unusual\", but this is largely based on expert opinion, because detailed quantitative information about WMH distribution frequencies in a memory clinic setting is lacking. Here we report voxel wise 3D WMH distribution frequencies in a large multicenter dataset and also aimed to identify individuals with unusual WMH patterns. METHODS: Individual participant data (N = 3525, including 777 participants with subjective cognitive decline, 1389 participants with mild cognitive impairment and 1359 patients with dementia) from eleven memory clinic cohorts, recruited through the Meta VCI Map Consortium, were used. WMH segmentations were provided by participating centers or performed in Utrecht and registered to the Montreal Neurological Institute (MNI)-152 brain template for spatial normalization. To determine WMH distribution frequencies, we calculated WMH probability maps at voxel level. To identify individuals with unusual WMH patterns, region-of-interest (ROI) based WMH probability maps, rule-based scores, and a machine learning method (Local Outlier Factor (LOF)), were implemented. RESULTS: WMH occurred in 82% of voxels from the white matter template with large variation between subjects. Only a small proportion of the white matter (1.7%), mainly in the periventricular areas, was affected by WMH in at least 20% of participants. A large portion of the total white matter was affected infrequently. Nevertheless, 93.8% of individual participants had lesions in voxels that were affected in less than 2% of the population, mainly located in subcortical areas. Only the machine learning method effectively identified individuals with unusual patterns, in particular subjects with asymmetric WMH distribution or with WMH at relatively rarely affected locations despite common locations not being affected. DISCUSSION: Aggregating data from several memory clinic cohorts, we provide a detailed 3D map of WMH lesion distribution frequencies, that informs on common as well as rare localizations. The use of data-driven analysis with LOF can be used to identify unusual patterns, which might serve as an alert that rare causes of WMH should be considered.\n

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\n \n\n \n \n \n \n \n Brain-derived Tau for Monitoring Brain Injury in Acute Ischemic Stroke.\n \n \n \n\n\n \n Vlegels, N.; Gonzalez-Ortiz, F.; Knuth, N. L.; Khalifeh, N.; Gesierich, B.; Müller, F.; Müller, P.; Klein, M.; Dimitriadis, K.; Franzmeier, N.; Liebig, T.; Duering, M.; Reidler, P.; Dichgans, M.; Karikari, T. K.; Blennow, K.; and Tiedt, S.\n\n\n \n\n\n\n medRxiv,2023.11.18.23298728. November 2023.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{vlegels_brain-derived_2023,\n\ttitle = {Brain-derived {Tau} for {Monitoring} {Brain} {Injury} in {Acute} {Ischemic} {Stroke}},\n\tdoi = {10.1101/2023.11.18.23298728},\n\tabstract = {The evolution of infarcts varies widely among patients with acute ischemic stroke (IS) and influences treatment decisions. Neuroimaging is not applicable for frequent monitoring and there is no blood-based biomarker to track ongoing brain injury in acute IS. Here, we examined the utility of plasma brain-derived tau (BD-tau) as a biomarker for brain injury in acute IS. We conducted the prospective, observational Precision Medicine in Stroke [PROMISE] study with serial blood sampling upon hospital admission and at days 2, 3, and 7 in patients with acute ischemic stroke (IS) and for comparison, in patients with stroke mimics (SM). We determined the temporal course of plasma BD-tau, its relation to infarct size and admission imaging-based metrics of brain injury, and its value to predict functional outcome. Upon admission (median time-from-onset, 4.4h), BD-tau levels in IS patients correlated with ASPECTS (ρ=-0.21, P{\\textless}.0001) and were predictive of final infarct volume (ρ=0.26, P{\\textless}.0001). In contrast to SM patients, BD-tau levels in IS patients increased from admission (median, 2.9 pg/ml [IQR, 1.8-4.8]) to day 2 (median time-from-onset, 22.7h; median BD-tau, 5.0 pg/ml [IQR, 2.6-10.3]; P{\\textless}.0001). The rate of change of BD-tau from admission to day 2 was significantly associated with collateral supply (R2=0.10, P{\\textless}.0001) and infarct progression (ρ=0.58, P{\\textless}.0001). At day 2, BD-tau was predictive of final infarct volume (ρ=0.59, P{\\textless}.0001) and showed superior value for predicting the 90-day mRS score compared with final infarct volume. In conclusion, in 502 patients with acute IS, plasma BD-tau was associated with imaging-based metrics of brain injury upon admission, increased within the first 24 hours in correlation with infarct progression, and at 24 hours was superior to final infarct volume in predicting 90-day functional outcome. Further research is needed to determine whether BD-tau assessments can inform decision-making in stroke care.},\n\tlanguage = {eng},\n\tjournal = {medRxiv},\n\tauthor = {Vlegels, Naomi and Gonzalez-Ortiz, Fernando and Knuth, Nicoló Luca and Khalifeh, Nada and Gesierich, Benno and Müller, Franziska and Müller, Philipp and Klein, Matthias and Dimitriadis, Konstantinos and Franzmeier, Nicolai and Liebig, Thomas and Duering, Marco and Reidler, Paul and Dichgans, Martin and Karikari, Thomas K. and Blennow, Kaj and Tiedt, Steffen},\n\tmonth = nov,\n\tyear = {2023},\n\tpmid = {38014197},\n\tpmcid = {PMC10680879},\n\tpages = {2023.11.18.23298728},\n}\n\n

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\n The evolution of infarcts varies widely among patients with acute ischemic stroke (IS) and influences treatment decisions. Neuroimaging is not applicable for frequent monitoring and there is no blood-based biomarker to track ongoing brain injury in acute IS. Here, we examined the utility of plasma brain-derived tau (BD-tau) as a biomarker for brain injury in acute IS. We conducted the prospective, observational Precision Medicine in Stroke [PROMISE] study with serial blood sampling upon hospital admission and at days 2, 3, and 7 in patients with acute ischemic stroke (IS) and for comparison, in patients with stroke mimics (SM). We determined the temporal course of plasma BD-tau, its relation to infarct size and admission imaging-based metrics of brain injury, and its value to predict functional outcome. Upon admission (median time-from-onset, 4.4h), BD-tau levels in IS patients correlated with ASPECTS (ρ=-0.21, P\\textless.0001) and were predictive of final infarct volume (ρ=0.26, P\\textless.0001). In contrast to SM patients, BD-tau levels in IS patients increased from admission (median, 2.9 pg/ml [IQR, 1.8-4.8]) to day 2 (median time-from-onset, 22.7h; median BD-tau, 5.0 pg/ml [IQR, 2.6-10.3]; P\\textless.0001). The rate of change of BD-tau from admission to day 2 was significantly associated with collateral supply (R2=0.10, P\\textless.0001) and infarct progression (ρ=0.58, P\\textless.0001). At day 2, BD-tau was predictive of final infarct volume (ρ=0.59, P\\textless.0001) and showed superior value for predicting the 90-day mRS score compared with final infarct volume. In conclusion, in 502 patients with acute IS, plasma BD-tau was associated with imaging-based metrics of brain injury upon admission, increased within the first 24 hours in correlation with infarct progression, and at 24 hours was superior to final infarct volume in predicting 90-day functional outcome. Further research is needed to determine whether BD-tau assessments can inform decision-making in stroke care.\n

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\n \n\n \n \n \n \n \n Computed tomography hypoperfusion-hypodensity mismatch vs. automated perfusion mismatch to identify stroke patients eligible for thrombolysis.\n \n \n \n\n\n \n Sporns, P. B.; Kemmling, A.; Meyer, L.; Krogias, C.; Puetz, V.; Thierfelder, K. M.; Duering, M.; Lukas, C.; Kaiser, D.; Langner, S.; Brehm, A.; Rotkopf, L. T.; Kunz, W. G.; Beuker, C.; Heindel, W.; Fiehler, J.; Schramm, P.; Wiendl, H.; Minnerup, H.; Psychogios, M. N.; and Minnerup, J.\n\n\n \n\n\n\n Front Neurol, 14: 1320620. 2023.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{sporns_computed_2023,\n\ttitle = {Computed tomography hypoperfusion-hypodensity mismatch vs. automated perfusion mismatch to identify stroke patients eligible for thrombolysis},\n\tvolume = {14},\n\tissn = {1664-2295},\n\tdoi = {10.3389/fneur.2023.1320620},\n\tabstract = {BACKGROUND AND PURPOSE: Automated perfusion imaging can detect stroke patients with unknown time of symptom onset who are eligible for thrombolysis. However, the availability of this technique is limited. We, therefore, established the novel concept of computed tomography (CT) hypoperfusion-hypodensity mismatch, i.e., an ischemic core lesion visible on cerebral perfusion CT without visible hypodensity in the corresponding native cerebral CT. We compared both methods regarding their accuracy in identifying patients suitable for thrombolysis.\nMETHODS: In a retrospective analysis of the MissPerfeCT observational cohort study, patients were classified as suitable or not for thrombolysis based on established time window and imaging criteria. We calculated predictive values for hypoperfusion-hypodensity mismatch and automated perfusion imaging to compare accuracy in the identification of patients suitable for thrombolysis.\nRESULTS: Of 247 patients, 219 (88.7\\%) were eligible for thrombolysis and 28 (11.3\\%) were not eligible for thrombolysis. Of 197 patients who were within 4.5 h of symptom onset, 190 (96.4\\%) were identified by hypoperfusion-hypodensity mismatch and 88 (44.7\\%) by automated perfusion mismatch (p {\\textless} 0.001). Of 22 patients who were beyond 4.5 h of symptom onset but were eligible for thrombolysis, 5 patients (22.7\\%) were identified by hypoperfusion-hypodensity mismatch. Predictive values for the hypoperfusion-hypodensity mismatch vs. automated perfusion mismatch were as follows: sensitivity, 89.0\\% vs. 50.2\\%; specificity, 71.4\\% vs. 100.0\\%; positive predictive value, 96.1\\% vs. 100.0\\%; and negative predictive value, 45.5\\% vs. 20.4\\%.\nCONCLUSION: The novel method of hypoperfusion-hypodensity mismatch can identify patients suitable for thrombolysis with higher sensitivity and lower specificity than established techniques. Using this simple method might therefore increase the proportion of patients treated with thrombolysis without the use of special automated software.The MissPerfeCT study is a retrospective observational multicenter cohort study and is registered with clinicaltrials.gov (NCT04277728).},\n\tlanguage = {eng},\n\tjournal = {Front Neurol},\n\tauthor = {Sporns, Peter B. and Kemmling, André and Meyer, Lennart and Krogias, Christos and Puetz, Volker and Thierfelder, Kolja M. and Duering, Marco and Lukas, Carsten and Kaiser, Daniel and Langner, Sönke and Brehm, Alex and Rotkopf, Lukas T. and Kunz, Wolfgang G. and Beuker, Carolin and Heindel, Walter and Fiehler, Jens and Schramm, Peter and Wiendl, Heinz and Minnerup, Heike and Psychogios, Marios Nikos and Minnerup, Jens},\n\tyear = {2023},\n\tpmid = {38225983},\n\tpmcid = {PMC10788186},\n\tkeywords = {stroke, computed tomography, thrombolysis, time window, unknown onset stroke},\n\tpages = {1320620},\n}\n\n

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\n BACKGROUND AND PURPOSE: Automated perfusion imaging can detect stroke patients with unknown time of symptom onset who are eligible for thrombolysis. However, the availability of this technique is limited. We, therefore, established the novel concept of computed tomography (CT) hypoperfusion-hypodensity mismatch, i.e., an ischemic core lesion visible on cerebral perfusion CT without visible hypodensity in the corresponding native cerebral CT. We compared both methods regarding their accuracy in identifying patients suitable for thrombolysis. METHODS: In a retrospective analysis of the MissPerfeCT observational cohort study, patients were classified as suitable or not for thrombolysis based on established time window and imaging criteria. We calculated predictive values for hypoperfusion-hypodensity mismatch and automated perfusion imaging to compare accuracy in the identification of patients suitable for thrombolysis. RESULTS: Of 247 patients, 219 (88.7%) were eligible for thrombolysis and 28 (11.3%) were not eligible for thrombolysis. Of 197 patients who were within 4.5 h of symptom onset, 190 (96.4%) were identified by hypoperfusion-hypodensity mismatch and 88 (44.7%) by automated perfusion mismatch (p \\textless 0.001). Of 22 patients who were beyond 4.5 h of symptom onset but were eligible for thrombolysis, 5 patients (22.7%) were identified by hypoperfusion-hypodensity mismatch. Predictive values for the hypoperfusion-hypodensity mismatch vs. automated perfusion mismatch were as follows: sensitivity, 89.0% vs. 50.2%; specificity, 71.4% vs. 100.0%; positive predictive value, 96.1% vs. 100.0%; and negative predictive value, 45.5% vs. 20.4%. CONCLUSION: The novel method of hypoperfusion-hypodensity mismatch can identify patients suitable for thrombolysis with higher sensitivity and lower specificity than established techniques. Using this simple method might therefore increase the proportion of patients treated with thrombolysis without the use of special automated software.The MissPerfeCT study is a retrospective observational multicenter cohort study and is registered with clinicaltrials.gov (NCT04277728).\n

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\n \n 2022\n \n \n (21)\n \n \n

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\n \n\n \n \n \n \n \n Performance evaluation of automated white matter hyperintensity segmentation algorithms in a multicenter cohort on cognitive impairment and dementia.\n \n \n \n\n\n \n Gaubert, M.; Dell'Orco, A.; Lange, C.; Garnier-Crussard, A.; Zimmermann, I.; Dyrba, M.; Duering, M.; Ziegler, G.; Peters, O.; Preis, L.; Priller, J.; Spruth, E. J.; Schneider, A.; Fliessbach, K.; Wiltfang, J.; Schott, B. H.; Maier, F.; Glanz, W.; Buerger, K.; Janowitz, D.; Perneczky, R.; Rauchmann, B.; Teipel, S.; Kilimann, I.; Laske, C.; Munk, M. H.; Spottke, A.; Roy, N.; Dobisch, L.; Ewers, M.; Dechent, P.; Haynes, J. D.; Scheffler, K.; Düzel, E.; Jessen, F.; Wirth, M.; and DELCODE study group\n\n\n \n\n\n\n Front Psychiatry, 13: 1010273. 2022.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{gaubert_performance_2022,\n\ttitle = {Performance evaluation of automated white matter hyperintensity segmentation algorithms in a multicenter cohort on cognitive impairment and dementia},\n\tvolume = {13},\n\tissn = {1664-0640},\n\tdoi = {10.3389/fpsyt.2022.1010273},\n\tabstract = {BACKGROUND: White matter hyperintensities (WMH), a biomarker of small vessel disease, are often found in Alzheimer's disease (AD) and their advanced detection and quantification can be beneficial for research and clinical applications. To investigate WMH in large-scale multicenter studies on cognitive impairment and AD, appropriate automated WMH segmentation algorithms are required. This study aimed to compare the performance of segmentation tools and provide information on their application in multicenter research.\nMETHODS: We used a pseudo-randomly selected dataset (n = 50) from the DZNE-multicenter observational Longitudinal Cognitive Impairment and Dementia Study (DELCODE) that included 3D fluid-attenuated inversion recovery (FLAIR) images from participants across the cognitive continuum. Performances of top-rated algorithms for automated WMH segmentation [Brain Intensity Abnormality Classification Algorithm (BIANCA), lesion segmentation toolbox (LST), lesion growth algorithm (LGA), LST lesion prediction algorithm (LPA), pgs, and sysu\\_media] were compared to manual reference segmentation (RS).\nRESULTS: Across tools, segmentation performance was moderate for global WMH volume and number of detected lesions. After retraining on a DELCODE subset, the deep learning algorithm sysu\\_media showed the highest performances with an average Dice's coefficient of 0.702 (±0.109 SD) for volume and a mean F1-score of 0.642 (±0.109 SD) for the number of lesions. The intra-class correlation was excellent for all algorithms ({\\textgreater}0.9) but BIANCA (0.835). Performance improved with high WMH burden and varied across brain regions.\nCONCLUSION: To conclude, the deep learning algorithm, when retrained, performed well in the multicenter context. Nevertheless, the performance was close to traditional methods. We provide methodological recommendations for future studies using automated WMH segmentation to quantify and assess WMH along the continuum of cognitive impairment and AD dementia.},\n\tlanguage = {eng},\n\tjournal = {Front Psychiatry},\n\tauthor = {Gaubert, Malo and Dell'Orco, Andrea and Lange, Catharina and Garnier-Crussard, Antoine and Zimmermann, Isabella and Dyrba, Martin and Duering, Marco and Ziegler, Gabriel and Peters, Oliver and Preis, Lukas and Priller, Josef and Spruth, Eike Jakob and Schneider, Anja and Fliessbach, Klaus and Wiltfang, Jens and Schott, Björn H. and Maier, Franziska and Glanz, Wenzel and Buerger, Katharina and Janowitz, Daniel and Perneczky, Robert and Rauchmann, Boris-Stephan and Teipel, Stefan and Kilimann, Ingo and Laske, Christoph and Munk, Matthias H. and Spottke, Annika and Roy, Nina and Dobisch, Laura and Ewers, Michael and Dechent, Peter and Haynes, John Dylan and Scheffler, Klaus and Düzel, Emrah and Jessen, Frank and Wirth, Miranka and {DELCODE study group}},\n\tyear = {2022},\n\tpmid = {36713907},\n\tpmcid = {PMC9877422},\n\tkeywords = {Alzheimer’s disease, aging, deep learning, evaluation, FLAIR, white matter hyperintensities segmentation},\n\tpages = {1010273},\n\tfile = {Full Text:/Users/mduering/Zotero/storage/VPTZWCH5/Gaubert et al. - 2022 - Performance evaluation of automated white matter h.pdf:application/pdf},\n}\n\n

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\n BACKGROUND: White matter hyperintensities (WMH), a biomarker of small vessel disease, are often found in Alzheimer's disease (AD) and their advanced detection and quantification can be beneficial for research and clinical applications. To investigate WMH in large-scale multicenter studies on cognitive impairment and AD, appropriate automated WMH segmentation algorithms are required. This study aimed to compare the performance of segmentation tools and provide information on their application in multicenter research. METHODS: We used a pseudo-randomly selected dataset (n = 50) from the DZNE-multicenter observational Longitudinal Cognitive Impairment and Dementia Study (DELCODE) that included 3D fluid-attenuated inversion recovery (FLAIR) images from participants across the cognitive continuum. Performances of top-rated algorithms for automated WMH segmentation [Brain Intensity Abnormality Classification Algorithm (BIANCA), lesion segmentation toolbox (LST), lesion growth algorithm (LGA), LST lesion prediction algorithm (LPA), pgs, and sysu_media] were compared to manual reference segmentation (RS). RESULTS: Across tools, segmentation performance was moderate for global WMH volume and number of detected lesions. After retraining on a DELCODE subset, the deep learning algorithm sysu_media showed the highest performances with an average Dice's coefficient of 0.702 (±0.109 SD) for volume and a mean F1-score of 0.642 (±0.109 SD) for the number of lesions. The intra-class correlation was excellent for all algorithms (\\textgreater0.9) but BIANCA (0.835). Performance improved with high WMH burden and varied across brain regions. CONCLUSION: To conclude, the deep learning algorithm, when retrained, performed well in the multicenter context. Nevertheless, the performance was close to traditional methods. We provide methodological recommendations for future studies using automated WMH segmentation to quantify and assess WMH along the continuum of cognitive impairment and AD dementia.\n

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\n \n\n \n \n \n \n \n Peak width of skeletonized mean diffusivity in cerebral amyloid angiopathy: Spatial signature, cognitive, and neuroimaging associations.\n \n \n \n\n\n \n Zanon Zotin, M. C.; Schoemaker, D.; Raposo, N.; Perosa, V.; Bretzner, M.; Sveikata, L.; Li, Q.; van Veluw, S. J.; Horn, M. J.; Etherton, M. R.; Charidimou, A.; Gurol, M. E.; Greenberg, S. M.; Duering, M.; Dos Santos, A. C.; Pontes-Neto, O. M.; and Viswanathan, A.\n\n\n \n\n\n\n Front Neurosci, 16: 1051038. 2022.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{zanon_zotin_peak_2022,\n\ttitle = {Peak width of skeletonized mean diffusivity in cerebral amyloid angiopathy: {Spatial} signature, cognitive, and neuroimaging associations},\n\tvolume = {16},\n\tissn = {1662-4548},\n\tshorttitle = {Peak width of skeletonized mean diffusivity in cerebral amyloid angiopathy},\n\tdoi = {10.3389/fnins.2022.1051038},\n\tabstract = {BACKGROUND: Peak width of skeletonized mean diffusivity (PSMD) is a promising diffusion tensor imaging (DTI) marker that shows consistent and strong cognitive associations in the context of different cerebral small vessel diseases (cSVD).\nPURPOSE: Investigate whether PSMD (1) is higher in patients with Cerebral Amyloid Angiopathy (CAA) than those with arteriolosclerosis; (2) can capture the anteroposterior distribution of CAA-related abnormalities; (3) shows similar neuroimaging and cognitive associations in comparison to other classical DTI markers, such as average mean diffusivity (MD) and fractional anisotropy (FA).\nMATERIALS AND METHODS: We analyzed cross-sectional neuroimaging and neuropsychological data from 90 non-demented memory-clinic subjects from a single center. Based on MRI findings, we classified them into probable-CAA (those that fulfilled the modified Boston criteria), subjects with MRI markers of cSVD not attributable to CAA (presumed arteriolosclerosis; cSVD), and subjects without evidence of cSVD on MRI (non-cSVD). We compared total and lobe-specific (frontal and occipital) DTI metrics values across the groups. We used linear regression models to investigate how PSMD, MD, and FA correlate with conventional neuroimaging markers of cSVD and cognitive scores in CAA.\nRESULTS: PSMD was comparable in probable-CAA (median 4.06 × 10-4 mm2/s) and cSVD (4.07 × 10-4 mm2/s) patients, but higher than in non-cSVD (3.30 × 10-4 mm2/s; p {\\textless} 0.001) subjects. Occipital-frontal PSMD gradients were higher in probable-CAA patients, and we observed a significant interaction between diagnosis and region on PSMD values [F(2, 87) = 3.887, p = 0.024]. PSMD was mainly associated with white matter hyperintensity volume, whereas MD and FA were also associated with other markers, especially with the burden of perivascular spaces. PSMD correlated with worse executive function (β = -0.581, p {\\textless} 0.001) and processing speed (β = -0.463, p = 0.003), explaining more variance than other MRI markers. MD and FA were not associated with performance in any cognitive domain.\nCONCLUSION: PSMD is a promising biomarker of cognitive impairment in CAA that outperforms other conventional and DTI-based neuroimaging markers. Although global PSMD is similarly increased in different forms of cSVD, PSMD's spatial variations could potentially provide insights into the predominant type of underlying microvascular pathology.},\n\tlanguage = {eng},\n\tjournal = {Front Neurosci},\n\tauthor = {Zanon Zotin, Maria Clara and Schoemaker, Dorothee and Raposo, Nicolas and Perosa, Valentina and Bretzner, Martin and Sveikata, Lukas and Li, Qi and van Veluw, Susanne J. and Horn, Mitchell J. and Etherton, Mark R. and Charidimou, Andreas and Gurol, M. Edip and Greenberg, Steven M. and Duering, Marco and Dos Santos, Antonio Carlos and Pontes-Neto, Octavio M. and Viswanathan, Anand},\n\tyear = {2022},\n\tpmid = {36440281},\n\tpmcid = {PMC9693722},\n\tkeywords = {dementia, cerebral small vessel disease, diffusion tensor imaging, cerebral amyloid angiopathy, vascular cognitive impairment, diffusion-weighted imaging},\n\tpages = {1051038},\n\tfile = {Full Text:/Users/mduering/Zotero/storage/9PACN2KX/Zanon Zotin et al. - 2022 - Peak width of skeletonized mean diffusivity in cer.pdf:application/pdf},\n}\n\n

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\n BACKGROUND: Peak width of skeletonized mean diffusivity (PSMD) is a promising diffusion tensor imaging (DTI) marker that shows consistent and strong cognitive associations in the context of different cerebral small vessel diseases (cSVD). PURPOSE: Investigate whether PSMD (1) is higher in patients with Cerebral Amyloid Angiopathy (CAA) than those with arteriolosclerosis; (2) can capture the anteroposterior distribution of CAA-related abnormalities; (3) shows similar neuroimaging and cognitive associations in comparison to other classical DTI markers, such as average mean diffusivity (MD) and fractional anisotropy (FA). MATERIALS AND METHODS: We analyzed cross-sectional neuroimaging and neuropsychological data from 90 non-demented memory-clinic subjects from a single center. Based on MRI findings, we classified them into probable-CAA (those that fulfilled the modified Boston criteria), subjects with MRI markers of cSVD not attributable to CAA (presumed arteriolosclerosis; cSVD), and subjects without evidence of cSVD on MRI (non-cSVD). We compared total and lobe-specific (frontal and occipital) DTI metrics values across the groups. We used linear regression models to investigate how PSMD, MD, and FA correlate with conventional neuroimaging markers of cSVD and cognitive scores in CAA. RESULTS: PSMD was comparable in probable-CAA (median 4.06 × 10-4 mm2/s) and cSVD (4.07 × 10-4 mm2/s) patients, but higher than in non-cSVD (3.30 × 10-4 mm2/s; p \\textless 0.001) subjects. Occipital-frontal PSMD gradients were higher in probable-CAA patients, and we observed a significant interaction between diagnosis and region on PSMD values [F(2, 87) = 3.887, p = 0.024]. PSMD was mainly associated with white matter hyperintensity volume, whereas MD and FA were also associated with other markers, especially with the burden of perivascular spaces. PSMD correlated with worse executive function (β = -0.581, p \\textless 0.001) and processing speed (β = -0.463, p = 0.003), explaining more variance than other MRI markers. MD and FA were not associated with performance in any cognitive domain. CONCLUSION: PSMD is a promising biomarker of cognitive impairment in CAA that outperforms other conventional and DTI-based neuroimaging markers. Although global PSMD is similarly increased in different forms of cSVD, PSMD's spatial variations could potentially provide insights into the predominant type of underlying microvascular pathology.\n

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\n \n\n \n \n \n \n \n Improved sensitivity and precision in multicentre diffusion MRI network analysis using thresholding and harmonization.\n \n \n \n\n\n \n de Brito Robalo, B. M.; de Luca, A.; Chen, C.; Dewenter, A.; Duering, M.; Hilal, S.; Koek, H. L.; Kopczak, A.; Lam, B. Y. K.; Leemans, A.; Mok, V.; Onkenhout, L. P.; van den Brink, H.; and Biessels, G. J.\n\n\n \n\n\n\n Neuroimage Clin, 36: 103217. 2022.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{de_brito_robalo_improved_2022,\n\ttitle = {Improved sensitivity and precision in multicentre diffusion {MRI} network analysis using thresholding and harmonization},\n\tvolume = {36},\n\tissn = {2213-1582},\n\tdoi = {10.1016/j.nicl.2022.103217},\n\tabstract = {PURPOSE: To investigate if network thresholding and raw data harmonization improve consistency of diffusion MRI (dMRI)-based brain networks while also increasing precision and sensitivity to detect disease effects in multicentre datasets.\nMETHODS: Brain networks were reconstructed from dMRI of five samples with cerebral small vessel disease (SVD; 629 patients, 166 controls), as a clinically relevant exemplar condition for studies on network integrity. We evaluated consistency of network architecture in age-matched controls, by calculating cross-site differences in connection probability and fractional anisotropy (FA). Subsequently we evaluated precision and sensitivity to disease effects by identifying connections with low FA in sporadic SVD patients relative to controls, using more severely affected patients with a pure form of genetically defined SVD as reference.\nRESULTS: In controls, thresholding and harmonization improved consistency of network architecture, minimizing cross-site differences in connection probability and FA. In patients relative to controls, thresholding improved precision to detect disrupted connections by removing false positive connections (precision, before: 0.09-0.19; after: 0.38-0.70). Before harmonization, sensitivity was low within individual sites, with few connections surviving multiple testing correction (k = 0-25 connections). Harmonization and pooling improved sensitivity (k = 38), while also achieving higher precision when combined with thresholding (0.97).\nCONCLUSION: We demonstrated that network consistency, precision and sensitivity to detect disease effects in SVD are improved by thresholding and harmonization. We recommend introducing these techniques to leverage large existing multicentre datasets to better understand the impact of disease on brain networks.},\n\tlanguage = {eng},\n\tjournal = {Neuroimage Clin},\n\tauthor = {de Brito Robalo, Bruno M. and de Luca, Alberto and Chen, Christopher and Dewenter, Anna and Duering, Marco and Hilal, Saima and Koek, Huiberdina L. and Kopczak, Anna and Lam, Bonnie Yin Ka and Leemans, Alexander and Mok, Vincent and Onkenhout, Laurien P. and van den Brink, Hilde and Biessels, Geert Jan},\n\tyear = {2022},\n\tpmid = {36240537},\n\tpmcid = {PMC9668636},\n\tkeywords = {Diffusion Magnetic Resonance Imaging, Diffusion Tensor Imaging, Humans, Brain, White Matter, Cerebral Small Vessel Diseases, White matter, Neural Pathways, Connectivity, Diffusion MRI, Harmonization: cerebral small vessel disease, Thresholding},\n\tpages = {103217},\n\tfile = {Full Text:/Users/mduering/Zotero/storage/WY32Z3P4/de Brito Robalo et al. - 2022 - Improved sensitivity and precision in multicentre .pdf:application/pdf},\n}\n\n

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\n \n\n \n \n \n \n \n Simplified Assessment of Lesion Water Uptake for Identification of Patients within 4.5 Hours of Stroke Onset: An Analysis of the MissPerfeCT Study.\n \n \n \n\n\n \n Sporns, P. B.; Höhne, M.; Meyer, L.; Krogias, C.; Puetz, V.; Thierfelder, K. M.; Duering, M.; Kaiser, D.; Langner, S.; Brehm, A.; Rotkopf, L. T.; Kunz, W. G.; Fiehler, J.; Heindel, W.; Schramm, P.; Wiendl, H.; Minnerup, H.; Psychogios, M. N.; Kemmling, A.; and Minnerup, J.\n\n\n \n\n\n\n J Stroke, 24(3): 390–395. September 2022.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n\n\n\n

@article{sporns_simplified_2022,\n\ttitle = {Simplified {Assessment} of {Lesion} {Water} {Uptake} for {Identification} of {Patients} within 4.5 {Hours} of {Stroke} {Onset}: {An} {Analysis} of the {MissPerfeCT} {Study}},\n\tvolume = {24},\n\tissn = {2287-6391},\n\tshorttitle = {Simplified {Assessment} of {Lesion} {Water} {Uptake} for {Identification} of {Patients} within 4.5 {Hours} of {Stroke} {Onset}},\n\tdoi = {10.5853/jos.2022.00220},\n\tabstract = {BACKGROUND AND PURPOSE: Many patients with stroke cannot receive intravenous thrombolysis because the time of symptom onset is unknown. We tested whether a simple method of computed tomography (CT)-based quantification of water uptake in the ischemic tissue can identify patients with stroke onset within 4.5 hours.\nMETHODS: This retrospective analysis of the MissPerfeCT study (August 2009 to November 2017) includes consecutive patients with known onset of symptoms from seven tertiary stroke centers. We developed a simplified algorithm based on region of interest (ROI) measurements to quantify water uptake of the ischemic lesion and thereby quantify time of symptom onset within and beyond 4.5 hours. Perfusion CT was used to identify ischemic brain tissue, and its density was measured in non-contrast CT and related to the density of the corresponding area of the contralateral hemisphere to quantify lesion water uptake.\nRESULTS: Of 263 patients, 204 (77.6\\%) had CT within 4.5 hours. Water uptake was significantly lower in patients with stroke onset within (6.7\\%; 95\\% confidence interval [CI], 6.0\\% to 7.4\\%) compared to beyond 4.5 hours (12.7\\%; 95\\% CI, 10.7\\% to 14.7\\%). The area under the curve for distinguishing these patient groups according to percentage water uptake was 0.744 with an optimal cut-off value of 9.5\\%. According to this cut-off the positive predictive value was 88.8\\%, sensitivity was 73.5\\%, specificity 67.8\\%, negative predictive value was 42.6\\%.\nCONCLUSIONS: Ischemic stroke patients with unknown time of symptom onset can be identified as being within a timeframe of 4.5 hours using a ROI-based method to assess water uptake on admission non-contrast head CT.},\n\tlanguage = {eng},\n\tnumber = {3},\n\tjournal = {J Stroke},\n\tauthor = {Sporns, Peter B. and Höhne, Marco and Meyer, Lennart and Krogias, Christos and Puetz, Volker and Thierfelder, Kolja M. and Duering, Marco and Kaiser, Daniel and Langner, Sönke and Brehm, Alex and Rotkopf, Lukas T. and Kunz, Wolfgang G. and Fiehler, Jens and Heindel, Walter and Schramm, Peter and Wiendl, Heinz and Minnerup, Heike and Psychogios, Marios Nikos and Kemmling, André and Minnerup, Jens},\n\tmonth = sep,\n\tyear = {2022},\n\tpmid = {36221942},\n\tpmcid = {PMC9561216},\n\tkeywords = {Stroke, Ischemic stroke, Brain ischemia},\n\tpages = {390--395},\n\tfile = {Full Text:/Users/mduering/Zotero/storage/7PEVLAQI/Sporns et al. - 2022 - Simplified Assessment of Lesion Water Uptake for I.pdf:application/pdf},\n}\n\n

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\n \n\n \n \n \n \n \n Spatial Relation Between White Matter Hyperintensities and Incident Lacunes of Presumed Vascular Origin: A 14-Year Follow-Up Study.\n \n \n \n\n\n \n Yi, F.; Cai, M.; Jacob, M. A.; Marques, J.; Norris, D. G.; Duering, M.; Tuladhar, A. M.; and de Leeuw, F.\n\n\n \n\n\n\n Stroke, 53(12): 3688–3695. December 2022.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{yi_spatial_2022,\n\ttitle = {Spatial {Relation} {Between} {White} {Matter} {Hyperintensities} and {Incident} {Lacunes} of {Presumed} {Vascular} {Origin}: {A} 14-{Year} {Follow}-{Up} {Study}},\n\tvolume = {53},\n\tissn = {1524-4628},\n\tshorttitle = {Spatial {Relation} {Between} {White} {Matter} {Hyperintensities} and {Incident} {Lacunes} of {Presumed} {Vascular} {Origin}},\n\tdoi = {10.1161/STROKEAHA.122.039903},\n\tabstract = {BACKGROUND: The underlying mechanisms of incident lacunes regarding their spatial distribution remain largely unknown. We investigated the spatial distribution pattern and MRI predictors of incident lacunes in relation to white matter hyperintensity (WMH) over 14 years follow-up in sporadic small vessel disease.\nMETHODS: Five hundred three participants from the ongoing prospective single-center Radboud University Nijmegen Diffusion Tensor and Magnetic resonance Cohort (RUN DMC) were recruited with baseline assessment in 2006 and follow ups in 2011, 2015, and 2020. Three hundred eighty-two participants who underwent at least 2 available brain MRI scans were included. Incident lacunes were systematically identified, and the spatial relationship between incident lacunes located in subcortical white matter and WMH were determined using a visual rating scale. Adjusted multiple logistic regression and linear mixed-effect regression models were used to assess the association between baseline small vessel disease markers, WMH progression, and incident lacunes. Participants with atrial fibrillation were excluded in multivariable analysis.\nRESULTS: Eighty incident lacunes were identified in 43 patients (mean age 66.5±8.2 years, 37.2\\% women) during a mean follow-up time of 11.2±3.3 years (incidence rate 10.0/1000 person-year). Sixty percent of incident lacunes were in the white matter, of which 48.9\\% showed no contact with preexisting WMH. Baseline WMH volume (odds ratio=2.5 [95\\% CI, 1.6-4.2]) predicted incident lacunes after adjustment for age, sex, and vascular risk factors. WMH progression was associated with incident lacunes independent of age, sex, baseline WMH volume, and vascular risk factors (odds ratio, 3.2 [95\\% CI, 1.5-6.9]). Baseline WMH volume and progression rate were higher in participants with incident lacunes in contact with preexisting WMH. No difference in vascular risk factors was observed regarding location or relation with preexisting WMH.\nCONCLUSIONS: The 2 different distribution patterns of lacunes regarding their relation to WMH may suggest distinct underlying mechanisms, one of which may be more closely linked to a similar pathophysiology as that of WMH. The longitudinal relation between WMH and lacunes further supports plausible shared mechanisms between the 2 key markers.},\n\tlanguage = {eng},\n\tnumber = {12},\n\tjournal = {Stroke},\n\tauthor = {Yi, Fang and Cai, Mengfei and Jacob, Mina A. and Marques, José and Norris, David G. and Duering, Marco and Tuladhar, Anil M. and de Leeuw, Frank-Erik},\n\tmonth = dec,\n\tyear = {2022},\n\tpmid = {36189679},\n\tpmcid = {PMC9698104},\n\tkeywords = {small vessel disease, Aged, Female, Humans, Male, Middle Aged, Prospective Studies, Follow-Up Studies, Magnetic Resonance Imaging, white matter hyperintensities, magnetic resonance imaging, White Matter, Cerebral Small Vessel Diseases, Leukoaraiosis, incident lacunes, spatial distribution},\n\tpages = {3688--3695},\n\tfile = {Full Text:/Users/mduering/Zotero/storage/E6C97ZU8/Yi et al. - 2022 - Spatial Relation Between White Matter Hyperintensi.pdf:application/pdf},\n}\n\n

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\n BACKGROUND: The underlying mechanisms of incident lacunes regarding their spatial distribution remain largely unknown. We investigated the spatial distribution pattern and MRI predictors of incident lacunes in relation to white matter hyperintensity (WMH) over 14 years follow-up in sporadic small vessel disease. METHODS: Five hundred three participants from the ongoing prospective single-center Radboud University Nijmegen Diffusion Tensor and Magnetic resonance Cohort (RUN DMC) were recruited with baseline assessment in 2006 and follow ups in 2011, 2015, and 2020. Three hundred eighty-two participants who underwent at least 2 available brain MRI scans were included. Incident lacunes were systematically identified, and the spatial relationship between incident lacunes located in subcortical white matter and WMH were determined using a visual rating scale. Adjusted multiple logistic regression and linear mixed-effect regression models were used to assess the association between baseline small vessel disease markers, WMH progression, and incident lacunes. Participants with atrial fibrillation were excluded in multivariable analysis. RESULTS: Eighty incident lacunes were identified in 43 patients (mean age 66.5±8.2 years, 37.2% women) during a mean follow-up time of 11.2±3.3 years (incidence rate 10.0/1000 person-year). Sixty percent of incident lacunes were in the white matter, of which 48.9% showed no contact with preexisting WMH. Baseline WMH volume (odds ratio=2.5 [95% CI, 1.6-4.2]) predicted incident lacunes after adjustment for age, sex, and vascular risk factors. WMH progression was associated with incident lacunes independent of age, sex, baseline WMH volume, and vascular risk factors (odds ratio, 3.2 [95% CI, 1.5-6.9]). Baseline WMH volume and progression rate were higher in participants with incident lacunes in contact with preexisting WMH. No difference in vascular risk factors was observed regarding location or relation with preexisting WMH. CONCLUSIONS: The 2 different distribution patterns of lacunes regarding their relation to WMH may suggest distinct underlying mechanisms, one of which may be more closely linked to a similar pathophysiology as that of WMH. The longitudinal relation between WMH and lacunes further supports plausible shared mechanisms between the 2 key markers.\n

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\n \n\n \n \n \n \n \n Framework for Clinical Trials in Cerebral Small Vessel Disease (FINESSE): A Review.\n \n \n \n\n\n \n Markus, H. S.; van Der Flier, W. M.; Smith, E. E.; Bath, P.; Biessels, G. J.; Briceno, E.; Brodtman, A.; Chabriat, H.; Chen, C.; de Leeuw, F.; Egle, M.; Ganesh, A.; Georgakis, M. K.; Gottesman, R. F.; Kwon, S.; Launer, L.; Mok, V.; O'Brien, J.; Ottenhoff, L.; Pendlebury, S.; Richard, E.; Sachdev, P.; Schmidt, R.; Springer, M.; Tiedt, S.; Wardlaw, J. M.; Verdelho, A.; Webb, A.; Werring, D.; Duering, M.; Levine, D.; and Dichgans, M.\n\n\n \n\n\n\n JAMA Neurol, 79(11): 1187–1198. November 2022.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{markus_framework_2022,\n\ttitle = {Framework for {Clinical} {Trials} in {Cerebral} {Small} {Vessel} {Disease} ({FINESSE}): {A} {Review}},\n\tvolume = {79},\n\tissn = {2168-6157},\n\tshorttitle = {Framework for {Clinical} {Trials} in {Cerebral} {Small} {Vessel} {Disease} ({FINESSE})},\n\tdoi = {10.1001/jamaneurol.2022.2262},\n\tabstract = {IMPORTANCE: Cerebral small vessel disease (SVD) causes a quarter of strokes and is the most common pathology underlying vascular cognitive impairment and dementia. An important step to developing new treatments is better trial methodology. Disease mechanisms in SVD differ from other stroke etiologies; therefore, treatments need to be evaluated in cohorts in which SVD has been well characterized. Furthermore, SVD itself can be caused by a number of different pathologies, the most common of which are arteriosclerosis and cerebral amyloid angiopathy. To date, there have been few sufficiently powered high-quality randomized clinical trials in SVD, and inconsistent trial methodology has made interpretation of some findings difficult.\nOBSERVATIONS: To address these issues and develop guidelines for optimizing design of clinical trials in SVD, the Framework for Clinical Trials in Cerebral Small Vessel Disease (FINESSE) was created under the auspices of the International Society of Vascular Behavioral and Cognitive Disorders. Experts in relevant aspects of SVD trial methodology were convened, and a structured Delphi consensus process was used to develop recommendations. Areas in which recommendations were developed included optimal choice of study populations, choice of clinical end points, use of brain imaging as a surrogate outcome measure, use of circulating biomarkers for participant selection and as surrogate markers, novel trial designs, and prioritization of therapeutic agents using genetic data via Mendelian randomization.\nCONCLUSIONS AND RELEVANCE: The FINESSE provides recommendations for trial design in SVD for which there are currently few effective treatments. However, new insights into understanding disease pathogenesis, particularly from recent genetic studies, provide novel pathways that could be therapeutically targeted. In addition, whether other currently available cardiovascular interventions are specifically effective in SVD, as opposed to other subtypes of stroke, remains uncertain. FINESSE provides a framework for design of trials examining such therapeutic approaches.},\n\tlanguage = {eng},\n\tnumber = {11},\n\tjournal = {JAMA Neurol},\n\tauthor = {Markus, Hugh S. and van Der Flier, Wiesje M. and Smith, Eric E. and Bath, Philip and Biessels, Geert Jan and Briceno, Emily and Brodtman, Amy and Chabriat, Hugues and Chen, Christopher and de Leeuw, Frank-Erik and Egle, Marco and Ganesh, Aravind and Georgakis, Marios K. and Gottesman, Rebecca F. and Kwon, Sun and Launer, Lenore and Mok, Vincent and O'Brien, John and Ottenhoff, Lois and Pendlebury, Sarah and Richard, Edo and Sachdev, Perminder and Schmidt, Reinhold and Springer, Melanie and Tiedt, Stefan and Wardlaw, Joanna M. and Verdelho, Ana and Webb, Alastair and Werring, David and Duering, Marco and Levine, Deborah and Dichgans, Martin},\n\tmonth = nov,\n\tyear = {2022},\n\tpmid = {35969390},\n\tkeywords = {Stroke, Humans, Magnetic Resonance Imaging, Brain, Cerebral Amyloid Angiopathy, Cerebral Small Vessel Diseases, biosketch},\n\tpages = {1187--1198},\n}\n\n

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\n IMPORTANCE: Cerebral small vessel disease (SVD) causes a quarter of strokes and is the most common pathology underlying vascular cognitive impairment and dementia. An important step to developing new treatments is better trial methodology. Disease mechanisms in SVD differ from other stroke etiologies; therefore, treatments need to be evaluated in cohorts in which SVD has been well characterized. Furthermore, SVD itself can be caused by a number of different pathologies, the most common of which are arteriosclerosis and cerebral amyloid angiopathy. To date, there have been few sufficiently powered high-quality randomized clinical trials in SVD, and inconsistent trial methodology has made interpretation of some findings difficult. OBSERVATIONS: To address these issues and develop guidelines for optimizing design of clinical trials in SVD, the Framework for Clinical Trials in Cerebral Small Vessel Disease (FINESSE) was created under the auspices of the International Society of Vascular Behavioral and Cognitive Disorders. Experts in relevant aspects of SVD trial methodology were convened, and a structured Delphi consensus process was used to develop recommendations. Areas in which recommendations were developed included optimal choice of study populations, choice of clinical end points, use of brain imaging as a surrogate outcome measure, use of circulating biomarkers for participant selection and as surrogate markers, novel trial designs, and prioritization of therapeutic agents using genetic data via Mendelian randomization. CONCLUSIONS AND RELEVANCE: The FINESSE provides recommendations for trial design in SVD for which there are currently few effective treatments. However, new insights into understanding disease pathogenesis, particularly from recent genetic studies, provide novel pathways that could be therapeutically targeted. In addition, whether other currently available cardiovascular interventions are specifically effective in SVD, as opposed to other subtypes of stroke, remains uncertain. FINESSE provides a framework for design of trials examining such therapeutic approaches.\n

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\n \n\n \n \n \n \n \n Determining the OPTIMAL DTI analysis method for application in cerebral small vessel disease.\n \n \n \n\n\n \n Egle, M.; Hilal, S.; Tuladhar, A. M.; Pirpamer, L.; Bell, S.; Hofer, E.; Duering, M.; Wason, J.; Morris, R. G.; Dichgans, M.; Schmidt, R.; Tozer, D. J.; Barrick, T. R.; Chen, C.; de Leeuw, F.; and Markus, H. S.\n\n\n \n\n\n\n Neuroimage Clin, 35: 103114. 2022.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{egle_determining_2022,\n\ttitle = {Determining the {OPTIMAL} {DTI} analysis method for application in cerebral small vessel disease},\n\tvolume = {35},\n\tissn = {2213-1582},\n\tdoi = {10.1016/j.nicl.2022.103114},\n\tabstract = {BACKGROUND: DTI is sensitive to white matter (WM) microstructural damage and has been suggested as a surrogate marker for phase 2 clinical trials in cerebral small vessel disease (SVD). The study's objective is to establish the best way to analyse the diffusion-weighted imaging data in SVD for this purpose. The ideal method would be sensitive to change and predict dementia conversion, but also straightforward to implement and ideally automated. As part of the OPTIMAL collaboration, we evaluated five different DTI analysis strategies across six different cohorts with differing SVD severity.\nMETHODS: Those 5 strategies were: (1) conventional mean diffusivity WM histogram measure (MD median), (2) a principal component-derived measure based on conventional WM histogram measures (PC1), (3) peak width skeletonized mean diffusivity (PSMD), (4) diffusion tensor image segmentation θ (DSEG θ) and (5) a WM measure of global network efficiency (Geff). The association between each measure and cognitive function was tested using a linear regression model adjusted by clinical markers. Changes in the imaging measures over time were determined. In three cohort studies, repeated imaging data together with data on incident dementia were available. The association between the baseline measure, change measure and incident dementia conversion was examined using Cox proportional-hazard regression or logistic regression models. Sample size estimates for a hypothetical clinical trial were furthermore computed for each DTI analysis strategy.\nRESULTS: There was a consistent cross-sectional association between the imaging measures and impaired cognitive function across all cohorts. All baseline measures predicted dementia conversion in severe SVD. In mild SVD, PC1, PSMD and Geff predicted dementia conversion. In MCI, all markers except Geff predicted dementia conversion. Baseline DTI was significantly different in patients converting to vascular dementia than to Alzheimer' s disease. Significant change in all measures was associated with dementia conversion in severe but not in mild SVD. The automatic and semi-automatic measures PSMD and DSEG θ required the lowest minimum sample sizes for a hypothetical clinical trial in single-centre sporadic SVD cohorts.\nCONCLUSION: DTI parameters obtained from all analysis methods predicted dementia, and there was no clear winner amongst the different analysis strategies. The fully automated analysis provided by PSMD offers advantages particularly for large datasets.},\n\tlanguage = {eng},\n\tjournal = {Neuroimage Clin},\n\tauthor = {Egle, Marco and Hilal, Saima and Tuladhar, Anil M. and Pirpamer, Lukas and Bell, Steven and Hofer, Edith and Duering, Marco and Wason, James and Morris, Robin G. and Dichgans, Martin and Schmidt, Reinhold and Tozer, Daniel J. and Barrick, Thomas R. and Chen, Christopher and de Leeuw, Frank-Erik and Markus, Hugh S.},\n\tyear = {2022},\n\tpmid = {35908307},\n\tpmcid = {PMC9421487},\n\tkeywords = {Cognition, Small vessel disease, Diffusion Tensor Imaging, Humans, Biomarkers, Dementia, Diffusion tensor imaging, Cross-Sectional Studies, White Matter, Cerebral Small Vessel Diseases, Surrogate marker},\n\tpages = {103114},\n\tfile = {Full Text:/Users/mduering/Zotero/storage/GBPX24QK/Egle et al. - 2022 - Determining the OPTIMAL DTI analysis method for ap.pdf:application/pdf},\n}\n\n

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\n BACKGROUND: DTI is sensitive to white matter (WM) microstructural damage and has been suggested as a surrogate marker for phase 2 clinical trials in cerebral small vessel disease (SVD). The study's objective is to establish the best way to analyse the diffusion-weighted imaging data in SVD for this purpose. The ideal method would be sensitive to change and predict dementia conversion, but also straightforward to implement and ideally automated. As part of the OPTIMAL collaboration, we evaluated five different DTI analysis strategies across six different cohorts with differing SVD severity. METHODS: Those 5 strategies were: (1) conventional mean diffusivity WM histogram measure (MD median), (2) a principal component-derived measure based on conventional WM histogram measures (PC1), (3) peak width skeletonized mean diffusivity (PSMD), (4) diffusion tensor image segmentation θ (DSEG θ) and (5) a WM measure of global network efficiency (Geff). The association between each measure and cognitive function was tested using a linear regression model adjusted by clinical markers. Changes in the imaging measures over time were determined. In three cohort studies, repeated imaging data together with data on incident dementia were available. The association between the baseline measure, change measure and incident dementia conversion was examined using Cox proportional-hazard regression or logistic regression models. Sample size estimates for a hypothetical clinical trial were furthermore computed for each DTI analysis strategy. RESULTS: There was a consistent cross-sectional association between the imaging measures and impaired cognitive function across all cohorts. All baseline measures predicted dementia conversion in severe SVD. In mild SVD, PC1, PSMD and Geff predicted dementia conversion. In MCI, all markers except Geff predicted dementia conversion. Baseline DTI was significantly different in patients converting to vascular dementia than to Alzheimer' s disease. Significant change in all measures was associated with dementia conversion in severe but not in mild SVD. The automatic and semi-automatic measures PSMD and DSEG θ required the lowest minimum sample sizes for a hypothetical clinical trial in single-centre sporadic SVD cohorts. CONCLUSION: DTI parameters obtained from all analysis methods predicted dementia, and there was no clear winner amongst the different analysis strategies. The fully automated analysis provided by PSMD offers advantages particularly for large datasets.\n

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\n \n\n \n \n \n \n \n Texture Features of Magnetic Resonance Images Predict Poststroke Cognitive Impairment: Validation in a Multicenter Study.\n \n \n \n\n\n \n Betrouni, N.; Jiang, J.; Duering, M.; Georgakis, M. K.; Oestreich, L.; Sachdev, P. S.; O'Sullivan, M.; Wright, P.; Lo, J. W.; Bordet, R.; Stroke; and Collaboration, C. (.\n\n\n \n\n\n\n Stroke, 53(11): 3446–3454. November 2022.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{betrouni_texture_2022,\n\ttitle = {Texture {Features} of {Magnetic} {Resonance} {Images} {Predict} {Poststroke} {Cognitive} {Impairment}: {Validation} in a {Multicenter} {Study}},\n\tvolume = {53},\n\tissn = {1524-4628},\n\tshorttitle = {Texture {Features} of {Magnetic} {Resonance} {Images} {Predict} {Poststroke} {Cognitive} {Impairment}},\n\tdoi = {10.1161/STROKEAHA.122.039732},\n\tabstract = {BACKGROUND: Imaging features derived from T1-weighted (T1w) images texture analysis were shown to be potential markers of poststroke cognitive impairment, with better sensitivity than atrophy measurement. However, in magnetic resonance images, the signal distribution is subject to variations and can limit transferability of the method between centers. This study examined the reliability of texture features against imaging settings using data from different centers.\nMETHODS: Data were collected from 327 patients within the Stroke and Cognition Consortium from centers in France, Germany, Australia, and the United Kingdom. T1w images were preprocessed to normalize the signal intensities and then texture features, including first- and second-order statistics, were measured in the hippocampus and the entorhinal cortex. Differences between the data led to the use of 2 methods of analysis. First, a machine learning modeling, using random forest, was used to build a poststroke cognitive impairment prediction model using one dataset and this was validated on another dataset as external unseen data. Second, the predictive ability of the texture features was examined in the 2 remaining datasets by ANCOVA with false discovery rate correction for multiple comparisons.\nRESULTS: The prediction model had a mean accuracy of 90\\% for individual classification of patients in the learning base while for the validation base it was ≈ 77\\%. ANCOVA showed significant differences, in all datasets, for the kurtosis and inverse difference moment texture features when measured in patients with cognitive impairment and those without.\nCONCLUSIONS: These results suggest that texture features obtained from routine clinical MR images are robust early predictors of poststroke cognitive impairment and can be combined with other demographic and clinical predictors to build an accurate prediction model.},\n\tlanguage = {eng},\n\tnumber = {11},\n\tjournal = {Stroke},\n\tauthor = {Betrouni, Nacim and Jiang, Jiyang and Duering, Marco and Georgakis, Marios K. and Oestreich, Lena and Sachdev, Perminder S. and O'Sullivan, Michael and Wright, Paul and Lo, Jessica W. and Bordet, Régis and {Stroke and Cognition (STROKOG) Collaboration}},\n\tmonth = nov,\n\tyear = {2022},\n\tpmid = {35862196},\n\tkeywords = {Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Reproducibility of Results, machine learning, hippocampus, Cognitive Dysfunction, atrophy, demography, Machine Learning, magnetic resonance imagingx},\n\tpages = {3446--3454},\n\tfile = {Submitted Version:/Users/mduering/Zotero/storage/JEA538KU/Betrouni et al. - 2022 - Texture Features of Magnetic Resonance Images Pred.pdf:application/pdf},\n}\n\n

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\n \n\n \n \n \n \n \n Diffusion-Weighted Lesions After Intracerebral Hemorrhage: Associated MRI Findings.\n \n \n \n\n\n \n Wiegertjes, K.; Voigt, S.; Jolink, W. M. T.; Koemans, E. A.; Schreuder, F. H. B. M.; van Walderveen, M. A. A.; Wermer, M. J. H.; Meijer, F. J. A.; Duering, M.; de Leeuw, F.; and Klijn, C. J. M.\n\n\n \n\n\n\n Front Neurol, 13: 882070. 2022.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{wiegertjes_diffusion-weighted_2022,\n\ttitle = {Diffusion-{Weighted} {Lesions} {After} {Intracerebral} {Hemorrhage}: {Associated} {MRI} {Findings}},\n\tvolume = {13},\n\tissn = {1664-2295},\n\tshorttitle = {Diffusion-{Weighted} {Lesions} {After} {Intracerebral} {Hemorrhage}},\n\tdoi = {10.3389/fneur.2022.882070},\n\tabstract = {The current study aimed to investigate whether diffusion-weighted imaging-positive (DWI+) lesions after acute intracerebral hemorrhage (ICH) are associated with underlying small vessel disease (SVD) or linked to the acute ICH. We included patients ≥18 years with spontaneous ICH confirmed on neuroimaging and performed 3T MRIs after a median of 11 days (interquartile range [IQR] 6-43). DWI+ lesions were assessed in relation to the hematoma (perihematomal vs. distant and ipsilateral vs. contralateral). Differences in clinical characteristics, ICH characteristics, and MRI markers of SVD between participants with or without DWI+ lesions were investigated using non-parametric tests. We observed 54 DWI+ lesions in 30 (22\\%) of the 138 patients (median age [IQR] 65 [55-73] years; 71\\% men, 59 lobar ICH) with available DWI images. We found DWI+ lesions ipsilateral (54\\%) and contralateral (46\\%) to the ICH, and 5 (9\\%) DWI+ lesions were located in the immediate perihematomal region. DWI+ lesion presence was associated with probable CAA diagnosis (38 vs. 15\\%, p = 0.01) and larger ICH volumes (37 [8-47] vs. 12 [6-24] ml, p = 0.01), but not with imaging features of SVD. Our findings suggest that DWI+ lesions after ICH are a feature of both the underlying SVD and ICH-related mechanisms.},\n\tlanguage = {eng},\n\tjournal = {Front Neurol},\n\tauthor = {Wiegertjes, Kim and Voigt, Sabine and Jolink, Wilmar M. T. and Koemans, Emma A. and Schreuder, Floris H. B. M. and van Walderveen, Marianne A. A. and Wermer, Marieke J. H. and Meijer, Frederick J. A. and Duering, Marco and de Leeuw, Frank-Erik and Klijn, Catharina J. M.},\n\tyear = {2022},\n\tpmid = {35785361},\n\tpmcid = {PMC9240258},\n\tkeywords = {small vessel disease, cerebral amyloid angiopathy, intracerebral hemorrhage, magnetic resonance imaging, diffusion-weighted imaging},\n\tpages = {882070},\n\tfile = {Full Text:/Users/mduering/Zotero/storage/FMCG6P95/Wiegertjes et al. - 2022 - Diffusion-Weighted Lesions After Intracerebral Hem.pdf:application/pdf},\n}\n\n

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\n \n\n \n \n \n \n \n Increased Neurofilament Light Chain Is Associated with Increased Risk of Long-Term Mortality in Cerebral Small Vessel Disease.\n \n \n \n\n\n \n Jacob, M. A.; Peters, N.; Cai, M.; Duering, M.; Engelter, S. T.; Kuhle, J.; de Leeuw, F.; and Tuladhar, A. M.\n\n\n \n\n\n\n J Stroke, 24(2): 296–299. May 2022.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{jacob_increased_2022,\n\ttitle = {Increased {Neurofilament} {Light} {Chain} {Is} {Associated} with {Increased} {Risk} of {Long}-{Term} {Mortality} in {Cerebral} {Small} {Vessel} {Disease}},\n\tvolume = {24},\n\tissn = {2287-6391},\n\tdoi = {10.5853/jos.2021.04385},\n\tlanguage = {eng},\n\tnumber = {2},\n\tjournal = {J Stroke},\n\tauthor = {Jacob, Mina A. and Peters, Nils and Cai, Mengfei and Duering, Marco and Engelter, Stefan T. and Kuhle, Jens and de Leeuw, Frank-Erik and Tuladhar, Anil M.},\n\tmonth = may,\n\tyear = {2022},\n\tpmid = {35677985},\n\tpmcid = {PMC9194543},\n\tpages = {296--299},\n\tfile = {Full Text:/Users/mduering/Zotero/storage/DD5XWMR3/Jacob et al. - 2022 - Increased Neurofilament Light Chain Is Associated .pdf:application/pdf},\n}\n\n

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\n \n\n \n \n \n \n \n Prevalence and Significance of the Vessel-Cluster Sign on Susceptibility-Weighted Imaging in Patients With Severe Small Vessel Disease.\n \n \n \n\n\n \n Rudilosso, S.; Chui, E.; Stringer, M. S.; Thrippleton, M.; Chappell, F.; Blair, G.; GarcÃa, D. J.; Doubal, F.; Hamilton, I.; Kopczak, A.; Ingrish, M.; Kerkhofs, D.; Backes, W. H.; Staals, J.; van Oostenbrugge, R.; Duering, M.; Dichgans, M.; Wardlaw, J. M.; and SVDs@Target Investigators\n\n\n \n\n\n\n Neurology, 99(5): e440–452. May 2022.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{rudilosso_prevalence_2022,\n\ttitle = {Prevalence and {Significance} of the {Vessel}-{Cluster} {Sign} on {Susceptibility}-{Weighted} {Imaging} in {Patients} {With} {Severe} {Small} {Vessel} {Disease}},\n\tvolume = {99},\n\tissn = {1526-632X},\n\tdoi = {10.1212/WNL.0000000000200614},\n\tabstract = {BACKGROUND: Magnetic resonance susceptibility-weighted imaging (SWI) can identify small brain blood vessels that contain deoxygenated blood due to its induced magnetic field disturbance. We observed focal clusters of possible dilated small vessels on SWI in white matter in severe small vessel disease (SVD). We assessed their prevalence, associations with SVD lesions and vascular reactivity in patients with sporadic SVD and in patients with Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy (CADASIL).\nMETHODS: Secondary cross-sectional analysis of a prospective multicentre observational study of patients with either sporadic SVD or CADASIL (INVESTIGATE-SVD) studied with 3 Tesla MRI including blood-oxygen-level-dependent-MRI cerebrovascular reactivity (CVR). Two independent raters evaluated SWI sequences to identify "vessel-clusters" in white matter as focal low-signal dots/lines with small vessel appearance (interrater agreement, kappa statistic= 0.66). We assessed per-patient and per-cluster associations with SVD lesions type and severity on structural MRI sequences. We also assessed CVR within and at 2-voxel concentric intervals around the vessel-clusters using contralateral volumes as reference.\nRESULTS: Amongst the 77 patients enrolled, 76 had usable SWI sequences, 45 with sporadic SVD [mean age 64 years (SD 11), 26 males (58\\%)] and 31 with CADASIL [53 years (11), 15 males (48\\%)]. We identified 94 vessel-clusters in 36/76 patients (15/45 sporadic SVD, 21/31 CADASIL). In covariate-adjusted analysis, patients with vessel-clusters had more lacunes (OR, 95\\%CI) (1.30, 1.05-1.62), higher white matter hyperintensity (WMH) volume (per-log10 increase, 1.92, 1.04-3.56), lower CVR in normal appearing white matter (per \\%/mmHg, 0.77 (0.60-0.99), compared with patients without vessel-clusters. Fifty-seven of 94 vessel-clusters (61\\%) corresponded to non-cavitated or partially-cavitated WMH on Fluid Attenuated Inversion Recovery, and 37/94 (39\\%) to complete cavities. CVR magnitude was lower than in corresponding contralateral volumes [mean difference (SD), t, p] within vessel-cluster volumes [-0.00046 (0.00088), -3.021, 0.005) and in surrounding volume expansion shells up to 4 voxels [-0.00011 (0.00031), -2.140, 0.039; and -0.00010 (0.00027), -2.295, 0.028] in vessel-clusters with complete cavities, but not in vessel-clusters without complete cavitation.\nCONCLUSIONS: Vessel-clusters might correspond to maximally dilated vessels in white matter that are approaching complete tissue injury and cavitation. The pathophysiological significance of this new feature warrants further longitudinal investigation.},\n\tlanguage = {eng},\n\tnumber = {5},\n\tjournal = {Neurology},\n\tauthor = {Rudilosso, Salvatore and Chui, Ernest and Stringer, Michael S. and Thrippleton, Michael and Chappell, Francesca and Blair, Gordon and GarcÃa, Daniela Jaime and Doubal, Fergus and Hamilton, Iona and Kopczak, Anna and Ingrish, Michael and Kerkhofs, Danielle and Backes, Walter H. and Staals, Julie and van Oostenbrugge, Robert and Duering, Marco and Dichgans, Martin and Wardlaw, Joanna M. and {SVDs@Target Investigators}},\n\tmonth = may,\n\tyear = {2022},\n\tpmid = {35606147},\n\tpmcid = {PMC9421604},\n\tkeywords = {small vessel disease, lacunes, CADASIL, cerebrovascular reactivity, cavitation, susceptibility-weighted imaging, venules},\n\tpages = {e440--452},\n\tfile = {Full Text:/Users/mduering/Zotero/storage/ZEHGSRF7/Rudilosso et al. - 2022 - Prevalence and Significance of the Vessel-Cluster .pdf:application/pdf},\n}\n\n

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\n BACKGROUND: Magnetic resonance susceptibility-weighted imaging (SWI) can identify small brain blood vessels that contain deoxygenated blood due to its induced magnetic field disturbance. We observed focal clusters of possible dilated small vessels on SWI in white matter in severe small vessel disease (SVD). We assessed their prevalence, associations with SVD lesions and vascular reactivity in patients with sporadic SVD and in patients with Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy (CADASIL). METHODS: Secondary cross-sectional analysis of a prospective multicentre observational study of patients with either sporadic SVD or CADASIL (INVESTIGATE-SVD) studied with 3 Tesla MRI including blood-oxygen-level-dependent-MRI cerebrovascular reactivity (CVR). Two independent raters evaluated SWI sequences to identify \"vessel-clusters\" in white matter as focal low-signal dots/lines with small vessel appearance (interrater agreement, kappa statistic= 0.66). We assessed per-patient and per-cluster associations with SVD lesions type and severity on structural MRI sequences. We also assessed CVR within and at 2-voxel concentric intervals around the vessel-clusters using contralateral volumes as reference. RESULTS: Amongst the 77 patients enrolled, 76 had usable SWI sequences, 45 with sporadic SVD [mean age 64 years (SD 11), 26 males (58%)] and 31 with CADASIL [53 years (11), 15 males (48%)]. We identified 94 vessel-clusters in 36/76 patients (15/45 sporadic SVD, 21/31 CADASIL). In covariate-adjusted analysis, patients with vessel-clusters had more lacunes (OR, 95%CI) (1.30, 1.05-1.62), higher white matter hyperintensity (WMH) volume (per-log10 increase, 1.92, 1.04-3.56), lower CVR in normal appearing white matter (per %/mmHg, 0.77 (0.60-0.99), compared with patients without vessel-clusters. Fifty-seven of 94 vessel-clusters (61%) corresponded to non-cavitated or partially-cavitated WMH on Fluid Attenuated Inversion Recovery, and 37/94 (39%) to complete cavities. CVR magnitude was lower than in corresponding contralateral volumes [mean difference (SD), t, p] within vessel-cluster volumes [-0.00046 (0.00088), -3.021, 0.005) and in surrounding volume expansion shells up to 4 voxels [-0.00011 (0.00031), -2.140, 0.039; and -0.00010 (0.00027), -2.295, 0.028] in vessel-clusters with complete cavities, but not in vessel-clusters without complete cavitation. CONCLUSIONS: Vessel-clusters might correspond to maximally dilated vessels in white matter that are approaching complete tissue injury and cavitation. The pathophysiological significance of this new feature warrants further longitudinal investigation.\n

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\n \n\n \n \n \n \n \n Free water diffusion MRI and executive function with a speed component in healthy aging.\n \n \n \n\n\n \n Berger, M.; Pirpamer, L.; Hofer, E.; Ropele, S.; Duering, M.; Gesierich, B.; Pasternak, O.; Enzinger, C.; Schmidt, R.; and Koini, M.\n\n\n \n\n\n\n Neuroimage, 257: 119303. August 2022.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{berger_free_2022,\n\ttitle = {Free water diffusion {MRI} and executive function with a speed component in healthy aging},\n\tvolume = {257},\n\tissn = {1095-9572},\n\tdoi = {10.1016/j.neuroimage.2022.119303},\n\tabstract = {Extracellular free water (FW) increases are suggested to better provide pathophysiological information in brain aging than conventional biomarkers such as fractional anisotropy. The aim of the present study was to determine the relationship between conventional biomarkers, FW in white matter hyperintensities (WMH), FW in normal appearing white matter (NAWM) and in white matter tracts and executive functions (EF) with a speed component in elderly persons. We examined 226 healthy elderly participants (median age 69.83 years, IQR: 56.99-74.42) who underwent brain MRI and neuropsychological examination. FW in WMH and in NAWM as well as FW corrected diffusion metrics and measures derived from conventional MRI (white matter hyperintensities, brain volume, lacunes) were used in partial correlation (adjusted for age) to assess their correlation with EF with a speed component. Random forest analysis was used to assess the relative importance of these variables as determinants. Lastly, linear regression analyses of FW in white matter tracts corrected for risk factors of cognitive and white matter deterioration, were used to examine the role of specific tracts on EF with a speed component, which were then ranked with random forest regression. Partial correlation analyses revealed that almost all imaging metrics showed a significant association with EF with a speed component (r = -0.213 - 0.266). Random forest regression highlighted FW in WMH and in NAWM as most important among all diffusion and structural MRI metrics. The fornix (R2=0.421, p = 0.018) and the corpus callosum (genu (R2 = 0.418, p = 0.021), prefrontal (R2 = 0.416, p = 0.026), premotor (R2 = 0.418, p = 0.021)) were associated with EF with a speed component in tract based regression analyses and had highest variables importance. In a normal aging population FW in WMH and NAWM is more closely related to EF with a speed component than standard DTI and brain structural measures. Higher amounts of FW in the fornix and the frontal part of the corpus callosum leads to deteriorating EF with a speed component.},\n\tlanguage = {eng},\n\tjournal = {Neuroimage},\n\tauthor = {Berger, Martin and Pirpamer, Lukas and Hofer, Edith and Ropele, Stefan and Duering, Marco and Gesierich, Benno and Pasternak, Ofer and Enzinger, Christian and Schmidt, Reinhold and Koini, Marisa},\n\tmonth = aug,\n\tyear = {2022},\n\tpmid = {35568345},\n\tpmcid = {PMC9465649},\n\tkeywords = {Aged, Diffusion Magnetic Resonance Imaging, Diffusion Tensor Imaging, Humans, Biomarkers, Executive Function, Aging, White Matter, Water, Leukoaraiosis, Corpus callosum, Cognitive speed, Executive functions, Fornix, Free water diffusion, Healthy Aging},\n\tpages = {119303},\n\tfile = {Accepted Version:/Users/mduering/Zotero/storage/ULLVJC6J/Berger et al. - 2022 - Free water diffusion MRI and executive function wi.pdf:application/pdf},\n}\n\n

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\n Extracellular free water (FW) increases are suggested to better provide pathophysiological information in brain aging than conventional biomarkers such as fractional anisotropy. The aim of the present study was to determine the relationship between conventional biomarkers, FW in white matter hyperintensities (WMH), FW in normal appearing white matter (NAWM) and in white matter tracts and executive functions (EF) with a speed component in elderly persons. We examined 226 healthy elderly participants (median age 69.83 years, IQR: 56.99-74.42) who underwent brain MRI and neuropsychological examination. FW in WMH and in NAWM as well as FW corrected diffusion metrics and measures derived from conventional MRI (white matter hyperintensities, brain volume, lacunes) were used in partial correlation (adjusted for age) to assess their correlation with EF with a speed component. Random forest analysis was used to assess the relative importance of these variables as determinants. Lastly, linear regression analyses of FW in white matter tracts corrected for risk factors of cognitive and white matter deterioration, were used to examine the role of specific tracts on EF with a speed component, which were then ranked with random forest regression. Partial correlation analyses revealed that almost all imaging metrics showed a significant association with EF with a speed component (r = -0.213 - 0.266). Random forest regression highlighted FW in WMH and in NAWM as most important among all diffusion and structural MRI metrics. The fornix (R2=0.421, p = 0.018) and the corpus callosum (genu (R2 = 0.418, p = 0.021), prefrontal (R2 = 0.416, p = 0.026), premotor (R2 = 0.418, p = 0.021)) were associated with EF with a speed component in tract based regression analyses and had highest variables importance. In a normal aging population FW in WMH and NAWM is more closely related to EF with a speed component than standard DTI and brain structural measures. Higher amounts of FW in the fornix and the frontal part of the corpus callosum leads to deteriorating EF with a speed component.\n

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\n \n\n \n \n \n \n \n Determinants and Temporal Dynamics of Cerebral Small Vessel Disease: 14-Year Follow-Up.\n \n \n \n\n\n \n Cai, M.; Jacob, M. A.; van Loenen, M. R.; Bergkamp, M.; Marques, J.; Norris, D. G.; Duering, M.; Tuladhar, A. M.; and de Leeuw, F.\n\n\n \n\n\n\n Stroke, 53(9): 2789–2798. September 2022.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{cai_determinants_2022,\n\ttitle = {Determinants and {Temporal} {Dynamics} of {Cerebral} {Small} {Vessel} {Disease}: 14-{Year} {Follow}-{Up}},\n\tvolume = {53},\n\tissn = {1524-4628},\n\tshorttitle = {Determinants and {Temporal} {Dynamics} of {Cerebral} {Small} {Vessel} {Disease}},\n\tdoi = {10.1161/STROKEAHA.121.038099},\n\tabstract = {BACKGROUND: The aim of this study is to investigate the temporal dynamics of small vessel disease (SVD) and the effect of vascular risk factors and baseline SVD burden on progression of SVD with 4 neuroimaging assessments over 14 years in patients with SVD.\nMETHODS: Five hundred three patients with sporadic SVD (50-85 years) from the ongoing prospective cohort study (RUN DMC [Radboud University Nijmegen Diffusion Tensor and Magnetic Resonance Cohort]) underwent baseline assessment in 2006 and follow-up in 2011, 2015, and 2020. Vascular risk factors and magnetic resonance imaging markers of SVD were evaluated. Linear mixed-effects model and negative binomial regression model were used to examine the determinants of temporal dynamics of SVD markers.\nRESULTS: A total of 382 SVD patients (mean [SD] 64.1 [8.4]; 219 men and 163 women) who underwent at least 2 serial brain magnetic resonance imaging scans were included, with mean (SD) follow-up of 11.15 (3.32) years. We found a highly variable temporal course of SVD. Mean (SD) WMH progression rate was 0.6 (0.74) mL/y (range, 0.02-4.73 mL/y) and 13.6\\% of patients had incident lacunes (1.03\\%/y) over the 14-year follow-up. About 4\\% showed net WMH regression over 14 years, whereas 38 out of 361 (10.5\\%), 5 out of 296 (2\\%), and 61 out of 231 (26\\%) patients showed WMH regression for the intervals 2006 to 2011, 2011 to 2015, and 2015 to 2020, respectively. Of these, 29 (76\\%), 5 (100\\%), and 57 (93\\%) showed overall progression across the 14-year follow-up, and the net overall WMH change between first and last scan considering all participants was a net average WMH progression over the 14-year period. Older age was a strong predictor for faster WMH progression and incident lacunes. Patients with mild baseline WMH rarely progressed to severe WMH. In addition, both baseline burden of SVD lesions and vascular risk factors independently and synergistically predicted WMH progression, whereas only baseline SVD burden predicted incident lacunes over the 14-year follow-up.\nCONCLUSIONS: SVD shows pronounced progression over time, but mild WMH rarely progresses to clinically severe WMH. WMH regression is noteworthy during some magnetic resonance imaging intervals, although it could be overall compensated by progression over the long follow-up.},\n\tlanguage = {eng},\n\tnumber = {9},\n\tjournal = {Stroke},\n\tauthor = {Cai, Mengfei and Jacob, Mina A. and van Loenen, Mark R. and Bergkamp, Mayra and Marques, José and Norris, David G. and Duering, Marco and Tuladhar, Anil M. and de Leeuw, Frank-Erik},\n\tmonth = sep,\n\tyear = {2022},\n\tpmid = {35506383},\n\tpmcid = {PMC9389939},\n\tkeywords = {Disease Progression, Female, Humans, Male, cerebral small vessel disease, Prospective Studies, Neuroimaging, Follow-Up Studies, Magnetic Resonance Imaging, white matter hyperintensities, neuroimaging, magnetic resonance imaging, White Matter, Cerebral Small Vessel Diseases, risk factor},\n\tpages = {2789--2798},\n\tfile = {Full Text:/Users/mduering/Zotero/storage/MUC44M7T/Cai et al. - 2022 - Determinants and Temporal Dynamics of Cerebral Sma.pdf:application/pdf},\n}\n\n

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\n BACKGROUND: The aim of this study is to investigate the temporal dynamics of small vessel disease (SVD) and the effect of vascular risk factors and baseline SVD burden on progression of SVD with 4 neuroimaging assessments over 14 years in patients with SVD. METHODS: Five hundred three patients with sporadic SVD (50-85 years) from the ongoing prospective cohort study (RUN DMC [Radboud University Nijmegen Diffusion Tensor and Magnetic Resonance Cohort]) underwent baseline assessment in 2006 and follow-up in 2011, 2015, and 2020. Vascular risk factors and magnetic resonance imaging markers of SVD were evaluated. Linear mixed-effects model and negative binomial regression model were used to examine the determinants of temporal dynamics of SVD markers. RESULTS: A total of 382 SVD patients (mean [SD] 64.1 [8.4]; 219 men and 163 women) who underwent at least 2 serial brain magnetic resonance imaging scans were included, with mean (SD) follow-up of 11.15 (3.32) years. We found a highly variable temporal course of SVD. Mean (SD) WMH progression rate was 0.6 (0.74) mL/y (range, 0.02-4.73 mL/y) and 13.6% of patients had incident lacunes (1.03%/y) over the 14-year follow-up. About 4% showed net WMH regression over 14 years, whereas 38 out of 361 (10.5%), 5 out of 296 (2%), and 61 out of 231 (26%) patients showed WMH regression for the intervals 2006 to 2011, 2011 to 2015, and 2015 to 2020, respectively. Of these, 29 (76%), 5 (100%), and 57 (93%) showed overall progression across the 14-year follow-up, and the net overall WMH change between first and last scan considering all participants was a net average WMH progression over the 14-year period. Older age was a strong predictor for faster WMH progression and incident lacunes. Patients with mild baseline WMH rarely progressed to severe WMH. In addition, both baseline burden of SVD lesions and vascular risk factors independently and synergistically predicted WMH progression, whereas only baseline SVD burden predicted incident lacunes over the 14-year follow-up. CONCLUSIONS: SVD shows pronounced progression over time, but mild WMH rarely progresses to clinically severe WMH. WMH regression is noteworthy during some magnetic resonance imaging intervals, although it could be overall compensated by progression over the long follow-up.\n

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\n \n\n \n \n \n \n \n Post-Stroke Cognitive Impairment and Dementia.\n \n \n \n\n\n \n Rost, N. S.; Brodtmann, A.; Pase, M. P.; van Veluw, S. J.; Biffi, A.; Duering, M.; Hinman, J. D.; and Dichgans, M.\n\n\n \n\n\n\n Circ Res, 130(8): 1252–1271. April 2022.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{rost_post-stroke_2022,\n\ttitle = {Post-{Stroke} {Cognitive} {Impairment} and {Dementia}},\n\tvolume = {130},\n\tissn = {1524-4571},\n\tdoi = {10.1161/CIRCRESAHA.122.319951},\n\tabstract = {Poststroke cognitive impairment and dementia (PSCID) is a major source of morbidity and mortality after stroke worldwide. PSCID occurs as a consequence of ischemic stroke, intracerebral hemorrhage, or subarachnoid hemorrhage. Cognitive impairment and dementia manifesting after a clinical stroke is categorized as vascular even in people with comorbid neurodegenerative pathology, which is common in elderly individuals and can contribute to the clinical expression of PSCID. Manifestations of cerebral small vessel disease, such as covert brain infarcts, white matter lesions, microbleeds, and cortical microinfarcts, are also common in patients with stroke and likewise contribute to cognitive outcomes. Although studies of PSCID historically varied in the approach to timing and methods of diagnosis, most of them demonstrate that older age, lower educational status, socioeconomic disparities, premorbid cognitive or functional decline, life-course exposure to vascular risk factors, and a history of prior stroke increase risk of PSCID. Stroke characteristics, in particular stroke severity, lesion volume, lesion location, multiplicity and recurrence, also influence PSCID risk. Understanding the complex interaction between an acute stroke event and preexisting brain pathology remains a priority and will be critical for developing strategies for personalized prediction, prevention, targeted interventions, and rehabilitation. Current challenges in the field relate to a lack of harmonization of definition and classification of PSCID, timing of diagnosis, approaches to neurocognitive assessment, and duration of follow-up after stroke. However, evolving knowledge on pathophysiology, neuroimaging, and biomarkers offers potential for clinical applications and may inform clinical trials. Preventing stroke and PSCID remains a cornerstone of any strategy to achieve optimal brain health. We summarize recent developments in the field and discuss future directions closing with a call for action to systematically include cognitive outcome assessment into any clinical studies of poststroke outcome.},\n\tlanguage = {eng},\n\tnumber = {8},\n\tjournal = {Circ Res},\n\tauthor = {Rost, Natalia S. and Brodtmann, Amy and Pase, Matthew P. and van Veluw, Susanne J. and Biffi, Alessandro and Duering, Marco and Hinman, Jason D. and Dichgans, Martin},\n\tmonth = apr,\n\tyear = {2022},\n\tpmid = {35420911},\n\tkeywords = {Stroke, dementia, Aged, Humans, white matter, Magnetic Resonance Imaging, Dementia, cognitive dysfunction, Dementia, Vascular, Cerebral Hemorrhage, Cerebral Small Vessel Diseases, Cognitive Dysfunction, brain ischemia, cerebral hemorrhage, subarachnoid hemorrhage},\n\tpages = {1252--1271},\n}\n\n

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\n Poststroke cognitive impairment and dementia (PSCID) is a major source of morbidity and mortality after stroke worldwide. PSCID occurs as a consequence of ischemic stroke, intracerebral hemorrhage, or subarachnoid hemorrhage. Cognitive impairment and dementia manifesting after a clinical stroke is categorized as vascular even in people with comorbid neurodegenerative pathology, which is common in elderly individuals and can contribute to the clinical expression of PSCID. Manifestations of cerebral small vessel disease, such as covert brain infarcts, white matter lesions, microbleeds, and cortical microinfarcts, are also common in patients with stroke and likewise contribute to cognitive outcomes. Although studies of PSCID historically varied in the approach to timing and methods of diagnosis, most of them demonstrate that older age, lower educational status, socioeconomic disparities, premorbid cognitive or functional decline, life-course exposure to vascular risk factors, and a history of prior stroke increase risk of PSCID. Stroke characteristics, in particular stroke severity, lesion volume, lesion location, multiplicity and recurrence, also influence PSCID risk. Understanding the complex interaction between an acute stroke event and preexisting brain pathology remains a priority and will be critical for developing strategies for personalized prediction, prevention, targeted interventions, and rehabilitation. Current challenges in the field relate to a lack of harmonization of definition and classification of PSCID, timing of diagnosis, approaches to neurocognitive assessment, and duration of follow-up after stroke. However, evolving knowledge on pathophysiology, neuroimaging, and biomarkers offers potential for clinical applications and may inform clinical trials. Preventing stroke and PSCID remains a cornerstone of any strategy to achieve optimal brain health. We summarize recent developments in the field and discuss future directions closing with a call for action to systematically include cognitive outcome assessment into any clinical studies of poststroke outcome.\n

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\n \n\n \n \n \n \n \n Instrumental validation of free water, peak-width of skeletonized mean diffusivity, and white matter hyperintensities: MarkVCID neuroimaging kits.\n \n \n \n\n\n \n Maillard, P.; Lu, H.; Arfanakis, K.; Gold, B. T.; Bauer, C. E.; Zachariou, V.; Stables, L.; Wang, D. J. J.; Jann, K.; Seshadri, S.; Duering, M.; Hillmer, L. J.; Rosenberg, G. A.; Snoussi, H.; Sepehrband, F.; Habes, M.; Singh, B.; Kramer, J. H.; Corriveau, R. A.; Singh, H.; Schwab, K.; Helmer, K. G.; Greenberg, S. M.; Caprihan, A.; DeCarli, C.; Satizabal, C. L.; and MarkVCID Consortium\n\n\n \n\n\n\n Alzheimers Dement (Amst), 14(1): e12261. 2022.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{maillard_instrumental_2022,\n\ttitle = {Instrumental validation of free water, peak-width of skeletonized mean diffusivity, and white matter hyperintensities: {MarkVCID} neuroimaging kits},\n\tvolume = {14},\n\tissn = {2352-8729},\n\tshorttitle = {Instrumental validation of free water, peak-width of skeletonized mean diffusivity, and white matter hyperintensities},\n\tdoi = {10.1002/dad2.12261},\n\tabstract = {INTRODUCTION: To describe the protocol and findings of the instrumental validation of three imaging-based biomarker kits selected by the MarkVCID consortium: free water (FW) and peak width of skeletonized mean diffusivity (PSMD), both derived from diffusion tensor imaging (DTI), and white matter hyperintensity (WMH) volume derived from fluid attenuation inversion recovery and T1-weighted imaging.\nMETHODS: The instrumental validation of imaging-based biomarker kits included inter-rater reliability among participating sites, test-retest repeatability, and inter-scanner reproducibility across three types of magnetic resonance imaging (MRI) scanners using intra-class correlation coefficients (ICC).\nRESULTS: The three biomarkers demonstrated excellent inter-rater reliability (ICC {\\textgreater}0.94, P-values {\\textless} .001), very high agreement between test and retest sessions (ICC {\\textgreater}0.98, P-values {\\textless} .001), and were extremely consistent across the three scanners (ICC {\\textgreater}0.98, P-values {\\textless} .001).\nDISCUSSION: The three biomarker kits demonstrated very high inter-rater reliability, test-retest repeatability, and inter-scanner reproducibility, offering robust biomarkers suitable for future multi-site observational studies and clinical trials in the context of vascular cognitive impairment and dementia (VCID).},\n\tlanguage = {eng},\n\tnumber = {1},\n\tjournal = {Alzheimers Dement (Amst)},\n\tauthor = {Maillard, Pauline and Lu, Hanzhang and Arfanakis, Konstantinos and Gold, Brian T. and Bauer, Christopher E. and Zachariou, Valentinos and Stables, Lara and Wang, Danny J. J. and Jann, Kay and Seshadri, Sudha and Duering, Marco and Hillmer, Laura J. and Rosenberg, Gary A. and Snoussi, Haykel and Sepehrband, Farshid and Habes, Mohamad and Singh, Baljeet and Kramer, Joel H. and Corriveau, Roderick A. and Singh, Herpreet and Schwab, Kristin and Helmer, Karl G. and Greenberg, Steven M. and Caprihan, Arvind and DeCarli, Charles and Satizabal, Claudia L. and {MarkVCID Consortium}},\n\tyear = {2022},\n\tpmid = {35382232},\n\tpmcid = {PMC8959640},\n\tkeywords = {small vessel disease, diffusion tensor imaging, magnetic resonance imaging, biomarker, free water, peak‐width skeletonized mean diffusivity, vascular contributions to cognitive impairment and dementia, VCID, white matter hyperintensity, white matter injury},\n\tpages = {e12261},\n\tfile = {Full Text:/Users/mduering/Zotero/storage/DY7SW2SZ/Maillard et al. - 2022 - Instrumental validation of free water, peak-width .pdf:application/pdf},\n}\n\n

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\n \n\n \n \n \n \n \n White matter volume loss drives cortical reshaping after thalamic infarcts.\n \n \n \n\n\n \n Conrad, J.; Habs, M.; Ruehl, R. M.; Bögle, R.; Ertl, M.; Kirsch, V.; Eren, O. E.; Becker-Bense, S.; Stephan, T.; Wollenweber, F. A.; Duering, M.; Zu Eulenburg, P.; and Dieterich, M.\n\n\n \n\n\n\n Neuroimage Clin, 33: 102953. 2022.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{conrad_white_2022,\n\ttitle = {White matter volume loss drives cortical reshaping after thalamic infarcts},\n\tvolume = {33},\n\tissn = {2213-1582},\n\tdoi = {10.1016/j.nicl.2022.102953},\n\tabstract = {OBJECTIVE: The integration of somatosensory, ocular motor and vestibular signals is necessary for self-location in space and goal-directed action. We aimed to detect remote changes in the cerebral cortex after thalamic infarcts to reveal the thalamo-cortical connections necessary for multisensory processing and ocular motor control.\nMETHODS: Thirteen patients with unilateral ischemic thalamic infarcts presenting with vestibular, somatosensory, and ocular motor symptoms were examined longitudinally in the acute phase and after six months. Voxel- and surface-based morphometry were used to detect changes in vestibular and multisensory cortical areas and known hubs of central ocular motor processing. The results were compared with functional connectivity data in 50 healthy volunteers.\nRESULTS: Patients with paramedian infarcts showed impaired saccades and vestibular perception, i.e., tilts of the subjective visual vertical (SVV). The most common complaint in these patients was double vision or vertigo / dizziness. Posterolateral thalamic infarcts led to tilts of the SVV and somatosensory deficits without vertigo. Tilts of the SVV were higher in paramedian compared to posterolateral infarcts (median 11.2° vs 3.8°). Vestibular and ocular motor symptoms recovered within six months. Somatosensory deficits persisted. Structural longitudinal imaging showed significant volume reduction in subcortical structures connected to the infarcted thalamic nuclei (vestibular nuclei region, dentate nucleus region, trigeminal root entry zone, medial lemniscus, superior colliculi). Volume loss was evident in connections to the frontal, parietal and cingulate lobes. Changes were larger in the ipsilesional hemisphere but were also detected in homotopical regions contralesionally. The white matter volume reduction led to deformation of the cortical projection zones of the infarcted nuclei.\nCONCLUSIONS: White matter volume loss after thalamic infarcts reflects sensory input from the brainstem as well the cortical projections of the main affected nuclei for sensory and ocular motor processing. Changes in the cortical geometry seem not to reflect gray matter atrophy but rather reshaping of the cortical surface due to the underlying white matter atrophy.},\n\tlanguage = {eng},\n\tjournal = {Neuroimage Clin},\n\tauthor = {Conrad, Julian and Habs, Maximilian and Ruehl, Ria M. and Bögle, Rainer and Ertl, Matthias and Kirsch, Valerie and Eren, Ozan E. and Becker-Bense, Sandra and Stephan, Thomas and Wollenweber, Frank A. and Duering, Marco and Zu Eulenburg, Peter and Dieterich, Marianne},\n\tyear = {2022},\n\tpmid = {35139478},\n\tpmcid = {PMC8844789},\n\tkeywords = {Stroke, Vestibular, Humans, Vbm, White Matter, Cerebral Infarction, Cerebral Cortex, Thalamus, Ocular motor, Vestibule, Labyrinth},\n\tpages = {102953},\n\tfile = {Full Text:/Users/mduering/Zotero/storage/HVGAX7JB/Conrad et al. - 2022 - White matter volume loss drives cortical reshaping.pdf:application/pdf},\n}\n\n

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\n OBJECTIVE: The integration of somatosensory, ocular motor and vestibular signals is necessary for self-location in space and goal-directed action. We aimed to detect remote changes in the cerebral cortex after thalamic infarcts to reveal the thalamo-cortical connections necessary for multisensory processing and ocular motor control. METHODS: Thirteen patients with unilateral ischemic thalamic infarcts presenting with vestibular, somatosensory, and ocular motor symptoms were examined longitudinally in the acute phase and after six months. Voxel- and surface-based morphometry were used to detect changes in vestibular and multisensory cortical areas and known hubs of central ocular motor processing. The results were compared with functional connectivity data in 50 healthy volunteers. RESULTS: Patients with paramedian infarcts showed impaired saccades and vestibular perception, i.e., tilts of the subjective visual vertical (SVV). The most common complaint in these patients was double vision or vertigo / dizziness. Posterolateral thalamic infarcts led to tilts of the SVV and somatosensory deficits without vertigo. Tilts of the SVV were higher in paramedian compared to posterolateral infarcts (median 11.2° vs 3.8°). Vestibular and ocular motor symptoms recovered within six months. Somatosensory deficits persisted. Structural longitudinal imaging showed significant volume reduction in subcortical structures connected to the infarcted thalamic nuclei (vestibular nuclei region, dentate nucleus region, trigeminal root entry zone, medial lemniscus, superior colliculi). Volume loss was evident in connections to the frontal, parietal and cingulate lobes. Changes were larger in the ipsilesional hemisphere but were also detected in homotopical regions contralesionally. The white matter volume reduction led to deformation of the cortical projection zones of the infarcted nuclei. CONCLUSIONS: White matter volume loss after thalamic infarcts reflects sensory input from the brainstem as well the cortical projections of the main affected nuclei for sensory and ocular motor processing. Changes in the cortical geometry seem not to reflect gray matter atrophy but rather reshaping of the cortical surface due to the underlying white matter atrophy.\n

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\n \n\n \n \n \n \n \n Reorganization of sensory networks after subcortical vestibular infarcts: A longitudinal symptom-related voxel-based morphometry study.\n \n \n \n\n\n \n Conrad, J.; Habs, M.; Ruehl, R. M.; Boegle, R.; Ertl, M.; Kirsch, V.; Eren, O. E.; Becker-Bense, S.; Stephan, T.; Wollenweber, F. A.; Duering, M.; Dieterich, M.; and Zu Eulenburg, P.\n\n\n \n\n\n\n Eur J Neurol, 29(5): 1514–1523. May 2022.\n \n\n\n\n
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@article{conrad_reorganization_2022,\n\ttitle = {Reorganization of sensory networks after subcortical vestibular infarcts: {A} longitudinal symptom-related voxel-based morphometry study},\n\tvolume = {29},\n\tissn = {1468-1331},\n\tshorttitle = {Reorganization of sensory networks after subcortical vestibular infarcts},\n\tdoi = {10.1111/ene.15263},\n\tabstract = {BACKGROUND AND PURPOSE: We aimed to delineate common principles of reorganization after infarcts of the subcortical vestibular circuitry related to the clinical symptomatology. Our hypothesis was that the recovery of specific symptoms is associated with changes in distinct regions within the core vestibular, somatosensory, and visual cortical and subcortical networks.\nMETHODS: We used voxel- and surface-based morphometry to investigate structural reorganization of subcortical and cortical brain areas in 42 patients with a unilateral, subcortical infarct with vestibular and ocular motor deficits in the acute phase. The patients received structural neuroimaging and clinical monitoring twice (acute phase and after 6 months) to detect within-subject changes over time.\nRESULTS: In patients with vestibular signs such as tilts of the subjective visual vertical (SVV) and ocular torsion in the acute phase, significant volumetric increases in the superficial white matter around the parieto-opercular (retro-)insular vestibular cortex (PIVC) were found at follow-up. In patients with SVV tilts, spontaneous nystagmus, and rotatory vertigo in the acute phase, gray matter volume decreases were located in the cerebellum and the visual cortex bilaterally at follow-up. Patients with saccade pathology demonstrated volumetric decreases in cerebellar, thalamic, and cortical centers for ocular motor control.\nCONCLUSIONS: The findings support the role of the PIVC as the key hub for vestibular processing and reorganization. The volumetric decreases represent the reciprocal interaction of the vestibular, visual, and ocular motor systems during self-location and egomotion detection. A modulation in vestibular and ocular motor as well as visual networks was induced independently of the vestibular lesion site.},\n\tlanguage = {eng},\n\tnumber = {5},\n\tjournal = {Eur J Neurol},\n\tauthor = {Conrad, Julian and Habs, Maximilian and Ruehl, Ria Maxine and Boegle, Rainer and Ertl, Matthias and Kirsch, Valerie and Eren, Ozan Emre and Becker-Bense, Sandra and Stephan, Thomas and Wollenweber, Frank Arne and Duering, Marco and Dieterich, Marianne and Zu Eulenburg, Peter},\n\tmonth = may,\n\tyear = {2022},\n\tpmid = {35098611},\n\tkeywords = {Humans, stroke, Brain, White Matter, Cerebral Infarction, Cerebral Cortex, Vestibule, Labyrinth, compensation, PIVC, SBM, VBM, Vertigo, vestibular network},\n\tpages = {1514--1523},\n}\n\n

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\n \n\n \n \n \n \n \n Imaging Markers of Vascular Brain Health: Quantification, Clinical Implications, and Future Directions.\n \n \n \n\n\n \n Vemuri, P.; Decarli, C.; and Duering, M.\n\n\n \n\n\n\n Stroke, 53(2): 416–426. February 2022.\n \n\n\n\n
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@article{vemuri_imaging_2022,\n\ttitle = {Imaging {Markers} of {Vascular} {Brain} {Health}: {Quantification}, {Clinical} {Implications}, and {Future} {Directions}},\n\tvolume = {53},\n\tissn = {1524-4628},\n\tshorttitle = {Imaging {Markers} of {Vascular} {Brain} {Health}},\n\tdoi = {10.1161/STROKEAHA.120.032611},\n\tabstract = {Cerebrovascular disease (CVD) manifests through a broad spectrum of mechanisms that negatively impact brain and cognitive health. Oftentimes, CVD changes (excluding acute stroke) are insufficiently considered in aging and dementia studies which can lead to an incomplete picture of the etiologies contributing to the burden of cognitive impairment. Our goal with this focused review is 3-fold. First, we provide a research update on the current magnetic resonance imaging methods that can measure CVD lesions as well as early CVD-related brain injury specifically related to small vessel disease. Second, we discuss the clinical implications and relevance of these CVD imaging markers for cognitive decline, incident dementia, and disease progression in Alzheimer disease, and Alzheimer-related dementias. Finally, we present our perspective on the outlook and challenges that remain in the field. With the increased research interest in this area, we believe that reliable CVD imaging biomarkers for aging and dementia studies are on the horizon.},\n\tlanguage = {eng},\n\tnumber = {2},\n\tjournal = {Stroke},\n\tauthor = {Vemuri, Prashanthi and Decarli, Charles and Duering, Marco},\n\tmonth = feb,\n\tyear = {2022},\n\tpmid = {35000423},\n\tpmcid = {PMC8830603},\n\tkeywords = {cerebrovascular disease, dementia, Humans, cognition, Neuroimaging, Magnetic Resonance Imaging, Biomarkers, biomarkers, Brain, Alzheimer Disease, Cerebrovascular Disorders, Health Status, Cognitive Dysfunction, brain, Alzheimer disease},\n\tpages = {416--426},\n\tfile = {Full Text:/Users/mduering/Zotero/storage/9G6TQVCM/Vemuri et al. - 2022 - Imaging Markers of Vascular Brain Health Quantifi.pdf:application/pdf;Full Text:/Users/mduering/Zotero/storage/USMACQYK/Vemuri et al. - 2022 - Imaging Markers of Vascular Brain Health Quantifi.pdf:application/pdf},\n}\n\n

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\n \n\n \n \n \n \n \n Prediction of dementia using diffusion tensor MRI measures: the OPTIMAL collaboration.\n \n \n \n\n\n \n Egle, M.; Hilal, S.; Tuladhar, A. M.; Pirpamer, L.; Hofer, E.; Duering, M.; Wason, J.; Morris, R. G.; Dichgans, M.; Schmidt, R.; Tozer, D.; Chen, C.; de Leeuw, F.; and Markus, H. S.\n\n\n \n\n\n\n J Neurol Neurosurg Psychiatry, 93(1): 14–23. January 2022.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{egle_prediction_2022,\n\ttitle = {Prediction of dementia using diffusion tensor {MRI} measures: the {OPTIMAL} collaboration},\n\tvolume = {93},\n\tissn = {1468-330X},\n\tshorttitle = {Prediction of dementia using diffusion tensor {MRI} measures},\n\tdoi = {10.1136/jnnp-2021-326571},\n\tabstract = {OBJECTIVES: It has been suggested that diffusion tensor imaging (DTI) measures sensitive to white matter (WM) damage may predict future dementia risk not only in cerebral small vessel disease (SVD), but also in mild cognitive impairment. To determine whether DTI measures were associated with cognition cross-sectionally and predicted future dementia risk across the full range of SVD severity, we established the International OPtimising mulTImodal MRI markers for use as surrogate markers in trials of Vascular Cognitive Impairment due to cerebrAl small vesseL disease collaboration which included six cohorts.\nMETHODS: Among the six cohorts, prospective data with dementia incidences were available for three cohorts. The associations between six different DTI measures and cognition or dementia conversion were tested. The additional contribution to prediction of other MRI markers of SVD was also determined.\nRESULTS: The DTI measure mean diffusivity (MD) median correlated with cognition in all cohorts, demonstrating the contribution of WM damage to cognition. Adding MD median significantly improved the model fit compared to the clinical risk model alone and further increased in all single-centre SVD cohorts when adding conventional MRI measures. Baseline MD median predicted dementia conversion. In a study with severe SVD (SCANS) change in MD median also predicted dementia conversion. The area under the curve was best when employing a multimodal MRI model using both DTI measures and other MRI measures.\nCONCLUSIONS: Our results support a central role for WM alterations in dementia pathogenesis in all cohorts. DTI measures such as MD median may be a useful clinical risk predictor. The contribution of other MRI markers varied according to disease severity.},\n\tlanguage = {eng},\n\tnumber = {1},\n\tjournal = {J Neurol Neurosurg Psychiatry},\n\tauthor = {Egle, Marco and Hilal, Saima and Tuladhar, A. M. and Pirpamer, Lukas and Hofer, Edith and Duering, Marco and Wason, James and Morris, Robin G. and Dichgans, Martin and Schmidt, Reinhold and Tozer, Daniel and Chen, Christopher and de Leeuw, Frank-Erik and Markus, Hugh S.},\n\tmonth = jan,\n\tyear = {2022},\n\tpmid = {34509999},\n\tkeywords = {Cognition, cerebrovascular disease, dementia, Diffusion Tensor Imaging, Humans, Prospective Studies, Cohort Studies, Dementia, vascular dementia, White Matter, Cerebral Small Vessel Diseases, Cognitive Dysfunction, MRI, alzheimer's disease},\n\tpages = {14--23},\n\tfile = {Submitted Version:/Users/mduering/Zotero/storage/ZH3ZTLDB/Egle et al. - 2022 - Prediction of dementia using diffusion tensor MRI .pdf:application/pdf},\n}\n\n

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\n \n\n \n \n \n \n \n Sex differences of vascular brain lesions in patients with atrial fibrillation.\n \n \n \n\n\n \n Ceylan, S.; Aeschbacher, S.; Altermatt, A.; Sinnecker, T.; Rodondi, N.; Blum, M.; Coslovsky, M.; Evers-Dörpfeld, S.; Niederberger, S.; Conen, D.; Osswald, S.; Kühne, M.; Düring, M.; Wuerfel, J.; Bonati, L.; and SWISS-AF Investigators\n\n\n \n\n\n\n Open Heart, 9(2): e002033. September 2022.\n \n\n\n\n
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@article{ceylan_sex_2022,\n\ttitle = {Sex differences of vascular brain lesions in patients with atrial fibrillation},\n\tvolume = {9},\n\tissn = {2053-3624},\n\tdoi = {10.1136/openhrt-2022-002033},\n\tabstract = {OBJECTIVE: To examine sex differences in prevalence, volume and distribution of vascular brain lesions on MRI among patients with atrial fibrillation (AF).\nMETHODS: In this cross-sectional analysis, we included 1743 patients with AF (27\\% women) from the multicentre Swiss Atrial Fibrillation study (SWISS-AF) with available baseline brain MRI. We compared presence and total volume of large non-cortical or cortical infarcts (LNCCIs), small non-cortical infarcts, microbleeds (MB) and white matter hyperintensities (WMH, Fazekas score ≥2 for moderate or severe degree) between men and women with multivariable logistic regression. We generated voxel-based probability maps to assess the anatomical distribution of lesions.\nRESULTS: We found no strong evidence for an association of female sex with the prevalence of all ischaemic infarcts (LNCCI and SNCI combined; adjusted OR 0.86, 95\\% CI 0.67 to 1.09, p=0.22), MB (adjusted OR 0.91, 95\\% CI 0.68 to 1.21, p=0.52) and moderate or severe WMH (adjusted OR 1.15, 95\\% CI 0.90 to 1.48, p=0.27). However, total WMH volume was 17\\% larger among women than men (multivariable adjusted multiplicative effect 1.17, 95\\% CI 1.01 to 1.35; p=0.04). Lesion probability maps showed a right hemispheric preponderance of ischaemic infarcts in both men and women, while WMH were distributed symmetrically.\nCONCLUSION: Women had higher white matter disease burden than men, while volume and prevalence of other lesions did not differ. Our findings highlight the importance of controlling risk factors for cerebral small vessel disease in patients with AF, especially among women.},\n\tlanguage = {eng},\n\tnumber = {2},\n\tjournal = {Open Heart},\n\tauthor = {Ceylan, Selinda and Aeschbacher, Stefanie and Altermatt, Anna and Sinnecker, Tim and Rodondi, Nicolas and Blum, Manuel and Coslovsky, Michael and Evers-Dörpfeld, Simone and Niederberger, Sacha and Conen, David and Osswald, Stefan and Kühne, Michael and Düring, Marco and Wuerfel, Jens and Bonati, Leo and {SWISS-AF Investigators}},\n\tmonth = sep,\n\tyear = {2022},\n\tpmid = {36100317},\n\tpmcid = {PMC9472202},\n\tkeywords = {Female, Humans, Male, Infarction, Cross-Sectional Studies, Brain, Atrial Fibrillation, Sex Characteristics, Atrial Flutter, STROKE},\n\tpages = {e002033},\n\tfile = {Full Text:/Users/mduering/Zotero/storage/2CDW77X7/Ceylan et al. - 2022 - Sex differences of vascular brain lesions in patie.pdf:application/pdf},\n}\n\n

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\n \n\n \n \n \n \n \n Systematic validation of structural brain networks in cerebral small vessel disease.\n \n \n \n\n\n \n Dewenter, A.; Gesierich, B.; Ter Telgte, A.; Wiegertjes, K.; Cai, M.; Jacob, M. A.; Marques, J. P.; Norris, D. G.; Franzmeier, N.; de Leeuw, F.; Tuladhar, A. M.; and Duering, M.\n\n\n \n\n\n\n J Cereb Blood Flow Metab, 42(6): 1020–1032. June 2022.\n \n\n\n\n
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@article{dewenter_systematic_2022,\n\ttitle = {Systematic validation of structural brain networks in cerebral small vessel disease},\n\tvolume = {42},\n\tissn = {1559-7016},\n\tdoi = {10.1177/0271678X211069228},\n\tabstract = {Cerebral small vessel disease (SVD) is considered a disconnection syndrome, which can be quantified using structural brain network analysis obtained from diffusion MRI. Network analysis is a demanding analysis approach and the added benefit over simpler diffusion MRI analysis is largely unexplored in SVD. In this pre-registered study, we assessed the clinical and technical validity of network analysis in two non-overlapping samples of SVD patients from the RUN DMC study (n = 52 for exploration and longitudinal analysis and n = 105 for validation). We compared two connectome pipelines utilizing single-shell or multi-shell diffusion MRI, while also systematically comparing different node and edge definitions. For clinical validation, we assessed the added benefit of network analysis in explaining processing speed and in detecting short-term disease progression. For technical validation, we determined test-retest repeatability.Our findings in clinical validation show that structural brain networks provide only a small added benefit over simpler global white matter diffusion metrics and do not capture short-term disease progression. Test-retest reliability was excellent for most brain networks. Our findings question the added value of brain network analysis in clinical applications in SVD and highlight the utility of simpler diffusion MRI based markers.},\n\tlanguage = {eng},\n\tnumber = {6},\n\tjournal = {J Cereb Blood Flow Metab},\n\tauthor = {Dewenter, Anna and Gesierich, Benno and Ter Telgte, Annemieke and Wiegertjes, Kim and Cai, Mengfei and Jacob, Mina A. and Marques, José P. and Norris, David G. and Franzmeier, Nicolai and de Leeuw, Frank-Erik and Tuladhar, Anil M. and Duering, Marco},\n\tmonth = jun,\n\tyear = {2022},\n\tpmid = {34929104},\n\tpmcid = {PMC9125482},\n\tkeywords = {Diffusion Tensor Imaging, Disease Progression, Humans, Magnetic Resonance Imaging, Reproducibility of Results, Brain, Cerebral Small Vessel Diseases, diffusion MRI, Cerebral small vessel disease, connectome, network analysis, quantitative MRI marker},\n\tpages = {1020--1032},\n\tfile = {Full Text:/Users/mduering/Zotero/storage/32HQQMRL/Dewenter et al. - 2022 - Systematic validation of structural brain networks.pdf:application/pdf},\n}\n\n

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\n \n\n \n \n \n \n \n Cognitive impairment in patients with cerebrovascular disease: A white paper from the links between stroke ESO Dementia Committee.\n \n \n \n\n\n \n Verdelho, A.; Wardlaw, J.; Pavlovic, A.; Pantoni, L.; Godefroy, O.; Duering, M.; Charidimou, A.; Chabriat, H.; and Biessels, G. J.\n\n\n \n\n\n\n Eur Stroke J, 6(1): 5–17. March 2021.\n \n\n\n\n
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@article{verdelho_cognitive_2021,\n\ttitle = {Cognitive impairment in patients with cerebrovascular disease: {A} white paper from the links between stroke {ESO} {Dementia} {Committee}},\n\tvolume = {6},\n\tissn = {2396-9881 (Electronic) 2396-9873 (Linking)},\n\tdoi = {10.1177/23969873211000258},\n\tabstract = {Purpose: Many daily-life clinical decisions in patients with cerebrovascular disease and cognitive impairment are complex. Evidence-based information sustaining these decisions is frequently lacking. The aim of this paper is to propose a practical clinical approach to cognitive impairments in patients with known cerebrovascular disease. Methods: The document was produced by the Dementia Committee of the European Stroke Organisation (ESO), based on evidence from the literature where available and on the clinical experience of the Committee members. This paper was endorsed by the ESO. Findings: Many patients with stroke or other cerebrovascular disease have cognitive impairment, but this is often not recognized. With improvement in acute stroke care, and with the ageing of populations, it is expected that more stroke survivors and more patients with cerebrovascular disease will need adequate management of cognitive impairment of vascular etiology. This document was conceived for the use of strokologists and for those clinicians involved in cerebrovascular disease, with specific and practical hints concerning diagnostic tools, cognitive impairment management and decision on some therapeutic options.Discussion and conclusions: It is essential to consider a possible cognitive deterioration in every patient who experiences a stroke. Neuropsychological evaluation should be adapted to the clinical status. Brain imaging is the most informative biomarker concerning prognosis. Treatment should always include adequate secondary prevention.},\n\tnumber = {1},\n\tjournal = {Eur Stroke J},\n\tauthor = {Verdelho, A. and Wardlaw, J. and Pavlovic, A. and Pantoni, L. and Godefroy, O. and Duering, M. and Charidimou, A. and Chabriat, H. and Biessels, G. J.},\n\tmonth = mar,\n\tyear = {2021},\n\tpmcid = {PMC7995319},\n\tpmid = {33817330},\n\tkeywords = {Stroke, cerebrovascular disease, cognitive impairment, dementia, small vessel disease, and received funding for travel and meetings from Bristol-Myers Squibb, Roche,, Biogen, Teva-sante, Boehringer-Ingelheim, Covidien, Ipsen. The remaining authors, declare that there are no conflict of interest concerning the paper., potential conflicts of interest with respect to the research, authorship, and/or, publication of this article: Olivier Godefroy during the last five years has, served on scientific advisory boards and speaker (Biogen, Astra Zeneca, Novartis)},\n\tpages = {5--17},\n}\n\n

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\n \n\n \n \n \n \n \n Structural reorganization of the cerebral cortex after vestibulo-cerebellar stroke.\n \n \n \n\n\n \n Conrad, J.; Habs, M.; Ruehl, M.; Boegle, R.; Ertl, M.; Kirsch, V.; Eren, O.; Becker-Bense, S.; Stephan, T.; Wollenweber, F.; Duering, M.; Dieterich, M.; and Eulenburg, P. Z.\n\n\n \n\n\n\n Neuroimage Clin, 30: 102603. February 2021.\n \n\n\n\n
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@article{conrad_structural_2021,\n\ttitle = {Structural reorganization of the cerebral cortex after vestibulo-cerebellar stroke},\n\tvolume = {30},\n\tissn = {2213-1582 (Electronic) 2213-1582 (Linking)},\n\tdoi = {10.1016/j.nicl.2021.102603},\n\tabstract = {OBJECTIVE: Structural reorganization following cerebellar infarcts is not yet known. This study aimed to demonstrate structural volumetric changes over time in the cortical vestibular and multisensory areas (i.e., brain plasticity) after acute cerebellar infarcts with vestibular and ocular motor symptoms. Additionally, we evaluated whether structural reorganization in the patients topographically correlates with cerebello-cortical connectivity that can be observed in healthy participants. METHODS: We obtained high-resolution structural imaging in seven patients with midline cerebellar infarcts at two time points. These data were compared to structural imaging of a group of healthy age-matched controls using voxel-based morphometry (2x2 ANOVA approach). The maximum overlap of the infarcts was used as a seed region for a separate resting-state functional connectivity analysis in healthy volunteers. RESULTS: Volumetric changes were detected in the multisensory cortical vestibular areas around the parieto-opercular and (retro-) insular cortex. Furthermore, structural reorganization was evident in parts of the frontal, temporal, parietal, limbic, and occipital lobes and reflected functional connections between the main infarct regions in the cerebellum and the cerebral cortex in healthy individuals. CONCLUSIONS: This study demonstrates structural reorganization in the parieto-opercular insular vestibular cortex after acute vestibulo-cerebellar infarcts. Additionally, the widely distributed structural reorganization after midline cerebellar infarcts provides additional in vivo evidence for the multifaceted contribution of cerebellar processing to cortical functions that extend beyond vestibular or ocular motor function.},\n\tjournal = {Neuroimage Clin},\n\tauthor = {Conrad, J. and Habs, M. and Ruehl, M. and Boegle, R. and Ertl, M. and Kirsch, V. and Eren, O. and Becker-Bense, S. and Stephan, T. and Wollenweber, F. and Duering, M. and Dieterich, M. and Eulenburg, P. Z.},\n\tmonth = feb,\n\tyear = {2021},\n\tpmid = {33676164},\n\tpmcid = {PMC7933782},\n\tkeywords = {Cerebellar, Neuroplasticity, Stroke, Vestibular, Humans, Magnetic Resonance Imaging, Vbm, Cerebral Cortex, Vestibule, Labyrinth, VBM, Neuronal Plasticity},\n\tpages = {102603},\n}\n\n

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\n \n\n \n \n \n \n \n Peak Width of Skeletonized Mean Diffusivity as Neuroimaging Biomarker in Cerebral Amyloid Angiopathy.\n \n \n \n\n\n \n Raposo, N.; Zanon Zotin, M. C.; Schoemaker, D.; Xiong, L.; Fotiadis, P.; Charidimou, A.; Pasi, M.; Boulouis, G.; Schwab, K.; Schirmer, M. D.; Etherton, M. R.; Gurol, M. E.; Greenberg, S. M.; Duering, M.; and Viswanathan, A.\n\n\n \n\n\n\n AJNR Am J Neuroradiol. March 2021.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{raposo_peak_2021,\n\ttitle = {Peak {Width} of {Skeletonized} {Mean} {Diffusivity} as {Neuroimaging} {Biomarker} in {Cerebral} {Amyloid} {Angiopathy}},\n\tissn = {1936-959X (Electronic) 0195-6108 (Linking)},\n\tdoi = {10.3174/ajnr.A7042},\n\tabstract = {BACKGROUND AND PURPOSE: Whole-brain network connectivity has been shown to be a useful biomarker of cerebral amyloid angiopathy and related cognitive impairment. We evaluated an automated DTI-based method, peak width of skeletonized mean diffusivity, in cerebral amyloid angiopathy, together with its association with conventional MRI markers and cognitive functions. MATERIALS AND METHODS: We included 24 subjects (mean age, 74.7 [SD, 6.0] years) with probable cerebral amyloid angiopathy and mild cognitive impairment and 62 patients with MCI not attributable to cerebral amyloid angiopathy (non-cerebral amyloid angiopathy-mild cognitive impairment). We compared peak width of skeletonized mean diffusivity between subjects with cerebral amyloid angiopathy-mild cognitive impairment and non-cerebral amyloid angiopathy-mild cognitive impairment and explored its associations with cognitive functions and conventional markers of cerebral small-vessel disease, using linear regression models. RESULTS: Subjects with Cerebral amyloid angiopathy-mild cognitive impairment showed increased peak width of skeletonized mean diffusivity in comparison to those with non-cerebral amyloid angiopathy-mild cognitive impairment (P {\\textless} .001). Peak width of skeletonized mean diffusivity values were correlated with the volume of white matter hyperintensities in both groups. Higher peak width of skeletonized mean diffusivity was associated with worse performance in processing speed among patients with cerebral amyloid angiopathy, after adjusting for other MRI markers of cerebral small vessel disease. The peak width of skeletonized mean diffusivity did not correlate with cognitive functions among those with non-cerebral amyloid angiopathy-mild cognitive impairment. CONCLUSIONS: Peak width of skeletonized mean diffusivity is altered in cerebral amyloid angiopathy and is associated with performance in processing speed. This DTI-based method may reflect the degree of white matter structural disruption in cerebral amyloid angiopathy and could be a useful biomarker for cognition in this population.},\n\tjournal = {AJNR Am J Neuroradiol},\n\tauthor = {Raposo, N. and Zanon Zotin, M. C. and Schoemaker, D. and Xiong, L. and Fotiadis, P. and Charidimou, A. and Pasi, M. and Boulouis, G. and Schwab, K. and Schirmer, M. D. and Etherton, M. R. and Gurol, M. E. and Greenberg, S. M. and Duering, M. and Viswanathan, A.},\n\tmonth = mar,\n\tyear = {2021},\n\tpmid = {33664113},\n\tpmcid = {PMC8115367},\n\tkeywords = {Cognition, Aged, Diffusion Magnetic Resonance Imaging, Diffusion Tensor Imaging, Female, Humans, Image Processing, Computer-Assisted, Male, Aged, 80 and over, Neuroimaging, Biomarkers, Psychomotor Performance, Cerebral Amyloid Angiopathy, Cerebral Small Vessel Diseases, Cognitive Dysfunction, Reaction Time},\n}\n\n

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\n BACKGROUND AND PURPOSE: Whole-brain network connectivity has been shown to be a useful biomarker of cerebral amyloid angiopathy and related cognitive impairment. We evaluated an automated DTI-based method, peak width of skeletonized mean diffusivity, in cerebral amyloid angiopathy, together with its association with conventional MRI markers and cognitive functions. MATERIALS AND METHODS: We included 24 subjects (mean age, 74.7 [SD, 6.0] years) with probable cerebral amyloid angiopathy and mild cognitive impairment and 62 patients with MCI not attributable to cerebral amyloid angiopathy (non-cerebral amyloid angiopathy-mild cognitive impairment). We compared peak width of skeletonized mean diffusivity between subjects with cerebral amyloid angiopathy-mild cognitive impairment and non-cerebral amyloid angiopathy-mild cognitive impairment and explored its associations with cognitive functions and conventional markers of cerebral small-vessel disease, using linear regression models. RESULTS: Subjects with Cerebral amyloid angiopathy-mild cognitive impairment showed increased peak width of skeletonized mean diffusivity in comparison to those with non-cerebral amyloid angiopathy-mild cognitive impairment (P \\textless .001). Peak width of skeletonized mean diffusivity values were correlated with the volume of white matter hyperintensities in both groups. Higher peak width of skeletonized mean diffusivity was associated with worse performance in processing speed among patients with cerebral amyloid angiopathy, after adjusting for other MRI markers of cerebral small vessel disease. The peak width of skeletonized mean diffusivity did not correlate with cognitive functions among those with non-cerebral amyloid angiopathy-mild cognitive impairment. CONCLUSIONS: Peak width of skeletonized mean diffusivity is altered in cerebral amyloid angiopathy and is associated with performance in processing speed. This DTI-based method may reflect the degree of white matter structural disruption in cerebral amyloid angiopathy and could be a useful biomarker for cognition in this population.\n

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\n \n\n \n \n \n \n \n Prediction of Long-term Cognitive Functions after Minor Stroke, Using Functional Connectivity.\n \n \n \n\n\n \n Lopes, R.; Bournonville, C.; Kuchcinski, G.; Dondaine, T.; Mendyk, A. M.; Viard, R.; Pruvo, J. P.; Henon, H.; Georgakis, M. K.; Duering, M.; Dichgans, M.; Cordonnier, C.; Leclerc, X.; and Bordet, R.\n\n\n \n\n\n\n Neurology. January 2021.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{lopes_prediction_2021,\n\ttitle = {Prediction of {Long}-term {Cognitive} {Functions} after {Minor} {Stroke}, {Using} {Functional} {Connectivity}},\n\tissn = {1526-632X (Electronic) 0028-3878 (Linking)},\n\tdoi = {10.1212/WNL.0000000000011452},\n\tabstract = {OBJECTIVE: To determine whether functional MRI connectivity can predict the long-term cognitive functions 36 months after minor stroke. METHODS: Seventy-two participants with first-ever stroke were included at baseline and followed up for 36 months. A ridge regression machine learning algorithm was developed and used to predict cognitive scores 36 months post-stroke on the basis of the functional networks measured using MRI at 6 months (referred to here as the post-stroke cognitive impairment (PSCI) network). The prediction accuracy was evaluated in four domains (memory, attention/executive, language and visuospatial functions) and compared with clinical data and other functional networks. The models' statistical significance was probed with permutation tests. The potential involvement of cortical atrophy was assessed 6 months post-stroke. A second, independent dataset (n=40) was used to validate the results and assess their generalizability. RESULTS: Based on the PSCI network, a machine learning model was able to predict memory, attention, visuospatial functions and language functions 36 months post-stroke (r(2): 0.67, 0.73, 0.55 and 0.48, respectively). The PSCI-based model was at least as accurate as models based on other functional networks or clinical data. Specific patterns were demonstrated for the four cognitive domains, with involvement of the left superior frontal cortex for memory, attention and visuospatial functions. The cortical thickness 6 months post-stroke was not correlated with cognitive function 36 months post-stroke. The independent validation dataset gave similar results. CONCLUSIONS: A machine learning model based on the PSCI network can predict the long-term cognitive outcome after stroke.},\n\tjournal = {Neurology},\n\tauthor = {Lopes, R. and Bournonville, C. and Kuchcinski, G. and Dondaine, T. and Mendyk, A. M. and Viard, R. and Pruvo, J. P. and Henon, H. and Georgakis, M. K. and Duering, M. and Dichgans, M. and Cordonnier, C. and Leclerc, X. and Bordet, R.},\n\tmonth = jan,\n\tyear = {2021},\n\tpmid = {33402437},\n}\n\n

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\n \n\n \n \n \n \n \n Neuronal densities and vascular pathology in the hippocampal formation in CADASIL.\n \n \n \n\n\n \n Yamamoto, Y.; Hase, Y.; Ihara, M.; Khundakar, A.; Roeber, S.; Duering, M.; and Kalaria, R. N.\n\n\n \n\n\n\n Neurobiol Aging, 97: 33–40. January 2021.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n \n \n 3 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{yamamoto_neuronal_2021,\n\ttitle = {Neuronal densities and vascular pathology in the hippocampal formation in {CADASIL}},\n\tvolume = {97},\n\tissn = {1558-1497 (Electronic) 0197-4580 (Linking)},\n\tdoi = {10.1016/j.neurobiolaging.2020.09.016},\n\tabstract = {Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) is the most common form of hereditary cerebral small vessel disease. Previous neuroimaging studies have suggested loss of hippocampal volume is a pathway for cognitive impairment in CADASIL. We used unbiased stereological methods to estimate SMI32-positive and total numbers and volumes of neurons in the hippocampal formation of 12 patients with CADASIL and similar age controls (young controls) and older controls. We found densities of SMI32-positive neurons in the entorhinal cortex, layer V, and cornu ammonis CA2 regions were reduced by 26\\%-50\\% in patients with CADASIL compared with young controls (p {\\textless} 0.01), with a decreasing trend observed in older controls in the order of young controls{\\textgreater} older controls {\\textgreater}/= CADASIL. These changes were not explained by any hippocampal infarct or vascular pathology or glial changes. Our results suggest notable loss of subsets of projection neurons within the hippocampal formation that may contribute to certain memory deficits in CADASIL, which is purely a vascular disease. It is likely that the severe arteriopathy leads to white matter damage which disconnects cortico-cortical and subcortical-cortical networks including the hippocampal formation.},\n\tjournal = {Neurobiol Aging},\n\tauthor = {Yamamoto, Y. and Hase, Y. and Ihara, M. and Khundakar, A. and Roeber, S. and Duering, M. and Kalaria, R. N.},\n\tmonth = jan,\n\tyear = {2021},\n\tpmid = {33130454},\n\tpmcid = {PMC7758782},\n\tkeywords = {Aged, Female, Humans, Male, Middle Aged, Cadasil, Cognitive impairment, Hippocampus, Neuronal density, Vascular dementia white matter damage, Organ Size, Cognitive Dysfunction, CADASIL, Neurons},\n\tpages = {33--40},\n}\n\n

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\n \n\n \n \n \n \n \n The BIN1 rs744373 Alzheimer's disease risk SNP is associated with faster Aβ-associated tau accumulation and cognitive decline.\n \n \n \n\n\n \n Franzmeier, N.; Ossenkoppele, R.; Brendel, M.; Rubinski, A.; Smith, R.; Kumar, A.; Mattsson-Carlgren, N.; Strandberg, O.; Duering, M.; Buerger, K.; Dichgans, M.; Hansson, O.; Ewers, M.; Alzheimer's Disease Neuroimaging Initiative (ADNI)*; and the Swedish BioFINDER study \n\n\n \n\n\n\n Alzheimers Dement. June 2021.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{franzmeier_bin1_2021,\n\ttitle = {The {BIN1} rs744373 {Alzheimer}'s disease risk {SNP} is associated with faster {Aβ}-associated tau accumulation and cognitive decline},\n\tissn = {1552-5279},\n\tdoi = {10.1002/alz.12371},\n\tabstract = {INTRODUCTION: The BIN1 rs744373 single nucleotide polymorphism (SNP) is a key genetic risk locus for Alzheimer's disease (AD) associated with tau pathology. Because tau typically accumulates in response to amyloid beta (Aβ), we tested whether BIN1 rs744373 accelerates Aβ-related tau accumulation.\nMETHODS: We included two samples (Alzheimer's Disease Neuroimaging Initiative [ADNI], n = 153; Biomarkers for Identifying Neurodegenerative Disorders Early and Reliably [BioFINDER], n = 63) with longitudinal 18 F-Flortaucipir positron emission tomography (PET), Aβ biomarkers, and longitudinal cognitive assessments. We assessed whether BIN1 rs744373 was associated with faster tau-PET accumulation at a given level of Aβ and whether faster BIN1 rs744373-associated tau-PET accumulation mediated cognitive decline.\nRESULTS: BIN1 rs744373 risk-allele carriers showed faster global tau-PET accumulation (ADNI/BioFINDER, P {\\textless} .001/P {\\textless} .001). We found significant Aβ by rs744373 interactions on global tau-PET change (ADNI: β/standard error [SE] = 0.42/0.14, P = 0.002; BioFINDER: β/SE = -0.35/0.15, P = .021), BIN1 risk-allele carriers showed accelerated tau-PET accumulation at higher Aβ levels. In ADNI, rs744373 effects on cognitive decline were mediated by faster global tau-PET accumulation (β/SE = 0.20/0.07, P = .005).\nDISCUSSION: BIN1-associated AD risk is potentially driven by accelerated tau accumulation in the face of Aβ.},\n\tlanguage = {eng},\n\tjournal = {Alzheimers Dement},\n\tauthor = {Franzmeier, Nicolai and Ossenkoppele, Rik and Brendel, Matthias and Rubinski, Anna and Smith, Ruben and Kumar, Atul and Mattsson-Carlgren, Niklas and Strandberg, Olof and Duering, Marco and Buerger, Katharina and Dichgans, Martin and Hansson, Oskar and Ewers, Michael and {Alzheimer's Disease Neuroimaging Initiative (ADNI)* and the Swedish BioFINDER study}},\n\tmonth = jun,\n\tyear = {2021},\n\tpmid = {34060233},\n\tkeywords = {Aged, Female, Humans, Male, Alzheimer's disease, Biomarkers, Positron-Emission Tomography, Amyloid beta-Peptides, amyloid, BIN1, tau, Brain, Alzheimer Disease, Cognitive Dysfunction, Adaptor Proteins, Signal Transducing, Nuclear Proteins, Polymorphism, Single Nucleotide, tau Proteins, Tumor Suppressor Proteins},\n}\n\n

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\n \n\n \n \n \n \n \n Diffusion MRI harmonization enables joint-analysis of multicentre data of patients with cerebral small vessel disease.\n \n \n \n\n\n \n de Brito Robalo, B. M.; Biessels, G. J.; Chen, C.; Dewenter, A.; Duering, M.; Hilal, S.; Koek, H. L.; Kopczak, A.; Yin Ka Lam, B.; Leemans, A.; Mok, V.; Onkenhout, L. P.; van den Brink, H.; and de Luca, A.\n\n\n \n\n\n\n Neuroimage Clin, 32: 102886. 2021.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{de_brito_robalo_diffusion_2021,\n\ttitle = {Diffusion {MRI} harmonization enables joint-analysis of multicentre data of patients with cerebral small vessel disease},\n\tvolume = {32},\n\tissn = {2213-1582},\n\tdoi = {10.1016/j.nicl.2021.102886},\n\tabstract = {OBJECTIVES: Acquisition-related differences in diffusion magnetic resonance imaging (dMRI) hamper pooling of multicentre data to achieve large sample sizes. A promising solution is to harmonize the raw diffusion signal using rotation invariant spherical harmonic (RISH) features, but this has not been tested in elderly subjects. Here we aimed to establish if RISH harmonization effectively removes acquisition-related differences in multicentre dMRI of elderly subjects with cerebral small vessel disease (SVD), while preserving sensitivity to disease effects.\nMETHODS: Five cohorts of patients with SVD (N = 397) and elderly controls (N = 175) with 3 Tesla MRI on different systems were included. First, to establish effectiveness of harmonization, the RISH method was trained with data of 13 to 15 age and sex-matched controls from each site. Fractional anisotropy (FA) and mean diffusivity (MD) were compared in matched controls between sites using tract-based spatial statistics (TBSS) and voxel-wise analysis, before and after harmonization. Second, to assess sensitivity to disease effects, we examined whether the contrast (effect sizes of FA, MD and peak width of skeletonized MD - PSMD) between patients and controls within each site remained unaffected by harmonization. Finally, we evaluated the association between white matter hyperintensity (WMH) burden, FA, MD and PSMD using linear regression analyses both within individual cohorts as well as with pooled scans from multiple sites, before and after harmonization.\nRESULTS: Before harmonization, significant differences in FA and MD were observed between matched controls of different sites (p {\\textless} 0.05). After harmonization these site-differences were removed. Within each site, RISH harmonization did not alter the effect sizes of FA, MD and PSMD between patients and controls (relative change in Cohen's d = 4 \\%) nor the strength of association with WMH volume (relative change in R2 = 2.8 \\%). After harmonization, patient data of all sites could be aggregated in a single analysis to infer the association between WMH volume and FA (R2 = 0.62), MD (R2 = 0.64), and PSMD (R2 = 0.60).\nCONCLUSIONS: We showed that RISH harmonization effectively removes acquisition-related differences in dMRI of elderly subjects while preserving sensitivity to SVD-related effects. This study provides proof of concept for future multicentre SVD studies with pooled datasets.},\n\tlanguage = {eng},\n\tjournal = {Neuroimage Clin},\n\tauthor = {de Brito Robalo, Bruno M. and Biessels, Geert Jan and Chen, Christopher and Dewenter, Anna and Duering, Marco and Hilal, Saima and Koek, Huiberdina L. and Kopczak, Anna and Yin Ka Lam, Bonnie and Leemans, Alexander and Mok, Vincent and Onkenhout, Laurien P. and van den Brink, Hilde and de Luca, Alberto},\n\tyear = {2021},\n\tpmid = {34911192},\n\tpmcid = {PMC8609094},\n\tkeywords = {Aged, Diffusion Magnetic Resonance Imaging, Humans, Magnetic Resonance Imaging, Regression Analysis, White matter hyperintensities, Anisotropy, White Matter, Cerebral Small Vessel Diseases, Cerebral small vessel disease, Diffusion MRI, Harmonization, Multicentre},\n\tpages = {102886},\n\tfile = {Full Text:/Users/mduering/Zotero/storage/ECPI9WYI/de Brito Robalo et al. - 2021 - Diffusion MRI harmonization enables joint-analysis.pdf:application/pdf},\n}\n\n

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\n OBJECTIVES: Acquisition-related differences in diffusion magnetic resonance imaging (dMRI) hamper pooling of multicentre data to achieve large sample sizes. A promising solution is to harmonize the raw diffusion signal using rotation invariant spherical harmonic (RISH) features, but this has not been tested in elderly subjects. Here we aimed to establish if RISH harmonization effectively removes acquisition-related differences in multicentre dMRI of elderly subjects with cerebral small vessel disease (SVD), while preserving sensitivity to disease effects. METHODS: Five cohorts of patients with SVD (N = 397) and elderly controls (N = 175) with 3 Tesla MRI on different systems were included. First, to establish effectiveness of harmonization, the RISH method was trained with data of 13 to 15 age and sex-matched controls from each site. Fractional anisotropy (FA) and mean diffusivity (MD) were compared in matched controls between sites using tract-based spatial statistics (TBSS) and voxel-wise analysis, before and after harmonization. Second, to assess sensitivity to disease effects, we examined whether the contrast (effect sizes of FA, MD and peak width of skeletonized MD - PSMD) between patients and controls within each site remained unaffected by harmonization. Finally, we evaluated the association between white matter hyperintensity (WMH) burden, FA, MD and PSMD using linear regression analyses both within individual cohorts as well as with pooled scans from multiple sites, before and after harmonization. RESULTS: Before harmonization, significant differences in FA and MD were observed between matched controls of different sites (p \\textless 0.05). After harmonization these site-differences were removed. Within each site, RISH harmonization did not alter the effect sizes of FA, MD and PSMD between patients and controls (relative change in Cohen's d = 4 %) nor the strength of association with WMH volume (relative change in R2 = 2.8 %). After harmonization, patient data of all sites could be aggregated in a single analysis to infer the association between WMH volume and FA (R2 = 0.62), MD (R2 = 0.64), and PSMD (R2 = 0.60). CONCLUSIONS: We showed that RISH harmonization effectively removes acquisition-related differences in dMRI of elderly subjects while preserving sensitivity to SVD-related effects. This study provides proof of concept for future multicentre SVD studies with pooled datasets.\n

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\n \n\n \n \n \n \n \n Differences in cerebral small vessel disease magnetic resonance imaging markers between lacunar stroke and non-Lobar intracerebral hemorrhage.\n \n \n \n\n\n \n Wiegertjes, K.; Jansen, M. G.; Jolink, W. M.; Duering, M.; Koemans, E. A.; Schreuder, F. H.; Tuladhar, A. M.; Wermer, M. J.; Klijn, C. J.; and de Leeuw, F.\n\n\n \n\n\n\n Eur Stroke J, 6(3): 236–244. September 2021.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{wiegertjes_differences_2021,\n\ttitle = {Differences in cerebral small vessel disease magnetic resonance imaging markers between lacunar stroke and non-{Lobar} intracerebral hemorrhage},\n\tvolume = {6},\n\tissn = {2396-9881},\n\tdoi = {10.1177/23969873211031753},\n\tabstract = {INTRODUCTION: It is unclear why cerebral small vessel disease (SVD) leads to lacunar stroke in some and to non-lobar intracerebral hemorrhage (ICH) in others. We investigated differences in MRI markers of SVD in patients with lacunar stroke or non-lobar ICH.\nPATIENTS AND METHODS: We included patients from two prospective cohort studies with either lacunar stroke (RUN DMC) or non-lobar ICH (FETCH). Differences in SVD markers (white matter hyperintensities [WMH], lacunes, cerebral microbleeds [CMB]) between groups were investigated with univariable tests; multivariable logistic regression analysis, adjusted for age, sex, and vascular risk factors; spatial correlation analysis and voxel-wise lesion symptom mapping.\nRESULTS: We included 82 patients with lacunar stroke (median age 63, IQR 57-72) and 54 with non-lobar ICH (66, 59-75). WMH volumes and distribution were not different between groups. Lacunes were more frequent in patients with a lacunar stroke (44\\% vs. 17\\%, adjusted odds ratio [aOR] 5.69, 95\\% CI [1.66-22.75]) compared to patients with a non-lobar ICH. CMB were more frequent in patients with a non-lobar ICH (71\\% vs. 23\\%, aOR for lacunar stroke vs non-lobar ICH 0.08 95\\% CI [0.02-0.26]), and more often located in non-lobar regions compared to CMB in lacunar stroke.\nDISCUSSION: Although we obserd different types of MRI markers of SVD within the same patient, ischemic markers of SVD were more frequent in the ischemic type of lacunar stroke, and hemorrhagic markers were more prevalent in the hemorrhagic phenotype of non-lobar ICH.\nCONCLUSION: There are differences between MRI markers of SVD between patients with a lacunar stroke and those with a non-lobar ICH.},\n\tlanguage = {eng},\n\tnumber = {3},\n\tjournal = {Eur Stroke J},\n\tauthor = {Wiegertjes, Kim and Jansen, Michelle G. and Jolink, Wilmar Mt and Duering, Marco and Koemans, Emma A. and Schreuder, Floris Hbm and Tuladhar, Anil M. and Wermer, Marieke Jh and Klijn, Catharina Jm and de Leeuw, Frank-Erik},\n\tmonth = sep,\n\tyear = {2021},\n\tpmid = {34746419},\n\tpmcid = {PMC8564151},\n\tkeywords = {small vessel disease, Magnetic resonance imaging, stroke, intracerebral hemorrhage, lacunar stroke},\n\tpages = {236--244},\n\tfile = {Full Text:/Users/mduering/Zotero/storage/KJ96SM4R/Wiegertjes et al. - 2021 - Differences in cerebral small vessel disease magne.pdf:application/pdf},\n}\n\n

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\n \n\n \n \n \n \n \n CT Hypoperfusion-Hypodensity Mismatch to Identify Patients With Acute Ischemic Stroke Within 4.5 Hours of Symptom Onset.\n \n \n \n\n\n \n Sporns, P. B.; Kemmling, A.; Minnerup, H.; Meyer, L.; Krogias, C.; Puetz, V.; Thierfelder, K.; Duering, M.; Kaiser, D.; Langner, S.; Massoth, C.; Brehm, A.; Rotkopf, L.; Kunz, W. G.; Karch, A.; Fiehler, J.; Heindel, W.; Schramm, P.; Royl, G.; Wiendl, H.; Psychogios, M.; and Minnerup, J.\n\n\n \n\n\n\n Neurology, 97(21): e2088–e2095. November 2021.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{sporns_ct_2021,\n\ttitle = {{CT} {Hypoperfusion}-{Hypodensity} {Mismatch} to {Identify} {Patients} {With} {Acute} {Ischemic} {Stroke} {Within} 4.5 {Hours} of {Symptom} {Onset}},\n\tvolume = {97},\n\tissn = {1526-632X},\n\tdoi = {10.1212/WNL.0000000000012891},\n\tabstract = {BACKGROUND AND OBJECTIVES: To test the hypothesis that CT hypoperfusion-hypodensity mismatch identifies patients with ischemic stroke within 4.5 hours of symptom onset.\nMETHODS: We therefore performed the Retrospective Multicenter Hypoperfusion-Hypodensity Mismatch for The identification of Patients With Stroke Within 4.5 Hours study of patients with acute ischemic stroke and known time of symptom onset. The predictive values of hypoperfusion-hypodensity mismatch for the identification of patients with symptom onset within 4.5 hours were the main outcome measure.\nRESULTS: Of 666 patients, 548 (82.3\\%) had multimodal CT within 4.5 hours and 118 (17.7\\%) beyond 4.5 hours. Hypoperfusion-hypodensity mismatch was visible in 516 (94.2\\%) patients with symptom onset within and in 30 (25.4\\%) patients beyond 4.5 hours. CT hypoperfusion-hypodensity mismatch identified patients within 4.5 hours of stroke onset with 94.2\\% (95\\% confidence interval [CI] 91.9\\%-95.8\\%) sensitivity, 74.6\\% (95\\% CI 66.0\\%-81.6\\%) specificity, 94.5\\% (95\\% CI 92.3\\%-96.1\\%) positive predictive value, and 73.3\\% (95\\% CI 64.8\\%-80.4\\%) negative predictive value. Interobserver agreement for hypoperfusion-hypodensity mismatch was substantial (κ = 0.61, 95\\% CI 0.53-0.69).\nDISCUSSION: Patients with acute ischemic stroke with absence of a hypodensity on native CT (NCCT) within the hypoperfused core lesion on perfusion CT (hypoperfusion-hypodensity mismatch) are likely to be within the time window of thrombolysis. Applying this method may guide the decision to use thrombolysis in patients with unknown time of stroke onset.\nTRIAL REGISTRATION INFORMATION: ClinicalTrials.gov Identifier: NCT04277728.\nCLASSIFICATION OF EVIDENCE: This study provides Class III evidence that CT hypoperfusion-hypodensity mismatch identifies patients with stroke within 4.5 hours of onset.},\n\tlanguage = {eng},\n\tnumber = {21},\n\tjournal = {Neurology},\n\tauthor = {Sporns, Peter B. and Kemmling, André and Minnerup, Heike and Meyer, Lennart and Krogias, Christos and Puetz, Volker and Thierfelder, Kolja and Duering, Marco and Kaiser, Daniel and Langner, Soenke and Massoth, Christina and Brehm, Alex and Rotkopf, Lukas and Kunz, Wolfgang G. and Karch, André and Fiehler, Jens and Heindel, Walter and Schramm, Peter and Royl, Georg and Wiendl, Heinz and Psychogios, Marios and Minnerup, Jens},\n\tmonth = nov,\n\tyear = {2021},\n\tpmid = {34649883},\n\tkeywords = {Stroke, Humans, Time Factors, Tomography, X-Ray Computed, Retrospective Studies, Brain Ischemia, Ischemic Stroke},\n\tpages = {e2088--e2095},\n}\n\n

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\n \n\n \n \n \n \n \n Assessing cortical cerebral microinfarcts on iron-sensitive MRI in cerebral small vessel disease.\n \n \n \n\n\n \n Wiegertjes, K.; Chan, K.; Telgte, A. T.; Gesierich, B.; Norris, D. G.; Klijn, C. J.; Duering, M.; Tuladhar, A. M.; Marques, J. P.; and Leeuw, F. d.\n\n\n \n\n\n\n J Cereb Blood Flow Metab, 41(12): 3391–3399. December 2021.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{wiegertjes_assessing_2021,\n\ttitle = {Assessing cortical cerebral microinfarcts on iron-sensitive {MRI} in cerebral small vessel disease},\n\tvolume = {41},\n\tissn = {1559-7016},\n\tdoi = {10.1177/0271678X211039609},\n\tabstract = {Recent studies suggest that a subset of cortical microinfarcts may be identifiable on T2* but invisible on T1 and T2 follow-up images. We aimed to investigate whether cortical microinfarcts are associated with iron accumulation after the acute stage. The RUN DMC - InTENse study is a serial MRI study including individuals with cerebral small vessel disease (SVD). 54 Participants underwent 10 monthly 3 T MRIs, including diffusion-weighted imaging, quantitative R1 (=1/T1), R2 (=1/T2), and R2* (=1/T2*) mapping, from which MRI parameters within areas corresponding to microinfarcts and control region of interests (ROIs) were retrieved within 16 participants. Finally, we compared pre- and post-lesional values with repeated measures ANOVA and post-hoc paired t-tests using the mean difference between lesion and control ROI values. We observed 21 acute cortical microinfarcts in 7 of the 54 participants (median age 69 years [IQR 66-74], 63\\% male). R2* maps demonstrated an increase in R2* values at the moment of the last available follow-up MRI (median [IQR], 5 [5-14] weeks after infarction) relative to prelesional values (p = .08), indicative of iron accumulation. Our data suggest that cortical microinfarcts are associated with increased R2* values, indicative of iron accumulation, possibly due to microhemorrhages, neuroinflammation or neurodegeneration, awaiting histopathological verification.},\n\tlanguage = {eng},\n\tnumber = {12},\n\tjournal = {J Cereb Blood Flow Metab},\n\tauthor = {Wiegertjes, Kim and Chan, Kwok-Shing and Telgte, Annemieke Ter and Gesierich, Benno and Norris, David G. and Klijn, Catharina Jm and Duering, Marco and Tuladhar, Anil M. and Marques, José P. and Leeuw, Frank-Erik de},\n\tmonth = dec,\n\tyear = {2021},\n\tpmid = {34415209},\n\tpmcid = {PMC8669205},\n\tkeywords = {cerebrovascular disease, small vessel disease, Aged, Diffusion Magnetic Resonance Imaging, Female, Humans, Male, magnetic resonance imaging, Cerebral Infarction, Cerebral Cortex, Cerebral Small Vessel Diseases, Iron, Acute ischemia, cortical microinfarcts},\n\tpages = {3391--3399},\n\tfile = {Full Text:/Users/mduering/Zotero/storage/MXKLRGJU/Wiegertjes et al. - 2021 - Assessing cortical cerebral microinfarcts on iron-.pdf:application/pdf},\n}\n\n

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\n \n\n \n \n \n \n \n Cerebrovascular disease in patients with cognitive impairment: A white paper from the ESO dementia committee - A practical point of view with suggestions for the management of cerebrovascular diseases in memory clinics.\n \n \n \n\n\n \n Verdelho, A.; Biessels, G. J.; Chabriat, H.; Charidimou, A.; Duering, M.; Godefroy, O.; Pantoni, L.; Pavlovic, A.; and Wardlaw, J.\n\n\n \n\n\n\n Eur Stroke J, 6(2): 111–119. June 2021.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{verdelho_cerebrovascular_2021,\n\ttitle = {Cerebrovascular disease in patients with cognitive impairment: {A} white paper from the {ESO} dementia committee - {A} practical point of view with suggestions for the management of cerebrovascular diseases in memory clinics},\n\tvolume = {6},\n\tissn = {2396-9881},\n\tshorttitle = {Cerebrovascular disease in patients with cognitive impairment},\n\tdoi = {10.1177/2396987321994294},\n\tabstract = {PURPOSE: Practical suggestions on clinical decisions about vascular disease management in patients with cognitive impairment are proposed.\nMETHODS: The document was produced by the Dementia Committee of the European Stroke Organisation (ESO) based on the evidence from the literature where available and on the clinical experience of the Committee members. This paper was endorsed by the ESO.\nFINDINGS: Vascular risk factors and cerebrovascular disease are frequent in patients with cognitive impairment. While acute stroke treatment has evolved substantially in last decades, evidence of management of cerebrovascular pathology beyond stroke in patients with cognitive impairment and dementia is quite limited. Additionally, trials to test some daily-life clinical decisions are likely to be complex, difficult to undertake and take many years to provide sufficient evidence to produce recommendations. This document was conceived to provide some suggestions until data from field trials are available. It was conceived for the use of clinicians from memory clinics or involved specifically in cognitive disorders, addressing practical aspects on diagnostic tools, vascular risk management and suggestions on some therapeutic options.\nDISCUSSION AND CONCLUSIONS: The authors did not aim to do an exhaustive or systematic review or to cover all current evidence. The document approach in a very practical way frequent issues concerning cerebrovascular disease in patients with known cognitive impairment.},\n\tlanguage = {eng},\n\tnumber = {2},\n\tjournal = {Eur Stroke J},\n\tauthor = {Verdelho, Ana and Biessels, Geert Jan and Chabriat, Hugues and Charidimou, Andreas and Duering, Marco and Godefroy, Olivier and Pantoni, Leonardo and Pavlovic, Aleksandra and Wardlaw, Joanna},\n\tmonth = jun,\n\tyear = {2021},\n\tpmid = {34414285},\n\tpmcid = {PMC8370070},\n\tkeywords = {cognitive impairment, dementia, small vessel disease, stroke, Cerebrovascular disease},\n\tpages = {111--119},\n\tfile = {Full Text:/Users/mduering/Zotero/storage/WNMQNJ68/Verdelho et al. - 2021 - Cerebrovascular disease in patients with cognitive.pdf:application/pdf},\n}\n\n

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\n \n\n \n \n \n \n \n RIPK1 or RIPK3 deletion prevents progressive neuronal cell death and improves memory function after traumatic brain injury.\n \n \n \n\n\n \n Wehn, A. C.; Khalin, I.; Duering, M.; Hellal, F.; Culmsee, C.; Vandenabeele, P.; Plesnila, N.; and Terpolilli, N. A.\n\n\n \n\n\n\n Acta Neuropathol Commun, 9(1): 138. August 2021.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{wehn_ripk1_2021,\n\ttitle = {{RIPK1} or {RIPK3} deletion prevents progressive neuronal cell death and improves memory function after traumatic brain injury},\n\tvolume = {9},\n\tissn = {2051-5960},\n\tdoi = {10.1186/s40478-021-01236-0},\n\tabstract = {Traumatic brain injury (TBI) causes acute and subacute tissue damage, but is also associated with chronic inflammation and progressive loss of brain tissue months and years after the initial event. The trigger and the subsequent molecular mechanisms causing chronic brain injury after TBI are not well understood. The aim of the current study was therefore to investigate the hypothesis that necroptosis, a form a programmed cell death mediated by the interaction of Receptor Interacting Protein Kinases (RIPK) 1 and 3, is involved in this process. Neuron-specific RIPK1- or RIPK3-deficient mice and their wild-type littermates were subjected to experimental TBI by controlled cortical impact. Posttraumatic brain damage and functional outcome were assessed longitudinally by repetitive magnetic resonance imaging (MRI) and behavioral tests (beam walk, Barnes maze, and tail suspension), respectively, for up to three months after injury. Thereafter, brains were investigated by immunohistochemistry for the necroptotic marker phosphorylated mixed lineage kinase like protein(pMLKL) and activation of astrocytes and microglia. WT mice showed progressive chronic brain damage in cortex and hippocampus and increased levels of pMLKL after TBI. Chronic brain damage occurred almost exclusively in areas with iron deposits and was significantly reduced in RIPK1- or RIPK3-deficient mice by up to 80\\%. Neuroprotection was accompanied by a reduction of astrocyte and microglia activation and improved memory function. The data of the current study suggest that progressive chronic brain damage and cognitive decline after TBI depend on the expression of RIPK1/3 in neurons. Hence, inhibition of necroptosis signaling may represent a novel therapeutic target for the prevention of chronic post-traumatic brain damage.},\n\tlanguage = {eng},\n\tnumber = {1},\n\tjournal = {Acta Neuropathol Commun},\n\tauthor = {Wehn, Antonia Clarissa and Khalin, Igor and Duering, Marco and Hellal, Farida and Culmsee, Carsten and Vandenabeele, Peter and Plesnila, Nikolaus and Terpolilli, Nicole Angela},\n\tmonth = aug,\n\tyear = {2021},\n\tpmid = {34404478},\n\tpmcid = {PMC8369637},\n\tkeywords = {Magnetic Resonance Imaging, Magnetic resonance imaging, Memory, Animals, Hippocampus, Mice, Brain, Neuroprotection, Cerebral Cortex, Astrocytes, Brain Injuries, Traumatic, Brain Injury, Chronic, Chronic posttraumatic brain damage, Ferroptosis, Hindlimb Suspension, Maze Learning, Mice, Knockout, Microglia, Necroptosis, Neurons, Protein Kinases, Receptor-Interacting Protein Serine-Threonine Kinases, Traumatic brain injury},\n\tpages = {138},\n\tfile = {Full Text:/Users/mduering/Zotero/storage/U65K9X7G/Wehn et al. - 2021 - RIPK1 or RIPK3 deletion prevents progressive neuro.pdf:application/pdf},\n}\n\n

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\n \n\n \n \n \n \n \n Imaging neurovascular, endothelial and structural integrity in preparation to treat small vessel diseases. The INVESTIGATE-SVDs study protocol. Part of the SVDs@Target project.\n \n \n \n\n\n \n Blair, G. W.; Stringer, M. S.; Thrippleton, M. J.; Chappell, F. M.; Shuler, K.; Hamilton, I.; Garcia, D. J.; Doubal, F. N.; Kopczak, A.; Duering, M.; Ingrisch, M.; Kerkhofs, D.; Staals, J.; van den Brink, H.; Arts, T.; Backes, W. H.; van Oostenbrugge, R.; Biessels, G. J.; Dichgans, M.; and Wardlaw, J. M.\n\n\n \n\n\n\n Cereb Circ Cogn Behav, 2: 100020. 2021.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{blair_imaging_2021,\n\ttitle = {Imaging neurovascular, endothelial and structural integrity in preparation to treat small vessel diseases. {The} {INVESTIGATE}-{SVDs} study protocol. {Part} of the {SVDs}@{Target} project},\n\tvolume = {2},\n\tissn = {2666-2450},\n\tdoi = {10.1016/j.cccb.2021.100020},\n\tabstract = {BACKGROUND: Sporadic cerebral small vessel disease (SVD) and cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) share clinical and neuroimaging features and possibly vascular dysfunction(s). However few studies have included both conditions, assessed more than one vascular dysfunction simultaneously, or included more than one centre. The INVESTIGATE-SVDs study will assess several cerebrovascular dysfunctions with MRI in participants with sporadic SVD or CADASIL at three European centres.\nMETHODS: We will recruit participants with sporadic SVDs (ischaemic stroke or vascular cognitive impairment) and CADASIL in Edinburgh, Maastricht and Munich. We will perform detailed clinical and neuropsychological phenotyping of the participants, and neuroimaging including structural MRI, cerebrovascular reactivity MRI (CVR: using carbon dioxide challenge), phase contrast MRI (arterial, venous and CSF flow and pulsatility), dynamic contrast-enhanced MRI (blood brain barrier (BBB) leakage) and multishell diffusion imaging. Participants will measure their blood pressure (BP) and its variability over seven days using a telemetric device.\nDISCUSSION: INVESTIGATE-SVDs will assess the relationships of BBB integrity, CVR, pulsatility and CSF flow in sporadic SVD and CADASIL using a multisite, multimodal MRI protocol. We aim to establish associations between these measures of vascular function, risk factors particularly BP and its variability, and brain parenchymal lesions in these two SVD phenotypes. Additionally we will test feasibility of complex multisite MRI, provide reliable intermediary outcome measures and sample size estimates for future trials.},\n\tlanguage = {eng},\n\tjournal = {Cereb Circ Cogn Behav},\n\tauthor = {Blair, Gordon W. and Stringer, Michael S. and Thrippleton, Michael J. and Chappell, Francesca M. and Shuler, Kirsten and Hamilton, Iona and Garcia, Daniela Jaime and Doubal, Fergus N. and Kopczak, Anna and Duering, Marco and Ingrisch, Michael and Kerkhofs, Danielle and Staals, Julie and van den Brink, Hilde and Arts, Tine and Backes, Walter H. and van Oostenbrugge, Robert and Biessels, Geert Jan and Dichgans, Martin and Wardlaw, Joanna M.},\n\tyear = {2021},\n\tpmid = {36324725},\n\tpmcid = {PMC9616332},\n\tkeywords = {MRI, CADASIL, GM, grey matter, WM, white matter, Cerebral small vessel disease, BBB, blood brain barrier, Blood-brain barrier permeability, BOLD, blood oxygen level dependent, BP, blood pressure, BPv, blood pressure variability, CADASIL, cerebral autosomal dominant arteriopathy with leukoencephalopathy and subcortical infarcts, CBF, cerebral blood flow, CERAD+, consortium to establish a disease registry for Alzheimer's disease plus battery, Cerebrovascular reactivity, CO2, carbon dioxide, CSF, cerebrospinal fluid, CVR, cerebrovascular reactivity, DCE, dynamic contrast enhanced, EtCO2, end-tidal carbon dioxide, MMSE, mini-mental state examination, MoCA, Montreal cognitive exam, NIHSS, national institute for health stroke scale, PI, pulsatility index, PVS, perivascular space, RSSI, recent small subcortical infarct, SVDs, small vessel diseases, WMH, white matter hyperintensity},\n\tpages = {100020},\n\tfile = {Full Text:/Users/mduering/Zotero/storage/WWY46G3V/Blair et al. - 2021 - Imaging neurovascular, endothelial and structural .pdf:application/pdf},\n}\n\n

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\n \n\n \n \n \n \n \n Pro-inflammatory Monocyte Phenotype During Acute Progression of Cerebral Small Vessel Disease.\n \n \n \n\n\n \n Noz, M. P.; Ter Telgte, A.; Wiegertjes, K.; Tuladhar, A. M.; Kaffa, C.; Kersten, S.; Bekkering, S.; van der Heijden, C. D. C. C.; Hoischen, A.; Joosten, L. A. B.; Netea, M. G.; Duering, M.; de Leeuw, F.; and Riksen, N. P.\n\n\n \n\n\n\n Front Cardiovasc Med, 8: 639361. 2021.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{noz_pro-inflammatory_2021,\n\ttitle = {Pro-inflammatory {Monocyte} {Phenotype} {During} {Acute} {Progression} of {Cerebral} {Small} {Vessel} {Disease}},\n\tvolume = {8},\n\tissn = {2297-055X},\n\tdoi = {10.3389/fcvm.2021.639361},\n\tabstract = {Background: The etiology of cerebral small vessel disease (SVD) remains elusive, though evidence is accumulating that inflammation contributes to its pathophysiology. We recently showed retrospectively that pro-inflammatory monocytes are associated with the long-term progression of white matter hyperintensities (WMHs). In this prospective high-frequency imaging study, we hypothesize that the incidence of SVD progression coincides with a pro-inflammatory monocyte phenotype. Methods: Individuals with SVD underwent monthly magnetic resonance imaging (MRI) for 10 consecutive months to detect SVD progression, defined as acute diffusion-weighted imaging-positive (DWI+) lesions, incident microbleeds, incident lacunes, and WMH progression. Circulating inflammatory markers were measured, cytokine production capacity of monocytes was assessed after ex vivo stimulation, and RNA sequencing was performed on isolated monocytes in a subset of participants. Results: 13 out of 35 individuals developed SVD progression (70 ± 6 years, 54\\% men) based on incident lesions (n = 7) and/or upper quartile WMH progression (n = 9). Circulating E-selectin concentration (p {\\textless} 0.05) and the cytokine production capacity of interleukin (IL)-1β and IL-6 (p {\\textless} 0.01) were higher in individuals with SVD progression. Moreover, RNA sequencing revealed a pro-inflammatory monocyte signature including genes involved in myelination, blood-brain barrier, and endothelial-leukocyte interaction. Conclusions: Circulating monocytes of individuals with progressive SVD have an inflammatory phenotype, characterized by an increased cytokine production capacity and a pro-inflammatory transcriptional signature.},\n\tlanguage = {eng},\n\tjournal = {Front Cardiovasc Med},\n\tauthor = {Noz, Marlies P. and Ter Telgte, Annemieke and Wiegertjes, Kim and Tuladhar, Anil M. and Kaffa, Charlotte and Kersten, Simone and Bekkering, Siroon and van der Heijden, Charlotte D. C. C. and Hoischen, Alexander and Joosten, Leo A. B. and Netea, Mihai G. and Duering, Marco and de Leeuw, Frank-Erik and Riksen, Niels P.},\n\tyear = {2021},\n\tpmid = {34055930},\n\tpmcid = {PMC8155247},\n\tkeywords = {cerebral small vessel disease, magnetic resonance imaging, inflammation, innate immunity, monocyte},\n\tpages = {639361},\n\tfile = {Full Text:/Users/mduering/Zotero/storage/ACTQSVAG/Noz et al. - 2021 - Pro-inflammatory Monocyte Phenotype During Acute P.pdf:application/pdf},\n}\n\n

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\n \n\n \n \n \n \n \n Cognition mediates the relation between structural network efficiency and gait in small vessel disease.\n \n \n \n\n\n \n Cai, M.; Jacob, M. A.; Norris, D. G.; Duering, M.; de Leeuw, F.; and Tuladhar, A. M.\n\n\n \n\n\n\n Neuroimage Clin, 30: 102667. 2021.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{cai_cognition_2021,\n\ttitle = {Cognition mediates the relation between structural network efficiency and gait in small vessel disease},\n\tvolume = {30},\n\tissn = {2213-1582},\n\tdoi = {10.1016/j.nicl.2021.102667},\n\tabstract = {Cerebral small vessel disease (SVD), including white matter hyperintensities (WMH), microbleeds, lacunes, was related to gait disturbances, while the underlying mechanism is unclear. Here, we investigated the relation between structural network efficiency, cognition and gait performance in 272 elderly subjects with SVD. All participants underwent 1.5 T MRI, gait and neuropsychological assessment. Conventional MRI markers for SVD, i.e. WMH volume, number of lacunes and microbleeds, were assessed. Diffusion tensor imaging-based tractography was used to reconstruct the brain network for each individual, followed by graph-theoretical analyses to compute the well-established network measure, global efficiency. We found that lower global efficiency was associated with worse gait performance, including slower gait speed and shorter stride length, independent of conventional MRI markers for SVD. This association was partly mediated via cognitive function. We identified subnetworks of white matter connections associated with gait and cognition, characterized by dominant involvement of frontal tracts. Our findings suggest that network disruption is associated with gait disturbances through cognitive dysfunction in elderly with SVD. Gait is a highly cognitive process and the crucial role of cognition should be considered when investigating gait disturbances in the elderly with SVD.},\n\tlanguage = {eng},\n\tjournal = {Neuroimage Clin},\n\tauthor = {Cai, Mengfei and Jacob, Mina A. and Norris, David G. and Duering, Marco and de Leeuw, Frank-Erik and Tuladhar, Anil M.},\n\tyear = {2021},\n\tpmid = {33887698},\n\tpmcid = {PMC8082689},\n\tkeywords = {Cognition, Small vessel disease, Aged, Diffusion Tensor Imaging, Humans, Magnetic Resonance Imaging, White Matter, Cerebral Small Vessel Diseases, Gait, Network efficiency},\n\tpages = {102667},\n}\n\n

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\n \n\n \n \n \n \n \n Zooming in on cerebral small vessel function in small vessel diseases with 7T MRI: Rationale and design of the \"ZOOM@SVDs\" study.\n \n \n \n\n\n \n van den Brink, H.; Kopczak, A.; Arts, T.; Onkenhout, L.; Siero, J. C. W.; Zwanenburg, J. J. M.; Duering, M.; Blair, G. W.; Doubal, F. N.; Stringer, M. S.; Thrippleton, M. J.; Kuijf, H. J.; de Luca, A.; Hendrikse, J.; Wardlaw, J. M.; Dichgans, M.; Biessels, G. J.; and SVDs@target group\n\n\n \n\n\n\n Cereb Circ Cogn Behav, 2: 100013. 2021.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{van_den_brink_zooming_2021,\n\ttitle = {Zooming in on cerebral small vessel function in small vessel diseases with {7T} {MRI}: {Rationale} and design of the "{ZOOM}@{SVDs}" study},\n\tvolume = {2},\n\tissn = {2666-2450},\n\tshorttitle = {Zooming in on cerebral small vessel function in small vessel diseases with {7T} {MRI}},\n\tdoi = {10.1016/j.cccb.2021.100013},\n\tabstract = {BACKGROUND: Cerebral small vessel diseases (SVDs) are a major cause of stroke and dementia. Yet, specific treatment strategies are lacking in part because of a limited understanding of the underlying disease processes. There is therefore an urgent need to study SVDs at their core, the small vessels themselves.\nOBJECTIVE: This paper presents the rationale and design of the ZOOM@SVDs study, which aims to establish measures of cerebral small vessel dysfunction on 7T MRI as novel disease markers of SVDs.\nMETHODS: ZOOM@SVDs is a prospective observational cohort study with two years follow-up. ZOOM@SVDs recruits participants with Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy (CADASIL, N = 20), sporadic SVDs (N = 60), and healthy controls (N = 40). Participants undergo 7T brain MRI to assess different aspects of small vessel function including small vessel reactivity, cerebral perforating artery flow, and pulsatility. Extensive work-up at baseline and follow-up further includes clinical and neuropsychological assessment as well as 3T brain MRI to assess conventional SVD imaging markers. Measures of small vessel dysfunction are compared between patients and controls, and related to the severity of clinical and conventional MRI manifestations of SVDs.\nDISCUSSION: ZOOM@SVDs will deliver novel markers of cerebral small vessel function in patients with monogenic and sporadic forms of SVDs, and establish their relation with disease burden and progression. These small vessel markers can support etiological studies in SVDs and may serve as surrogate outcome measures in future clinical trials to show target engagement of drugs directed at the small vessels.},\n\tlanguage = {eng},\n\tjournal = {Cereb Circ Cogn Behav},\n\tauthor = {van den Brink, Hilde and Kopczak, Anna and Arts, Tine and Onkenhout, Laurien and Siero, Jeroen C. W. and Zwanenburg, Jaco J. M. and Duering, Marco and Blair, Gordon W. and Doubal, Fergus N. and Stringer, Michael S. and Thrippleton, Michael J. and Kuijf, Hugo J. and de Luca, Alberto and Hendrikse, Jeroen and Wardlaw, Joanna M. and Dichgans, Martin and Biessels, Geert Jan and {SVDs@target group}},\n\tyear = {2021},\n\tpmid = {36324717},\n\tpmcid = {PMC9616370},\n\tkeywords = {Stroke, CADASIL, Cerebral small vessel disease, ASL, Arterial Spin Labeling, BOLD, Blood Oxygenation Level-Dependent, CADASIL, Cerebral Autosomal Dominant Arteriopathy with Leukoencephalopathy and Subcortical Infarcts, CDR, Clinical Dementia Rating scale, CERAD+, Consortium to Establish a Disease Registry for Alzheimer's Disease Plus battery, CES-D, Center for Epidemiologic Studies Depression Scale, CO2, Carbon Dioxide, CSF, Cerebrospinal Fluid, DTI, Diffusion Tensor Imaging, EPIC, European Prospective Investigation into Cancer and Nutrition, EtCO2, End-tidal Carbon Dioxide, FLAIR, Fluid Attenuated Inversion Recovery, fMRI, Functional Magnetic Resonance Imaging, FOV, Field Of View, FWHM, Full-Width-at-Half-Maximum, GE, Gradient Echo, GM, Grey Matter, GPRS, General Packet Radio Service, High field strength MRI, HRF, Hemodynamic Response Function, LMU, Ludwig-Maximilians-Universität, MMSE, Mini-Mental State Examination, NAWM, Normal Appearing White Matter, NIHSS, National Institute for Health Stroke Scale, PI, Pulsatility Index, ROI, Region Of Interest, Small vessel function, Sporadic SVD, SPPB, Short Physical Performance Battery, SVDs, Small Vessel Diseases, SWI, Susceptibility Weighted Imaging, TE, Echo Time, TI, Inversion Time, TR, Repetition Time, TSE, Turbo Spin Echo, UMCU, University Medical Center Utrecht, Vmax, Maximum velocity, Vmean, Mean velocity, Vmin, Minimum velocity, WM, White Matter, WMH, White Matter Hyperintensity},\n\tpages = {100013},\n}\n\n

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\n \n\n \n \n \n \n \n Multi-shell diffusion MRI models for white matter characterization in cerebral small vessel disease.\n \n \n \n\n\n \n Konieczny, M. J.; Dewenter, A.; Telgte, A. T.; Gesierich, B.; Wiegertjes, K.; Finsterwalder, S.; Kopczak, A.; Hubner, M.; Malik, R.; Tuladhar, A. M.; Marques, J. P.; Norris, D. G.; Koch, A.; Dietrich, O.; Ewers, M.; Schmidt, R.; de Leeuw, F. E.; and Duering, M.\n\n\n \n\n\n\n Neurology. November 2020.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{konieczny_multi-shell_2020,\n\ttitle = {Multi-shell diffusion {MRI} models for white matter characterization in cerebral small vessel disease},\n\tissn = {1526-632X (Electronic) 0028-3878 (Linking)},\n\tdoi = {10.1212/WNL.0000000000011213},\n\tabstract = {OBJECTIVE: To test the hypothesis that multi-shell diffusion models improve the characterization of microstructural alterations in cerebral small vessel disease (SVD), we assessed associations with processing speed performance, longitudinal change and reproducibility of diffusion metrics. METHODS: We included 50 sporadic and 59 genetically defined SVD patients (CADASIL) with cognitive testing and standardized 3T MRI, including multi-shell diffusion imaging. We applied the simple diffusion tensor imaging (DTI) model and 2 advanced models: diffusion kurtosis imaging (DKI) and neurite orientation dispersion and density imaging (NODDI). Linear regression and multivariable random forest regression (including conventional SVD markers) were used to determine associations between diffusion metrics and processing speed performance. The detection of short-term disease progression was assessed by linear mixed models in 49 sporadic SVD patients with longitudinal high-frequency imaging (in total 459 MRIs). Inter-site reproducibility was determined in 10 CADASIL patients scanned back-to-back on 2 different 3T MRI scanners. RESULTS: Metrics from DKI showed the strongest associations with processing speed performance (R (2) up to 21\\%) and the largest added benefit on top of conventional SVD imaging markers in sporadic SVD and CADASIL patients with lower SVD burden. Several metrics from DTI and DKI performed similarly in detecting disease progression. Reproducibility was excellent (intraclass correlation coefficient {\\textgreater}0.93) for DTI and DKI metrics. NODDI metrics were less reproducible. CONCLUSION: Multi-shell diffusion imaging and DKI improve the detection and characterization of cognitively relevant microstructural white matter alterations in SVD. Excellent reproducibility of diffusion metrics endorses their use as SVD markers in research and clinical care. Our publicly available inter-site dataset facilitates future studies. CLASSIFICATION OF EVIDENCE: This study provides Class I evidence that in patients with SVD, diffusion MRI metrics are associated with processing speed performance.},\n\tjournal = {Neurology},\n\tauthor = {Konieczny, M. J. and Dewenter, A. and Telgte, A. T. and Gesierich, B. and Wiegertjes, K. and Finsterwalder, S. and Kopczak, A. and Hubner, M. and Malik, R. and Tuladhar, A. M. and Marques, J. P. and Norris, D. G. and Koch, A. and Dietrich, O. and Ewers, M. and Schmidt, R. and de Leeuw, F. E. and Duering, M.},\n\tmonth = nov,\n\tyear = {2020},\n\tpmid = {33199431},\n\tkeywords = {Adult, Aged, Diffusion Magnetic Resonance Imaging, Diffusion Tensor Imaging, Disease Progression, Female, Humans, Image Processing, Computer-Assisted, Male, Middle Aged, White Matter, Cerebral Hemorrhage, Cerebral Small Vessel Diseases, CADASIL, Stroke, Lacunar, Leukoaraiosis},\n}\n\n

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\n OBJECTIVE: To test the hypothesis that multi-shell diffusion models improve the characterization of microstructural alterations in cerebral small vessel disease (SVD), we assessed associations with processing speed performance, longitudinal change and reproducibility of diffusion metrics. METHODS: We included 50 sporadic and 59 genetically defined SVD patients (CADASIL) with cognitive testing and standardized 3T MRI, including multi-shell diffusion imaging. We applied the simple diffusion tensor imaging (DTI) model and 2 advanced models: diffusion kurtosis imaging (DKI) and neurite orientation dispersion and density imaging (NODDI). Linear regression and multivariable random forest regression (including conventional SVD markers) were used to determine associations between diffusion metrics and processing speed performance. The detection of short-term disease progression was assessed by linear mixed models in 49 sporadic SVD patients with longitudinal high-frequency imaging (in total 459 MRIs). Inter-site reproducibility was determined in 10 CADASIL patients scanned back-to-back on 2 different 3T MRI scanners. RESULTS: Metrics from DKI showed the strongest associations with processing speed performance (R (2) up to 21%) and the largest added benefit on top of conventional SVD imaging markers in sporadic SVD and CADASIL patients with lower SVD burden. Several metrics from DTI and DKI performed similarly in detecting disease progression. Reproducibility was excellent (intraclass correlation coefficient \\textgreater0.93) for DTI and DKI metrics. NODDI metrics were less reproducible. CONCLUSION: Multi-shell diffusion imaging and DKI improve the detection and characterization of cognitively relevant microstructural white matter alterations in SVD. Excellent reproducibility of diffusion metrics endorses their use as SVD markers in research and clinical care. Our publicly available inter-site dataset facilitates future studies. CLASSIFICATION OF EVIDENCE: This study provides Class I evidence that in patients with SVD, diffusion MRI metrics are associated with processing speed performance.\n

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\n \n\n \n \n \n \n \n Small vessel disease more than Alzheimer's disease determines diffusion MRI alterations in memory clinic patients.\n \n \n \n\n\n \n Finsterwalder, S.; Vlegels, N.; Gesierich, B.; Araque Caballero, M. A.; Weaver, N. A.; Franzmeier, N.; Georgakis, M. K.; Konieczny, M. J.; Koek, H. L.; Dominantly Inherited Alzheimer, N.; Karch, C. M.; Graff-Radford, N. R.; Salloway, S.; Oh, H.; Allegri, R. F.; Chhatwal, J. P.; study group , D.; Jessen, F.; Duzel, E.; Dobisch, L.; Metzger, C.; Peters, O.; Incesoy, E. I.; Priller, J.; Spruth, E. J.; Schneider, A.; Fliessbach, K.; Buerger, K.; Janowitz, D.; Teipel, S. J.; Kilimann, I.; Laske, C.; Buchmann, M.; Heneka, M. T.; Brosseron, F.; Spottke, A.; Roy, N.; Ertl-Wagner, B.; Scheffler, K.; Alzheimer's Disease Neuroimaging, I.; Utrecht, V. C. I. s. g.; Seo, S. W.; Kim, Y.; Na, D. L.; Kim, H. J.; Jang, H.; Ewers, M.; Levin, J.; Schmidt, R.; Pasternak, O.; Dichgans, M.; Biessels, G. J.; and Duering, M.\n\n\n \n\n\n\n Alzheimers Dement, 16(11): 1504–1514. November 2020.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{finsterwalder_small_2020,\n\ttitle = {Small vessel disease more than {Alzheimer}'s disease determines diffusion {MRI} alterations in memory clinic patients},\n\tvolume = {16},\n\tissn = {1552-5279 (Electronic) 1552-5260 (Linking)},\n\tdoi = {10.1002/alz.12150},\n\tabstract = {INTRODUCTION: Microstructural alterations as assessed by diffusion tensor imaging (DTI) are key findings in both Alzheimer's disease (AD) and small vessel disease (SVD). We determined the contribution of each of these conditions to diffusion alterations. METHODS: We studied six samples (N = 365 participants) covering the spectrum of AD and SVD, including genetically defined samples. We calculated diffusion measures from DTI and free water imaging. Simple linear, multivariable random forest, and voxel-based regressions were used to evaluate associations between AD biomarkers (amyloid beta, tau), SVD imaging markers, and diffusion measures. RESULTS: SVD markers were strongly associated with diffusion measures and showed a higher contribution than AD biomarkers in multivariable analysis across all memory clinic samples. Voxel-wise analyses between tau and diffusion measures were not significant. DISCUSSION: In memory clinic patients, the effect of SVD on diffusion alterations largely exceeds the effect of AD, supporting the value of diffusion measures as markers of SVD.},\n\tnumber = {11},\n\tjournal = {Alzheimers Dement},\n\tauthor = {Finsterwalder, S. and Vlegels, N. and Gesierich, B. and Araque Caballero, M. A. and Weaver, N. A. and Franzmeier, N. and Georgakis, M. K. and Konieczny, M. J. and Koek, H. L. and Dominantly Inherited Alzheimer, Network and Karch, C. M. and Graff-Radford, N. R. and Salloway, S. and Oh, H. and Allegri, R. F. and Chhatwal, J. P. and Delcode study group and Jessen, F. and Duzel, E. and Dobisch, L. and Metzger, C. and Peters, O. and Incesoy, E. I. and Priller, J. and Spruth, E. J. and Schneider, A. and Fliessbach, K. and Buerger, K. and Janowitz, D. and Teipel, S. J. and Kilimann, I. and Laske, C. and Buchmann, M. and Heneka, M. T. and Brosseron, F. and Spottke, A. and Roy, N. and Ertl-Wagner, B. and Scheffler, K. and Alzheimer's Disease Neuroimaging, Initiative and Utrecht, V. C. I. study group and Seo, S. W. and Kim, Y. and Na, D. L. and Kim, H. J. and Jang, H. and Ewers, M. and Levin, J. and Schmidt, R. and Pasternak, O. and Dichgans, M. and Biessels, G. J. and Duering, M.},\n\tmonth = nov,\n\tyear = {2020},\n\tpmid = {32808747},\n\tpmcid = {PMC8102202},\n\tkeywords = {*Alzheimer's disease, *biomarker, *cerebral small vessel disease, *diffusion tensor imaging, *free water imaging, *white matter},\n\tpages = {1504--1514},\n}\n\n

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\n \n\n \n \n \n \n \n Alterations and test-retest reliability of functional connectivity network measures in cerebral small vessel disease.\n \n \n \n\n\n \n Gesierich, B.; Tuladhar, A. M.; Ter Telgte, A.; Wiegertjes, K.; Konieczny, M. J.; Finsterwalder, S.; Hubner, M.; Pirpamer, L.; Koini, M.; Abdulkadir, A.; Franzmeier, N.; Norris, D. G.; Marques, J. P.; Zu Eulenburg, P.; Ewers, M.; Schmidt, R.; de Leeuw, F. E.; and Duering, M.\n\n\n \n\n\n\n Hum Brain Mapp, 41(10): 2629–2641. February 2020.\n \n\n\n\n
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@article{gesierich_alterations_2020,\n\ttitle = {Alterations and test-retest reliability of functional connectivity network measures in cerebral small vessel disease},\n\tvolume = {41},\n\tissn = {1097-0193 (Electronic) 1065-9471 (Linking)},\n\tdoi = {10.1002/hbm.24967},\n\tabstract = {While structural network analysis consolidated the hypothesis of cerebral small vessel disease (SVD) being a disconnection syndrome, little is known about functional changes on the level of brain networks. In patients with genetically defined SVD (CADASIL, n = 41) and sporadic SVD (n = 46), we independently tested the hypothesis that functional networks change with SVD burden and mediate the effect of disease burden on cognitive performance, in particular slowing of processing speed. We further determined test-retest reliability of functional network measures in sporadic SVD patients participating in a high-frequency (monthly) serial imaging study (RUN DMC-InTENse, median: 8 MRIs per participant). Functional networks for the whole brain and major subsystems (i.e., default mode network, DMN; fronto-parietal task control network, FPCN; visual network, VN; hand somatosensory-motor network, HSMN) were constructed based on resting-state multi-band functional MRI. In CADASIL, global efficiency (a graph metric capturing network integration) of the DMN was lower in patients with high disease burden (standardized beta = -.44; p [corrected] = .035) and mediated the negative effect of disease burden on processing speed (indirect path: std. beta = -.20, p = .047; direct path: std. beta = -.19, p = .25; total effect: std. beta = -.39, p = .02). The corresponding analyses in sporadic SVD showed no effect. Intraclass correlations in the high-frequency serial MRI dataset of the sporadic SVD patients revealed poor test-retest reliability and analysis of individual variability suggested an influence of age, but not disease burden, on global efficiency. In conclusion, our results suggest that changes in functional connectivity networks mediate the effect of SVD-related brain damage on cognitive deficits. However, limited reliability of functional network measures, possibly due to age-related comorbidities, impedes the analysis in elderly SVD patients.},\n\tnumber = {10},\n\tjournal = {Hum Brain Mapp},\n\tauthor = {Gesierich, B. and Tuladhar, A. M. and Ter Telgte, A. and Wiegertjes, K. and Konieczny, M. J. and Finsterwalder, S. and Hubner, M. and Pirpamer, L. and Koini, M. and Abdulkadir, A. and Franzmeier, N. and Norris, D. G. and Marques, J. P. and Zu Eulenburg, P. and Ewers, M. and Schmidt, R. and de Leeuw, F. E. and Duering, M.},\n\tmonth = feb,\n\tyear = {2020},\n\tpmcid = {PMC7294060},\n\tpmid = {32087047},\n\tkeywords = {cerebrovascular disease, Adult, Aged, Diffusion Tensor Imaging, Female, Humans, Male, Middle Aged, cognition, functional brain imaging, functional networks, resting-state fMRI, test-retest reliability, Aged, 80 and over, Reproducibility of Results, Longitudinal Studies, Cross-Sectional Studies, Cerebral Small Vessel Diseases, Cognitive Dysfunction, CADASIL, Nerve Net, Connectome, Default Mode Network},\n\tpages = {2629--2641},\n}\n\n

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\n \n\n \n \n \n \n \n Patient-centered connectivity-based prediction of tau pathology spread in Alzheimer's disease.\n \n \n \n\n\n \n Franzmeier, N.; Dewenter, A.; Frontzkowski, L.; Dichgans, M.; Rubinski, A.; Neitzel, J.; Smith, R.; Strandberg, O.; Ossenkoppele, R.; Buerger, K.; Duering, M.; Hansson, O.; and Ewers, M.\n\n\n \n\n\n\n Sci Adv, 6(48). November 2020.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{franzmeier_patient-centered_2020,\n\ttitle = {Patient-centered connectivity-based prediction of tau pathology spread in {Alzheimer}'s disease},\n\tvolume = {6},\n\tissn = {2375-2548 (Electronic) 2375-2548 (Linking)},\n\tdoi = {10.1126/sciadv.abd1327},\n\tabstract = {In Alzheimer's disease (AD), the Braak staging scheme suggests a stereotypical tau spreading pattern that does, however, not capture interindividual variability in tau deposition. This complicates the prediction of tau spreading, which may become critical for defining individualized tau-PET readouts in clinical trials. Since tau is assumed to spread throughout connected regions, we used functional connectivity to improve tau spreading predictions over Braak staging methods. We included two samples with longitudinal tau-PET from controls and AD patients. Cross-sectionally, we found connectivity of tau epicenters (i.e., regions with earliest tau) to predict estimated tau spreading sequences. Longitudinally, we found tau accumulation rates to correlate with connectivity strength to patient-specific tau epicenters. A connectivity-based, patient-centered tau spreading model improved the assessment of tau accumulation rates compared to Braak stage-specific readouts and reduced sample sizes by {\\textasciitilde}40\\% in simulated tau-targeting interventions. Thus, connectivity-based tau spreading models may show utility in clinical trials.},\n\tnumber = {48},\n\tjournal = {Sci Adv},\n\tauthor = {Franzmeier, N. and Dewenter, A. and Frontzkowski, L. and Dichgans, M. and Rubinski, A. and Neitzel, J. and Smith, R. and Strandberg, O. and Ossenkoppele, R. and Buerger, K. and Duering, M. and Hansson, O. and Ewers, M.},\n\tmonth = nov,\n\tyear = {2020},\n\tpmcid = {PMC7695466},\n\tpmid = {33246962},\n\tkeywords = {Humans, Positron-Emission Tomography, Brain, Alzheimer Disease, tau Proteins, Patient-Centered Care},\n}\n\n

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\n \n\n \n \n \n \n \n Serum Neurofilament Light Chain Is Associated with Incident Lacunes in Progressive Cerebral Small Vessel Disease.\n \n \n \n\n\n \n Peters, N.; van Leijsen, E.; Tuladhar, A. M.; Barro, C.; Konieczny, M. J.; Ewers, M.; Lyrer, P.; Engelter, S. T.; Kuhle, J.; Duering, M.; and de Leeuw, F. E.\n\n\n \n\n\n\n J Stroke, 22(3): 369–376. September 2020.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{peters_serum_2020,\n\ttitle = {Serum {Neurofilament} {Light} {Chain} {Is} {Associated} with {Incident} {Lacunes} in {Progressive} {Cerebral} {Small} {Vessel} {Disease}},\n\tvolume = {22},\n\tissn = {2287-6391 (Print) 2287-6391 (Linking)},\n\tdoi = {10.5853/jos.2019.02845},\n\tabstract = {BACKGROUND AND PURPOSE: Serum neurofilament light (NfL)-chain is a circulating marker for neuroaxonal injury and is also associated with severity of cerebral small vessel disease (SVD) cross-sectionally. Here we explored the association of serum-NfL with imaging and cognitive measures in SVD longitudinally. METHODS: From 503 subjects with SVD, baseline and follow-up magnetic resonance imaging (MRI) was available for 264 participants (follow-up 8.7+/-0.2 years). Baseline serum-NfL was measured by an ultrasensitive single-molecule-assay. SVD-MRI-markers including white matter hyperintensity (WMH)-volume, mean diffusivity (MD), lacunes, and microbleeds were assessed at both timepoints. Cognitive testing was performed in 336 participants, including SVD-related domains as well as global cognition and memory. Associations with NfL were assessed using linear regression analyses and analysis of covariance (ANCOVA). RESULTS: Serum-NfL was associated with baseline WMH-volume, MD-values and presence of lacunes and microbleeds. SVD-related MRI- and cognitive measures showed progression during follow-up. NfL-levels were associated with future MRI-markers of SVD, including WMH, MD and lacunes. For the latter, this association was independent of baseline lacunes. Furthermore, NfL was associated with incident lacunes during follow-up (P=0.040). NfL-levels were associated with future SVD-related cognitive impairment (processing speed: beta=-0.159; 95\\% confidence interval [CI], -0.242 to -0.068; P=0.001; executive function beta=-0.095; 95\\% CI, -0.170 to -0.007; P=0.033), adjusted for age, sex, education, and depression. Dementia-risk increased with higher NfL-levels (hazard ratio, 5.0; 95\\% CI, 2.6 to 9.4; P{\\textless}0.001), however not after adjusting for age. CONCLUSIONS: Longitudinally, serum-NfL is associated with markers of SVD, especially with incident lacunes, and future cognitive impairment affecting various domains. NfL may potentially serve as an additional marker for disease monitoring and outcome in SVD, potentially capturing both vascular and neurodegenerative processes in the elderly.},\n\tnumber = {3},\n\tjournal = {J Stroke},\n\tauthor = {Peters, N. and van Leijsen, E. and Tuladhar, A. M. and Barro, C. and Konieczny, M. J. and Ewers, M. and Lyrer, P. and Engelter, S. T. and Kuhle, J. and Duering, M. and de Leeuw, F. E.},\n\tmonth = sep,\n\tyear = {2020},\n\tpmcid = {PMC7568975},\n\tpmid = {33053952},\n\tkeywords = {Stroke, Biomarkers, Magnetic resonance imaging, Dementia, Neurofilament, Small vessel diseases},\n\tpages = {369--376},\n}\n\n

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\n BACKGROUND AND PURPOSE: Serum neurofilament light (NfL)-chain is a circulating marker for neuroaxonal injury and is also associated with severity of cerebral small vessel disease (SVD) cross-sectionally. Here we explored the association of serum-NfL with imaging and cognitive measures in SVD longitudinally. METHODS: From 503 subjects with SVD, baseline and follow-up magnetic resonance imaging (MRI) was available for 264 participants (follow-up 8.7+/-0.2 years). Baseline serum-NfL was measured by an ultrasensitive single-molecule-assay. SVD-MRI-markers including white matter hyperintensity (WMH)-volume, mean diffusivity (MD), lacunes, and microbleeds were assessed at both timepoints. Cognitive testing was performed in 336 participants, including SVD-related domains as well as global cognition and memory. Associations with NfL were assessed using linear regression analyses and analysis of covariance (ANCOVA). RESULTS: Serum-NfL was associated with baseline WMH-volume, MD-values and presence of lacunes and microbleeds. SVD-related MRI- and cognitive measures showed progression during follow-up. NfL-levels were associated with future MRI-markers of SVD, including WMH, MD and lacunes. For the latter, this association was independent of baseline lacunes. Furthermore, NfL was associated with incident lacunes during follow-up (P=0.040). NfL-levels were associated with future SVD-related cognitive impairment (processing speed: beta=-0.159; 95% confidence interval [CI], -0.242 to -0.068; P=0.001; executive function beta=-0.095; 95% CI, -0.170 to -0.007; P=0.033), adjusted for age, sex, education, and depression. Dementia-risk increased with higher NfL-levels (hazard ratio, 5.0; 95% CI, 2.6 to 9.4; P\\textless0.001), however not after adjusting for age. CONCLUSIONS: Longitudinally, serum-NfL is associated with markers of SVD, especially with incident lacunes, and future cognitive impairment affecting various domains. NfL may potentially serve as an additional marker for disease monitoring and outcome in SVD, potentially capturing both vascular and neurodegenerative processes in the elderly.\n

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\n \n\n \n \n \n \n \n The human corticocortical vestibular network.\n \n \n \n\n\n \n Raiser, T. M.; Flanagin, V. L.; Duering, M.; van Ombergen, A.; Ruehl, R. M.; and Zu Eulenburg, P.\n\n\n \n\n\n\n Neuroimage, 223: 117362. September 2020.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{raiser_human_2020,\n\ttitle = {The human corticocortical vestibular network},\n\tvolume = {223},\n\tissn = {1095-9572 (Electronic) 1053-8119 (Linking)},\n\tdoi = {10.1016/j.neuroimage.2020.117362},\n\tabstract = {BACKGROUND: Little is known about the cortical organization of human vestibular information processing. Instead of a dedicated primary vestibular cortex, a distributed network of regions across the cortex respond to vestibular input. The aim of this study is to characterize the human corticocortical vestibular network and compare it to established results in non-human primates. METHODS: We collected high-resolution multi-shell diffusion-weighted (DWI) and state-of-the-art resting-state functional MR images of 29 right-handed normal subjects. Ten cortical vestibular regions per hemisphere were predefined from previous vestibular stimulation studies and applied as regions of interest. Four different structural corticocortical vestibular networks accounting for relevant constraints were investigated. The analyses included the investigation of common network measures and hemispheric differences for functional and structural connectivity patterns alike. In addition, the results of the structural vestibular network were compared to findings previously reported in non-human primates with respect to tracer injections (Guldin and Grusser, 1998). RESULTS: All structural networks independent of the applied constraints showed a recurring subdivision into identical three submodules. The structural human network was characterized by a predominantly intrahemispheric connectivity, whereas the functional pattern highlighted a strong connectivity for all homotopic nodes. A significant laterality preference towards the right hemisphere can be observed throughout the analyses: (1) with larger nodes, (2) stronger connectivity values structurally and functionally, and (3) a higher functional relevance. Similar connectivity patterns to non-human primate data were found in sensory and higher association cortices rather than premotor and motor areas. CONCLUSION: Our analysis delineated a remarkably stable organization of cortical vestibular connectivity. Differences found between primate species may be attributed to phylogeny as well as methodological differences. With our work we solidified evidence for lateralization within the corticocortical vestibular network. Our results might explain why cortical lesions in humans do not lead to persistent vestibular symptoms. Redundant structural routing throughout the network and a high-degree functional connectivity may buffer the network and reestablish network integrity quickly in case of injury.},\n\tjournal = {Neuroimage},\n\tauthor = {Raiser, T. M. and Flanagin, V. L. and Duering, M. and van Ombergen, A. and Ruehl, R. M. and Zu Eulenburg, P.},\n\tmonth = sep,\n\tyear = {2020},\n\tpmid = {32919059},\n\tkeywords = {Adult, Diffusion Magnetic Resonance Imaging, Female, Humans, Male, Young Adult, Comparative connectomics, Functional network, Structural network, Vestibular system, Brain Mapping, Functional Laterality, Cerebral Cortex, Neural Pathways, Vestibule, Labyrinth},\n\tpages = {117362},\n}\n\n

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\n BACKGROUND: Little is known about the cortical organization of human vestibular information processing. Instead of a dedicated primary vestibular cortex, a distributed network of regions across the cortex respond to vestibular input. The aim of this study is to characterize the human corticocortical vestibular network and compare it to established results in non-human primates. METHODS: We collected high-resolution multi-shell diffusion-weighted (DWI) and state-of-the-art resting-state functional MR images of 29 right-handed normal subjects. Ten cortical vestibular regions per hemisphere were predefined from previous vestibular stimulation studies and applied as regions of interest. Four different structural corticocortical vestibular networks accounting for relevant constraints were investigated. The analyses included the investigation of common network measures and hemispheric differences for functional and structural connectivity patterns alike. In addition, the results of the structural vestibular network were compared to findings previously reported in non-human primates with respect to tracer injections (Guldin and Grusser, 1998). RESULTS: All structural networks independent of the applied constraints showed a recurring subdivision into identical three submodules. The structural human network was characterized by a predominantly intrahemispheric connectivity, whereas the functional pattern highlighted a strong connectivity for all homotopic nodes. A significant laterality preference towards the right hemisphere can be observed throughout the analyses: (1) with larger nodes, (2) stronger connectivity values structurally and functionally, and (3) a higher functional relevance. Similar connectivity patterns to non-human primate data were found in sensory and higher association cortices rather than premotor and motor areas. CONCLUSION: Our analysis delineated a remarkably stable organization of cortical vestibular connectivity. Differences found between primate species may be attributed to phylogeny as well as methodological differences. With our work we solidified evidence for lateralization within the corticocortical vestibular network. Our results might explain why cortical lesions in humans do not lead to persistent vestibular symptoms. Redundant structural routing throughout the network and a high-degree functional connectivity may buffer the network and reestablish network integrity quickly in case of injury.\n

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\n \n\n \n \n \n \n \n Global multisensory reorganization after vestibular brain stem stroke.\n \n \n \n\n\n \n Conrad, J.; Habs, M.; Boegle, R.; Ertl, M.; Kirsch, V.; Stefanova-Brostek, I.; Eren, O.; Becker-Bense, S.; Stephan, T.; Wollenweber, F.; Duering, M.; Zu Eulenburg, P.; and Dieterich, M.\n\n\n \n\n\n\n Ann Clin Transl Neurol, 7(10): 1788–1801. August 2020.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{conrad_global_2020,\n\ttitle = {Global multisensory reorganization after vestibular brain stem stroke},\n\tvolume = {7},\n\tissn = {2328-9503 (Electronic) 2328-9503 (Linking)},\n\tdoi = {10.1002/acn3.51161},\n\tabstract = {OBJECTIVE: Patients with acute central vestibular syndrome suffer from vertigo, spontaneous nystagmus, postural instability with lateral falls, and tilts of visual vertical. Usually, these symptoms compensate within months. The mechanisms of compensation in vestibular infarcts are yet unclear. This study focused on structural changes in gray and white matter volume that accompany clinical compensation. METHODS: We studied patients with acute unilateral brain stem infarcts prospectively over 6 months. Structural changes were compared between the acute phase and follow-up with a group of healthy controls using voxel-based morphometry. RESULTS: Restitution of vestibular function following brain stem infarcts was accompanied by downstream structural changes in multisensory cortical areas. The changes depended on the location of the infarct along the vestibular pathways in patients with pathological tilts of the SVV and on the quality of the vestibular percept (rotatory vs graviceptive) in patients with pontomedullary infarcts. Patients with pontomedullary infarcts with vertigo or spontaneous nystagmus showed volumetric increases in vestibular parietal opercular multisensory and (retro-) insular areas with right-sided preference. Compensation of graviceptive deficits was accompanied by adaptive changes in multiple multisensory vestibular areas in both hemispheres in lower brain stem infarcts and by additional changes in the motor system in upper brain stem infarcts. INTERPRETATION: This study demonstrates multisensory neuroplasticity in both hemispheres along with the clinical compensation of vestibular deficits following unilateral brain stem infarcts. The data further solidify the concept of a right-hemispheric specialization for core vestibular processing. The identification of cortical structures involved in central compensation could serve as a platform to launch novel rehabilitative treatments such as transcranial stimulations.},\n\tnumber = {10},\n\tjournal = {Ann Clin Transl Neurol},\n\tauthor = {Conrad, J. and Habs, M. and Boegle, R. and Ertl, M. and Kirsch, V. and Stefanova-Brostek, I. and Eren, O. and Becker-Bense, S. and Stephan, T. and Wollenweber, F. and Duering, M. and Zu Eulenburg, P. and Dieterich, M.},\n\tmonth = aug,\n\tyear = {2020},\n\tpmcid = {PMC7545594},\n\tpmid = {32856758},\n\tkeywords = {Adult, Female, Humans, Male, Middle Aged, Functional Laterality, Brain, Brain Stem, Vestibule, Labyrinth, Vertigo, Brain Stem Infarctions, Neuronal Plasticity},\n\tpages = {1788--1801},\n}\n\n

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\n \n\n \n \n \n \n \n Circulating Metabolites Differentiate Acute Ischemic Stroke from Stroke Mimics.\n \n \n \n\n\n \n Tiedt, S.; Brandmaier, S.; Kollmeier, H.; Duering, M.; Artati, A.; Adamski, J.; Klein, M.; Liebig, T.; Holdt, L. M.; Teupser, D.; Wang-Sattler, R.; Schwedhelm, E.; Gieger, C.; and Dichgans, M.\n\n\n \n\n\n\n Ann Neurol, 88(4): 736–746. August 2020.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{tiedt_circulating_2020,\n\ttitle = {Circulating {Metabolites} {Differentiate} {Acute} {Ischemic} {Stroke} from {Stroke} {Mimics}},\n\tvolume = {88},\n\tissn = {1531-8249 (Electronic) 0364-5134 (Linking)},\n\tdoi = {10.1002/ana.25859},\n\tabstract = {OBJECTIVE: Early discrimination of patients with ischemic stroke (IS) from stroke mimics (SMs) poses a diagnostic challenge. The circulating metabolome might reflect pathophysiological events related to acute IS. Here, we investigated the utility of early metabolic changes for differentiating IS from SM. METHODS: We performed untargeted metabolomics on serum samples obtained from patients with IS (N = 508) and SM (N = 349; defined by absence of a diffusion weighted imaging [DWI] positive lesion on magnetic resonance imaging [MRI]) who presented to the hospital within 24 hours after symptom onset (median time from symptom onset to blood sampling = 3.3 hours; interquartile range [IQR] = 1.6-6.7 hours) and from neurologically normal controls (NCs; N = 112). We compared diagnostic groups in a discovery-validation approach by applying multivariable linear regression models, machine learning techniques, and propensity score matching. We further performed a targeted look-up of published metabolite sets. RESULTS: Levels of 41 metabolites were significantly associated with IS compared to NCs. The top metabolites showing the highest value in separating IS from SMs were asymmetrical and symmetrical dimethylarginine, pregnenolone sulfate, and adenosine. Together, these 4 metabolites differentiated patients with IS from SMs with an area under the curve (AUC) of 0.90 in the replication sample, which was superior to multimodal cranial computed tomography (CT; AUC = 0.80) obtained for routine diagnostics. They were further superior to previously published metabolite sets detected in our samples. All 4 metabolites returned to control levels by day 90. INTERPRETATION: A set of 4 metabolites with known biological effects relevant to stroke pathophysiology shows unprecedented utility to identify patients with IS upon hospital arrival, thus encouraging further investigation, including multicenter studies. ANN NEUROL 2020.},\n\tnumber = {4},\n\tjournal = {Ann Neurol},\n\tauthor = {Tiedt, S. and Brandmaier, S. and Kollmeier, H. and Duering, M. and Artati, A. and Adamski, J. and Klein, M. and Liebig, T. and Holdt, L. M. and Teupser, D. and Wang-Sattler, R. and Schwedhelm, E. and Gieger, C. and Dichgans, M.},\n\tmonth = aug,\n\tyear = {2020},\n\tpmid = {32748431},\n\tkeywords = {Aged, Female, Humans, Male, Middle Aged, Biomarkers, Biomarkers/*blood, Diagnosis, Differential, Ischemic Stroke/*blood/*diagnosis, Metabolomics/methods, Sensitivity and Specificity, Ischemic Stroke, Metabolomics},\n\tpages = {736--746},\n}\n\n

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\n \n\n \n \n \n \n \n Broad phenotype of cysteine altering NOTCH3 variants in UK Biobank: CADASIL to non-penetrance.\n \n \n \n\n\n \n Rutten, J. W.; Hack, R. J.; Duering, M.; Gravesteijn, G. G.; Dauwerse, J. G.; Overzier, M.; van den Akker, E. B.; Slagboom, E.; Holstege, H.; Nho, K.; Saykin, A.; Dichgans, M.; Malik, R.; and Lesnik Oberstein, S. A. J.\n\n\n \n\n\n\n Neurology, 95(13): e1835–e1843. July 2020.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{rutten_broad_2020,\n\ttitle = {Broad phenotype of cysteine altering {NOTCH3} variants in {UK} {Biobank}: {CADASIL} to non-penetrance},\n\tvolume = {95},\n\tissn = {1526-632X (Electronic) 0028-3878 (Linking)},\n\tdoi = {10.1212/WNL.0000000000010525},\n\tabstract = {OBJECTIVE: To determine the small vessel disease spectrum associated with cysteine altering NOTCH3 variants in community dwelling individuals, by analyzing the clinical and neuroimaging features of UK Biobank participants harboring such variants. METHODS: The exome- and genome sequencing datasets of UK Biobank (n=50,000) and cohorts of cognitively healthy elderly (n=751) were queried for cysteine altering NOTCH3 variants. Brain MRI's of individuals harboring such variants were scored according to STRIVE criteria and clinical information was extracted using ICD-10 codes. Clinical and neuroimaging data were compared to age- and sex matched UK Biobank controls and clinically diagnosed patients from the Dutch CADASIL registry. RESULTS: We identified 108 individuals harboring a cysteine altering NOTCH3 variant (2.2/1000), of which 75\\% has a variant which has been previously reported in CADASIL pedigrees. Almost all variants were located in one of the NOTCH3 protein epidermal growth factor-like repeat domains 7-34. White matter hyperintensity lesion load was higher in individuals with NOTCH3 variants than in controls (p=0.006), but lower than in CADASIL patients with the same variants (p{\\textless}0.001). Almost half of the 24 individuals with brain MRI had a Fazekas score of 0 or 1 up to age 70. There was no increased risk of stroke. CONCLUSIONS: Although community dwelling individuals harboring a cysteine altering NOTCH3 variant have a higher small vessel disease MRI burden than controls, almost half have no MRI abnormalities up to age 70. This shows that NOTCH3 cysteine altering variants are associated with an extremely broad phenotypic spectrum, ranging from CADASIL to non-penetrance.},\n\tnumber = {13},\n\tjournal = {Neurology},\n\tauthor = {Rutten, J. W. and Hack, R. J. and Duering, M. and Gravesteijn, G. G. and Dauwerse, J. G. and Overzier, M. and van den Akker, E. B. and Slagboom, E. and Holstege, H. and Nho, K. and Saykin, A. and Dichgans, M. and Malik, R. and Lesnik Oberstein, S. A. J.},\n\tmonth = jul,\n\tyear = {2020},\n\tpmcid = {PMC7682826},\n\tpmid = {32732295},\n\tkeywords = {Adult, Aged, Female, Humans, Male, Middle Aged, Aged, 80 and over, Neuroimaging, Magnetic Resonance Imaging, Genotype, Receptor, Notch3, Age Factors, Biological Specimen Banks, Brain/pathology, CADASIL/*genetics/pathology, Case-Control Studies, Cysteine/metabolism, Ethnic Groups/genetics, Mutation, Netherlands, Penetrance, Receptor, Notch3/*genetics, Registries/*statistics \\& numerical data, United Kingdom, White Matter/pathology, Brain, White Matter, CADASIL, Cysteine, Ethnicity, Registries},\n\tpages = {e1835--e1843},\n}\n\n

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\n \n\n \n \n \n \n \n Cross-sectional and Longitudinal Assessment of Brain Iron Level in Alzheimer Disease Using 3-T MRI.\n \n \n \n\n\n \n Damulina, A.; Pirpamer, L.; Soellradl, M.; Sackl, M.; Tinauer, C.; Hofer, E.; Enzinger, C.; Gesierich, B.; Duering, M.; Ropele, S.; Schmidt, R.; and Langkammer, C.\n\n\n \n\n\n\n Radiology, 296(3): 192541. June 2020.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{damulina_cross-sectional_2020,\n\ttitle = {Cross-sectional and {Longitudinal} {Assessment} of {Brain} {Iron} {Level} in {Alzheimer} {Disease} {Using} 3-{T} {MRI}},\n\tvolume = {296},\n\tissn = {1527-1315 (Electronic) 0033-8419 (Linking)},\n\tdoi = {10.1148/radiol.2020192541},\n\tabstract = {Background Deep gray matter structures in patients with Alzheimer disease (AD) contain higher brain iron concentrations. However, few studies have included neocortical areas, which are challenging to assess with MRI. Purpose To investigate baseline and change in brain iron levels using MRI at 3 T with R2* relaxation rate mapping in individuals with AD compared with healthy control (HC) participants. Materials and Methods In this prospective study, participants with AD recruited between 2010 and 2016 and age-matched HC participants selected from 2010 to 2014 were evaluated. Of 100 participants with AD, 56 underwent subsequent neuropsychological testing and brain MRI at a mean follow-up of 17 months. All participants underwent 3-T MRI, including R2* mapping corrected for macroscopic B0 field inhomogeneities. Anatomic structures were segmented, and median R2* values were calculated in the neocortex and cortical lobes, basal ganglia (BG), hippocampi, and thalami. Multivariable linear regression analysis was applied to study the difference in R2* levels between groups and the association between longitudinal changes in R2* values and cognition in the AD group. Results A total of 100 participants with AD (mean age, 73 years +/- 9 [standard deviation]; 58 women) and 100 age-matched HC participants (mean age, 73 years +/- 9; 60 women) were evaluated. Median R2* levels were higher in the AD group than in the HC group in the BG (HC, 29.0 sec(-1); AD, 30.2 sec(-1); P = .01) and total neocortex (HC, 17.0 sec(-1); AD, 17.4 sec(-1); P {\\textless} .001) and regionally in the occipital (HC, 19.6 sec(-1); AD, 20.2 sec(-1); P = .007) and temporal (HC, 16.4 sec(-1); AD, 18.1 sec(-1); P {\\textless} .001) lobes. R2* values in the temporal lobe were associated with longitudinal changes in Consortium to Establish a Registry for Alzheimer's Disease total score (beta = -3.23 score/sec(-1), P = .003) in participants with AD independent of longitudinal changes in brain volume. Conclusion Iron concentration in the deep gray matter and neocortical regions was higher in patients with Alzheimer disease than in healthy control participants. Change in iron levels over time in the temporal lobe was associated with cognitive decline in individuals with Alzheimer disease. (c) RSNA, 2020 Online supplemental material is available for this article.},\n\tnumber = {3},\n\tjournal = {Radiology},\n\tauthor = {Damulina, A. and Pirpamer, L. and Soellradl, M. and Sackl, M. and Tinauer, C. and Hofer, E. and Enzinger, C. and Gesierich, B. and Duering, M. and Ropele, S. and Schmidt, R. and Langkammer, C.},\n\tmonth = jun,\n\tyear = {2020},\n\tpmid = {32602825},\n\tkeywords = {Aged, Humans, Middle Aged, Prospective Studies, Aged, 80 and over, Magnetic Resonance Imaging, Alzheimer Disease/*diagnostic imaging, Brain Chemistry/*physiology, Brain/*diagnostic imaging, Iron/*analysis, Magnetic Resonance Imaging/*methods, Brain, Alzheimer Disease, Brain Chemistry, Iron},\n\tpages = {192541},\n}\n\n

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\n Background Deep gray matter structures in patients with Alzheimer disease (AD) contain higher brain iron concentrations. However, few studies have included neocortical areas, which are challenging to assess with MRI. Purpose To investigate baseline and change in brain iron levels using MRI at 3 T with R2* relaxation rate mapping in individuals with AD compared with healthy control (HC) participants. Materials and Methods In this prospective study, participants with AD recruited between 2010 and 2016 and age-matched HC participants selected from 2010 to 2014 were evaluated. Of 100 participants with AD, 56 underwent subsequent neuropsychological testing and brain MRI at a mean follow-up of 17 months. All participants underwent 3-T MRI, including R2* mapping corrected for macroscopic B0 field inhomogeneities. Anatomic structures were segmented, and median R2* values were calculated in the neocortex and cortical lobes, basal ganglia (BG), hippocampi, and thalami. Multivariable linear regression analysis was applied to study the difference in R2* levels between groups and the association between longitudinal changes in R2* values and cognition in the AD group. Results A total of 100 participants with AD (mean age, 73 years +/- 9 [standard deviation]; 58 women) and 100 age-matched HC participants (mean age, 73 years +/- 9; 60 women) were evaluated. Median R2* levels were higher in the AD group than in the HC group in the BG (HC, 29.0 sec(-1); AD, 30.2 sec(-1); P = .01) and total neocortex (HC, 17.0 sec(-1); AD, 17.4 sec(-1); P \\textless .001) and regionally in the occipital (HC, 19.6 sec(-1); AD, 20.2 sec(-1); P = .007) and temporal (HC, 16.4 sec(-1); AD, 18.1 sec(-1); P \\textless .001) lobes. R2* values in the temporal lobe were associated with longitudinal changes in Consortium to Establish a Registry for Alzheimer's Disease total score (beta = -3.23 score/sec(-1), P = .003) in participants with AD independent of longitudinal changes in brain volume. Conclusion Iron concentration in the deep gray matter and neocortical regions was higher in patients with Alzheimer disease than in healthy control participants. Change in iron levels over time in the temporal lobe was associated with cognitive decline in individuals with Alzheimer disease. (c) RSNA, 2020 Online supplemental material is available for this article.\n

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\n \n\n \n \n \n \n \n Gray Matter Covariance Networks as Classifiers and Predictors of Cognitive Function in Alzheimer's Disease.\n \n \n \n\n\n \n Wagner, F.; Duering, M.; Gesierich, B. G.; Enzinger, C.; Ropele, S.; Dal-Bianco, P.; Mayer, F.; Schmidt, R.; and Koini, M.\n\n\n \n\n\n\n Front Psychiatry, 11: 360. 2020.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{wagner_gray_2020,\n\ttitle = {Gray {Matter} {Covariance} {Networks} as {Classifiers} and {Predictors} of {Cognitive} {Function} in {Alzheimer}'s {Disease}},\n\tvolume = {11},\n\tissn = {1664-0640 (Print) 1664-0640 (Linking)},\n\tdoi = {10.3389/fpsyt.2020.00360},\n\tabstract = {The study of shared variation in gray matter morphology may define neurodegenerative diseases beyond what can be detected from the isolated assessment of regional brain volumes. We, therefore, aimed to (1) identify SCNs (structural covariance networks) that discriminate between Alzheimer's disease (AD) patients and healthy controls (HC), (2) investigate their diagnostic accuracy in comparison and above established markers, and (3) determine if they are associated with cognitive abilities. We applied a random forest algorithm to identify discriminating networks from a set of 20 SCNs. The algorithm was trained on a main sample of 104 AD patients and 104 age-matched HC and was then validated in an independent sample of 28 AD patients and 28 controls from another center. Only two of the 20 SCNs contributed significantly to the discrimination between AD and controls. These were a temporal and a secondary somatosensory SCN. Their diagnostic accuracy was 74\\% in the original cohort and 80\\% in the independent samples. The diagnostic accuracy of SCNs was comparable with that of conventional volumetric MRI markers including whole brain volume and hippocampal volume. SCN did not significantly increase diagnostic accuracy beyond that of conventional MRI markers. We found the temporal SCN to be associated with verbal memory at baseline. No other associations with cognitive functions were seen. SCNs failed to predict the course of cognitive decline over an average of 18 months. We conclude that SCNs have diagnostic potential, but the diagnostic information gain beyond conventional MRI markers is limited.},\n\tjournal = {Front Psychiatry},\n\tauthor = {Wagner, F. and Duering, M. and Gesierich, B. G. and Enzinger, C. and Ropele, S. and Dal-Bianco, P. and Mayer, F. and Schmidt, R. and Koini, M.},\n\tyear = {2020},\n\tpmcid = {PMC7214682},\n\tpmid = {32431629},\n\tkeywords = {cognition, Alzheimer, longitudinal, random forest, structural covariance network},\n\tpages = {360},\n}\n\n

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\n \n\n \n \n \n \n \n Age-Related Changes of Peak Width Skeletonized Mean Diffusivity (PSMD) Across the Adult Lifespan: A Multi-Cohort Study.\n \n \n \n\n\n \n Beaudet, G.; Tsuchida, A.; Petit, L.; Tzourio, C.; Caspers, S.; Schreiber, J.; Pausova, Z.; Patel, Y.; Paus, T.; Schmidt, R.; Pirpamer, L.; Sachdev, P. S.; Brodaty, H.; Kochan, N.; Trollor, J.; Wen, W.; Armstrong, N. J.; Deary, I. J.; Bastin, M. E.; Wardlaw, J. M.; Munoz Maniega, S.; Witte, A. V.; Villringer, A.; Duering, M.; Debette, S.; and Mazoyer, B.\n\n\n \n\n\n\n Front Psychiatry, 11: 342. 2020.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{beaudet_age-related_2020,\n\ttitle = {Age-{Related} {Changes} of {Peak} {Width} {Skeletonized} {Mean} {Diffusivity} ({PSMD}) {Across} the {Adult} {Lifespan}: {A} {Multi}-{Cohort} {Study}},\n\tvolume = {11},\n\tissn = {1664-0640 (Print) 1664-0640 (Linking)},\n\tdoi = {10.3389/fpsyt.2020.00342},\n\tabstract = {Parameters of water diffusion in white matter derived from diffusion-weighted imaging (DWI), such as fractional anisotropy (FA), mean, axial, and radial diffusivity (MD, AD, and RD), and more recently, peak width of skeletonized mean diffusivity (PSMD), have been proposed as potential markers of normal and pathological brain ageing. However, their relative evolution over the entire adult lifespan in healthy individuals remains partly unknown during early and late adulthood, and particularly for the PSMD index. Here, we gathered and analyzed cross-sectional diffusion tensor imaging (DTI) data from 10 population-based cohort studies in order to establish the time course of white matter water diffusion phenotypes from post-adolescence to late adulthood. DTI data were obtained from a total of 20,005 individuals aged 18.1 to 92.6 years and analyzed with the same pipeline for computing skeletonized DTI metrics from DTI maps. For each individual, MD, AD, RD, and FA mean values were computed over their FA volume skeleton, PSMD being calculated as the 90\\% peak width of the MD values distribution across the FA skeleton. Mean values of each DTI metric were found to strongly vary across cohorts, most likely due to major differences in DWI acquisition protocols as well as pre-processing and DTI model fitting. However, age effects on each DTI metric were found to be highly consistent across cohorts. RD, MD, and AD variations with age exhibited the same U-shape pattern, first slowly decreasing during post-adolescence until the age of 30, 40, and 50 years, respectively, then progressively increasing until late life. FA showed a reverse profile, initially increasing then continuously decreasing, slowly until the 70s, then sharply declining thereafter. By contrast, PSMD constantly increased, first slowly until the 60s, then more sharply. These results demonstrate that, in the general population, age affects PSMD in a manner different from that of other DTI metrics. The constant increase in PSMD throughout the entire adult life, including during post-adolescence, indicates that PSMD could be an early marker of the ageing process.},\n\tjournal = {Front Psychiatry},\n\tauthor = {Beaudet, G. and Tsuchida, A. and Petit, L. and Tzourio, C. and Caspers, S. and Schreiber, J. and Pausova, Z. and Patel, Y. and Paus, T. and Schmidt, R. and Pirpamer, L. and Sachdev, P. S. and Brodaty, H. and Kochan, N. and Trollor, J. and Wen, W. and Armstrong, N. J. and Deary, I. J. and Bastin, M. E. and Wardlaw, J. M. and Munoz Maniega, S. and Witte, A. V. and Villringer, A. and Duering, M. and Debette, S. and Mazoyer, B.},\n\tyear = {2020},\n\tpmcid = {PMC7212692},\n\tpmid = {32425831},\n\tkeywords = {white matter, ageing, diffusion, Mri, neurodegeneration, Psmd, MRI, PSMD},\n\tpages = {342},\n}\n\n

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\n Parameters of water diffusion in white matter derived from diffusion-weighted imaging (DWI), such as fractional anisotropy (FA), mean, axial, and radial diffusivity (MD, AD, and RD), and more recently, peak width of skeletonized mean diffusivity (PSMD), have been proposed as potential markers of normal and pathological brain ageing. However, their relative evolution over the entire adult lifespan in healthy individuals remains partly unknown during early and late adulthood, and particularly for the PSMD index. Here, we gathered and analyzed cross-sectional diffusion tensor imaging (DTI) data from 10 population-based cohort studies in order to establish the time course of white matter water diffusion phenotypes from post-adolescence to late adulthood. DTI data were obtained from a total of 20,005 individuals aged 18.1 to 92.6 years and analyzed with the same pipeline for computing skeletonized DTI metrics from DTI maps. For each individual, MD, AD, RD, and FA mean values were computed over their FA volume skeleton, PSMD being calculated as the 90% peak width of the MD values distribution across the FA skeleton. Mean values of each DTI metric were found to strongly vary across cohorts, most likely due to major differences in DWI acquisition protocols as well as pre-processing and DTI model fitting. However, age effects on each DTI metric were found to be highly consistent across cohorts. RD, MD, and AD variations with age exhibited the same U-shape pattern, first slowly decreasing during post-adolescence until the age of 30, 40, and 50 years, respectively, then progressively increasing until late life. FA showed a reverse profile, initially increasing then continuously decreasing, slowly until the 70s, then sharply declining thereafter. By contrast, PSMD constantly increased, first slowly until the 60s, then more sharply. These results demonstrate that, in the general population, age affects PSMD in a manner different from that of other DTI metrics. The constant increase in PSMD throughout the entire adult life, including during post-adolescence, indicates that PSMD could be an early marker of the ageing process.\n

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\n \n\n \n \n \n \n \n Cognitive Improvement After Kidney Transplantation Is Associated With Structural and Functional Changes on MRI.\n \n \n \n\n\n \n van Sandwijk, M. S.; Ten Berge, I. J. M.; Caan, M. W. A.; During, M.; van Gool, W. A.; Majoie, C.; Mutsaerts, H. M. M.; Schmand, B. A.; Schrantee, A.; de Sonneville, L. M. J.; and Bemelman, F. J.\n\n\n \n\n\n\n Transplant Direct, 6(3): e531. March 2020.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{van_sandwijk_cognitive_2020,\n\ttitle = {Cognitive {Improvement} {After} {Kidney} {Transplantation} {Is} {Associated} {With} {Structural} and {Functional} {Changes} on {MRI}},\n\tvolume = {6},\n\tissn = {2373-8731 (Print) 2373-8731 (Linking)},\n\tdoi = {10.1097/TXD.0000000000000976},\n\tabstract = {Background: Several studies have reported improved cognitive outcomes after kidney transplantation, but most studies either did not include controls or lacked extensive neuroimaging. In addition, there is uncertainty whether kidney donation is a safe procedure in terms of cognitive outcomes. Methods: We prospectively studied neurocognitive function in kidney transplant recipients. The primary outcome was change in neurocognitive function after 1 year compared with baseline, which was evaluated using the Amsterdam Neuropsychological Task battery and verbal fluency tests. Secondary outcomes included changes in depression and anxiety (measured by the Hospital Anxiety and Depression scale) and changes in fatigue (measured by the Checklist for Individual Strength). We included kidney donors to control for learning effects, socioeconomic status, and surgery. In addition, kidney transplant recipients were evaluated with MRI scans at baseline and at year 1. The MRI protocol included conventional MRI, automated volumetric measurement, diffusion tensor imaging, magnetic resonance spectroscopy, arterial spin labeling, and a resting state functional MRI. Results: Twenty-seven recipients and 24 donors were included. For both recipients and donors, neuropsychologic testing scores improved 1 year after transplantation (donation). Recipient improvement significantly exceeded donor improvement on tasks measuring attention and working memory. These improvements were associated with increases in white matter volume and N-acetylaspartate/creatine (a marker for neuronal integrity). Conclusions: Attention and working memory improve significantly 1 year after kidney transplantation. Learning effects do not account for these improvements because recipient improvement in these areas exceeds donor improvement and correlates with an improvement in white matter integrity after transplantation. Kidney donation appears to be a safe procedure in terms of cognitive outcomes.},\n\tnumber = {3},\n\tjournal = {Transplant Direct},\n\tauthor = {van Sandwijk, M. S. and Ten Berge, I. J. M. and Caan, M. W. A. and During, M. and van Gool, W. A. and Majoie, Cblm and Mutsaerts, H. M. M. and Schmand, B. A. and Schrantee, A. and de Sonneville, L. M. J. and Bemelman, F. J.},\n\tmonth = mar,\n\tyear = {2020},\n\tpmcid = {PMC7056275},\n\tpmid = {32195322},\n\tpages = {e531},\n}\n\n

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\n \n\n \n \n \n \n \n Age-dependent amyloid deposition is associated with white matter alterations in cognitively normal adults during the adult life span.\n \n \n \n\n\n \n Caballero, M. A. A.; Song, Z.; Rubinski, A.; Duering, M.; Dichgans, M.; Park, D. C.; and Ewers, M.\n\n\n \n\n\n\n Alzheimers Dement, 16(4): 651–661. March 2020.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{caballero_age-dependent_2020,\n\ttitle = {Age-dependent amyloid deposition is associated with white matter alterations in cognitively normal adults during the adult life span},\n\tvolume = {16},\n\tissn = {1552-5279 (Electronic) 1552-5260 (Linking)},\n\tdoi = {10.1002/alz.12062},\n\tabstract = {INTRODUCTION: Both beta-amyloid (Ab) deposition and decline in white matter integrity, are brain alterations observed in Alzheimer's disease (AD) and start to occur by the fourth and fifth decades. However, the association between both brain alterations in asymptomatic subjects is unclear. METHODS: Amyloid positron emission tomography (PET) and diffusion tensor imaging (DTI) were obtained in 282 cognitively normal subjects (age 30-89 years). We assessed the interaction of age by abnormal amyloid PET status (Florbetapir F-18 PET {\\textgreater}1.2 standard uptake value ratio [SUVR]) on regional mean diffusivity (MD) and global white matter hyperintensity (WMH) volume, controlled for sex, education, and hypertension. RESULTS: Subjects with abnormal amyloid PET (n = 87) showed stronger age-related increase in global WMH and regional MD, particularly within the posterior parietal regions of the white matter. DISCUSSION: Sporadic Abeta deposition is associated with white matter alterations in AD predilection areas in an age-dependent manner in cognitively normal individuals.},\n\tnumber = {4},\n\tjournal = {Alzheimers Dement},\n\tauthor = {Caballero, M. A. A. and Song, Z. and Rubinski, A. and Duering, M. and Dichgans, M. and Park, D. C. and Ewers, M.},\n\tmonth = mar,\n\tyear = {2020},\n\tpmid = {32147939},\n\tkeywords = {Cognition, Adult, Aged, Diffusion Tensor Imaging, Female, Humans, Male, Middle Aged, Alzheimer's disease, diffusion tensor imaging, white matter, white matter hyperintensities, Neuropsychological Tests, amyloid beta, life span, mean diffusivity, Positron-Emission Tomography, Amyloid beta-Peptides, White Matter, Alzheimer Disease, Healthy Volunteers, amyloid β, Longevity},\n\tpages = {651--661},\n}\n\n

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\n \n\n \n \n \n \n \n Histopathology of diffusion-weighted imaging-positive lesions in cerebral amyloid angiopathy.\n \n \n \n\n\n \n Ter Telgte, A.; Scherlek, A. A.; Reijmer, Y. D.; van der Kouwe, A. J.; van Harten, T.; Duering, M.; Bacskai, B. J.; de Leeuw, F. E.; Frosch, M. P.; Greenberg, S. M.; and van Veluw, S. J.\n\n\n \n\n\n\n Acta Neuropathol, 139(5): 799–812. February 2020.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{ter_telgte_histopathology_2020,\n\ttitle = {Histopathology of diffusion-weighted imaging-positive lesions in cerebral amyloid angiopathy},\n\tvolume = {139},\n\tissn = {1432-0533 (Electronic) 0001-6322 (Linking)},\n\tdoi = {10.1007/s00401-020-02140-y},\n\tabstract = {Small subclinical hyperintense lesions are frequently encountered on brain diffusion-weighted imaging (DWI) scans of patients with cerebral amyloid angiopathy (CAA). Interpretation of these DWI+ lesions, however, has been limited by absence of histopathological examination. We aimed to determine whether DWI+ lesions represent acute microinfarcts on histopathology in brains with advanced CAA, using a combined in vivo MRI-ex vivo MRI-histopathology approach. We first investigated the histopathology of a punctate cortical DWI+ lesion observed on clinical in vivo MRI 7 days prior to death in a CAA case. Subsequently, we assessed the use of ex vivo DWI to identify similar punctate cortical lesions post-mortem. Intact formalin-fixed hemispheres of 12 consecutive cases with CAA and three non-CAA controls were subjected to high-resolution 3 T ex vivo DWI and T2 imaging. Small cortical lesions were classified as either DWI+/T2+ or DWI-/T2+. A representative subset of lesions from three CAA cases was selected for detailed histopathological examination. The DWI+ lesion observed on in vivo MRI could be matched to an area with evidence of recent ischemia on histopathology. Ex vivo MRI of the intact hemispheres revealed a total of 130 DWI+/T2+ lesions in 10/12 CAA cases, but none in controls (p = 0.022). DWI+/T2+ lesions examined histopathologically proved to be acute microinfarcts (classification accuracy 100\\%), characterized by presence of eosinophilic neurons on hematoxylin and eosin and absence of reactive astrocytes on glial fibrillary acidic protein-stained sections. In conclusion, we suggest that small DWI+ lesions in CAA represent acute microinfarcts. Furthermore, our findings support the use of ex vivo DWI as a method to detect acute microinfarcts post-mortem, which may benefit future histopathological investigations on the etiology of microinfarcts.},\n\tnumber = {5},\n\tjournal = {Acta Neuropathol},\n\tauthor = {Ter Telgte, A. and Scherlek, A. A. and Reijmer, Y. D. and van der Kouwe, A. J. and van Harten, T. and Duering, M. and Bacskai, B. J. and de Leeuw, F. E. and Frosch, M. P. and Greenberg, S. M. and van Veluw, S. J.},\n\tmonth = feb,\n\tyear = {2020},\n\tpmcid = {PMC7185568},\n\tpmid = {32108259},\n\tkeywords = {Diffusion Magnetic Resonance Imaging, Female, Humans, Aged, 80 and over, Neuroimaging, Magnetic Resonance Imaging, Caa, DWI+ lesions, Ischemia, Microinfarcts, Post-mortem MRI, Brain, Cerebral Hemorrhage, Cerebral Amyloid Angiopathy, Autopsy, CAA},\n\tpages = {799--812},\n}\n\n

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\n \n\n \n \n \n \n \n Temporal Dynamics of Cortical Microinfarcts in Cerebral Small Vessel Disease.\n \n \n \n\n\n \n Ter Telgte, A.; Wiegertjes, K.; Gesierich, B.; Baskaran, B. S.; Marques, J. P.; Kuijf, H. J.; Norris, D. G.; Tuladhar, A. M.; Duering, M.; and de Leeuw, F. E.\n\n\n \n\n\n\n JAMA Neurol, 77(5): 643–647. February 2020.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{ter_telgte_temporal_2020,\n\ttitle = {Temporal {Dynamics} of {Cortical} {Microinfarcts} in {Cerebral} {Small} {Vessel} {Disease}},\n\tvolume = {77},\n\tissn = {2168-6157 (Electronic) 2168-6149 (Linking)},\n\tdoi = {10.1001/jamaneurol.2019.5106},\n\tabstract = {Importance: Neuropathology studies show a high prevalence of cortical microinfarcts (CMIs) in aging individuals, especially in patients with cerebrovascular disease and dementia. However, most, are invisible on T1- and T2-weighted magnetic resonance imaging (MRI), raising the question of how to explain this mismatch. Studies on small acute infarcts, detected on diffusion-weighted imaging (DWI), suggest that infarcts are largest in their acute phase and reduce in size thereafter. Therefore, we hypothesized that a subset of the CMI that are invisible on MRI can be detected on MRI in their acute phase. However, to our knowledge, a serial imaging study investigating the temporal dynamics of acute CMI (A-CMI) is lacking. Objective: To determine the prevalence of chronic CMI (C-CMI) and the cumulative incidence and temporal dynamics of A-CMI in individuals with cerebral small vessel disease (SVD). Design, Setting, Participants and Exposures: The RUN DMC-Intense study is a single-center hospital-based prospective cohort study on SVD performed between March 2016 and November 2017 and comprising 10 monthly 3-T MRI scans, including high-resolution DWI, 3-dimensional T1, 3-dimensional fluid-attenuated inversion recovery, and T2. One hundred six individuals from the previous longitudinal RUN DMC study were recruited based on the presence of progression of white matter hyperintensities on MRI between 2006 and 2015 and exclusion of causes of cerebral ischemia other than SVD. Fifty-four individuals (50.9\\%) participated. The median total follow-up duration was 39.5 weeks (interquartile range, 37.8-40.3). Statistical data analysis was performed between May and October 2019. Main Outcomes and Measures: We determined the prevalence of C-CMI using the baseline T1, fluid-attenuated inversion recovery, and T2 scans. Monthly high-resolution DWI scans (n = 472) were screened to determine the cumulative incidence of A-CMI. The temporal dynamics of A-CMI were determined based on the MRI scans collected during the first follow-up visit after A-CMI onset and the last available follow-up visit. Results: The median age of the cohort at baseline MRI was 69 years (interquartile range, 66-74 years) and 34 participants (63\\%) were men. The prevalence of C-CMI was 35\\% (95\\% CI, 0.24-0.49). Monthly DWI detected 21 A-CMI in 7 of 54 participants, resulting in a cumulative incidence of 13\\% (95\\% CI, 0.06-0.24). All A-CMI disappeared on follow-up MRI. Conclusions and Relevance: Acute CMI never evolved into chronically MRI-detectable lesions. We suggest that these A-CMI underlie part of the submillimeter C-CMI encountered on neuropathological examination and thereby provide a source for the high CMI burden on neuropathology.},\n\tnumber = {5},\n\tjournal = {JAMA Neurol},\n\tauthor = {Ter Telgte, A. and Wiegertjes, K. and Gesierich, B. and Baskaran, B. S. and Marques, J. P. and Kuijf, H. J. and Norris, D. G. and Tuladhar, A. M. and Duering, M. and de Leeuw, F. E.},\n\tmonth = feb,\n\tyear = {2020},\n\tpmcid = {PMC7042834},\n\tpmid = {32065609},\n\tkeywords = {Aged, Diffusion Magnetic Resonance Imaging, Female, Humans, Male, Incidence, Cohort Studies, Time Factors, Cerebral Infarction/*diagnostic imaging/*epidemiology/*etiology, Cerebral Small Vessel Diseases/*complications/*pathology, Diffusion Magnetic Resonance Imaging/methods, Cerebral Infarction, Cerebral Small Vessel Diseases},\n\tpages = {643--647},\n}\n\n

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\n Importance: Neuropathology studies show a high prevalence of cortical microinfarcts (CMIs) in aging individuals, especially in patients with cerebrovascular disease and dementia. However, most, are invisible on T1- and T2-weighted magnetic resonance imaging (MRI), raising the question of how to explain this mismatch. Studies on small acute infarcts, detected on diffusion-weighted imaging (DWI), suggest that infarcts are largest in their acute phase and reduce in size thereafter. Therefore, we hypothesized that a subset of the CMI that are invisible on MRI can be detected on MRI in their acute phase. However, to our knowledge, a serial imaging study investigating the temporal dynamics of acute CMI (A-CMI) is lacking. Objective: To determine the prevalence of chronic CMI (C-CMI) and the cumulative incidence and temporal dynamics of A-CMI in individuals with cerebral small vessel disease (SVD). Design, Setting, Participants and Exposures: The RUN DMC-Intense study is a single-center hospital-based prospective cohort study on SVD performed between March 2016 and November 2017 and comprising 10 monthly 3-T MRI scans, including high-resolution DWI, 3-dimensional T1, 3-dimensional fluid-attenuated inversion recovery, and T2. One hundred six individuals from the previous longitudinal RUN DMC study were recruited based on the presence of progression of white matter hyperintensities on MRI between 2006 and 2015 and exclusion of causes of cerebral ischemia other than SVD. Fifty-four individuals (50.9%) participated. The median total follow-up duration was 39.5 weeks (interquartile range, 37.8-40.3). Statistical data analysis was performed between May and October 2019. Main Outcomes and Measures: We determined the prevalence of C-CMI using the baseline T1, fluid-attenuated inversion recovery, and T2 scans. Monthly high-resolution DWI scans (n = 472) were screened to determine the cumulative incidence of A-CMI. The temporal dynamics of A-CMI were determined based on the MRI scans collected during the first follow-up visit after A-CMI onset and the last available follow-up visit. Results: The median age of the cohort at baseline MRI was 69 years (interquartile range, 66-74 years) and 34 participants (63%) were men. The prevalence of C-CMI was 35% (95% CI, 0.24-0.49). Monthly DWI detected 21 A-CMI in 7 of 54 participants, resulting in a cumulative incidence of 13% (95% CI, 0.06-0.24). All A-CMI disappeared on follow-up MRI. Conclusions and Relevance: Acute CMI never evolved into chronically MRI-detectable lesions. We suggest that these A-CMI underlie part of the submillimeter C-CMI encountered on neuropathological examination and thereby provide a source for the high CMI burden on neuropathology.\n

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\n \n\n \n \n \n \n \n Cellular and Molecular Probing of Intact Human Organs.\n \n \n \n\n\n \n Zhao, S.; Todorov, M. I.; Cai, R.; Maskari, R. A.; Steinke, H.; Kemter, E.; Mai, H.; Rong, Z.; Warmer, M.; Stanic, K.; Schoppe, O.; Paetzold, J. C.; Gesierich, B.; Wong, M. N.; Huber, T. B.; Duering, M.; Bruns, O. T.; Menze, B.; Lipfert, J.; Puelles, V. G.; Wolf, E.; Bechmann, I.; and Erturk, A.\n\n\n \n\n\n\n Cell, 180(4): 796–812 e19. February 2020.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{zhao_cellular_2020,\n\ttitle = {Cellular and {Molecular} {Probing} of {Intact} {Human} {Organs}},\n\tvolume = {180},\n\tissn = {1097-4172 (Electronic) 0092-8674 (Linking)},\n\tdoi = {10.1016/j.cell.2020.01.030},\n\tabstract = {Optical tissue transparency permits scalable cellular and molecular investigation of complex tissues in 3D. Adult human organs are particularly challenging to render transparent because of the accumulation of dense and sturdy molecules in decades-aged tissues. To overcome these challenges, we developed SHANEL, a method based on a new tissue permeabilization approach to clear and label stiff human organs. We used SHANEL to render the intact adult human brain and kidney transparent and perform 3D histology with antibodies and dyes in centimeters-depth. Thereby, we revealed structural details of the intact human eye, human thyroid, human kidney, and transgenic pig pancreas at the cellular resolution. Furthermore, we developed a deep learning pipeline to analyze millions of cells in cleared human brain tissues within hours with standard lab computers. Overall, SHANEL is a robust and unbiased technology to chart the cellular and molecular architecture of large intact mammalian organs.},\n\tnumber = {4},\n\tjournal = {Cell},\n\tauthor = {Zhao, S. and Todorov, M. I. and Cai, R. and Maskari, R. A. and Steinke, H. and Kemter, E. and Mai, H. and Rong, Z. and Warmer, M. and Stanic, K. and Schoppe, O. and Paetzold, J. C. and Gesierich, B. and Wong, M. N. and Huber, T. B. and Duering, M. and Bruns, O. T. and Menze, B. and Lipfert, J. and Puelles, V. G. and Wolf, E. and Bechmann, I. and Erturk, A.},\n\tmonth = feb,\n\tyear = {2020},\n\tpmcid = {PMC7557154},\n\tpmid = {32059778},\n\tkeywords = {Female, Humans, Male, Middle Aged, Aged, 80 and over, Brain/diagnostic imaging, Animals, *Deep Learning, Eye/diagnostic imaging, Imaging, Three-Dimensional/*methods/standards, Kidney/diagnostic imaging, Limit of Detection, Mice, Optical Imaging/*methods/standards, Pancreas/diagnostic imaging, Staining and Labeling/*methods/standards, Swine, Thyroid Gland/diagnostic imaging, Imaging, Three-Dimensional, Brain, Deep Learning, Eye, Kidney, Optical Imaging, Pancreas, Staining and Labeling, Thyroid Gland},\n\tpages = {796--812 e19},\n}\n\n

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\n \n\n \n \n \n \n \n Predicting sporadic Alzheimer's disease progression via inherited Alzheimer's disease-informed machine-learning.\n \n \n \n\n\n \n Franzmeier, N.; Koutsouleris, N.; Benzinger, T.; Goate, A.; Karch, C. M.; Fagan, A. M.; McDade, E.; Duering, M.; Dichgans, M.; Levin, J.; Gordon, B. A.; Lim, Y. Y.; Masters, C. L.; Rossor, M.; Fox, N. C.; O'Connor, A.; Chhatwal, J.; Salloway, S.; Danek, A.; Hassenstab, J.; Schofield, P. R.; Morris, J. C.; Bateman, R. J.; Alzheimer's disease neuroimaging , i.; Dominantly Inherited Alzheimer, N.; and Ewers, M.\n\n\n \n\n\n\n Alzheimers Dement, 16(3): 501–511. February 2020.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{franzmeier_predicting_2020,\n\ttitle = {Predicting sporadic {Alzheimer}'s disease progression via inherited {Alzheimer}'s disease-informed machine-learning},\n\tvolume = {16},\n\tissn = {1552-5279 (Electronic) 1552-5260 (Linking)},\n\tdoi = {10.1002/alz.12032},\n\tabstract = {INTRODUCTION: Developing cross-validated multi-biomarker models for the prediction of the rate of cognitive decline in Alzheimer's disease (AD) is a critical yet unmet clinical challenge. METHODS: We applied support vector regression to AD biomarkers derived from cerebrospinal fluid, structural magnetic resonance imaging (MRI), amyloid-PET and fluorodeoxyglucose positron-emission tomography (FDG-PET) to predict rates of cognitive decline. Prediction models were trained in autosomal-dominant Alzheimer's disease (ADAD, n = 121) and subsequently cross-validated in sporadic prodromal AD (n = 216). The sample size needed to detect treatment effects when using model-based risk enrichment was estimated. RESULTS: A model combining all biomarker modalities and established in ADAD predicted the 4-year rate of decline in global cognition (R(2) = 24\\%) and memory (R(2) = 25\\%) in sporadic AD. Model-based risk-enrichment reduced the sample size required for detecting simulated intervention effects by 50\\%-75\\%. DISCUSSION: Our independently validated machine-learning model predicted cognitive decline in sporadic prodromal AD and may substantially reduce sample size needed in clinical trials in AD.},\n\tnumber = {3},\n\tjournal = {Alzheimers Dement},\n\tauthor = {Franzmeier, N. and Koutsouleris, N. and Benzinger, T. and Goate, A. and Karch, C. M. and Fagan, A. M. and McDade, E. and Duering, M. and Dichgans, M. and Levin, J. and Gordon, B. A. and Lim, Y. Y. and Masters, C. L. and Rossor, M. and Fox, N. C. and O'Connor, A. and Chhatwal, J. and Salloway, S. and Danek, A. and Hassenstab, J. and Schofield, P. R. and Morris, J. C. and Bateman, R. J. and Alzheimer's disease neuroimaging, initiative and Dominantly Inherited Alzheimer, Network and Ewers, M.},\n\tmonth = feb,\n\tyear = {2020},\n\tpmcid = {PMC7222030},\n\tpmid = {32043733},\n\tkeywords = {Adult, Disease Progression, Female, Humans, Male, Alzheimer's disease, Magnetic Resonance Imaging, Biomarkers, Mri, autosomal-dominant Alzheimer's disease, biomarkers, machine learning, Pet, progression prediction, risk enrichment, Positron-Emission Tomography, Alzheimer Disease, Cognitive Dysfunction, MRI, Machine Learning, PET},\n\tpages = {501--511},\n}\n\n

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\n \n\n \n \n \n \n \n Cerebral Autosomal Dominant Arteriopathy With Subcortical Infarcts and Leukoencephalopathy: Lessons From Neuroimaging.\n \n \n \n\n\n \n Jouvent, E.; Duering, M.; and Chabriat, H.\n\n\n \n\n\n\n Stroke, 51(1): 21–28. January 2020.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{jouvent_cerebral_2020,\n\ttitle = {Cerebral {Autosomal} {Dominant} {Arteriopathy} {With} {Subcortical} {Infarcts} and {Leukoencephalopathy}: {Lessons} {From} {Neuroimaging}},\n\tvolume = {51},\n\tissn = {1524-4628 (Electronic) 0039-2499 (Linking)},\n\tdoi = {10.1161/STROKEAHA.119.024152},\n\tnumber = {1},\n\tjournal = {Stroke},\n\tauthor = {Jouvent, E. and Duering, M. and Chabriat, H.},\n\tmonth = jan,\n\tyear = {2020},\n\tpmid = {31752612},\n\tkeywords = {Humans, cerebral small vessel disease, *cerebral small vessel disease, Neuroimaging, Magnetic Resonance Imaging, *cadasil, CADASIL/*diagnostic imaging, lacunes, white matter hyperintensities, Magnetic Resonance Imaging/methods, Brain/*diagnostic imaging, *ischemic stroke, *lacunes, *Neuroimaging, *recent small subcortical ischemic lesions, *white matter hyperintensities, Leukoencephalopathies/*diagnostic imaging, Patient Care/statistics \\& numerical data, Brain, CADASIL, Leukoencephalopathies, ischemic stroke, Patient Care, recent small subcortical ischemic lesions},\n\tpages = {21--28},\n}\n\n

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\n \n\n \n \n \n \n \n Brain atrophy in cerebral small vessel diseases: Extent, consequences, technical limitations and perspectives: The HARNESS initiative.\n \n \n \n\n\n \n De Guio, F.; Duering, M.; Fazekas, F.; De Leeuw, F. E.; Greenberg, S. M.; Pantoni, L.; Aghetti, A.; Smith, E. E.; Wardlaw, J.; and Jouvent, E.\n\n\n \n\n\n\n J Cereb Blood Flow Metab, 40(2): 231–245. February 2020.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{de_guio_brain_2020,\n\ttitle = {Brain atrophy in cerebral small vessel diseases: {Extent}, consequences, technical limitations and perspectives: {The} {HARNESS} initiative},\n\tvolume = {40},\n\tissn = {1559-7016 (Electronic) 0271-678X (Linking)},\n\tdoi = {10.1177/0271678X19888967},\n\tnumber = {2},\n\tjournal = {J Cereb Blood Flow Metab},\n\tauthor = {De Guio, F. and Duering, M. and Fazekas, F. and De Leeuw, F. E. and Greenberg, S. M. and Pantoni, L. and Aghetti, A. and Smith, E. E. and Wardlaw, J. and Jouvent, E.},\n\tmonth = feb,\n\tyear = {2020},\n\tpmcid = {PMC7370623},\n\tpmid = {31744377},\n\tkeywords = {Female, Humans, Male, Magnetic Resonance Imaging, lacunes, white matter hyperintensities, *lacunes, *white matter hyperintensities, *brain atrophy, *brain volume, *Brain/blood supply/diagnostic imaging/pathology, *Cerebral small vessel disease, *Cerebral Small Vessel Diseases/diagnostic imaging/pathology, *cognitive alterations, *Cognitive Dysfunction/diagnostic imaging/pathology, *cognitive performances, *Magnetic Resonance Imaging, *segmentation, Atrophy, Brain, Cerebral Small Vessel Diseases, segmentation, Cognitive Dysfunction, brain atrophy, Cerebral small vessel disease, brain volume, cognitive alterations, cognitive performances},\n\tpages = {231--245},\n}\n\n

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\n \n\n \n \n \n \n \n Machine learning analysis of whole mouse brain vasculature.\n \n \n \n\n\n \n Todorov, M. I.; Paetzold, J. C.; Schoppe, O.; Tetteh, G.; Shit, S.; Efremov, V.; Todorov-Völgyi, K.; Düring, M.; Dichgans, M.; Piraud, M.; Menze, B.; and Ertürk, A.\n\n\n \n\n\n\n Nat Methods, 17(4): 442–449. April 2020.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{todorov_machine_2020,\n\ttitle = {Machine learning analysis of whole mouse brain vasculature},\n\tvolume = {17},\n\tissn = {1548-7105},\n\tdoi = {10.1038/s41592-020-0792-1},\n\tabstract = {Tissue clearing methods enable the imaging of biological specimens without sectioning. However, reliable and scalable analysis of large imaging datasets in three dimensions remains a challenge. Here we developed a deep learning-based framework to quantify and analyze brain vasculature, named Vessel Segmentation \\& Analysis Pipeline (VesSAP). Our pipeline uses a convolutional neural network (CNN) with a transfer learning approach for segmentation and achieves human-level accuracy. By using VesSAP, we analyzed the vascular features of whole C57BL/6J, CD1 and BALB/c mouse brains at the micrometer scale after registering them to the Allen mouse brain atlas. We report evidence of secondary intracranial collateral vascularization in CD1 mice and find reduced vascularization of the brainstem in comparison to the cerebrum. Thus, VesSAP enables unbiased and scalable quantifications of the angioarchitecture of cleared mouse brains and yields biological insights into the vascular function of the brain.},\n\tlanguage = {eng},\n\tnumber = {4},\n\tjournal = {Nat Methods},\n\tauthor = {Todorov, Mihail Ivilinov and Paetzold, Johannes Christian and Schoppe, Oliver and Tetteh, Giles and Shit, Suprosanna and Efremov, Velizar and Todorov-Völgyi, Katalin and Düring, Marco and Dichgans, Martin and Piraud, Marie and Menze, Bjoern and Ertürk, Ali},\n\tmonth = apr,\n\tyear = {2020},\n\tpmid = {32161395},\n\tpmcid = {PMC7591801},\n\tkeywords = {Animals, Mice, Imaging, Three-Dimensional, Brain, Machine Learning},\n\tpages = {442--449},\n\tfile = {Accepted Version:/Users/mduering/Zotero/storage/46DWAQVU/Todorov et al. - 2020 - Machine learning analysis of whole mouse brain vas.pdf:application/pdf},\n}\n\n

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\n \n\n \n \n \n \n \n Minor gait impairment despite white matter damage in pure small vessel disease.\n \n \n \n\n\n \n Finsterwalder, S.; Wuehr, M.; Gesierich, B.; Dietze, A.; Konieczny, M. J.; Schmidt, R.; Schniepp, R.; and Duering, M.\n\n\n \n\n\n\n Ann Clin Transl Neurol, 6(10): 2026–2036. October 2019.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{finsterwalder_minor_2019,\n\ttitle = {Minor gait impairment despite white matter damage in pure small vessel disease},\n\tvolume = {6},\n\tissn = {2328-9503 (Electronic) 2328-9503 (Linking)},\n\tdoi = {10.1002/acn3.50891},\n\tabstract = {OBJECTIVE: Gait impairment is common in patients with cerebral small vessel disease (SVD). However, gait studies in elderly SVD patients might be confounded by age-related comorbidities, such as polyneuropathy or sarcopenia. We therefore studied young patients with the genetically defined SVD CADASIL. Our aim was to examine the effects of pure SVD on single and dual task gait, and to investigate associations of gait performance with cognitive deficits and white matter alterations. METHODS: We investigated single task walking and calculatory, semantic, or motoric dual task costs in 39 CADASIL patients (mean age 50 +/- 8) using a computerized walkway. We obtained 3.0T MRI and neuropsychological data on processing speed, the main cognitive deficit in CADASIL. Spatiotemporal gait parameters were standardized based on data from 192 healthy controls. Associations between white matter integrity, assessed by diffusion tensor imaging, and gait were analyzed using both a global marker and voxel-wise analysis. RESULTS: Compared to controls, CADASIL patients showed only mild single task gait impairment, and only in the rhythm domain. The semantic dual task additionally uncovered mild deficits in the pace domain. Processing speed was not associated with gait. White matter alterations were related to single task stride length but not to dual task performance. INTERPRETATION: Despite severe disease burden, gait performance in patients with pure small vessel disease was relatively preserved in single and dual tasks. Results suggest that age-related pathologies other than small vessel disease might play a role for gait impairment in elderly SVD patients.},\n\tnumber = {10},\n\tjournal = {Ann Clin Transl Neurol},\n\tauthor = {Finsterwalder, S. and Wuehr, M. and Gesierich, B. and Dietze, A. and Konieczny, M. J. and Schmidt, R. and Schniepp, R. and Duering, M.},\n\tmonth = oct,\n\tyear = {2019},\n\tpmcid = {PMC6801180},\n\tpmid = {31524338},\n\tkeywords = {Adult, Diffusion Tensor Imaging, Female, Humans, Male, Middle Aged, CADASIL/complications/diagnostic imaging/*pathology/*physiopathology, Cognitive Dysfunction/etiology/*physiopathology, Executive Function/*physiology, Gait Disorders, Neurologic/etiology/*physiopathology, Prospective Studies, Psychomotor Performance/*physiology, White Matter/diagnostic imaging/*pathology, Executive Function, Psychomotor Performance, White Matter, Cognitive Dysfunction, CADASIL, Gait Disorders, Neurologic},\n\tpages = {2026--2036},\n}\n\n

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\n \n\n \n \n \n \n \n Within-lesion heterogeneity of subcortical DWI lesion evolution, and stroke outcome: A voxel-based analysis.\n \n \n \n\n\n \n Duering, M.; Adam, R.; Wollenweber, F. A.; Bayer-Karpinska, A.; Baykara, E.; Cubillos-Pinilla, L. Y.; Gesierich, B.; Araque Caballero, M. A.; Stoecklein, S.; Ewers, M.; Pasternak, O.; and Dichgans, M.\n\n\n \n\n\n\n J Cereb Blood Flow Metab, 40(7): 271678X19865916. July 2019.\n \n\n\n\n
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@article{duering_within-lesion_2019,\n\ttitle = {Within-lesion heterogeneity of subcortical {DWI} lesion evolution, and stroke outcome: {A} voxel-based analysis},\n\tvolume = {40},\n\tissn = {1559-7016 (Electronic) 0271-678X (Linking)},\n\tdoi = {10.1177/0271678X19865916},\n\tabstract = {The fate of subcortical diffusion-weighted imaging (DWI) lesions in stroke patients is highly variable, ranging from complete tissue loss to no visible lesion on follow-up. Little is known about within-lesion heterogeneity and its relevance for stroke outcome. Patients with subcortical stroke and recruited through the prospective DEDEMAS study (NCT01334749) were examined at baseline (n = 45), six months (n = 45), and three years (n = 28) post-stroke. We performed high-resolution structural MRI including DWI. Tissue fate was determined voxel-wise using fully automated tissue segmentation. Within-lesion heterogeneity at baseline was assessed by free water diffusion imaging measures. The majority of DWI lesions (66\\%) showed cavitation on six months follow-up but the proportion of tissue turning into a cavity was small (9 +/- 13.5\\% of the DWI lesion). On average, 69 +/- 25\\% of the initial lesion resolved without any visually apparent signal abnormality. The extent of cavitation at six months post-stroke was independently associated with clinical outcome, i.e. modified Rankin scale score at six months (OR = 4.71, p = 0.005). DWI lesion size and the free water-corrected tissue mean diffusivity at baseline independently predicted cavitation. In conclusion, the proportion of cavitating tissue is typically small, but relevant for clinical outcome. Within-lesion heterogeneity at baseline on advanced diffusion imaging is predictive of tissue fate.},\n\tnumber = {7},\n\tjournal = {J Cereb Blood Flow Metab},\n\tauthor = {Duering, M. and Adam, R. and Wollenweber, F. A. and Bayer-Karpinska, A. and Baykara, E. and Cubillos-Pinilla, L. Y. and Gesierich, B. and Araque Caballero, M. A. and Stoecklein, S. and Ewers, M. and Pasternak, O. and Dichgans, M.},\n\tmonth = jul,\n\tyear = {2019},\n\tpmcid = {PMC7308518},\n\tpmid = {31342832},\n\tkeywords = {Stroke, Aged, Diffusion Magnetic Resonance Imaging, Female, Humans, Male, Middle Aged, diffusion tensor imaging, *diffusion tensor imaging, *Clinical outcome, *free water, *stroke, *subcortical infarction, Aged, 80 and over, Neuroimaging, stroke, Image Interpretation, Computer-Assisted, free water, Clinical outcome, Recovery of Function, subcortical infarction},\n\tpages = {271678X19865916},\n}\n\n

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\n \n\n \n \n \n \n \n Contribution of acute infarcts to cerebral small vessel disease progression.\n \n \n \n\n\n \n Ter Telgte, A.; Wiegertjes, K.; Gesierich, B.; Marques, J. P.; Huebner, M.; de Klerk, J. J.; Schreuder, F.; Araque Caballero, M. A.; Kuijf, H. J.; Norris, D. G.; Klijn, C. J. M.; Dichgans, M.; Tuladhar, A. M.; Duering, M.; and de Leeuw, F. E.\n\n\n \n\n\n\n Ann Neurol, 86(4): 582–592. October 2019.\n \n\n\n\n
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@article{ter_telgte_contribution_2019,\n\ttitle = {Contribution of acute infarcts to cerebral small vessel disease progression},\n\tvolume = {86},\n\tissn = {1531-8249 (Electronic) 0364-5134 (Linking)},\n\tdoi = {10.1002/ana.25556},\n\tabstract = {OBJECTIVE: To determine the contribution of acute infarcts, evidenced by diffusion-weighted imaging positive (DWI+) lesions, to progression of white matter hyperintensities (WMH) and other cerebral small vessel disease (SVD) markers. METHODS: We performed monthly 3T magnetic resonance imaging (MRI) for 10 consecutive months in 54 elderly individuals with SVD. MRI included high-resolution multishell DWI, and 3-dimensional fluid-attenuated inversion recovery, T1, and susceptibility-weighted imaging. We determined DWI+ lesion evolution, WMH progression rate (ml/mo), and number of incident lacunes and microbleeds, and calculated for each marker the proportion of progression explained by DWI+ lesions. RESULTS: We identified 39 DWI+ lesions on 21 of 472 DWI scans in 9 of 54 subjects. Of the 36 DWI+ lesions with follow-up MRI, 2 evolved into WMH, 4 evolved into a lacune (3 with cavity {\\textless}3mm), 3 evolved into a microbleed, and 27 were not detectable on follow-up. WMH volume increased at a median rate of 0.027 ml/mo (interquartile range = 0.005-0.073), but was not significantly higher in subjects with DWI+ lesions compared to those without (p = 0.195). Of the 2 DWI+ lesions evolving into WMH on follow-up, one explained 23\\% of the total WMH volume increase in one subject, whereas the WMH regressed in the other subject. DWI+ lesions preceded 4 of 5 incident lacunes and 3 of 10 incident microbleeds. INTERPRETATION: DWI+ lesions explain only a small proportion of the total WMH progression. Hence, WMH progression seems to be mostly driven by factors other than acute infarcts. DWI+ lesions explain the majority of incident lacunes and small cavities, and almost one-third of incident microbleeds, confirming that WMH, lacunes, and microbleeds, although heterogeneous on MRI, can have a common initial appearance on MRI. ANN NEUROL 2019;86:582-592.},\n\tnumber = {4},\n\tjournal = {Ann Neurol},\n\tauthor = {Ter Telgte, A. and Wiegertjes, K. and Gesierich, B. and Marques, J. P. and Huebner, M. and de Klerk, J. J. and Schreuder, Fhbm and Araque Caballero, M. A. and Kuijf, H. J. and Norris, D. G. and Klijn, C. J. M. and Dichgans, M. and Tuladhar, A. M. and Duering, M. and de Leeuw, F. E.},\n\tmonth = oct,\n\tyear = {2019},\n\tpmcid = {PMC6771732},\n\tpmid = {31340067},\n\tkeywords = {Aged, Diffusion Magnetic Resonance Imaging, Disease Progression, Female, Humans, Male, Aged, 80 and over, Brain Infarction/complications/*pathology, Cerebral Small Vessel Diseases/complications/*pathology, Incidence, Intracranial Hemorrhages/complications/pathology, Neuroimaging, Stroke, Lacunar/complications/pathology, White Matter/blood supply/pathology, White Matter, Cerebral Small Vessel Diseases, Intracranial Hemorrhages, Brain Infarction, Stroke, Lacunar},\n\tpages = {582--592},\n}\n\n

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\n \n\n \n \n \n \n \n In vivo widefield calcium imaging of the mouse cortex for analysis of network connectivity in health and brain disease.\n \n \n \n\n\n \n Cramer, J. V.; Gesierich, B.; Roth, S.; Dichgans, M.; During, M.; and Liesz, A.\n\n\n \n\n\n\n Neuroimage, 199: 570–584. October 2019.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{cramer_vivo_2019,\n\ttitle = {In vivo widefield calcium imaging of the mouse cortex for analysis of network connectivity in health and brain disease},\n\tvolume = {199},\n\tissn = {1095-9572 (Electronic) 1053-8119 (Linking)},\n\tdoi = {10.1016/j.neuroimage.2019.06.014},\n\tabstract = {The organization of brain areas in functionally connected networks, their dynamic changes, and perturbations in disease states are subject of extensive investigations. Research on functional networks in humans predominantly uses functional magnetic resonance imaging (fMRI). However, adopting fMRI and other functional imaging methods to mice, the most widely used model to study brain physiology and disease, poses major technical challenges and faces important limitations. Hence, there is great demand for alternative imaging modalities for network characterization. Here, we present a refined protocol for in vivo widefield calcium imaging of both cerebral hemispheres in mice expressing a calcium sensor in excitatory neurons. We implemented a stringent protocol for minimizing anesthesia and excluding movement artifacts which both imposed problems in previous approaches. We further adopted a method for unbiased identification of functional cortical areas using independent component analysis (ICA) on resting-state imaging data. Biological relevance of identified components was confirmed using stimulus-dependent cortical activation. To explore this novel approach in a model of focal brain injury, we induced photothrombotic lesions of the motor cortex, determined changes in inter- and intrahemispheric connectivity at multiple time points up to 56 days post-stroke and correlated them with behavioral deficits. We observed a severe loss in interhemispheric connectivity after stroke, which was partially restored in the chronic phase and associated with corresponding behavioral motor deficits. Taken together, we present an improved widefield calcium imaging tool accounting for anesthesia and movement artifacts, adopting an advanced analysis pipeline based on human fMRI algorithms and with superior sensitivity to recovery mechanisms in mouse models compared to behavioral tests. This tool will enable new studies on interhemispheric connectivity in murine models with comparability to human imaging studies for a wide spectrum of neuroscience applications in health and disease.},\n\tjournal = {Neuroimage},\n\tauthor = {Cramer, J. V. and Gesierich, B. and Roth, S. and Dichgans, M. and During, M. and Liesz, A.},\n\tmonth = oct,\n\tyear = {2019},\n\tpmid = {31181333},\n\tkeywords = {Stroke, Female, Male, Neuroimaging, *ica, *In vivo imaging, *Mouse models, *Neuronal network connectivity, *Recovery, *Stroke, Animals, Mice, Calcium, Cerebral Cortex, Motor Cortex, Nerve Net, Connectome, Optical Imaging, Disease Models, Animal, ICA, In vivo imaging, Mice, Inbred C57BL, Mouse models, Neuronal network connectivity, Prosencephalon, Recovery},\n\tpages = {570--584},\n}\n\n

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\n The organization of brain areas in functionally connected networks, their dynamic changes, and perturbations in disease states are subject of extensive investigations. Research on functional networks in humans predominantly uses functional magnetic resonance imaging (fMRI). However, adopting fMRI and other functional imaging methods to mice, the most widely used model to study brain physiology and disease, poses major technical challenges and faces important limitations. Hence, there is great demand for alternative imaging modalities for network characterization. Here, we present a refined protocol for in vivo widefield calcium imaging of both cerebral hemispheres in mice expressing a calcium sensor in excitatory neurons. We implemented a stringent protocol for minimizing anesthesia and excluding movement artifacts which both imposed problems in previous approaches. We further adopted a method for unbiased identification of functional cortical areas using independent component analysis (ICA) on resting-state imaging data. Biological relevance of identified components was confirmed using stimulus-dependent cortical activation. To explore this novel approach in a model of focal brain injury, we induced photothrombotic lesions of the motor cortex, determined changes in inter- and intrahemispheric connectivity at multiple time points up to 56 days post-stroke and correlated them with behavioral deficits. We observed a severe loss in interhemispheric connectivity after stroke, which was partially restored in the chronic phase and associated with corresponding behavioral motor deficits. Taken together, we present an improved widefield calcium imaging tool accounting for anesthesia and movement artifacts, adopting an advanced analysis pipeline based on human fMRI algorithms and with superior sensitivity to recovery mechanisms in mouse models compared to behavioral tests. This tool will enable new studies on interhemispheric connectivity in murine models with comparability to human imaging studies for a wide spectrum of neuroscience applications in health and disease.\n

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\n \n\n \n \n \n \n \n Microglia monitor and protect neuronal function via specialized somatic purinergic junctions.\n \n \n \n\n\n \n Cserep, C.; Posfai, B.; Lenart, N.; Fekete, R.; Laszlo, Z. I.; Lele, Z.; Orsolits, B.; Molnar, G.; Heindl, S.; Schwarcz, A. D.; Ujvari, K.; Kornyei, Z.; Toth, K.; Szabadits, E.; Sperlagh, B.; Baranyi, M.; Csiba, L.; Hortobagyi, T.; Magloczky, Z.; Martinecz, B.; Szabo, G.; Erdelyi, F.; Szipocs, R.; Tamkun, M. M.; Gesierich, B.; Duering, M.; Katona, I.; Liesz, A.; Tamas, G.; and Denes, A.\n\n\n \n\n\n\n Science, 367(6477): 528–537. December 2019.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{cserep_microglia_2019,\n\ttitle = {Microglia monitor and protect neuronal function via specialized somatic purinergic junctions},\n\tvolume = {367},\n\tissn = {1095-9203 (Electronic) 0036-8075 (Linking)},\n\tdoi = {10.1126/science.aax6752},\n\tabstract = {Microglia are the main immune cells in the brain with roles in brain homeostasis and neurological diseases. Mechanisms underlying microglia-neuron communication remain elusive. Here, we identified an interaction site between neuronal cell bodies and microglial processes in mouse and human brain. Somatic microglia-neuron junctions possessed specialized nanoarchitecture optimized for purinergic signaling. Activity of neuronal mitochondria was linked with microglial junction formation, which was induced rapidly in response to neuronal activation and blocked by inhibition of P2Y12 receptors (P2Y12R). Brain injury-induced changes at somatic junctions triggered P2Y12R-dependent microglial neuroprotection, regulating neuronal calcium load and functional connectivity. Thus, microglial processes at these junctions could potentially monitor and protect neuronal functions.},\n\tnumber = {6477},\n\tjournal = {Science},\n\tauthor = {Cserep, C. and Posfai, B. and Lenart, N. and Fekete, R. and Laszlo, Z. I. and Lele, Z. and Orsolits, B. and Molnar, G. and Heindl, S. and Schwarcz, A. D. and Ujvari, K. and Kornyei, Z. and Toth, K. and Szabadits, E. and Sperlagh, B. and Baranyi, M. and Csiba, L. and Hortobagyi, T. and Magloczky, Z. and Martinecz, B. and Szabo, G. and Erdelyi, F. and Szipocs, R. and Tamkun, M. M. and Gesierich, B. and Duering, M. and Katona, I. and Liesz, A. and Tamas, G. and Denes, A.},\n\tmonth = dec,\n\tyear = {2019},\n\tpmid = {31831638},\n\tkeywords = {Humans, HEK293 Cells, Animals, Mice, Brain Injuries/*immunology/pathology, Brain/*immunology/ultrastructure, Calcium, Cell Communication/immunology, Intercellular Junctions/*immunology, Microglia/*immunology, Mitochondria/immunology, Neurons/*immunology, Receptors, Purinergic P2Y12/*physiology, Shab Potassium Channels/genetics/physiology, Signal Transduction, Brain, Microglia, Neurons, Brain Injuries, Cell Communication, Intercellular Junctions, Mitochondria, Receptors, Purinergic P2Y12, Shab Potassium Channels},\n\tpages = {528--537},\n}\n\n

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\n \n\n \n \n \n \n \n Proceedings from the Albert Charitable Trust Inaugural Workshop on white matter and cognition in aging.\n \n \n \n\n\n \n Sorond, F. A.; Whitehead, S.; Arai, K.; Arnold, D.; Carmichael, S. T.; De Carli, C.; Duering, M.; Fornage, M.; Flores-Obando, R. E.; Graff-Radford, J.; Hamel, E.; Hess, D. C.; Ihara, M.; Jensen, M. K.; Markus, H. S.; Montagne, A.; Rosenberg, G.; Shih, A. Y.; Smith, E. E.; Thiel, A.; Tse, K. H.; Wilcock, D.; and Barone, F.\n\n\n \n\n\n\n Geroscience, 42(1): 81–96. December 2019.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{sorond_proceedings_2019,\n\ttitle = {Proceedings from the {Albert} {Charitable} {Trust} {Inaugural} {Workshop} on white matter and cognition in aging},\n\tvolume = {42},\n\tissn = {2509-2723 (Electronic) 2509-2723 (Linking)},\n\tdoi = {10.1007/s11357-019-00141-8},\n\tabstract = {This third in a series of vascular cognitive impairment (VCI) workshops, supported by "The Leo and Anne Albert Charitable Trust," was held from February 8 to 12 at the Omni Resort in Carlsbad, CA. This workshop followed the information gathered from the earlier two workshops suggesting that we focus more specifically on brain white matter in age-related cognitive impairment. The Scientific Program Committee (Frank Barone, Shawn Whitehead, Eric Smith, and Rod Corriveau) assembled translational, clinical, and basic scientists with unique expertise in acute and chronic white matter injury at the intersection of cerebrovascular and neurodegenerative etiologies. As in previous Albert Trust workshops, invited participants addressed key topics related to mechanisms of white matter injury, biomarkers of white matter injury, and interventions to prevent white matter injury and age-related cognitive decline. This report provides a synopsis of the presentations and discussions by the participants, including the existing knowledge gaps and the delineation of the next steps towards advancing our understanding of white matter injury and age-related cognitive decline. Workshop discussions and consensus resulted in action by The Albert Trust to (1) increase support from biannual to annual "White Matter and Cognition" workshops; (2) provide funding for two collaborative, novel research grants annually submitted by meeting participants; and (3) coordinate the formation of the "Albert Research Institute for White Matter and Cognition." This institute will fill a gap in white matter science, providing white matter and cognition communications, including annual updates from workshops and the literature and interconnecting with other Albert Trust scientific endeavors in cognition and dementia, and providing support for newly established collaborations between seasoned investigators and to the development of talented young investigators in the VCI-dementia (VCID) and white matter cognition arena.},\n\tnumber = {1},\n\tjournal = {Geroscience},\n\tauthor = {Sorond, F. A. and Whitehead, S. and Arai, K. and Arnold, D. and Carmichael, S. T. and De Carli, C. and Duering, M. and Fornage, M. and Flores-Obando, R. E. and Graff-Radford, J. and Hamel, E. and Hess, D. C. and Ihara, M. and Jensen, M. K. and Markus, H. S. and Montagne, A. and Rosenberg, G. and Shih, A. Y. and Smith, E. E. and Thiel, A. and Tse, K. H. and Wilcock, D. and Barone, F.},\n\tmonth = dec,\n\tyear = {2019},\n\tpmcid = {PMC7031447},\n\tpmid = {31811528},\n\tkeywords = {Cognition, Humans, Aging, Blood-brain barrier, Brain white matter, Myelin, Neurovascular, Oligovascular, Vascular cognitive impairment (VCID), Dementia, Vascular, White Matter, Cognitive Dysfunction},\n\tpages = {81--96},\n}\n\n

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\n This third in a series of vascular cognitive impairment (VCI) workshops, supported by \"The Leo and Anne Albert Charitable Trust,\" was held from February 8 to 12 at the Omni Resort in Carlsbad, CA. This workshop followed the information gathered from the earlier two workshops suggesting that we focus more specifically on brain white matter in age-related cognitive impairment. The Scientific Program Committee (Frank Barone, Shawn Whitehead, Eric Smith, and Rod Corriveau) assembled translational, clinical, and basic scientists with unique expertise in acute and chronic white matter injury at the intersection of cerebrovascular and neurodegenerative etiologies. As in previous Albert Trust workshops, invited participants addressed key topics related to mechanisms of white matter injury, biomarkers of white matter injury, and interventions to prevent white matter injury and age-related cognitive decline. This report provides a synopsis of the presentations and discussions by the participants, including the existing knowledge gaps and the delineation of the next steps towards advancing our understanding of white matter injury and age-related cognitive decline. Workshop discussions and consensus resulted in action by The Albert Trust to (1) increase support from biannual to annual \"White Matter and Cognition\" workshops; (2) provide funding for two collaborative, novel research grants annually submitted by meeting participants; and (3) coordinate the formation of the \"Albert Research Institute for White Matter and Cognition.\" This institute will fill a gap in white matter science, providing white matter and cognition communications, including annual updates from workshops and the literature and interconnecting with other Albert Trust scientific endeavors in cognition and dementia, and providing support for newly established collaborations between seasoned investigators and to the development of talented young investigators in the VCI-dementia (VCID) and white matter cognition arena.\n

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\n \n\n \n \n \n \n \n Peak width of skeletonized mean diffusivity and its association with age-related cognitive alterations and vascular risk factors.\n \n \n \n\n\n \n Lam, B. Y. K.; Leung, K. T.; Yiu, B.; Zhao, L.; Biesbroek, J. M.; Au, L.; Tang, Y.; Wang, K.; Fan, Y.; Fu, J. H.; Xu, Q.; Song, H.; Tian, X.; Chu, W. C. W.; Abrigo, J.; Shi, L.; Ko, H.; Lau, A.; Duering, M.; Wong, A.; and Mok, V. C. T.\n\n\n \n\n\n\n Alzheimers Dement (Amst), 11: 721–729. December 2019.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{lam_peak_2019,\n\ttitle = {Peak width of skeletonized mean diffusivity and its association with age-related cognitive alterations and vascular risk factors},\n\tvolume = {11},\n\tissn = {2352-8729 (Print)},\n\tdoi = {10.1016/j.dadm.2019.09.003},\n\tabstract = {Introduction: Only two studies investigated the associations between peak width of skeletonized mean diffusivity (PSMD) and age-related cognitive alterations, whereas none of the studies investigated the association with vascular risk factors. Methods: We evaluated 801 stroke- and dementia-free elderlies with baseline and 3-year follow-up assessments. Regression analyses were used to assess the association between age-related cognitive functions and PSMD. Simple mediation models were used to study the mediation effect of PSMD between vascular risk factors and age-related cognitive outcomes. Results: PSMD was negatively associated with processing speed at baseline and negatively associated with processing and memory scores at 3-year follow-up. The association between vascular risk factors and age-related cognition was mediated by PSMD, as well as other diffusion tensor imaging markers. Discussion: PSMD is preferred over other diffusion tensor imaging markers as it is sensitive to age-related cognitive alterations and calculation is fully automated. PSMD is proposed as a research tool to monitor age-related cognitive alterations.},\n\tjournal = {Alzheimers Dement (Amst)},\n\tauthor = {Lam, B. Y. K. and Leung, K. T. and Yiu, B. and Zhao, L. and Biesbroek, J. M. and Au, L. and Tang, Y. and Wang, K. and Fan, Y. and Fu, J. H. and Xu, Q. and Song, H. and Tian, X. and Chu, W. C. W. and Abrigo, J. and Shi, L. and Ko, H. and Lau, A. and Duering, M. and Wong, A. and Mok, V. C. T.},\n\tmonth = dec,\n\tyear = {2019},\n\tpmcid = {PMC6829102},\n\tpmid = {31700990},\n\tkeywords = {Small vessel disease, Processing speed, Community subjects, Diffusion tensor imaging, Peak width of skeletonized mean diffusivity},\n\tpages = {721--729},\n}\n\n

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\n \n\n \n \n \n \n \n Author Correction: Multimodal imaging analyses in patients with genetic and sporadic forms of small vessel disease.\n \n \n \n\n\n \n Kim, K. W.; Kwon, H.; Kim, Y. E.; Yoon, C. W.; Kim, Y. J.; Kim, Y. B.; Lee, J. M.; Yoon, W. T.; Kim, H. J.; Lee, J. S.; Jang, Y. K.; Kim, Y.; Jang, H.; Ki, C. S.; Youn, Y. C.; Shin, B. S.; Bang, O. Y.; Kim, G. M.; Chung, C. S.; Kim, S. J.; Na, D. L.; Duering, M.; Cho, H.; and Seo, S. W.\n\n\n \n\n\n\n Sci Rep, 9(1): 15010. October 2019.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{kim_author_2019,\n\ttitle = {Author {Correction}: {Multimodal} imaging analyses in patients with genetic and sporadic forms of small vessel disease},\n\tvolume = {9},\n\tissn = {2045-2322 (Electronic) 2045-2322 (Linking)},\n\tdoi = {10.1038/s41598-019-51400-9},\n\tabstract = {An amendment to this paper has been published and can be accessed via a link at the top of the paper.},\n\tnumber = {1},\n\tjournal = {Sci Rep},\n\tauthor = {Kim, K. W. and Kwon, H. and Kim, Y. E. and Yoon, C. W. and Kim, Y. J. and Kim, Y. B. and Lee, J. M. and Yoon, W. T. and Kim, H. J. and Lee, J. S. and Jang, Y. K. and Kim, Y. and Jang, H. and Ki, C. S. and Youn, Y. C. and Shin, B. S. and Bang, O. Y. and Kim, G. M. and Chung, C. S. and Kim, S. J. and Na, D. L. and Duering, M. and Cho, H. and Seo, S. W.},\n\tmonth = oct,\n\tyear = {2019},\n\tpmcid = {PMC6791941},\n\tpmid = {31611605},\n\tpages = {15010},\n}\n\n

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\n \n\n \n \n \n \n \n Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping.\n \n \n \n\n\n \n Biesbroek, J. M.; Kuijf, H. J.; Weaver, N. A.; Zhao, L.; Duering, M.; Meta, V. C. I. M. C.; and Biessels, G. J.\n\n\n \n\n\n\n J Vis Exp, (151). September 2019.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{biesbroek_brain_2019,\n\ttitle = {Brain {Infarct} {Segmentation} and {Registration} on {MRI} or {CT} for {Lesion}-symptom {Mapping}},\n\tissn = {1940-087X (Electronic) 1940-087X (Linking)},\n\tdoi = {10.3791/59653},\n\tabstract = {In lesion-symptom mapping (LSM), brain function is inferred by relating the location of acquired brain lesions to behavioral or cognitive symptoms in a group of patients. With recent advances in brain imaging and image processing, LSM has become a popular tool in cognitive neuroscience. LSM can provide fundamental insights into the functional architecture of the human brain for a variety of cognitive and non-cognitive functions. A crucial step in performing LSM studies is the segmentation of lesions on brains scans of a large group of patients and registration of each scan to a common stereotaxic space (also called standard space or a standardized brain template). Described here is an open-access, standardized method for infarct segmentation and registration for the purpose of LSM, as well as a detailed and hands-on walkthrough based on exemplary cases. A comprehensive tutorial for the manual segmentation of brain infarcts on CT scans and DWI or FLAIR MRI sequences is provided, including criteria for infarct identification and pitfalls for different scan types. The registration software provides multiple registration schemes that can be used for processing of CT and MRI data with heterogeneous acquisition parameters. A tutorial on using this registration software and performing visual quality checks and manual corrections (which are needed in some cases) is provided. This approach provides researchers with a framework for the entire process of brain image processing required to perform an LSM study, from gathering of the data to final quality checks of the results.},\n\tnumber = {151},\n\tjournal = {J Vis Exp},\n\tauthor = {Biesbroek, J. M. and Kuijf, H. J. and Weaver, N. A. and Zhao, L. and Duering, M. and Meta, V. C. I. Map Consortium and Biessels, G. J.},\n\tmonth = sep,\n\tyear = {2019},\n\tpmid = {31609325},\n\tkeywords = {Female, Humans, Image Processing, Computer-Assisted, Male, Middle Aged, Magnetic Resonance Imaging, *Magnetic Resonance Imaging, *Image Processing, Computer-Assisted, *Tomography, X-Ray Computed, Artifacts, Brain Infarction/*diagnostic imaging, Brain Mapping/methods, Motion, Software, Tomography, X-Ray Computed, Brain Mapping, Brain Infarction},\n}\n\n

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\n \n\n \n \n \n \n \n Safety and efficacy of epigallocatechin gallate in multiple system atrophy (PROMESA): a randomised, double-blind, placebo-controlled trial.\n \n \n \n\n\n \n Levin, J.; Maass, S.; Schuberth, M.; Giese, A.; Oertel, W. H.; Poewe, W.; Trenkwalder, C.; Wenning, G. K.; Mansmann, U.; Sudmeyer, M.; Eggert, K.; Mollenhauer, B.; Lipp, A.; Lohle, M.; Classen, J.; Munchau, A.; Kassubek, J.; Gandor, F.; Berg, D.; Egert-Schwender, S.; Eberhardt, C.; Paul, F.; Botzel, K.; Ertl-Wagner, B.; Huppertz, H. J.; Ricard, I.; Hoglinger, G. U.; and Group, P. S.\n\n\n \n\n\n\n Lancet Neurol, 18(8): 724–735. August 2019.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{levin_safety_2019,\n\ttitle = {Safety and efficacy of epigallocatechin gallate in multiple system atrophy ({PROMESA}): a randomised, double-blind, placebo-controlled trial},\n\tvolume = {18},\n\tissn = {1474-4465 (Electronic) 1474-4422 (Linking)},\n\tdoi = {10.1016/S1474-4422(19)30141-3},\n\tabstract = {BACKGROUND: Multiple system atrophy is a rare neurodegenerative disease characterised by aggregation of alpha-synuclein in oligodendrocytes and neurons. The polyphenol epigallocatechin gallate inhibits alpha-synuclein aggregation and reduces associated toxicity. We aimed to establish if epigallocatechin gallate could safely slow disease progression in patients with multiple system atrophy. METHODS: We did a randomised, double-blind, parallel group, placebo-controlled clinical trial at 12 specialist centres in Germany. Eligible participants were older than 30 years; met consensus criteria for possible or probable multiple system atrophy and could ambulate independently (ie, were at Hoehn and Yahr stages 1-3); and were on stable anti-Parkinson's, anti-dysautonomia, anti-dementia, and anti-depressant regimens (if necessary) for at least 1 month. Participants were randomly assigned (1:1) to epigallocatechin gallate or placebo (mannitol) via a web-generated permuted blockwise randomisation list (block size=2) that was stratified by disease subtype (parkinsonism-predominant disease vs cerebellar-ataxia-predominant disease). All participants and study personnel were masked to treatment assignment. Participants were given one hard gelatin capsule (containing either 400 mg epigallocatechin gallate or mannitol) orally once daily for 4 weeks, then one capsule twice daily for 4 weeks, and then one capsule three times daily for 40 weeks. After 48 weeks, all patients underwent a 4-week wash-out period. The primary endpoint was change in motor examination score of the Unified Multiple System Atrophy Rating Scale (UMSARS) from baseline to 52 weeks. Efficacy analyses were done in all people who received at least one dose of study medication. Safety was analysed in all people who received at least one dose of the study medication to which they had been randomly assigned. This trial is registered with ClinicalTrials.gov (NCT02008721) and EudraCT (2012-000928-18), and is completed. FINDINGS: Between April 23, 2014, and Sept 3, 2015, 127 participants were screened and 92 were randomly assigned-47 to epigallocatechin gallate and 45 to placebo. Of these, 67 completed treatment and 64 completed the study (altough one of these patients had a major protocol violation). There was no evidence of a difference in the mean change from baseline to week 52 in motor examination scores on UMSARS between the epigallocatechin gallate (5.66 [SE 1.01]) and placebo (6.60 [0.99]) groups (mean difference -0.94 [SE 1.41; 95\\% CI -3.71 to 1.83]; p=0.51). Four patients in the epigallocatechin gallate group and two in the placebo group died. Two patients in the epigallocatechin gallate group had to stop treatment because of hepatotoxicity. INTERPRETATION: 48 weeks of epigallocatechin gallate treatment did not modify disease progression in patients with multiple system atrophy. Epigallocatechin gallate was overall well tolerated but was associated with hepatotoxic effects in some patients, and thus doses of more than 1200 mg should not be used. FUNDING: ParkinsonFonds Deutschland, German Parkinson Society, German Neurology Foundation, Luneburg Foundation, Bischof Dr Karl Golser Foundation, and Dr Arthur Arnstein Foundation.},\n\tnumber = {8},\n\tjournal = {Lancet Neurol},\n\tauthor = {Levin, J. and Maass, S. and Schuberth, M. and Giese, A. and Oertel, W. H. and Poewe, W. and Trenkwalder, C. and Wenning, G. K. and Mansmann, U. and Sudmeyer, M. and Eggert, K. and Mollenhauer, B. and Lipp, A. and Lohle, M. and Classen, J. and Munchau, A. and Kassubek, J. and Gandor, F. and Berg, D. and Egert-Schwender, S. and Eberhardt, C. and Paul, F. and Botzel, K. and Ertl-Wagner, B. and Huppertz, H. J. and Ricard, I. and Hoglinger, G. U. and Promesa Study Group},\n\tmonth = aug,\n\tyear = {2019},\n\tpmid = {31278067},\n\tkeywords = {Aged, Disease Progression, Female, Humans, Male, Middle Aged, Germany, Treatment Outcome, Catechin, Double-Blind Method, Multiple System Atrophy, Neuroprotective Agents},\n\tpages = {724--735},\n}\n\n

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\n BACKGROUND: Multiple system atrophy is a rare neurodegenerative disease characterised by aggregation of alpha-synuclein in oligodendrocytes and neurons. The polyphenol epigallocatechin gallate inhibits alpha-synuclein aggregation and reduces associated toxicity. We aimed to establish if epigallocatechin gallate could safely slow disease progression in patients with multiple system atrophy. METHODS: We did a randomised, double-blind, parallel group, placebo-controlled clinical trial at 12 specialist centres in Germany. Eligible participants were older than 30 years; met consensus criteria for possible or probable multiple system atrophy and could ambulate independently (ie, were at Hoehn and Yahr stages 1-3); and were on stable anti-Parkinson's, anti-dysautonomia, anti-dementia, and anti-depressant regimens (if necessary) for at least 1 month. Participants were randomly assigned (1:1) to epigallocatechin gallate or placebo (mannitol) via a web-generated permuted blockwise randomisation list (block size=2) that was stratified by disease subtype (parkinsonism-predominant disease vs cerebellar-ataxia-predominant disease). All participants and study personnel were masked to treatment assignment. Participants were given one hard gelatin capsule (containing either 400 mg epigallocatechin gallate or mannitol) orally once daily for 4 weeks, then one capsule twice daily for 4 weeks, and then one capsule three times daily for 40 weeks. After 48 weeks, all patients underwent a 4-week wash-out period. The primary endpoint was change in motor examination score of the Unified Multiple System Atrophy Rating Scale (UMSARS) from baseline to 52 weeks. Efficacy analyses were done in all people who received at least one dose of study medication. Safety was analysed in all people who received at least one dose of the study medication to which they had been randomly assigned. This trial is registered with ClinicalTrials.gov (NCT02008721) and EudraCT (2012-000928-18), and is completed. FINDINGS: Between April 23, 2014, and Sept 3, 2015, 127 participants were screened and 92 were randomly assigned-47 to epigallocatechin gallate and 45 to placebo. Of these, 67 completed treatment and 64 completed the study (altough one of these patients had a major protocol violation). There was no evidence of a difference in the mean change from baseline to week 52 in motor examination scores on UMSARS between the epigallocatechin gallate (5.66 [SE 1.01]) and placebo (6.60 [0.99]) groups (mean difference -0.94 [SE 1.41; 95% CI -3.71 to 1.83]; p=0.51). Four patients in the epigallocatechin gallate group and two in the placebo group died. Two patients in the epigallocatechin gallate group had to stop treatment because of hepatotoxicity. INTERPRETATION: 48 weeks of epigallocatechin gallate treatment did not modify disease progression in patients with multiple system atrophy. Epigallocatechin gallate was overall well tolerated but was associated with hepatotoxic effects in some patients, and thus doses of more than 1200 mg should not be used. FUNDING: ParkinsonFonds Deutschland, German Parkinson Society, German Neurology Foundation, Luneburg Foundation, Bischof Dr Karl Golser Foundation, and Dr Arthur Arnstein Foundation.\n

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\n \n\n \n \n \n \n \n Vascular Cognitive Impairment and Dementia: JACC Scientific Expert Panel.\n \n \n \n\n\n \n Iadecola, C.; Duering, M.; Hachinski, V.; Joutel, A.; Pendlebury, S. T.; Schneider, J. A.; and Dichgans, M.\n\n\n \n\n\n\n J Am Coll Cardiol, 73(25): 3326–3344. July 2019.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{iadecola_vascular_2019,\n\ttitle = {Vascular {Cognitive} {Impairment} and {Dementia}: {JACC} {Scientific} {Expert} {Panel}},\n\tvolume = {73},\n\tissn = {1558-3597 (Electronic) 0735-1097 (Linking)},\n\tdoi = {10.1016/j.jacc.2019.04.034},\n\tabstract = {Cognitive impairment associated with aging has emerged as one of the major public health challenges of our time. Although Alzheimer's disease is the leading cause of clinically diagnosed dementia in Western countries, cognitive impairment of vascular etiology is the second most common cause and may be the predominant one in East Asia. Furthermore, alterations of the large and small cerebral vasculature, including those affecting the microcirculation of the subcortical white matter, are key contributors to the clinical expression of cognitive dysfunction caused by other pathologies, including Alzheimer's disease. This scientific expert panel provides a critical appraisal of the epidemiology, pathobiology, neuropathology, and neuroimaging of vascular cognitive impairment and dementia, and of current diagnostic and therapeutic approaches. Unresolved issues are also examined to shed light on new basic and clinical research avenues that may lead to mitigating one of the most devastating human conditions.},\n\tnumber = {25},\n\tjournal = {J Am Coll Cardiol},\n\tauthor = {Iadecola, C. and Duering, M. and Hachinski, V. and Joutel, A. and Pendlebury, S. T. and Schneider, J. A. and Dichgans, M.},\n\tmonth = jul,\n\tyear = {2019},\n\tpmcid = {PMC6719789},\n\tpmid = {31248555},\n\tkeywords = {small vessel disease, Humans, Alzheimer's disease, stroke, cerebral blood flow, cognitive dysfunction, Dementia, Vascular, Alzheimer’s disease, Cognitive Dysfunction},\n\tpages = {3326--3344},\n}\n\n

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\n \n\n \n \n \n \n \n Decreased CSF Levels of ss-Amyloid in Patients With Cortical Superficial Siderosis.\n \n \n \n\n\n \n Catak, C.; Zedde, M.; Malik, R.; Janowitz, D.; Soric, V.; Seegerer, A.; Krebs, A.; During, M.; Opherk, C.; Linn, J.; and Wollenweber, F. A.\n\n\n \n\n\n\n Front Neurol, 10: 439. 2019.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{catak_decreased_2019,\n\ttitle = {Decreased {CSF} {Levels} of ss-{Amyloid} in {Patients} {With} {Cortical} {Superficial} {Siderosis}},\n\tvolume = {10},\n\tissn = {1664-2295 (Print) 1664-2295 (Linking)},\n\tdoi = {10.3389/fneur.2019.00439},\n\tabstract = {Background: Cortical superficial siderosis (cSS) represents a key neuroimaging marker of cerebral amyloid angiopathy (CAA) that is associated with intracranial hemorrhages and cognitive impairment. Nevertheless, the association between cSS and core cerebrospinal fluid (CSF) biomarkers for dementia remain unclear. Methods: One hundred and one patients with probable (79\\%, 80/101) or possible (21\\%, 21/101) CAA according to the modified Boston criteria and mild cognitive impairment according to Petersen criteria were prospectively included between 2011 and 2016. CSF analyses of ss-amyloid 42, ss-amyloid 40, total tau and phosphorylated tau were performed using sandwich-type enzyme-linked immunosorbent-assay. All patients received MRI and Mini-Mental-State Examination (MMSE). Logistic regression analysis was used to adjust for possible confounders. Results: cSS was present in 61\\% (62/101). Of those, 53\\% (33/62) had disseminated cSS and 47\\% (29/62) focal cSS. ss-amyloid 42 was lower in patients with cSS than in patients without cSS (OR 0.2; 95\\% CI 0.08-0.6; p = 0.0052) and lower in patients with disseminated cSS than in those with focal cSS (OR 0.02; 95\\% CI 0.003-0.2; p = 0.00057). Presence of cSS had no association with regard to ss-amyloid 40, total tau and phosphorylated tau. Conclusions: Our results demonstrate that the presence and extent of cSS are associated with reduced CSF ss-amyloid 42 levels. Further studies are needed to investigate the underlying mechanisms of this association.},\n\tjournal = {Front Neurol},\n\tauthor = {Catak, C. and Zedde, M. and Malik, R. and Janowitz, D. and Soric, V. and Seegerer, A. and Krebs, A. and During, M. and Opherk, C. and Linn, J. and Wollenweber, F. A.},\n\tyear = {2019},\n\tpmcid = {PMC6498501},\n\tpmid = {31105644},\n\tkeywords = {cerebral amyloid angiopathy, cerebral microbleeds, cerebrospinal fluid, cortical superficial siderosis, neuroimaging},\n\tpages = {439},\n}\n\n

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\n \n\n \n \n \n \n \n The Meta VCI Map consortium for meta-analyses on strategic lesion locations for vascular cognitive impairment using lesion-symptom mapping: Design and multicenter pilot study.\n \n \n \n\n\n \n Weaver, N. A.; Zhao, L.; Biesbroek, J. M.; Kuijf, H. J.; Aben, H. P.; Bae, H. J.; Caballero, M. A. A.; Chappell, F. M.; Chen, C.; Dichgans, M.; Duering, M.; Georgakis, M. K.; van der Giessen, R. S.; Gyanwali, B.; Hamilton, O. K. L.; Hilal, S.; Vom Hofe, E. M.; de Kort, P. L. M.; Koudstaal, P. J.; Lam, B. Y. K.; Lim, J. S.; Makin, S. D. J.; Mok, V. C. T.; Shi, L.; Valdes Hernandez, M. C.; Venketasubramanian, N.; Wardlaw, J. M.; Wollenweber, F. A.; Wong, A.; Xin, X.; Meta, V. C. I. M. c.; and Biessels, G. J.\n\n\n \n\n\n\n Alzheimers Dement (Amst), 11: 310–326. December 2019.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{weaver_meta_2019,\n\ttitle = {The {Meta} {VCI} {Map} consortium for meta-analyses on strategic lesion locations for vascular cognitive impairment using lesion-symptom mapping: {Design} and multicenter pilot study},\n\tvolume = {11},\n\tissn = {2352-8729 (Print)},\n\tdoi = {10.1016/j.dadm.2019.02.007},\n\tabstract = {Introduction: The Meta VCI Map consortium performs meta-analyses on strategic lesion locations for vascular cognitive impairment using lesion-symptom mapping. Integration of data from different cohorts will increase sample sizes, to improve brain lesion coverage and support comprehensive lesion-symptom mapping studies. Methods: Cohorts with available imaging on white matter hyperintensities or infarcts and cognitive testing were invited. We performed a pilot study to test the feasibility of multicenter data processing and analysis and determine the benefits to lesion coverage. Results: Forty-seven groups have joined Meta VCI Map (stroke n = 7800 patients; memory clinic n = 4900; population-based n = 14,400). The pilot study (six ischemic stroke cohorts, n = 878) demonstrated feasibility of multicenter data integration (computed tomography/magnetic resonance imaging) and achieved marked improvement of lesion coverage. Discussion: Meta VCI Map will provide new insights into the relevance of vascular lesion location for cognitive dysfunction. After the successful pilot study, further projects are being prepared. Other investigators are welcome to join.},\n\tjournal = {Alzheimers Dement (Amst)},\n\tauthor = {Weaver, N. A. and Zhao, L. and Biesbroek, J. M. and Kuijf, H. J. and Aben, H. P. and Bae, H. J. and Caballero, M. A. A. and Chappell, F. M. and Chen, Cplh and Dichgans, M. and Duering, M. and Georgakis, M. K. and van der Giessen, R. S. and Gyanwali, B. and Hamilton, O. K. L. and Hilal, S. and Vom Hofe, E. M. and de Kort, P. L. M. and Koudstaal, P. J. and Lam, B. Y. K. and Lim, J. S. and Makin, S. D. J. and Mok, V. C. T. and Shi, L. and Valdes Hernandez, M. C. and Venketasubramanian, N. and Wardlaw, J. M. and Wollenweber, F. A. and Wong, A. and Xin, X. and Meta, V. C. I. Map consortium and Biessels, G. J.},\n\tmonth = dec,\n\tyear = {2019},\n\tpmcid = {PMC6465616},\n\tpmid = {31011619},\n\tkeywords = {Small vessel disease, Stroke, Vascular cognitive impairment, Cerebrovascular disease, Consortium, Data harmonization, Lesion location, Lesion-symptom mapping, Support vector regression},\n\tpages = {310--326},\n}\n\n

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\n \n\n \n \n \n \n \n The BDNFVal66Met SNP modulates the association between beta-amyloid and hippocampal disconnection in Alzheimer's disease.\n \n \n \n\n\n \n Franzmeier, N.; Ren, J.; Damm, A.; Monte-Rubio, G.; Boada, M.; Ruiz, A.; Ramirez, A.; Jessen, F.; Duzel, E.; Rodriguez Gomez, O.; Benzinger, T.; Goate, A.; Karch, C. M.; Fagan, A. M.; McDade, E.; Buerger, K.; Levin, J.; Duering, M.; Dichgans, M.; Suarez-Calvet, M.; Haass, C.; Gordon, B. A.; Lim, Y. Y.; Masters, C. L.; Janowitz, D.; Catak, C.; Wolfsgruber, S.; Wagner, M.; Milz, E.; Moreno-Grau, S.; Teipel, S.; Grothe, M. J.; Kilimann, I.; Rossor, M.; Fox, N.; Laske, C.; Chhatwal, J.; Falkai, P.; Perneczky, R.; Lee, J. H.; Spottke, A.; Boecker, H.; Brosseron, F.; Fliessbach, K.; Heneka, M. T.; Nestor, P.; Peters, O.; Fuentes, M.; Menne, F.; Priller, J.; Spruth, E. J.; Franke, C.; Schneider, A.; Westerteicher, C.; Speck, O.; Wiltfang, J.; Bartels, C.; Araque Caballero, M. A.; Metzger, C.; Bittner, D.; Salloway, S.; Danek, A.; Hassenstab, J.; Yakushev, I.; Schofield, P. R.; Morris, J. C.; Bateman, R. J.; and Ewers, M.\n\n\n \n\n\n\n Mol Psychiatry, 26(2): 614–628. March 2019.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{franzmeier_bdnfval66met_2019,\n\ttitle = {The {BDNFVal66Met} {SNP} modulates the association between beta-amyloid and hippocampal disconnection in {Alzheimer}'s disease},\n\tvolume = {26},\n\tissn = {1476-5578 (Electronic) 1359-4184 (Linking)},\n\tdoi = {10.1038/s41380-019-0404-6},\n\tabstract = {In Alzheimer's disease (AD), a single-nucleotide polymorphism in the gene encoding brain-derived neurotrophic factor (BDNFVal66Met) is associated with worse impact of primary AD pathology (beta-amyloid, Abeta) on neurodegeneration and cognitive decline, rendering BDNFVal66Met an important modulating factor of cognitive impairment in AD. However, the effect of BDNFVal66Met on functional networks that may underlie cognitive impairment in AD is poorly understood. Using a cross-validation approach, we first explored in subjects with autosomal dominant AD (ADAD) from the Dominantly Inherited Alzheimer Network (DIAN) the effect of BDNFVal66Met on resting-state fMRI assessed functional networks. In seed-based connectivity analysis of six major large-scale networks, we found a stronger decrease of hippocampus (seed) to medial-frontal connectivity in the BDNFVal66Met carriers compared to BDNFVal homozogytes. BDNFVal66Met was not associated with connectivity in any other networks. Next, we tested whether the finding of more pronounced decrease in hippocampal-medial-frontal connectivity in BDNFVal66Met could be also found in elderly subjects with sporadically occurring Abeta, including a group with subjective cognitive decline (N = 149, FACEHBI study) and a group ranging from preclinical to AD dementia (N = 114, DELCODE study). In both of these independently recruited groups, BDNFVal66Met was associated with a stronger effect of more abnormal Abeta-levels (assessed by biofluid-assay or amyloid-PET) on hippocampal-medial-frontal connectivity decreases, controlled for hippocampus volume and other confounds. Lower hippocampal-medial-frontal connectivity was associated with lower global cognitive performance in the DIAN and DELCODE studies. Together these results suggest that BDNFVal66Met is selectively associated with a higher vulnerability of hippocampus-frontal connectivity to primary AD pathology, resulting in greater AD-related cognitive impairment.},\n\tnumber = {2},\n\tjournal = {Mol Psychiatry},\n\tauthor = {Franzmeier, N. and Ren, J. and Damm, A. and Monte-Rubio, G. and Boada, M. and Ruiz, A. and Ramirez, A. and Jessen, F. and Duzel, E. and Rodriguez Gomez, O. and Benzinger, T. and Goate, A. and Karch, C. M. and Fagan, A. M. and McDade, E. and Buerger, K. and Levin, J. and Duering, M. and Dichgans, M. and Suarez-Calvet, M. and Haass, C. and Gordon, B. A. and Lim, Y. Y. and Masters, C. L. and Janowitz, D. and Catak, C. and Wolfsgruber, S. and Wagner, M. and Milz, E. and Moreno-Grau, S. and Teipel, S. and Grothe, M. J. and Kilimann, I. and Rossor, M. and Fox, N. and Laske, C. and Chhatwal, J. and Falkai, P. and Perneczky, R. and Lee, J. H. and Spottke, A. and Boecker, H. and Brosseron, F. and Fliessbach, K. and Heneka, M. T. and Nestor, P. and Peters, O. and Fuentes, M. and Menne, F. and Priller, J. and Spruth, E. J. and Franke, C. and Schneider, A. and Westerteicher, C. and Speck, O. and Wiltfang, J. and Bartels, C. and Araque Caballero, M. A. and Metzger, C. and Bittner, D. and Salloway, S. and Danek, A. and Hassenstab, J. and Yakushev, I. and Schofield, P. R. and Morris, J. C. and Bateman, R. J. and Ewers, M.},\n\tmonth = mar,\n\tyear = {2019},\n\tpmcid = {PMC6754794},\n\tpmid = {30899092},\n\tkeywords = {Aged, Humans, Magnetic Resonance Imaging, Hippocampus, Positron-Emission Tomography, Amyloid beta-Peptides, Brain, Alzheimer Disease, Cognitive Dysfunction, Polymorphism, Single Nucleotide, Brain-Derived Neurotrophic Factor},\n\tpages = {614--628},\n}\n\n

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\n \n\n \n \n \n \n \n Harmonizing brain magnetic resonance imaging methods for vascular contributions to neurodegeneration.\n \n \n \n\n\n \n Smith, E. E.; Biessels, G. J.; De Guio, F.; de Leeuw, F. E.; Duchesne, S.; During, M.; Frayne, R.; Ikram, M. A.; Jouvent, E.; MacIntosh, B. J.; Thrippleton, M. J.; Vernooij, M. W.; Adams, H.; Backes, W. H.; Ballerini, L.; Black, S. E.; Chen, C.; Corriveau, R.; DeCarli, C.; Greenberg, S. M.; Gurol, M. E.; Ingrisch, M.; Job, D.; Lam, B. Y. K.; Launer, L. J.; Linn, J.; McCreary, C. R.; Mok, V. C. T.; Pantoni, L.; Pike, G. B.; Ramirez, J.; Reijmer, Y. D.; Romero, J. R.; Ropele, S.; Rost, N. S.; Sachdev, P. S.; Scott, C. J. M.; Seshadri, S.; Sharma, M.; Sourbron, S.; Steketee, R. M. E.; Swartz, R. H.; van Oostenbrugge, R.; van Osch, M.; van Rooden, S.; Viswanathan, A.; Werring, D.; Dichgans, M.; and Wardlaw, J. M.\n\n\n \n\n\n\n Alzheimers Dement (Amst), 11: 191–204. December 2019.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{smith_harmonizing_2019,\n\ttitle = {Harmonizing brain magnetic resonance imaging methods for vascular contributions to neurodegeneration},\n\tvolume = {11},\n\tissn = {2352-8729 (Print)},\n\tdoi = {10.1016/j.dadm.2019.01.002},\n\tabstract = {Introduction: Many consequences of cerebrovascular disease are identifiable by magnetic resonance imaging (MRI), but variation in methods limits multicenter studies and pooling of data. The European Union Joint Program on Neurodegenerative Diseases (EU JPND) funded the HARmoNizing Brain Imaging MEthodS for VaScular Contributions to Neurodegeneration (HARNESS) initiative, with a focus on cerebral small vessel disease. Methods: Surveys, teleconferences, and an in-person workshop were used to identify gaps in knowledge and to develop tools for harmonizing imaging and analysis. Results: A framework for neuroimaging biomarker development was developed based on validating repeatability and reproducibility, biological principles, and feasibility of implementation. The status of current MRI biomarkers was reviewed. A website was created at www.harness-neuroimaging.org with acquisition protocols, a software database, rating scales and case report forms, and a deidentified MRI repository. Conclusions: The HARNESS initiative provides resources to reduce variability in measurement in MRI studies of cerebral small vessel disease.},\n\tjournal = {Alzheimers Dement (Amst)},\n\tauthor = {Smith, E. E. and Biessels, G. J. and De Guio, F. and de Leeuw, F. E. and Duchesne, S. and During, M. and Frayne, R. and Ikram, M. A. and Jouvent, E. and MacIntosh, B. J. and Thrippleton, M. J. and Vernooij, M. W. and Adams, H. and Backes, W. H. and Ballerini, L. and Black, S. E. and Chen, C. and Corriveau, R. and DeCarli, C. and Greenberg, S. M. and Gurol, M. E. and Ingrisch, M. and Job, D. and Lam, B. Y. K. and Launer, L. J. and Linn, J. and McCreary, C. R. and Mok, V. C. T. and Pantoni, L. and Pike, G. B. and Ramirez, J. and Reijmer, Y. D. and Romero, J. R. and Ropele, S. and Rost, N. S. and Sachdev, P. S. and Scott, C. J. M. and Seshadri, S. and Sharma, M. and Sourbron, S. and Steketee, R. M. E. and Swartz, R. H. and van Oostenbrugge, R. and van Osch, M. and van Rooden, S. and Viswanathan, A. and Werring, D. and Dichgans, M. and Wardlaw, J. M.},\n\tmonth = dec,\n\tyear = {2019},\n\tpmcid = {PMC6396326},\n\tpmid = {30859119},\n\tkeywords = {Stroke, Magnetic resonance imaging, Dementia, Cerebrovascular disease, Radiology},\n\tpages = {191--204},\n}\n\n

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\n \n\n \n \n \n \n \n White Matter Hyperintensities in Alzheimer's Disease: A Lesion Probability Mapping Study.\n \n \n \n\n\n \n Damulina, A.; Pirpamer, L.; Seiler, S.; Benke, T.; Dal-Bianco, P.; Ransmayr, G.; Struhal, W.; Hofer, E.; Langkammer, C.; Duering, M.; Fazekas, F.; and Schmidt, R.\n\n\n \n\n\n\n J Alzheimers Dis, 68(2): 789–796. February 2019.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{damulina_white_2019,\n\ttitle = {White {Matter} {Hyperintensities} in {Alzheimer}'s {Disease}: {A} {Lesion} {Probability} {Mapping} {Study}},\n\tvolume = {68},\n\tissn = {1875-8908 (Electronic) 1387-2877 (Linking)},\n\tdoi = {10.3233/JAD-180982},\n\tabstract = {BACKGROUND/OBJECTIVE: Higher white matter hyperintensity (WMH) load has been reported in Alzheimer's disease (AD) patients in different brain regions when compared to controls. We aimed to assess possible differences of WMH spatial distribution between AD patients and age-matched controls by means of lesion probability maps. METHODS: The present study included MRI scans of 130 probable AD patients with a mean age of 73.4+/-8.2 years from the Prospective Dementia Registry Austria Study and 130 age-matched healthy controls (HC) from the Austrian Stroke Prevention Family Study. Risk factors such as hypertension, diabetes mellitus, hypercholesterolemia, coronary artery disease, and smoking were assessed. Manually segmented FLAIR WMH masks were non-linearly registered to a template and voxel-based probability mapping was performed. RESULTS: There were no significant between-group differences in cardiovascular risk factors and WMH volume. AD patients showed a significantly higher likelihood of having WMH in a bilateral periventricular distribution than controls before and after correcting for age, sex, cardiovascular risk factors, and ventricular volume (p{\\textless}/=0.05; threshold-free cluster enhancement corrected). There was no significant association between the periventricular WMH volume and cognitive decline of AD patients. CONCLUSION: In AD, WMH were preferentially found in a periventricular location but the volume of lesions was unrelated to cognitive decline in our study irrespective of lesion location.},\n\tnumber = {2},\n\tjournal = {J Alzheimers Dis},\n\tauthor = {Damulina, A. and Pirpamer, L. and Seiler, S. and Benke, T. and Dal-Bianco, P. and Ransmayr, G. and Struhal, W. and Hofer, E. and Langkammer, C. and Duering, M. and Fazekas, F. and Schmidt, R.},\n\tmonth = feb,\n\tyear = {2019},\n\tpmid = {30775995},\n\tkeywords = {Aged, Female, Humans, Male, Middle Aged, Alzheimer's disease, Prospective Studies, Aged, 80 and over, Follow-Up Studies, Cohort Studies, white matter hyperintensities, magnetic resonance imaging, periventricular white matter, Brain Mapping, Longitudinal Studies, Brain, White Matter, Alzheimer Disease, Alzheimer’s disease, Registries, Austria},\n\tpages = {789--796},\n}\n\n

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\n \n\n \n \n \n \n \n Functional connectivity associated with tau levels in ageing, Alzheimer's, and small vessel disease.\n \n \n \n\n\n \n Franzmeier, N.; Rubinski, A.; Neitzel, J.; Kim, Y.; Damm, A.; Na, D. L.; Kim, H. J.; Lyoo, C. H.; Cho, H.; Finsterwalder, S.; Duering, M.; Seo, S. W.; Ewers, M.; and Alzheimer's Disease Neuroimaging, I.\n\n\n \n\n\n\n Brain, 142(4): 1093–1107. April 2019.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{franzmeier_functional_2019,\n\ttitle = {Functional connectivity associated with tau levels in ageing, {Alzheimer}'s, and small vessel disease},\n\tvolume = {142},\n\tissn = {1460-2156 (Electronic) 0006-8950 (Linking)},\n\tdoi = {10.1093/brain/awz026},\n\tabstract = {In Alzheimer's disease, tau pathology spreads hierarchically from the inferior temporal lobe throughout the cortex, ensuing cognitive decline and dementia. Similarly, circumscribed patterns of pathological tau have been observed in normal ageing and small vessel disease, suggesting a spatially ordered distribution of tau pathology across normal ageing and different diseases. In vitro findings suggest that pathological tau may spread 'prion-like' across neuronal connections in an activity-dependent manner. Supporting this notion, functional brain networks show a spatial correspondence to tau deposition patterns. However, it remains unclear whether higher network-connectivity facilitates tau propagation. To address this, we included 55 normal aged elderly (i.e. cognitively normal, amyloid-negative), 50 Alzheimer's disease patients (i.e. amyloid-positive) covering the preclinical to dementia spectrum, as well as 36 patients with pure (i.e. amyloid-negative) vascular cognitive impairment due to small vessel disease. All subjects were assessed with AV1451 tau-PET and resting-state functional MRI. Within each group, we computed atlas-based resting-state functional MRI functional connectivity across 400 regions of interest covering the entire neocortex. Using the same atlas, we also assessed within each group the covariance of tau-PET levels among the 400 regions of interest. We found that higher resting-state functional MRI assessed functional connectivity between any given region of interest pair was associated with higher covariance in tau-PET binding in corresponding regions of interest. This result was consistently found in normal ageing, Alzheimer's disease and vascular cognitive impairment. In particular, inferior temporal tau-hotspots, as defined by highest tau-PET uptake, showed high predictive value of tau-PET levels in functionally closely connected regions of interest. These associations between functional connectivity and tau-PET uptake were detected regardless of presence of dementia symptoms (mild cognitive impairment or dementia), amyloid deposition (as assessed by amyloid-PET) or small vessel disease. Our findings suggest that higher functional connectivity between brain regions is associated with shared tau-levels, supporting the view of prion-like tau spreading facilitated by neural activity.},\n\tnumber = {4},\n\tjournal = {Brain},\n\tauthor = {Franzmeier, N. and Rubinski, A. and Neitzel, J. and Kim, Y. and Damm, A. and Na, D. L. and Kim, H. J. and Lyoo, C. H. and Cho, H. and Finsterwalder, S. and Duering, M. and Seo, S. W. and Ewers, M. and Alzheimer's Disease Neuroimaging, Initiative},\n\tmonth = apr,\n\tyear = {2019},\n\tpmcid = {PMC6439332},\n\tpmid = {30770704},\n\tkeywords = {Aged, Female, Humans, Male, Middle Aged, Alzheimer's disease, Magnetic Resonance Imaging, Neuropsychological Tests, Aging, functional connectivity, resting-state functional MRI, tau-PET, tau-spreading, Brain Mapping, Positron-Emission Tomography, Brain, Alzheimer Disease, Alzheimer’s disease, Cerebral Small Vessel Diseases, Cognitive Dysfunction, tau Proteins, Connectome},\n\tpages = {1093--1107},\n}\n\n

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\n In Alzheimer's disease, tau pathology spreads hierarchically from the inferior temporal lobe throughout the cortex, ensuing cognitive decline and dementia. Similarly, circumscribed patterns of pathological tau have been observed in normal ageing and small vessel disease, suggesting a spatially ordered distribution of tau pathology across normal ageing and different diseases. In vitro findings suggest that pathological tau may spread 'prion-like' across neuronal connections in an activity-dependent manner. Supporting this notion, functional brain networks show a spatial correspondence to tau deposition patterns. However, it remains unclear whether higher network-connectivity facilitates tau propagation. To address this, we included 55 normal aged elderly (i.e. cognitively normal, amyloid-negative), 50 Alzheimer's disease patients (i.e. amyloid-positive) covering the preclinical to dementia spectrum, as well as 36 patients with pure (i.e. amyloid-negative) vascular cognitive impairment due to small vessel disease. All subjects were assessed with AV1451 tau-PET and resting-state functional MRI. Within each group, we computed atlas-based resting-state functional MRI functional connectivity across 400 regions of interest covering the entire neocortex. Using the same atlas, we also assessed within each group the covariance of tau-PET levels among the 400 regions of interest. We found that higher resting-state functional MRI assessed functional connectivity between any given region of interest pair was associated with higher covariance in tau-PET binding in corresponding regions of interest. This result was consistently found in normal ageing, Alzheimer's disease and vascular cognitive impairment. In particular, inferior temporal tau-hotspots, as defined by highest tau-PET uptake, showed high predictive value of tau-PET levels in functionally closely connected regions of interest. These associations between functional connectivity and tau-PET uptake were detected regardless of presence of dementia symptoms (mild cognitive impairment or dementia), amyloid deposition (as assessed by amyloid-PET) or small vessel disease. Our findings suggest that higher functional connectivity between brain regions is associated with shared tau-levels, supporting the view of prion-like tau spreading facilitated by neural activity.\n

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\n \n\n \n \n \n \n \n WMH and long-term outcomes in ischemic stroke: A systematic review and meta-analysis.\n \n \n \n\n\n \n Georgakis, M. K.; Duering, M.; Wardlaw, J. M.; and Dichgans, M.\n\n\n \n\n\n\n Neurology, 92(12): e1298–e1308. March 2019.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{georgakis_wmh_2019,\n\ttitle = {{WMH} and long-term outcomes in ischemic stroke: {A} systematic review and meta-analysis},\n\tvolume = {92},\n\tissn = {1526-632X (Electronic) 0028-3878 (Linking)},\n\tdoi = {10.1212/WNL.0000000000007142},\n\tabstract = {OBJECTIVE: To investigate the relationship between baseline white matter hyperintensities (WMH) in patients with ischemic stroke and long-term risk of dementia, functional impairment, recurrent stroke, and mortality. METHODS: Following the Meta-analysis of Observational Studies in Epidemiology and Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines (PROSPERO protocol: CRD42018092857), we systematically searched Medline and Scopus for cohort studies of ischemic stroke patients examining whether MRI- or CT-assessed WMH at baseline are associated with dementia, functional impairment, recurrent stroke, and mortality at 3 months or later poststroke. We extracted data and evaluated study quality with the Newcastle-Ottawa scale. We pooled relative risks (RR) for the presence and severity of WMH using random-effects models. RESULTS: We included 104 studies with 71,298 ischemic stroke patients. Moderate/severe WMH at baseline were associated with increased risk of dementia (RR 2.17, 95\\% confidence interval [CI] 1.72-2.73), cognitive impairment (RR 2.29, 95\\% CI 1.48-3.54), functional impairment (RR 2.21, 95\\% CI 1.83-2.67), any recurrent stroke (RR 1.65, 95\\% CI 1.36-2.01), recurrent ischemic stroke (RR 1.90, 95\\% CI 1.26-2.88), all-cause mortality (RR 1.72, 95\\% CI 1.47-2.01), and cardiovascular mortality (RR 2.02, 95\\% CI 1.44-2.83). The associations followed dose-response patterns for WMH severity and were consistent for both MRI- and CT-defined WMH. The results remained stable in sensitivity analyses adjusting for age, stroke severity, and cardiovascular risk factors, in analyses of studies scoring high in quality, and in analyses adjusted for publication bias. CONCLUSIONS: Presence and severity of WMH are associated with substantially increased risk of dementia, functional impairment, stroke recurrence, and mortality after ischemic stroke. WMH may aid clinical prognostication and the planning of future clinical trials.},\n\tnumber = {12},\n\tjournal = {Neurology},\n\tauthor = {Georgakis, M. K. and Duering, M. and Wardlaw, J. M. and Dichgans, M.},\n\tmonth = mar,\n\tyear = {2019},\n\tpmid = {30770431},\n\tkeywords = {Stroke, Humans, Dementia, White Matter, Cognitive Dysfunction, Brain Ischemia},\n\tpages = {e1298--e1308},\n}\n\n

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\n \n\n \n \n \n \n \n Multimodal imaging analyses in patients with genetic and sporadic forms of small vessel disease.\n \n \n \n\n\n \n Kim, K. W.; Kwon, H.; Kim, Y. E.; Yoon, C. W.; Kim, Y. J.; Kim, Y. B.; Lee, J. M.; Yoon, W. T.; Kim, H. J.; Lee, J. S.; Jang, Y. K.; Kim, Y.; Jang, H.; Ki, C. S.; Youn, Y. C.; Shin, B. S.; Bang, O. Y.; Kim, G. M.; Chung, C. S.; Kim, S. J.; Na, D. L.; Duering, M.; Cho, H.; and Seo, S. W.\n\n\n \n\n\n\n Sci Rep, 9(1): 787. January 2019.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{kim_multimodal_2019,\n\ttitle = {Multimodal imaging analyses in patients with genetic and sporadic forms of small vessel disease},\n\tvolume = {9},\n\tissn = {2045-2322 (Electronic) 2045-2322 (Linking)},\n\tdoi = {10.1038/s41598-018-36580-0},\n\tabstract = {Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) is thought to be a pure genetic form of subcortical vascular cognitive impairment (SVCI). The aim of this study was to compare white matter integrity and cortical thickness between typical CADASIL, a genetic form, and two sporadic forms of SVCI (with NOTCH3 and without NOTCH3 variants). We enrolled typical CADASIL patients (N = 11) and SVCI patients [with NOTCH3 variants (N = 15), without NOTCH3 variants (N = 101)]. To adjust the age difference, which reflects the known difference in clinical and radiologic courses between typical CADASIL patients and SVCI patients, we constructed a W-score of measurement for diffusion tensor image and cortical thickness. Typical CADASIL patients showed more frequent white matter hyperintensities in the bilateral posterior temporal region compared to SVCI patients (p {\\textless} 0.001, uncorrected). We found that SVCI patients, regardless of the presence of NOTCH3 variants, showed significantly greater microstructural alterations (W-score, p {\\textless} 0.05, FWE-corrected) and cortical thinning (W-score, p {\\textless} 0.05, FDR-corrected) than typical CADASIL patients. In this study, typical CADASIL and SVCI showed distinct anatomic vulnerabilities in the cortical and subcortical structures. However, there was no difference between SVCI with NOTCH3 variants and SVCI without NOTCH3 variants.},\n\tnumber = {1},\n\tjournal = {Sci Rep},\n\tauthor = {Kim, K. W. and Kwon, H. and Kim, Y. E. and Yoon, C. W. and Kim, Y. J. and Kim, Y. B. and Lee, J. M. and Yoon, W. T. and Kim, H. J. and Lee, J. S. and Jang, Y. K. and Kim, Y. and Jang, H. and Ki, C. S. and Youn, Y. C. and Shin, B. S. and Bang, O. Y. and Kim, G. M. and Chung, C. S. and Kim, S. J. and Na, D. L. and Duering, M. and Cho, H. and Seo, S. W.},\n\tmonth = jan,\n\tyear = {2019},\n\tpmcid = {PMC6349863},\n\tpmid = {30692550},\n\tkeywords = {Aged, Diffusion Tensor Imaging, Female, Humans, Male, Middle Aged, White Matter/diagnostic imaging/*pathology, Aged, 80 and over, Receptor, Notch3, CADASIL/*diagnostic imaging/genetics/pathology, Cerebral Cortex/diagnostic imaging/*pathology, Dementia, Vascular/*diagnostic imaging/genetics/pathology, Genetic Predisposition to Disease, Multimodal Imaging, Receptor, Notch3/genetics, Dementia, Vascular, White Matter, Cerebral Cortex, CADASIL},\n\tpages = {787},\n}\n\n

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\n \n\n \n \n \n \n \n Prognostic relevance of cortical superficial siderosis in cerebral amyloid angiopathy.\n \n \n \n\n\n \n Wollenweber, F. A.; Opherk, C.; Zedde, M.; Catak, C.; Malik, R.; Duering, M.; Konieczny, M. J.; Pascarella, R.; Samoes, R.; Correia, M.; Marti-Fabregas, J.; Linn, J.; and Dichgans, M.\n\n\n \n\n\n\n Neurology, 92(8): e792–e801. February 2019.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{wollenweber_prognostic_2019,\n\ttitle = {Prognostic relevance of cortical superficial siderosis in cerebral amyloid angiopathy},\n\tvolume = {92},\n\tissn = {1526-632X (Electronic) 0028-3878 (Linking)},\n\tdoi = {10.1212/WNL.0000000000006956},\n\tabstract = {OBJECTIVE: To investigate the prognostic relevance of cortical superficial siderosis (cSS) in patients with cerebral amyloid angiopathy (CAA). METHODS: A total of 302 patients fulfilling clinical and imaging criteria for probable or possible CAA were enrolled into a prospective, multicenter cohort study and followed for 12 months. cSS was assessed on T2*/susceptibility-weighted imaging MRI. The predefined primary composite endpoint was incident stroke or death in patients with cSS compared to those without. Secondary analyses included cerebrovascular events and functional outcome measured by the modified Rankin Scale (mRS). Multiple regression analysis was performed to adjust for possible confounders. RESULTS: cSS prevalence was 40\\%. The primary endpoint occurred more frequently in patients with cSS (22\\%, 27/121) compared to those without (8\\%, 15/181, p = 0.001). Rates of CAA-related incident intracranial hemorrhage were 17\\% (cSS) and 4\\% (no cSS, p = 0.0003). The proportion of patients being functionally independent (mRS 0-2) 12 months from baseline were 59\\% (cSS) and 82\\% (no cSS, p = 0.00002). Presence of cSS was associated with the primary endpoint (adjusted odds ratio [OR] 1.2, 95\\% confidence interval [CI] 1.1-1.3, p = 0.0005), incident intracranial hemorrhage (adjusted OR 1.2, 95\\% CI 1.1-1.3, p = 0.0003), and less favorable outcome as assessed by the mRS (common OR 1.9, 95\\% CI 1.2-3.1, p = 0.009). Similar results were obtained in analyses restricted to patients with probable CAA and to patients with disseminated cSS (all p {\\textless} 0.005). CONCLUSIONS: Patients with cSS and suspected CAA are at high risk for CAA-related incident intracranial hemorrhage and poor functional outcome. Both the presence and extent of cSS have prognostic relevance and may influence clinical decision-making.},\n\tnumber = {8},\n\tjournal = {Neurology},\n\tauthor = {Wollenweber, F. A. and Opherk, C. and Zedde, M. and Catak, C. and Malik, R. and Duering, M. and Konieczny, M. J. and Pascarella, R. and Samoes, R. and Correia, M. and Marti-Fabregas, J. and Linn, J. and Dichgans, M.},\n\tmonth = feb,\n\tyear = {2019},\n\tpmid = {30674596},\n\tkeywords = {Stroke, Aged, Female, Humans, Male, Prospective Studies, Aged, 80 and over, Incidence, Magnetic Resonance Imaging, Prognosis, Odds Ratio, Brain, Cerebral Amyloid Angiopathy, Cerebral Cortex, Siderosis, Intracranial Hemorrhages, Mortality},\n\tpages = {e792--e801},\n}\n\n

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\n \n\n \n \n \n \n \n The effect of NOTCH3 pathogenic variant position on CADASIL disease severity: NOTCH3 EGFr 1-6 pathogenic variant are associated with a more severe phenotype and lower survival compared with EGFr 7-34 pathogenic variant.\n \n \n \n\n\n \n Rutten, J. W.; Van Eijsden, B. J.; Duering, M.; Jouvent, E.; Opherk, C.; Pantoni, L.; Federico, A.; Dichgans, M.; Markus, H. S.; Chabriat, H.; and Lesnik Oberstein, S. A. J.\n\n\n \n\n\n\n Genet Med, 21(3): 676–682. March 2019.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{rutten_effect_2019,\n\ttitle = {The effect of {NOTCH3} pathogenic variant position on {CADASIL} disease severity: {NOTCH3} {EGFr} 1-6 pathogenic variant are associated with a more severe phenotype and lower survival compared with {EGFr} 7-34 pathogenic variant},\n\tvolume = {21},\n\tissn = {1530-0366 (Electronic) 1098-3600 (Linking)},\n\tdoi = {10.1038/s41436-018-0088-3},\n\tabstract = {PURPOSE: CADASIL is a small-vessel disease caused by a cysteine-altering pathogenic variant in one of the 34 epidermal growth factor-like repeat (EGFr) domains of the NOTCH3 protein. We recently found that pathogenic variant in EGFr domains 7-34 have an unexpectedly high frequency in the general population (1:300). We hypothesized that EGFr 7-34 pathogenic variant more frequently cause a much milder phenotype, thereby explaining an important part of CADASIL disease variability. METHODS: Age at first stroke, survival and white matter hyperintensity volume were compared between 664 CADASIL patients with either a NOTCH3 EGFr 1-6 pathogenic variant or an EGFr 7-34 pathogenic variant. The frequencies of NOTCH3 EGFr 1-6 and EGFr 7-34 pathogenic variant were compared between individuals in the genome Aggregation Database and CADASIL patients. RESULTS: CADASIL patients with an EGFr 1-6 pathogenic variant have a 12-year earlier onset of stroke than those with an EGFr 7-34 pathogenic variant, lower survival, and higher white matter hyperintensity volumes. Among diagnosed CADASIL patients, 70\\% have an EGFr 1-6 pathogenic variant, whereas EGFr 7-34 pathogenic variant strongly predominate in the population. CONCLUSION: NOTCH3 pathogenic variant position is the most important determinant of CADASIL disease severity, with EGFr 7-34 pathogenic variant predisposing to a later onset of stroke and longer survival.},\n\tnumber = {3},\n\tjournal = {Genet Med},\n\tauthor = {Rutten, J. W. and Van Eijsden, B. J. and Duering, M. and Jouvent, E. and Opherk, C. and Pantoni, L. and Federico, A. and Dichgans, M. and Markus, H. S. and Chabriat, H. and Lesnik Oberstein, S. A. J.},\n\tmonth = mar,\n\tyear = {2019},\n\tpmcid = {PMC6752295},\n\tpmid = {30032161},\n\tkeywords = {Stroke, Adult, Aged, Disease Progression, Female, Humans, Male, Middle Aged, *cadasil, Receptor, Notch3, Brain/pathology, Netherlands, *Genotype-phenotype correlation, *notch3, *Small-vessel disease, CADASIL/*genetics/physiopathology, Phenotype, Protein Domains/genetics, Receptor, Notch3/*genetics/physiology, Stroke/etiology/genetics, Brain, CADASIL, NOTCH3, Genotype–phenotype correlation, Protein Domains, Small-vessel disease},\n\tpages = {676--682},\n}\n\n

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\n \n\n \n \n \n \n \n Clinical correlates of longitudinal MRI changes in CADASIL.\n \n \n \n\n\n \n Ling, Y.; De Guio, F.; Jouvent, E.; Duering, M.; Herve, D.; Guichard, J. P.; Godin, O.; Dichgans, M.; and Chabriat, H.\n\n\n \n\n\n\n J Cereb Blood Flow Metab, 39(7): 1299–1305. July 2019.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{ling_clinical_2019,\n\ttitle = {Clinical correlates of longitudinal {MRI} changes in {CADASIL}},\n\tvolume = {39},\n\tissn = {1559-7016 (Electronic) 0271-678X (Linking)},\n\tdoi = {10.1177/0271678X18757875},\n\tabstract = {Previous studies showed that various types of cerebral lesions, as assessed on MRI, largely contribute to the clinical severity of CADASIL. However, the clinical impact of longitudinal changes of classical markers of small vessel disease on conventional MRI has been only poorly investigated. One hundred sixty NOTCH3 mutation carriers (mean age +/- SD, 49.8 +/- 10.9 years) were followed over three years. Validated methods were used to determine the percent brain volume change (PBVC), number of incident lacunes, change of volume of white matter hyperintensities and change of number of cerebral microbleeds. Multivariable logistic regression analyses were performed to assess the independent association between changes of these MRI markers and incident clinical events. Mixed-effect multiple linear regression analyses were used to assess their association with changes of clinical scales. Over a mean period of 3.1 +/- 0.2 years, incident lacunes are found independently associated with incident stroke and change of Trail Making Test Part B. PBVC is independently associated with all incident events and clinical scale changes except the modified Rankin Scale at three years. Our results suggest that, on conventional MRI, PBVC and the number of incident lacunes are the most sensitive and independent correlates of clinical worsening over three years in CADASIL.},\n\tnumber = {7},\n\tjournal = {J Cereb Blood Flow Metab},\n\tauthor = {Ling, Y. and De Guio, F. and Jouvent, E. and Duering, M. and Herve, D. and Guichard, J. P. and Godin, O. and Dichgans, M. and Chabriat, H.},\n\tmonth = jul,\n\tyear = {2019},\n\tpmcid = {PMC6668524},\n\tpmid = {29400120},\n\tkeywords = {Stroke, Adult, Disease Progression, Female, Humans, Male, Middle Aged, cerebral small vessel disease, Prospective Studies, Magnetic Resonance Imaging, Receptor, Notch3, lacunes, Dementia, Mutation, Atrophy, leukoencephalopathy, magnetic resonance imaging, cerebral atrophy, Cerebral autosomal dominant arteriopathy with subcortical infarcts and, Longitudinal Studies, Brain, CADASIL, Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy},\n\tpages = {1299--1305},\n}\n\n

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\n \n 2018\n \n \n (15)\n \n \n

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\n \n\n \n \n \n \n \n Serum neurofilament light: A biomarker of neuroaxonal injury after ischemic stroke.\n \n \n \n\n\n \n Tiedt, S.; Duering, M.; Barro, C.; Kaya, A. G.; Boeck, J.; Bode, F. J.; Klein, M.; Dorn, F.; Gesierich, B.; Kellert, L.; Ertl-Wagner, B.; Goertler, M. W.; Petzold, G. C.; Kuhle, J.; Wollenweber, F. A.; Peters, N.; and Dichgans, M.\n\n\n \n\n\n\n Neurology, 91(14): e1338–e1347. October 2018.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{tiedt_serum_2018,\n\ttitle = {Serum neurofilament light: {A} biomarker of neuroaxonal injury after ischemic stroke},\n\tvolume = {91},\n\tissn = {1526-632X (Electronic) 0028-3878 (Linking)},\n\tdoi = {10.1212/WNL.0000000000006282},\n\tabstract = {OBJECTIVE: To explore the utility of serum neurofilament light chain (NfL) as a biomarker for primary and secondary neuroaxonal injury after ischemic stroke (IS) and study its value for the prediction of clinical outcome. METHODS: We used an ultrasensitive single-molecule array assay to measure serum NfL levels in healthy controls (n = 30) and 2 independent cohorts of patients with IS: (1) with serial serum sampling at hospital arrival (n = 196), at days 2, 3, and 7 (n = 89), and up to 6 months post stroke; and (2) with standardized MRI at baseline and at 6 months post stroke, and with cross-sectional serum sampling at 6 months (n = 95). We determined the temporal profile of serum NfL levels, their association with imaging markers of neuroaxonal injury, and with clinical outcome. RESULTS: Patients with IS had higher serum NfL levels compared with healthy controls starting from admission until 6 months post stroke. Serum NfL levels peaked at day 7 (211.2 pg/mL [104.7-442.6], median [IQR]) and correlated with infarct volumes (day 7: partial r = 0.736, p = 1.5 x 10(-15)). Six months post stroke, patients with recurrent ischemic lesions on MRI (n = 19) had higher serum NfL levels compared to those without new lesions (n = 76, p = 0.002). Serum NfL levels 6 months post stroke further correlated with a quantitative measure of secondary neurodegeneration obtained from diffusion tensor imaging MRI (r = 0.361, p = 0.001). Serum NfL levels 7 days post stroke independently predicted modified Rankin Scale scores 3 months post stroke (cumulative odds ratio [95\\% confidence interval] = 2.35 [1.60-3.45]; p = 1.24 x 10(-05)). CONCLUSION: Serum NfL holds promise as a biomarker for monitoring primary and secondary neuroaxonal injury after IS and for predicting functional outcome.},\n\tnumber = {14},\n\tjournal = {Neurology},\n\tauthor = {Tiedt, S. and Duering, M. and Barro, C. and Kaya, A. G. and Boeck, J. and Bode, F. J. and Klein, M. and Dorn, F. and Gesierich, B. and Kellert, L. and Ertl-Wagner, B. and Goertler, M. W. and Petzold, G. C. and Kuhle, J. and Wollenweber, F. A. and Peters, N. and Dichgans, M.},\n\tmonth = oct,\n\tyear = {2018},\n\tpmid = {30217937},\n\tkeywords = {Stroke, Aged, Female, Humans, Male, Axons, Biomarkers/blood, Brain Ischemia/*blood/complications/diagnostic imaging, Brain/diagnostic imaging, Follow-Up Studies, Magnetic Resonance Imaging, Neural Pathways/diagnostic imaging, Neurodegenerative Diseases/*blood/diagnostic imaging/*etiology, Neurofilament Proteins/*blood, Prognosis, Stroke/*blood/*complications/diagnostic imaging, Biomarkers, Brain, Neural Pathways, Neurodegenerative Diseases, Neurofilament Proteins, Brain Ischemia},\n\tpages = {e1338--e1347},\n}\n\n

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\n \n\n \n \n \n \n \n Zerebrale Mikroangiopathien.\n \n \n \n\n\n \n Düring, M.; and Opherk, C.\n\n\n \n\n\n\n Akt Neurol, 45(08): 592–604. January 2018.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@article{during_zerebrale_2018,\n\ttitle = {Zerebrale {Mikroangiopathien}},\n\tvolume = {45},\n\tissn = {0302-4350},\n\tdoi = {10.1055/a-0646-3746},\n\tlanguage = {De},\n\tnumber = {08},\n\tjournal = {Akt Neurol},\n\tauthor = {Düring, Marco and Opherk, Christian},\n\tmonth = jan,\n\tyear = {2018},\n\tpages = {592--604},\n}\n\n

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\n \n\n \n \n \n \n \n Serum Neurofilament Light Chain Levels Are Related to Small Vessel Disease Burden.\n \n \n \n\n\n \n Duering, M.; Konieczny, M. J.; Tiedt, S.; Baykara, E.; Tuladhar, A. M.; Leijsen, E. V.; Lyrer, P.; Engelter, S. T.; Gesierich, B.; Achmuller, M.; Barro, C.; Adam, R.; Ewers, M.; Dichgans, M.; Kuhle, J.; de Leeuw, F. E.; and Peters, N.\n\n\n \n\n\n\n J Stroke, 20(2): 228–238. May 2018.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{duering_serum_2018,\n\ttitle = {Serum {Neurofilament} {Light} {Chain} {Levels} {Are} {Related} to {Small} {Vessel} {Disease} {Burden}},\n\tvolume = {20},\n\tissn = {2287-6391 (Print) 2287-6391 (Linking)},\n\tdoi = {10.5853/jos.2017.02565},\n\tabstract = {BACKGROUND AND PURPOSE: Neurofilament light chain (NfL) is a blood marker for neuroaxonal damage. We assessed the association between serum NfL and cerebral small vessel disease (SVD), which is highly prevalent in elderly individuals and a major cause of stroke and vascular cognitive impairment. METHODS: Using a cross-sectional design, we studied 53 and 439 patients with genetically defined SVD (Cerebral Autosomal-Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy [CADASIL]) and sporadic SVD, respectively, as well as 93 healthy controls. Serum NfL was measured by an ultrasensitive single-molecule array assay. We quantified magnetic resonance imaging (MRI) markers of SVD, i.e., white matter hyperintensity volume, lacune volume, brain volume, microbleed count, and mean diffusivity obtained from diffusion tensor imaging. Clinical characterization included neuropsychological testing in both SVD samples. CADASIL patients were further characterized for focal neurological deficits (National Institutes of Health stroke scale [NIHSS]) and disability (modified Rankin scale [mRS]). RESULTS: Serum NfL levels were elevated in both SVD samples (P{\\textless}1e-05 compared with controls) and associated with all SVD MRI markers. The strongest association was found for mean diffusivity (CADASIL, R(2)=0.52, P=1.2e-09; sporadic SVD, R(2)=0.21, P{\\textless}1e-15). Serum NfL levels were independently related to processing speed performance (CADASIL, R(2)=0.27, P=7.6e-05; sporadic SVD, R(2)=0.06, P=4.8e-08), focal neurological symptoms (CADASIL, NIHSS, P=4.2e-05) and disability (CADASIL, mRS, P=3.0e-06). CONCLUSIONS: We found serum NfL levels to be associated with both imaging and clinical features of SVD. Serum NfL might complement MRI markers in assessing SVD burden. Importantly, SVD needs to be considered when interpreting serum NfL levels in the context of other age-related diseases.},\n\tnumber = {2},\n\tjournal = {J Stroke},\n\tauthor = {Duering, M. and Konieczny, M. J. and Tiedt, S. and Baykara, E. and Tuladhar, A. M. and Leijsen, E. V. and Lyrer, P. and Engelter, S. T. and Gesierich, B. and Achmuller, M. and Barro, C. and Adam, R. and Ewers, M. and Dichgans, M. and Kuhle, J. and de Leeuw, F. E. and Peters, N.},\n\tmonth = may,\n\tyear = {2018},\n\tpmcid = {PMC6007291},\n\tpmid = {29886723},\n\tkeywords = {Biomarkers, Cerebral small vessel diseases, Dementia, vascular, Magnetic resonance imaging, Serum},\n\tpages = {228--238},\n}\n\n

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\n \n\n \n \n \n \n \n Automated Morphological Analysis of Microglia After Stroke.\n \n \n \n\n\n \n Heindl, S.; Gesierich, B.; Benakis, C.; Llovera, G.; Duering, M.; and Liesz, A.\n\n\n \n\n\n\n Front Cell Neurosci, 12: 106. 2018.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{heindl_automated_2018,\n\ttitle = {Automated {Morphological} {Analysis} of {Microglia} {After} {Stroke}},\n\tvolume = {12},\n\tissn = {1662-5102 (Print) 1662-5102 (Linking)},\n\tdoi = {10.3389/fncel.2018.00106},\n\tabstract = {Microglia are the resident immune cells of the brain and react quickly to changes in their environment with transcriptional regulation and morphological changes. Brain tissue injury such as ischemic stroke induces a local inflammatory response encompassing microglial activation. The change in activation status of a microglia is reflected in its gradual morphological transformation from a highly ramified into a less ramified or amoeboid cell shape. For this reason, the morphological changes of microglia are widely utilized to quantify microglial activation and studying their involvement in virtually all brain diseases. However, the currently available methods, which are mainly based on manual rating of immunofluorescent microscopic images, are often inaccurate, rater biased, and highly time consuming. To address these issues, we created a fully automated image analysis tool, which enables the analysis of microglia morphology from a confocal Z-stack and providing up to 59 morphological features. We developed the algorithm on an exploratory dataset of microglial cells from a stroke mouse model and validated the findings on an independent data set. In both datasets, we could demonstrate the ability of the algorithm to sensitively discriminate between the microglia morphology in the peri-infarct and the contralateral, unaffected cortex. Dimensionality reduction by principal component analysis allowed to generate a highly sensitive compound score for microglial shape analysis. Finally, we tested for concordance of results between the novel automated analysis tool and the conventional manual analysis and found a high degree of correlation. In conclusion, our novel method for the fully automatized analysis of microglia morphology shows excellent accuracy and time efficacy compared to traditional analysis methods. This tool, which we make openly available, could find application to study microglia morphology using fluorescence imaging in a wide range of brain disease models.},\n\tjournal = {Front Cell Neurosci},\n\tauthor = {Heindl, S. and Gesierich, B. and Benakis, C. and Llovera, G. and Duering, M. and Liesz, A.},\n\tyear = {2018},\n\tpmid = {29725290},\n\tpmcid = {PMC5917008},\n\tkeywords = {image analysis, microglia, morphology, neuroinflammation, stroke},\n\tpages = {106},\n}\n\n

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\n Microglia are the resident immune cells of the brain and react quickly to changes in their environment with transcriptional regulation and morphological changes. Brain tissue injury such as ischemic stroke induces a local inflammatory response encompassing microglial activation. The change in activation status of a microglia is reflected in its gradual morphological transformation from a highly ramified into a less ramified or amoeboid cell shape. For this reason, the morphological changes of microglia are widely utilized to quantify microglial activation and studying their involvement in virtually all brain diseases. However, the currently available methods, which are mainly based on manual rating of immunofluorescent microscopic images, are often inaccurate, rater biased, and highly time consuming. To address these issues, we created a fully automated image analysis tool, which enables the analysis of microglia morphology from a confocal Z-stack and providing up to 59 morphological features. We developed the algorithm on an exploratory dataset of microglial cells from a stroke mouse model and validated the findings on an independent data set. In both datasets, we could demonstrate the ability of the algorithm to sensitively discriminate between the microglia morphology in the peri-infarct and the contralateral, unaffected cortex. Dimensionality reduction by principal component analysis allowed to generate a highly sensitive compound score for microglial shape analysis. Finally, we tested for concordance of results between the novel automated analysis tool and the conventional manual analysis and found a high degree of correlation. In conclusion, our novel method for the fully automatized analysis of microglia morphology shows excellent accuracy and time efficacy compared to traditional analysis methods. This tool, which we make openly available, could find application to study microglia morphology using fluorescence imaging in a wide range of brain disease models.\n

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\n \n\n \n \n \n \n \n Free water determines diffusion alterations and clinical status in cerebral small vessel disease.\n \n \n \n\n\n \n Duering, M.; Finsterwalder, S.; Baykara, E.; Tuladhar, A. M.; Gesierich, B.; Konieczny, M. J.; Malik, R.; Franzmeier, N.; Ewers, M.; Jouvent, E.; Biessels, G. J.; Schmidt, R.; de Leeuw, F. E.; Pasternak, O.; and Dichgans, M.\n\n\n \n\n\n\n Alzheimers Dement, 14(6): 764–774. June 2018.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{duering_free_2018,\n\ttitle = {Free water determines diffusion alterations and clinical status in cerebral small vessel disease},\n\tvolume = {14},\n\tissn = {1552-5279 (Electronic) 1552-5260 (Linking)},\n\tdoi = {10.1016/j.jalz.2017.12.007},\n\tabstract = {INTRODUCTION: Diffusion tensor imaging detects early tissue alterations in Alzheimer's disease and cerebral small vessel disease (SVD). However, the origin of diffusion alterations in SVD is largely unknown. METHODS: To gain further insight, we applied free water (FW) imaging to patients with genetically defined SVD (Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy [CADASIL], n = 57), sporadic SVD (n = 444), and healthy controls (n = 28). We modeled freely diffusing water in the extracellular space (FW) and measures reflecting fiber structure (tissue compartment). We tested associations between these measures and clinical status (processing speed and disability). RESULTS: Diffusion alterations in SVD were mostly driven by increased FW and less by tissue compartment alterations. Among imaging markers, FW showed the strongest association with clinical status (R(2) up to 34\\%, P {\\textless} .0001). Findings were consistent across patients with CADASIL and sporadic SVD. DISCUSSION: Diffusion alterations and clinical status in SVD are largely determined by extracellular fluid increase rather than alterations of white matter fiber organization.},\n\tnumber = {6},\n\tjournal = {Alzheimers Dement},\n\tauthor = {Duering, M. and Finsterwalder, S. and Baykara, E. and Tuladhar, A. M. and Gesierich, B. and Konieczny, M. J. and Malik, R. and Franzmeier, N. and Ewers, M. and Jouvent, E. and Biessels, G. J. and Schmidt, R. and de Leeuw, F. E. and Pasternak, O. and Dichgans, M.},\n\tmonth = jun,\n\tyear = {2018},\n\tpmcid = {PMC5994358},\n\tpmid = {29406155},\n\tkeywords = {Small vessel disease, Aged, Diffusion Tensor Imaging, Female, Humans, Male, Middle Aged, *Brain atrophy, *Diffusion tensor imaging, *Disability, *Free water, *Lacunes, *Processing speed, *Small vessel disease, *Structural imaging, *Vascular cognitive impairment, *Water, *White matter hyperintensities, Alzheimer Disease/*diagnostic imaging, Cerebral Small Vessel Diseases/*diagnostic imaging, Diffusion Tensor Imaging/*methods, Processing speed, Vascular cognitive impairment, White matter hyperintensities, Diffusion tensor imaging, Alzheimer Disease, Brain atrophy, Cerebral Small Vessel Diseases, Disability, Free water, Lacunes, Structural imaging, Water},\n\tpages = {764--774},\n}\n\n

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\n \n\n \n \n \n \n \n Investigating the origin and evolution of cerebral small vessel disease: The RUN DMC - InTENse study.\n \n \n \n\n\n \n Ter Telgte, A.; Wiegertjes, K.; Tuladhar, A. M.; Noz, M. P.; Marques, J. P.; Gesierich, B.; Huebner, M.; Mutsaerts, H. M.; Elias-Smale, S. E.; Beelen, M. J.; Ropele, S.; Kessels, R. P.; Riksen, N. P.; Klijn, C. J.; Norris, D. G.; Duering, M.; and de Leeuw, F. E.\n\n\n \n\n\n\n Eur Stroke J, 3(4): 369–378. December 2018.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{ter_telgte_investigating_2018,\n\ttitle = {Investigating the origin and evolution of cerebral small vessel disease: {The} {RUN} {DMC} - {InTENse} study},\n\tvolume = {3},\n\tissn = {2396-9881 (Electronic) 2396-9873 (Linking)},\n\tdoi = {10.1177/2396987318776088},\n\tabstract = {Background: Neuroimaging in older adults commonly reveals signs of cerebral small vessel disease (SVD). SVD is believed to be caused by chronic hypoperfusion based on animal models and longitudinal studies with inter-scan intervals of years. Recent imaging evidence, however, suggests a role for acute ischaemia, as indicated by incidental diffusion-weighted imaging lesions (DWI+ lesions), in the origin of SVD. Furthermore, it becomes increasingly recognised that focal SVD lesions likely affect the structure and function of brain areas remote from the original SVD lesion. However, the temporal dynamics of these events are largely unknown. Aims: (1) To investigate the monthly incidence of DWI+ lesions in subjects with SVD; (2) to assess to which extent these lesions explain progression of SVD imaging markers; (3) to investigate their effects on cortical thickness, structural and functional connectivity and cognitive and motor performance; and (4) to investigate the potential role of the innate immune system in the pathophysiology of SVD. Design/methods: The RUN DMC - InTENse study is a longitudinal observational study among 54 non-demented RUN DMC survivors with mild to severe SVD and no other presumed cause of ischaemia. We performed MRI assessments monthly during 10 consecutive months (totalling up to 10 scans per subject), complemented with clinical, motor and cognitive examinations. Discussion: Our study will provide a better understanding of the role of DWI+ lesions in the pathophysiology of SVD and will further unravel the structural and functional consequences and clinical importance of these lesions, with an unprecedented temporal resolution. Understanding the role of acute, potentially ischaemic, processes in SVD may provide new strategies for therapies.},\n\tnumber = {4},\n\tjournal = {Eur Stroke J},\n\tauthor = {Ter Telgte, A. and Wiegertjes, K. and Tuladhar, A. M. and Noz, M. P. and Marques, J. P. and Gesierich, B. and Huebner, M. and Mutsaerts, H. M. and Elias-Smale, S. E. and Beelen, M. J. and Ropele, S. and Kessels, R. P. and Riksen, N. P. and Klijn, C. J. and Norris, D. G. and Duering, M. and de Leeuw, F. E.},\n\tmonth = dec,\n\tyear = {2018},\n\tpmcid = {PMC6571506},\n\tpmid = {31236485},\n\tkeywords = {cognition, DWI+ lesions, acute incidental infarcts, ischaemia, motor performance, remote effects, Serial imaging, silent stroke},\n\tpages = {369--378},\n}\n\n

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\n \n\n \n \n \n \n \n Correspondence Between Resting-State and Episodic Memory-Task Related Networks in Elderly Subjects.\n \n \n \n\n\n \n Simon-Vermot, L.; Taylor, A. N. W.; Araque Caballero, M. A.; Franzmeier, N.; Buerger, K.; Catak, C.; Janowitz, D.; Kambeitz-Ilankovic, L. M.; Ertl-Wagner, B.; Duering, M.; and Ewers, M.\n\n\n \n\n\n\n Front Aging Neurosci, 10: 362. 2018.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{simon-vermot_correspondence_2018,\n\ttitle = {Correspondence {Between} {Resting}-{State} and {Episodic} {Memory}-{Task} {Related} {Networks} in {Elderly} {Subjects}},\n\tvolume = {10},\n\tissn = {1663-4365 (Print) 1663-4365 (Linking)},\n\tdoi = {10.3389/fnagi.2018.00362},\n\tabstract = {Resting-state fMRI studies demonstrated temporally synchronous fluctuations in brain activity among ensembles of brain regions, suggesting the existence of intrinsic functional networks. A spatial match between some of the resting-state networks and regional brain activation during cognitive tasks has been noted, suggesting that resting-state networks support particular cognitive abilities. However, the spatial match and predictive value of any resting-state network and regional brain activation during episodic memory is only poorly understood. In order to address this research gap, we obtained fMRI acquired both during rest and a face-name association task in 38 healthy elderly subjects. In separate independent component analyses, networks of correlated brain activity during rest or the episodic memory task were identified. For the independent components identified for task-based fMRI, the design matrix of successful encoding or retrieval trials was regressed against the time course of each of the component to identify significantly activated networks. Spatial regression was used to assess the match of resting-state networks against those related to successful memory encoding or retrieval. We found that resting-state networks covering the medial temporal, middle temporal, and frontal areas showed increased activity during successful encoding. Resting-state networks located within posterior brain regions showed increased activity during successful recognition. However, the level of resting-state network connectivity was not predictive of the task-related activity in these networks. These results suggest that a circumscribed number of functional networks detectable during rest become engaged during successful episodic memory. However, higher intrinsic connectivity at rest may not translate into higher network expression during episodic memory.},\n\tjournal = {Front Aging Neurosci},\n\tauthor = {Simon-Vermot, L. and Taylor, A. N. W. and Araque Caballero, M. A. and Franzmeier, N. and Buerger, K. and Catak, C. and Janowitz, D. and Kambeitz-Ilankovic, L. M. and Ertl-Wagner, B. and Duering, M. and Ewers, M.},\n\tyear = {2018},\n\tpmcid = {PMC6236026},\n\tpmid = {30467476},\n\tkeywords = {resting-state fMRI, brain activation, connectivity, episodic memory, network},\n\tpages = {362},\n}\n\n

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\n \n\n \n \n \n \n \n Is VLSM a valid tool for determining the functional anatomy of the brain? Usefulness of additional Bayesian network analysis.\n \n \n \n\n\n \n Arnoux, A.; Toba, M. N.; Duering, M.; Diouf, M.; Daouk, J.; Constans, J. M.; Puy, L.; Barbay, M.; and Godefroy, O.\n\n\n \n\n\n\n Neuropsychologia, 121: 69–78. December 2018.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{arnoux_is_2018,\n\ttitle = {Is {VLSM} a valid tool for determining the functional anatomy of the brain? {Usefulness} of additional {Bayesian} network analysis},\n\tvolume = {121},\n\tissn = {1873-3514 (Electronic) 0028-3932 (Linking)},\n\tdoi = {10.1016/j.neuropsychologia.2018.10.003},\n\tabstract = {OBJECTIVES: The ability of voxel-based lesion-symptom mapping (VLSM) to define the functional anatomy of the human brain has not been fully assessed. With a view to assessing VLSM's validity, the present study analyzed the technique's ability to determine the known clinical-anatomic correlates of hemiparesis in stroke patients. DESIGN: Lesions (damaged in at least 5 patients) associated with transformed limb motor score (after adjustment on lesion volume) at 6 months were examined in 272 patients using VLSM. The value of additional multivariable linear, logistic and Bayesian analyses was examined. RESULTS: We first checked that motor hemiparesis was fully accounted for by corticospinal tract (CST) lesions (sensitivity = 100\\%; p = 0.0001). Conventional VLSM analysis flagged up 2 regions corresponding to the CST, but also 8 regions located outside the CST. All 10 brain regions achieving statistical significance in the VLSM analysis were submitted to 3 additional analyses. The backward linear regression analysis selected 5 regions, one only corresponding to the CST (R(2): 0.03, p = 0.0008). The logistic regression analysis selected correctly the CST (OR: 2.39, 95\\%CI: 1.44-3.96; 0.001). The Bayesian network analysis selected regions including the CST (in 92\\% of 3000 bootstrap replications) and identified the source of multicollinearity. These lesions evaluated by structural equation modeling resulted in an excellent fit (p-value = 0.228, chi/df = 1.19, RMSEA = 0.032, CFI = 0.999). Analyses of confusion factors showed that conventional VLSM analyses were strongly influenced by lesion frequency (R(2) = 0.377; p = 0.0001) and multicollinearity. CONCLUSIONS: Conventional VLSM analyses are sensitive but weakened by a type I error due to the combined effects of multicollinearity and lesion frequency. We demonstrate that the addition of a Bayesian network analysis, and to a lesser extent of logistic regression, controlled for this type I error and constituted a reliable means of defining the functional anatomy of the motor system in stroke patients.},\n\tjournal = {Neuropsychologia},\n\tauthor = {Arnoux, A. and Toba, M. N. and Duering, M. and Diouf, M. and Daouk, J. and Constans, J. M. and Puy, L. and Barbay, M. and Godefroy, O.},\n\tmonth = dec,\n\tyear = {2018},\n\tpmid = {30449718},\n\tkeywords = {Stroke, Aged, Female, Humans, Male, Middle Aged, *Stroke, Magnetic Resonance Imaging, Bayes Theorem, Magnetic Resonance Imaging/*methods, *Brain-lesion mapping, *Clinical anatomical correlation, *Disability evaluation, *Structure-function, *Voxel-based lesion-symptom mapping (VLSM), Brain Mapping/*methods, Brain/anatomy \\& histology/*diagnostic imaging/physiology/*physiopathology, Linear Models, Logistic Models, Multivariate Analysis, Paresis/diagnostic imaging/etiology/pathology/physiopathology, Stroke/complications/*diagnostic imaging/pathology/*physiopathology, Brain Mapping, Brain, Brain-lesion mapping, Clinical anatomical correlation, Disability evaluation, Paresis, Structure-function, Voxel-based lesion-symptom mapping (VLSM)},\n\tpages = {69--78},\n}\n\n

\n\n\n

\n OBJECTIVES: The ability of voxel-based lesion-symptom mapping (VLSM) to define the functional anatomy of the human brain has not been fully assessed. With a view to assessing VLSM's validity, the present study analyzed the technique's ability to determine the known clinical-anatomic correlates of hemiparesis in stroke patients. DESIGN: Lesions (damaged in at least 5 patients) associated with transformed limb motor score (after adjustment on lesion volume) at 6 months were examined in 272 patients using VLSM. The value of additional multivariable linear, logistic and Bayesian analyses was examined. RESULTS: We first checked that motor hemiparesis was fully accounted for by corticospinal tract (CST) lesions (sensitivity = 100%; p = 0.0001). Conventional VLSM analysis flagged up 2 regions corresponding to the CST, but also 8 regions located outside the CST. All 10 brain regions achieving statistical significance in the VLSM analysis were submitted to 3 additional analyses. The backward linear regression analysis selected 5 regions, one only corresponding to the CST (R(2): 0.03, p = 0.0008). The logistic regression analysis selected correctly the CST (OR: 2.39, 95%CI: 1.44-3.96; 0.001). The Bayesian network analysis selected regions including the CST (in 92% of 3000 bootstrap replications) and identified the source of multicollinearity. These lesions evaluated by structural equation modeling resulted in an excellent fit (p-value = 0.228, chi/df = 1.19, RMSEA = 0.032, CFI = 0.999). Analyses of confusion factors showed that conventional VLSM analyses were strongly influenced by lesion frequency (R(2) = 0.377; p = 0.0001) and multicollinearity. CONCLUSIONS: Conventional VLSM analyses are sensitive but weakened by a type I error due to the combined effects of multicollinearity and lesion frequency. We demonstrate that the addition of a Bayesian network analysis, and to a lesser extent of logistic regression, controlled for this type I error and constituted a reliable means of defining the functional anatomy of the motor system in stroke patients.\n

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\n \n\n \n \n \n \n \n White matter diffusion alterations precede symptom onset in autosomal dominant Alzheimer's disease.\n \n \n \n\n\n \n Araque Caballero, M. A.; Suarez-Calvet, M.; Duering, M.; Franzmeier, N.; Benzinger, T.; Fagan, A. M.; Bateman, R. J.; Jack, C. R.; Levin, J.; Dichgans, M.; Jucker, M.; Karch, C.; Masters, C. L.; Morris, J. C.; Weiner, M.; Rossor, M.; Fox, N. C.; Lee, J. H.; Salloway, S.; Danek, A.; Goate, A.; Yakushev, I.; Hassenstab, J.; Schofield, P. R.; Haass, C.; and Ewers, M.\n\n\n \n\n\n\n Brain, 141(10): 3065–3080. October 2018.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{araque_caballero_white_2018,\n\ttitle = {White matter diffusion alterations precede symptom onset in autosomal dominant {Alzheimer}'s disease},\n\tvolume = {141},\n\tissn = {1460-2156 (Electronic) 0006-8950 (Linking)},\n\tdoi = {10.1093/brain/awy229},\n\tabstract = {White matter alterations are present in the majority of patients with Alzheimer's disease type dementia. However, the spatiotemporal pattern of white matter changes preceding dementia symptoms in Alzheimer's disease remains unclear, largely due to the inherent diagnostic uncertainty in the preclinical phase and increased risk of confounding age-related vascular disease and stroke in late-onset Alzheimer's disease. In early-onset autosomal-dominantly inherited Alzheimer's disease, participants are destined to develop dementia, which provides the opportunity to assess brain changes years before the onset of symptoms, and in the absence of ageing-related vascular disease. Here, we assessed mean diffusivity alterations in the white matter in 64 mutation carriers compared to 45 non-carrier family non-carriers. Using tract-based spatial statistics, we mapped the interaction of mutation status by estimated years from symptom onset on mean diffusivity. For major atlas-derived fibre tracts, we determined the earliest time point at which abnormal mean diffusivity changes in the mutation carriers were detectable. Lastly, we assessed the association between mean diffusivity and cerebrospinal fluid biomarkers of amyloid, tau, phosphorylated-tau, and soluble TREM2, i.e. a marker of microglia activity. Results showed a significant interaction of mutations status by estimated years from symptom onset, i.e. a stronger increase of mean diffusivity, within the posterior parietal and medial frontal white matter in mutation carriers compared with non-carriers. The earliest increase of mean diffusivity was observed in the forceps major, forceps minor and long projecting fibres-many connecting default mode network regions-between 5 to 10 years before estimated symptom onset. Higher mean diffusivity in fibre tracts was associated with lower grey matter volume in the tracts' projection zones. Global mean diffusivity was correlated with lower cerebrospinal fluid levels of amyloid-beta1-42 but higher levels of tau, phosphorylated-tau and soluble TREM2. Together, these results suggest that regionally selective white matter degeneration occurs years before the estimated symptom onset. Such white matter alterations are associated with primary Alzheimer's disease pathology and microglia activity in the brain.},\n\tnumber = {10},\n\tjournal = {Brain},\n\tauthor = {Araque Caballero, M. A. and Suarez-Calvet, M. and Duering, M. and Franzmeier, N. and Benzinger, T. and Fagan, A. M. and Bateman, R. J. and Jack, C. R. and Levin, J. and Dichgans, M. and Jucker, M. and Karch, C. and Masters, C. L. and Morris, J. C. and Weiner, M. and Rossor, M. and Fox, N. C. and Lee, J. H. and Salloway, S. and Danek, A. and Goate, A. and Yakushev, I. and Hassenstab, J. and Schofield, P. R. and Haass, C. and Ewers, M.},\n\tmonth = oct,\n\tyear = {2018},\n\tpmcid = {PMC6158739},\n\tpmid = {30239611},\n\tkeywords = {Adult, Diffusion Tensor Imaging, Female, Humans, Male, Middle Aged, White Matter/*pathology, Alzheimer Disease/*pathology, Brain/*pathology, Brain, White Matter, Alzheimer Disease},\n\tpages = {3065--3080},\n}\n\n

\n\n\n

\n White matter alterations are present in the majority of patients with Alzheimer's disease type dementia. However, the spatiotemporal pattern of white matter changes preceding dementia symptoms in Alzheimer's disease remains unclear, largely due to the inherent diagnostic uncertainty in the preclinical phase and increased risk of confounding age-related vascular disease and stroke in late-onset Alzheimer's disease. In early-onset autosomal-dominantly inherited Alzheimer's disease, participants are destined to develop dementia, which provides the opportunity to assess brain changes years before the onset of symptoms, and in the absence of ageing-related vascular disease. Here, we assessed mean diffusivity alterations in the white matter in 64 mutation carriers compared to 45 non-carrier family non-carriers. Using tract-based spatial statistics, we mapped the interaction of mutation status by estimated years from symptom onset on mean diffusivity. For major atlas-derived fibre tracts, we determined the earliest time point at which abnormal mean diffusivity changes in the mutation carriers were detectable. Lastly, we assessed the association between mean diffusivity and cerebrospinal fluid biomarkers of amyloid, tau, phosphorylated-tau, and soluble TREM2, i.e. a marker of microglia activity. Results showed a significant interaction of mutations status by estimated years from symptom onset, i.e. a stronger increase of mean diffusivity, within the posterior parietal and medial frontal white matter in mutation carriers compared with non-carriers. The earliest increase of mean diffusivity was observed in the forceps major, forceps minor and long projecting fibres-many connecting default mode network regions-between 5 to 10 years before estimated symptom onset. Higher mean diffusivity in fibre tracts was associated with lower grey matter volume in the tracts' projection zones. Global mean diffusivity was correlated with lower cerebrospinal fluid levels of amyloid-beta1-42 but higher levels of tau, phosphorylated-tau and soluble TREM2. Together, these results suggest that regionally selective white matter degeneration occurs years before the estimated symptom onset. Such white matter alterations are associated with primary Alzheimer's disease pathology and microglia activity in the brain.\n

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\n \n\n \n \n \n \n \n Different Types of White Matter Hyperintensities in CADASIL.\n \n \n \n\n\n \n Duchesnay, E.; Hadj Selem, F.; De Guio, F.; Dubois, M.; Mangin, J. F.; Duering, M.; Ropele, S.; Schmidt, R.; Dichgans, M.; Chabriat, H.; and Jouvent, E.\n\n\n \n\n\n\n Front Neurol, 9: 526. 2018.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{duchesnay_different_2018,\n\ttitle = {Different {Types} of {White} {Matter} {Hyperintensities} in {CADASIL}},\n\tvolume = {9},\n\tissn = {1664-2295 (Print) 1664-2295 (Linking)},\n\tdoi = {10.3389/fneur.2018.00526},\n\tabstract = {Objective: In CADASIL (Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy), white matter hyperintensities (WMH) are considered to result from hypoperfusion. We hypothesized that in fact the burden of WMH results from the combination of several regional populations of WMH with different mechanisms and clinical consequences. Methods: To identify regional WMH populations, we used a 4-step approach. First, we used an unsupervised principal component algorithm to determine, without a priori knowledge, the main sources of variation of the global spatial pattern of WMH. Thereafter, to determine whether these sources are likely to include relevant information regarding regional populations of WMH, we tested their relationships with: (1) MRI markers of the disease; (2) the clinical severity assessed by the Mattis Dementia Rating scale (MDRS) (cognitive outcome) and the modified Rankin's score (disability outcome). Finally, through careful interpretation of all the results, we tried to identify different regional populations of WMH. Results: The unsupervised principal component algorithm identified 3 main sources of variation of the global spatial pattern of WMH, which showed significant and sometime inverse relationships with MRI markers and clinical scores. The models predicting clinical severity based on these sources outperformed those evaluating WMH by their volume (MDRS, coefficient of determination of 39.0 vs. 35.3\\%, p = 0.01; modified Rankin's score, 43.7 vs. 38.1\\%, p = 0.001). By carefully interpreting the visual aspect of these sources as well as their relationships with MRI markers and clinical severity, we found strong arguments supporting the existence of different regional populations of WMH. For instance, in multivariate analyses, larger extents of WMH in anterior temporal poles and superior frontal gyri were associated with better outcomes, while larger extents of WMH in pyramidal tracts were associated with worse outcomes, which could not be explained if WMH in these different areas shared the same mechanisms. Conclusion: The results of the present study support the hypothesis that the whole extent of WMH results from a combination of different regional populations of WMH, some of which are associated, for yet undetermined reasons, with milder forms of the disease.},\n\tjournal = {Front Neurol},\n\tauthor = {Duchesnay, E. and Hadj Selem, F. and De Guio, F. and Dubois, M. and Mangin, J. F. and Duering, M. and Ropele, S. and Schmidt, R. and Dichgans, M. and Chabriat, H. and Jouvent, E.},\n\tyear = {2018},\n\tpmcid = {PMC6048276},\n\tpmid = {30042721},\n\tkeywords = {cerebral small vessel disease, Cadasil, white matter hyperintensities, clinical severity, white matter changes, CADASIL},\n\tpages = {526},\n}\n\n

\n\n\n

\n Objective: In CADASIL (Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy), white matter hyperintensities (WMH) are considered to result from hypoperfusion. We hypothesized that in fact the burden of WMH results from the combination of several regional populations of WMH with different mechanisms and clinical consequences. Methods: To identify regional WMH populations, we used a 4-step approach. First, we used an unsupervised principal component algorithm to determine, without a priori knowledge, the main sources of variation of the global spatial pattern of WMH. Thereafter, to determine whether these sources are likely to include relevant information regarding regional populations of WMH, we tested their relationships with: (1) MRI markers of the disease; (2) the clinical severity assessed by the Mattis Dementia Rating scale (MDRS) (cognitive outcome) and the modified Rankin's score (disability outcome). Finally, through careful interpretation of all the results, we tried to identify different regional populations of WMH. Results: The unsupervised principal component algorithm identified 3 main sources of variation of the global spatial pattern of WMH, which showed significant and sometime inverse relationships with MRI markers and clinical scores. The models predicting clinical severity based on these sources outperformed those evaluating WMH by their volume (MDRS, coefficient of determination of 39.0 vs. 35.3%, p = 0.01; modified Rankin's score, 43.7 vs. 38.1%, p = 0.001). By carefully interpreting the visual aspect of these sources as well as their relationships with MRI markers and clinical severity, we found strong arguments supporting the existence of different regional populations of WMH. For instance, in multivariate analyses, larger extents of WMH in anterior temporal poles and superior frontal gyri were associated with better outcomes, while larger extents of WMH in pyramidal tracts were associated with worse outcomes, which could not be explained if WMH in these different areas shared the same mechanisms. Conclusion: The results of the present study support the hypothesis that the whole extent of WMH results from a combination of different regional populations of WMH, some of which are associated, for yet undetermined reasons, with milder forms of the disease.\n

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\n \n\n \n \n \n \n \n Genetic Study of White Matter Integrity in UK Biobank (N=8448) and the Overlap With Stroke, Depression, and Dementia.\n \n \n \n\n\n \n Rutten-Jacobs, L. C. A.; Tozer, D. J.; Duering, M.; Malik, R.; Dichgans, M.; Markus, H. S.; and Traylor, M.\n\n\n \n\n\n\n Stroke, 49(6): 1340–1347. June 2018.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{rutten-jacobs_genetic_2018,\n\ttitle = {Genetic {Study} of {White} {Matter} {Integrity} in {UK} {Biobank} ({N}=8448) and the {Overlap} {With} {Stroke}, {Depression}, and {Dementia}},\n\tvolume = {49},\n\tissn = {1524-4628 (Electronic) 0039-2499 (Linking)},\n\tdoi = {10.1161/STROKEAHA.118.020811},\n\tabstract = {BACKGROUND AND PURPOSE: Structural integrity of the white matter is a marker of cerebral small vessel disease, which is the major cause of vascular dementia and a quarter of all strokes. Genetic studies provide a way to obtain novel insights in the disease mechanism underlying cerebral small vessel disease. The aim was to identify common variants associated with microstructural integrity of the white matter and to elucidate the relationships of white matter structural integrity with stroke, major depressive disorder, and Alzheimer disease. METHODS: This genome-wide association analysis included 8448 individuals from UK Biobank-a population-based cohort study that recruited individuals from across the United Kingdom between 2006 and 2010, aged 40 to 69 years. Microstructural integrity was measured as fractional anisotropy- (FA) and mean diffusivity (MD)-derived parameters on diffusion tensor images. White matter hyperintensity volumes (WMHV) were assessed on T2-weighted fluid-attenuated inversion recovery images. RESULTS: We identified 1 novel locus at genome-wide significance (VCAN [versican]: rs13164785; P=3.7x10(-18) for MD and rs67827860; P=1.3x10(-14) for FA). LD score regression showed a significant genome-wide correlation between FA, MD, and WMHV (FA-WMHV rG 0.39 [SE, 0.15]; MD-WMHV rG 0.56 [SE, 0.19]). In polygenic risk score analysis, FA, MD, and WMHV were significantly associated with lacunar stroke, MD with major depressive disorder, and WMHV with Alzheimer disease. CONCLUSIONS: Genetic variants within the VCAN gene may play a role in the mechanisms underlying microstructural integrity of the white matter in the brain measured as FA and MD. Mechanisms underlying white matter alterations are shared with cerebrovascular disease, and inherited differences in white matter microstructure impact on Alzheimer disease and major depressive disorder.},\n\tnumber = {6},\n\tjournal = {Stroke},\n\tauthor = {Rutten-Jacobs, L. C. A. and Tozer, D. J. and Duering, M. and Malik, R. and Dichgans, M. and Markus, H. S. and Traylor, M.},\n\tmonth = jun,\n\tyear = {2018},\n\tpmcid = {PMC5976227},\n\tpmid = {29752348},\n\tkeywords = {Stroke, Adult, Aged, Diffusion Magnetic Resonance Imaging, Female, Humans, Male, Middle Aged, diffusion tensor imaging, white matter, *diffusion tensor imaging, *white matter, *cerebral small vessel diseases, Genome-Wide Association Study, White Matter/*pathology, Dementia, Biological Specimen Banks, United Kingdom, Diffusion Magnetic Resonance Imaging/methods, *genetic association studies, *Genome-Wide Association Study, *humans, Cerebral Small Vessel Diseases/genetics, Dementia/complications/*genetics, Depression/genetics, Depressive Disorder, Major/complications/*genetics, Stroke/complications/*genetics, cerebral small vessel diseases, White Matter, Cerebral Small Vessel Diseases, Depression, Depressive Disorder, Major, genetic association studies, humans},\n\tpages = {1340--1347},\n}\n\n

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\n \n\n \n \n \n \n \n Thalamic Diaschisis in Acute Ischemic Stroke: Occurrence, Perfusion Characteristics, and Impact on Outcome.\n \n \n \n\n\n \n Reidler, P.; Thierfelder, K. M.; Fabritius, M. P.; Sommer, W. H.; Meinel, F. G.; Dorn, F.; Wollenweber, F. A.; Duering, M.; and Kunz, W. G.\n\n\n \n\n\n\n Stroke, 49(4): 931–937. April 2018.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{reidler_thalamic_2018,\n\ttitle = {Thalamic {Diaschisis} in {Acute} {Ischemic} {Stroke}: {Occurrence}, {Perfusion} {Characteristics}, and {Impact} on {Outcome}},\n\tvolume = {49},\n\tissn = {1524-4628 (Electronic) 0039-2499 (Linking)},\n\tdoi = {10.1161/STROKEAHA.118.020698},\n\tabstract = {BACKGROUND AND PURPOSE: Ipsilateral thalamic diaschisis (ITD) describes the reduction of thalamic function, metabolism, and perfusion resulting from a distant lesion of the ipsilateral hemisphere. Our aim was to evaluate the perfusion characteristics and clinical impact of ITD in acute middle cerebral artery stroke, which does not directly affect the thalamus. METHODS: One hundred twenty-four patients with middle cerebral artery infarction were selected from a prospectively acquired cohort of 1644 patients who underwent multiparametric computed tomography (CT), including CT perfusion for suspected stroke. Two blinded readers evaluated the occurrence of ITD, defined as ipsilateral thalamic hypoperfusion present on {\\textgreater}/=2 CT perfusion maps. Perfusion alterations were defined according to the Alberta Stroke Program Early CT Score regions. Final infarction volume and subacute complications were assessed on follow-up imaging. Clinical outcome was quantified using the modified Rankin Scale. Multivariable linear and ordinal logistic regression analysis were applied to identify independent associations. RESULTS: ITD was present in 25/124 subjects (20.2\\%, ITD+). In ITD+ subjects, perfusion of the caudate nucleus, internal capsule, and lentiform nucleus was more frequently affected than in ITD- patients (each with P{\\textless}0.001). In the ITD+ group, larger cerebral blood flow (P=0.002) and cerebral blood volume (P{\\textless}0.001) deficit volumes, as well as smaller cerebral blood flow-cerebral blood volume mismatch (P=0.021) were observed. There was no independent association of ITD with final infarction volume or clinical outcome at discharge in treatment subgroups (each with P{\\textgreater}0.05). ITD had no influence on the development of subacute stroke complications. CONCLUSIONS: ITD in the form of thalamic hypoperfusion is a frequent CT perfusion finding in the acute phase in middle cerebral artery stroke patients with marked involvement of subcortical areas. ITD does not result in thalamic infarction and had no independent impact on patient outcome. Notably, ITD was misclassified as part of the ischemic core by automated software, which might affect patient selection in CT perfusion-based trials.},\n\tnumber = {4},\n\tjournal = {Stroke},\n\tauthor = {Reidler, P. and Thierfelder, K. M. and Fabritius, M. P. and Sommer, W. H. and Meinel, F. G. and Dorn, F. and Wollenweber, F. A. and Duering, M. and Kunz, W. G.},\n\tmonth = apr,\n\tyear = {2018},\n\tpmid = {29523650},\n\tkeywords = {Stroke, Aged, Female, Humans, Male, Middle Aged, Aged, 80 and over, Case-Control Studies, cerebral blood flow, Linear Models, Logistic Models, Multivariate Analysis, *acute stroke, *brain ischemia, *cerebral blood flow, *perfusion, *thalamus, Brain Ischemia/*diagnostic imaging/etiology/physiopathology, Caudate Nucleus/blood supply/diagnostic imaging, Cerebrovascular Circulation, Corpus Striatum/blood supply/diagnostic imaging, imaging/physiopathology, Infarction, Middle Cerebral Artery/complications/*diagnostic, Internal Capsule/blood supply/diagnostic imaging, Perfusion Imaging, Stroke/complications/diagnostic imaging/physiopathology, Thalamic Diseases/*diagnostic imaging/etiology/physiopathology, Thalamus/blood supply/diagnostic imaging, Tomography, X-Ray Computed, thalamus, Corpus Striatum, Thalamus, brain ischemia, Brain Ischemia, acute stroke, Caudate Nucleus, Infarction, Middle Cerebral Artery, Internal Capsule, perfusion, Thalamic Diseases},\n\tpages = {931--937},\n}\n\n

\n\n\n

\n BACKGROUND AND PURPOSE: Ipsilateral thalamic diaschisis (ITD) describes the reduction of thalamic function, metabolism, and perfusion resulting from a distant lesion of the ipsilateral hemisphere. Our aim was to evaluate the perfusion characteristics and clinical impact of ITD in acute middle cerebral artery stroke, which does not directly affect the thalamus. METHODS: One hundred twenty-four patients with middle cerebral artery infarction were selected from a prospectively acquired cohort of 1644 patients who underwent multiparametric computed tomography (CT), including CT perfusion for suspected stroke. Two blinded readers evaluated the occurrence of ITD, defined as ipsilateral thalamic hypoperfusion present on \\textgreater/=2 CT perfusion maps. Perfusion alterations were defined according to the Alberta Stroke Program Early CT Score regions. Final infarction volume and subacute complications were assessed on follow-up imaging. Clinical outcome was quantified using the modified Rankin Scale. Multivariable linear and ordinal logistic regression analysis were applied to identify independent associations. RESULTS: ITD was present in 25/124 subjects (20.2%, ITD+). In ITD+ subjects, perfusion of the caudate nucleus, internal capsule, and lentiform nucleus was more frequently affected than in ITD- patients (each with P\\textless0.001). In the ITD+ group, larger cerebral blood flow (P=0.002) and cerebral blood volume (P\\textless0.001) deficit volumes, as well as smaller cerebral blood flow-cerebral blood volume mismatch (P=0.021) were observed. There was no independent association of ITD with final infarction volume or clinical outcome at discharge in treatment subgroups (each with P\\textgreater0.05). ITD had no influence on the development of subacute stroke complications. CONCLUSIONS: ITD in the form of thalamic hypoperfusion is a frequent CT perfusion finding in the acute phase in middle cerebral artery stroke patients with marked involvement of subcortical areas. ITD does not result in thalamic infarction and had no independent impact on patient outcome. Notably, ITD was misclassified as part of the ischemic core by automated software, which might affect patient selection in CT perfusion-based trials.\n

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\n \n\n \n \n \n \n \n Grey-matter network disintegration as predictor of cognitive and motor function with aging.\n \n \n \n\n\n \n Koini, M.; Duering, M.; Gesierich, B. G.; Rombouts, S.; Ropele, S.; Wagner, F.; Enzinger, C.; and Schmidt, R.\n\n\n \n\n\n\n Brain Struct Funct, 223(5): 2475–2487. June 2018.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{koini_grey-matter_2018,\n\ttitle = {Grey-matter network disintegration as predictor of cognitive and motor function with aging},\n\tvolume = {223},\n\tissn = {1863-2661 (Electronic) 1863-2653 (Linking)},\n\tdoi = {10.1007/s00429-018-1642-0},\n\tabstract = {Loss of grey-matter volume with advancing age affects the entire cortex. It has been suggested that atrophy occurs in a network-dependent manner with advancing age rather than in independent brain areas. The relationship between networks of structural covariance (SCN) disintegration and cognitive functioning during normal aging is not fully explored. We, therefore, aimed to (1) identify networks that lose GM integrity with advancing age, (2) investigate if age-related impairment of integrity in GM networks associates with cognitive function and decreasing fine motor skills (FMS), and (3) examine if GM disintegration is a mediator between age and cognition and FMS. T1-weighted scans of n = 257 participants (age range: 20-87) were used to identify GM networks using independent component analysis. Random forest analysis was implemented to examine the importance of network integrity as predictors of memory, executive functions, and FMS. The associations between GM disintegration, age and cognitive performance, and FMS were assessed using mediation analyses. Advancing age was associated with decreasing cognitive performance and FMS. Fourteen of 20 GM networks showed integrity changes with advancing age. Next to age and education, eight networks (fronto-parietal, fronto-occipital, temporal, limbic, secondary somatosensory, cuneal, sensorimotor network, and a cerebellar network) showed an association with cognition and FMS (up to 15.08\\%). GM networks partially mediated the effect between age and cognition and age and FMS. We confirm an age-related decline in cognitive functioning and FMS in non-demented community-dwelling subjects and showed that aging selectively affects the integrity of GM networks. The negative effect of age on cognition and FMS is associated with distinct GM networks and is partly mediated by their disintegration.},\n\tnumber = {5},\n\tjournal = {Brain Struct Funct},\n\tauthor = {Koini, M. and Duering, M. and Gesierich, B. G. and Rombouts, Sarb and Ropele, S. and Wagner, F. and Enzinger, C. and Schmidt, R.},\n\tmonth = jun,\n\tyear = {2018},\n\tpmcid = {PMC5968058},\n\tpmid = {29511859},\n\tkeywords = {Cognition, Adult, Aged, Female, Humans, Image Processing, Computer-Assisted, Male, Middle Aged, Aged, 80 and over, Magnetic Resonance Imaging, Young Adult, Neuropsychological Tests, Age Factors, Aging, Atrophy, Aging/*pathology, Atrophy/diagnostic imaging/etiology/pathology, Brain Mapping, Cognitive Aging/*physiology, Fine motor skills, Functional Laterality, Gray Matter/diagnostic imaging/*pathology, Grey-matter atrophy, Motor Skills Disorders/diagnostic imaging/etiology/*pathology, Structural covariance networks, Gray Matter, Cognitive Aging, Motor Skills Disorders},\n\tpages = {2475--2487},\n}\n\n

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\n \n\n \n \n \n \n \n The left frontal cortex supports reserve in aging by enhancing functional network efficiency.\n \n \n \n\n\n \n Franzmeier, N.; Hartmann, J.; Taylor, A. N. W.; Araque-Caballero, M. A.; Simon-Vermot, L.; Kambeitz-Ilankovic, L.; Burger, K.; Catak, C.; Janowitz, D.; Muller, C.; Ertl-Wagner, B.; Stahl, R.; Dichgans, M.; Duering, M.; and Ewers, M.\n\n\n \n\n\n\n Alzheimers Res Ther, 10(1): 28. March 2018.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{franzmeier_left_2018,\n\ttitle = {The left frontal cortex supports reserve in aging by enhancing functional network efficiency},\n\tvolume = {10},\n\tissn = {1758-9193 (Electronic)},\n\tdoi = {10.1186/s13195-018-0358-y},\n\tabstract = {BACKGROUND: Recent evidence derived from functional magnetic resonance imaging (fMRI) studies suggests that functional hubs (i.e., highly connected brain regions) are important for mental health. We found recently that global connectivity of a hub in the left frontal cortex (LFC connectivity) is associated with relatively preserved memory abilities and higher levels of protective factors (education, IQ) in normal aging and Alzheimer's disease. These results suggest that LFC connectivity supports reserve capacity, alleviating memory decline. An open question, however, is why LFC connectivity is beneficial and supports memory function in the face of neurodegeneration. We hypothesized that higher LFC connectivity is associated with enhanced efficiency in connected major networks involved in episodic memory. We further hypothesized that higher LFC-related network efficiency predicts higher memory abilities. METHODS: We assessed fMRI during a face-name association learning task performed by 26 healthy, cognitively normal elderly participants. Using beta-series correlation analysis, we computed task-related LFC connectivity to key memory networks, including the default mode network (DMN) and dorsal attention network (DAN). Network efficiency within the DMN and DAN was estimated by the graph theoretical small-worldness statistic. We applied linear regression analyses to test the association between LFC connectivity with the DMN/DAN and small-worldness of these networks. Mediation analysis was applied to test LFC connectivity to the DMN and DAN as a mediator of the association between education and higher DMN and DAN small-worldness. Last, we tested network small-worldness as a predictor of memory performance. RESULTS: We found that higher LFC connectivity to the DMN and DAN during successful memory encoding and recognition was associated with higher small-worldness of those networks. Higher task-related LFC connectivity mediated the association between education and higher small-worldness in the DMN and DAN. Further, higher small-worldness of these networks predicted better performance in the memory task. CONCLUSIONS: The present results suggest that higher education-related LFC connectivity to key memory networks during a memory task is associated with higher network efficiency and thus enhanced reserve of memory abilities in aging.},\n\tnumber = {1},\n\tjournal = {Alzheimers Res Ther},\n\tauthor = {Franzmeier, N. and Hartmann, J. and Taylor, A. N. W. and Araque-Caballero, M. A. and Simon-Vermot, L. and Kambeitz-Ilankovic, L. and Burger, K. and Catak, C. and Janowitz, D. and Muller, C. and Ertl-Wagner, B. and Stahl, R. and Dichgans, M. and Duering, M. and Ewers, M.},\n\tmonth = mar,\n\tyear = {2018},\n\tpmcid = {PMC5838935},\n\tpmid = {29510747},\n\tkeywords = {Aged, Female, Humans, Image Processing, Computer-Assisted, Male, Middle Aged, Aged, 80 and over, Magnetic Resonance Imaging, Oxygen/blood, *Brain Mapping, Aging, Aging/*pathology, Brain Mapping, Functional Laterality, *Aging, *Cognitive reserve, *Frontoparietal control network, *Memory task fMRI, *Small-worldness, Association Learning/physiology, Attention/physiology, Frontal Lobe/*diagnostic imaging, Functional Laterality/*physiology, Models, Neurological, Neural Pathways/*diagnostic imaging, Photic Stimulation, Frontal Lobe, Neural Pathways, Oxygen, Association Learning, Attention, Cognitive reserve, Frontoparietal control network, Memory task fMRI, Small-worldness},\n\tpages = {28},\n}\n\n

\n\n\n

\n BACKGROUND: Recent evidence derived from functional magnetic resonance imaging (fMRI) studies suggests that functional hubs (i.e., highly connected brain regions) are important for mental health. We found recently that global connectivity of a hub in the left frontal cortex (LFC connectivity) is associated with relatively preserved memory abilities and higher levels of protective factors (education, IQ) in normal aging and Alzheimer's disease. These results suggest that LFC connectivity supports reserve capacity, alleviating memory decline. An open question, however, is why LFC connectivity is beneficial and supports memory function in the face of neurodegeneration. We hypothesized that higher LFC connectivity is associated with enhanced efficiency in connected major networks involved in episodic memory. We further hypothesized that higher LFC-related network efficiency predicts higher memory abilities. METHODS: We assessed fMRI during a face-name association learning task performed by 26 healthy, cognitively normal elderly participants. Using beta-series correlation analysis, we computed task-related LFC connectivity to key memory networks, including the default mode network (DMN) and dorsal attention network (DAN). Network efficiency within the DMN and DAN was estimated by the graph theoretical small-worldness statistic. We applied linear regression analyses to test the association between LFC connectivity with the DMN/DAN and small-worldness of these networks. Mediation analysis was applied to test LFC connectivity to the DMN and DAN as a mediator of the association between education and higher DMN and DAN small-worldness. Last, we tested network small-worldness as a predictor of memory performance. RESULTS: We found that higher LFC connectivity to the DMN and DAN during successful memory encoding and recognition was associated with higher small-worldness of those networks. Higher task-related LFC connectivity mediated the association between education and higher small-worldness in the DMN and DAN. Further, higher small-worldness of these networks predicted better performance in the memory task. CONCLUSIONS: The present results suggest that higher education-related LFC connectivity to key memory networks during a memory task is associated with higher network efficiency and thus enhanced reserve of memory abilities in aging.\n

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\n \n\n \n \n \n \n \n Left frontal hub connectivity delays cognitive impairment in autosomal-dominant and sporadic Alzheimer's disease.\n \n \n \n\n\n \n Franzmeier, N.; Duzel, E.; Jessen, F.; Buerger, K.; Levin, J.; Duering, M.; Dichgans, M.; Haass, C.; Suarez-Calvet, M.; Fagan, A. M.; Paumier, K.; Benzinger, T.; Masters, C. L.; Morris, J. C.; Perneczky, R.; Janowitz, D.; Catak, C.; Wolfsgruber, S.; Wagner, M.; Teipel, S.; Kilimann, I.; Ramirez, A.; Rossor, M.; Jucker, M.; Chhatwal, J.; Spottke, A.; Boecker, H.; Brosseron, F.; Falkai, P.; Fliessbach, K.; Heneka, M. T.; Laske, C.; Nestor, P.; Peters, O.; Fuentes, M.; Menne, F.; Priller, J.; Spruth, E. J.; Franke, C.; Schneider, A.; Kofler, B.; Westerteicher, C.; Speck, O.; Wiltfang, J.; Bartels, C.; Araque Caballero, M. A.; Metzger, C.; Bittner, D.; Weiner, M.; Lee, J. H.; Salloway, S.; Danek, A.; Goate, A.; Schofield, P. R.; Bateman, R. J.; and Ewers, M.\n\n\n \n\n\n\n Brain, 141(4): 1186–1200. April 2018.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{franzmeier_left_2018-1,\n\ttitle = {Left frontal hub connectivity delays cognitive impairment in autosomal-dominant and sporadic {Alzheimer}'s disease},\n\tvolume = {141},\n\tissn = {1460-2156 (Electronic) 0006-8950 (Linking)},\n\tdoi = {10.1093/brain/awy008},\n\tabstract = {Patients with Alzheimer's disease vary in their ability to sustain cognitive abilities in the presence of brain pathology. A major open question is which brain mechanisms may support higher reserve capacity, i.e. relatively high cognitive performance at a given level of Alzheimer's pathology. Higher functional MRI-assessed functional connectivity of a hub in the left frontal cortex is a core candidate brain mechanism underlying reserve as it is associated with education (i.e. a protective factor often associated with higher reserve) and attenuated cognitive impairment in prodromal Alzheimer's disease. However, no study has yet assessed whether such hub connectivity of the left frontal cortex supports reserve throughout the evolution of pathological brain changes in Alzheimer's disease, including the presymptomatic stage when cognitive decline is subtle. To address this research gap, we obtained cross-sectional resting state functional MRI in 74 participants with autosomal dominant Alzheimer's disease, 55 controls from the Dominantly Inherited Alzheimer's Network and 75 amyloid-positive elderly participants, as well as 41 amyloid-negative cognitively normal elderly subjects from the German Center of Neurodegenerative Diseases multicentre study on biomarkers in sporadic Alzheimer's disease. For each participant, global left frontal cortex connectivity was computed as the average resting state functional connectivity between the left frontal cortex (seed) and each voxel in the grey matter. As a marker of disease stage, we applied estimated years from symptom onset in autosomal dominantly inherited Alzheimer's disease and cerebrospinal fluid tau levels in sporadic Alzheimer's disease cases. In both autosomal dominant and sporadic Alzheimer's disease patients, higher levels of left frontal cortex connectivity were correlated with greater education. For autosomal dominant Alzheimer's disease, a significant left frontal cortex connectivity x estimated years of onset interaction was found, indicating slower decline of memory and global cognition at higher levels of connectivity. Similarly, in sporadic amyloid-positive elderly subjects, the effect of tau on cognition was attenuated at higher levels of left frontal cortex connectivity. Polynomial regression analysis showed that the trajectory of cognitive decline was shifted towards a later stage of Alzheimer's disease in patients with higher levels of left frontal cortex connectivity. Together, our findings suggest that higher resilience against the development of cognitive impairment throughout the early stages of Alzheimer's disease is at least partially attributable to higher left frontal cortex-hub connectivity.},\n\tnumber = {4},\n\tjournal = {Brain},\n\tauthor = {Franzmeier, N. and Duzel, E. and Jessen, F. and Buerger, K. and Levin, J. and Duering, M. and Dichgans, M. and Haass, C. and Suarez-Calvet, M. and Fagan, A. M. and Paumier, K. and Benzinger, T. and Masters, C. L. and Morris, J. C. and Perneczky, R. and Janowitz, D. and Catak, C. and Wolfsgruber, S. and Wagner, M. and Teipel, S. and Kilimann, I. and Ramirez, A. and Rossor, M. and Jucker, M. and Chhatwal, J. and Spottke, A. and Boecker, H. and Brosseron, F. and Falkai, P. and Fliessbach, K. and Heneka, M. T. and Laske, C. and Nestor, P. and Peters, O. and Fuentes, M. and Menne, F. and Priller, J. and Spruth, E. J. and Franke, C. and Schneider, A. and Kofler, B. and Westerteicher, C. and Speck, O. and Wiltfang, J. and Bartels, C. and Araque Caballero, M. A. and Metzger, C. and Bittner, D. and Weiner, M. and Lee, J. H. and Salloway, S. and Danek, A. and Goate, A. and Schofield, P. R. and Bateman, R. J. and Ewers, M.},\n\tmonth = apr,\n\tyear = {2018},\n\tpmcid = {PMC5888938},\n\tpmid = {29462334},\n\tkeywords = {Adult, Female, Humans, Male, Middle Aged, Magnetic Resonance Imaging, Presenilin-1, Mutation, Brain Mapping, Functional Laterality, Frontal Lobe/*diagnostic imaging, Functional Laterality/*physiology, Alzheimer Disease/*complications/diagnostic imaging/genetics, Amyloid beta-Protein Precursor/genetics, Cognitive Dysfunction/*diagnostic imaging/*etiology, Imaging, Three-Dimensional, Mutation/genetics, Nerve Net/*diagnostic imaging/physiology, Presenilin-1/genetics, Presenilin-2/genetics, Presenilin-2, Alzheimer Disease, Frontal Lobe, Amyloid beta-Protein Precursor, Cognitive Dysfunction, Nerve Net},\n\tpages = {1186--1200},\n}\n\n

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\n Patients with Alzheimer's disease vary in their ability to sustain cognitive abilities in the presence of brain pathology. A major open question is which brain mechanisms may support higher reserve capacity, i.e. relatively high cognitive performance at a given level of Alzheimer's pathology. Higher functional MRI-assessed functional connectivity of a hub in the left frontal cortex is a core candidate brain mechanism underlying reserve as it is associated with education (i.e. a protective factor often associated with higher reserve) and attenuated cognitive impairment in prodromal Alzheimer's disease. However, no study has yet assessed whether such hub connectivity of the left frontal cortex supports reserve throughout the evolution of pathological brain changes in Alzheimer's disease, including the presymptomatic stage when cognitive decline is subtle. To address this research gap, we obtained cross-sectional resting state functional MRI in 74 participants with autosomal dominant Alzheimer's disease, 55 controls from the Dominantly Inherited Alzheimer's Network and 75 amyloid-positive elderly participants, as well as 41 amyloid-negative cognitively normal elderly subjects from the German Center of Neurodegenerative Diseases multicentre study on biomarkers in sporadic Alzheimer's disease. For each participant, global left frontal cortex connectivity was computed as the average resting state functional connectivity between the left frontal cortex (seed) and each voxel in the grey matter. As a marker of disease stage, we applied estimated years from symptom onset in autosomal dominantly inherited Alzheimer's disease and cerebrospinal fluid tau levels in sporadic Alzheimer's disease cases. In both autosomal dominant and sporadic Alzheimer's disease patients, higher levels of left frontal cortex connectivity were correlated with greater education. For autosomal dominant Alzheimer's disease, a significant left frontal cortex connectivity x estimated years of onset interaction was found, indicating slower decline of memory and global cognition at higher levels of connectivity. Similarly, in sporadic amyloid-positive elderly subjects, the effect of tau on cognition was attenuated at higher levels of left frontal cortex connectivity. Polynomial regression analysis showed that the trajectory of cognitive decline was shifted towards a later stage of Alzheimer's disease in patients with higher levels of left frontal cortex connectivity. Together, our findings suggest that higher resilience against the development of cognitive impairment throughout the early stages of Alzheimer's disease is at least partially attributable to higher left frontal cortex-hub connectivity.\n

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\n \n\n \n \n \n \n \n Remote changes after ischaemic infarcts: a distant target for therapy?.\n \n \n \n\n\n \n Duering, M.; and Schmidt, R.\n\n\n \n\n\n\n Brain, 140(7): 1818–1820. July 2017.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{duering_remote_2017,\n\ttitle = {Remote changes after ischaemic infarcts: a distant target for therapy?},\n\tvolume = {140},\n\tissn = {1460-2156 (Electronic) 0006-8950 (Linking)},\n\tdoi = {10.1093/brain/awx135},\n\tnumber = {7},\n\tjournal = {Brain},\n\tauthor = {Duering, M. and Schmidt, R.},\n\tmonth = jul,\n\tyear = {2017},\n\tpmid = {29177495},\n\tkeywords = {*Iron, *Thalamus, Iron, Thalamus},\n\tpages = {1818--1820},\n}\n\n

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\n \n\n \n \n \n \n \n Cortical Superficial Siderosis in Different Types of Cerebral Small Vessel Disease.\n \n \n \n\n\n \n Wollenweber, F. A.; Baykara, E.; Zedde, M.; Gesierich, B.; Achmuller, M.; Jouvent, E.; Viswanathan, A.; Ropele, S.; Chabriat, H.; Schmidt, R.; Opherk, C.; Dichgans, M.; Linn, J.; and Duering, M.\n\n\n \n\n\n\n Stroke, 48(5): 1404–1407. May 2017.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{wollenweber_cortical_2017,\n\ttitle = {Cortical {Superficial} {Siderosis} in {Different} {Types} of {Cerebral} {Small} {Vessel} {Disease}},\n\tvolume = {48},\n\tissn = {1524-4628 (Electronic) 0039-2499 (Linking)},\n\tdoi = {10.1161/STROKEAHA.117.016833},\n\tabstract = {BACKGROUND AND PURPOSE: Cortical superficial siderosis (cSS) has emerged as a clinically relevant imaging feature of cerebral amyloid angiopathy (CAA). However, it remains unknown whether cSS is also present in nonamyloid-associated small vessel disease and whether patients with cSS differ in terms of other small vessel disease imaging features. METHODS: Three hundred sixty-four CADASIL (cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy) patients, 372 population-based controls, and 100 CAA patients with cSS (fulfilling the modified Boston criteria for possible/probable CAA) were included. cSS and cerebral microbleeds were visually rated on T2*-weighted magnetic resonance imaging. White matter hyperintensities were segmented on fluid-attenauted inversion recovery images, and their spatial distribution was compared between groups using colocalization analysis. Cerebral microbleeds location was determined in an observer-independent way using an atlas in standard space. RESULTS: cSS was absent in CADASIL and present in only 2 population-based controls (0.5\\%). Cerebral microbleeds were present in 64\\% of CAA patients with cSS, 34\\% of patients with CADASIL, and 12\\% of population-based controls. Among patients with cerebral microbleeds, lobar location was found in 95\\% of CAA patients with cSS, 48\\% of CADASIL patients, and 69\\% of population-based controls. The spatial distribution of white matter hyperintensities was comparable between CAA with cSS and CADASIL as indicated by high colocalization coefficients. CONCLUSIONS: cSS was absent in CADASIL, whereas other small vessel disease imaging features were similar to CAA patients with cSS. Our findings suggest that cSS in combination with other small vessel disease imaging markers is highly indicative of CAA.},\n\tnumber = {5},\n\tjournal = {Stroke},\n\tauthor = {Wollenweber, F. A. and Baykara, E. and Zedde, M. and Gesierich, B. and Achmuller, M. and Jouvent, E. and Viswanathan, A. and Ropele, S. and Chabriat, H. and Schmidt, R. and Opherk, C. and Dichgans, M. and Linn, J. and Duering, M.},\n\tmonth = may,\n\tyear = {2017},\n\tpmid = {28364025},\n\tkeywords = {Adult, Aged, Female, Humans, Male, Middle Aged, Aged, 80 and over, Magnetic Resonance Imaging, *cadasil, *cerebral amyloid angiopathy, *cerebral small vessel diseases, *intracranial hemorrhages, *magnetic resonance imaging, CADASIL/diagnostic imaging/epidemiology, Cerebral Amyloid Angiopathy/*diagnostic imaging/epidemiology, Cerebral Cortex/*diagnostic imaging/metabolism, Cerebral Hemorrhage/*diagnostic imaging/epidemiology, Cerebral Small Vessel Diseases/*diagnostic imaging/epidemiology, Comorbidity, Hemosiderosis/*diagnostic imaging/epidemiology, Young Adult, cerebral amyloid angiopathy, magnetic resonance imaging, cerebral small vessel diseases, Cerebral Hemorrhage, Cerebral Amyloid Angiopathy, Cerebral Cortex, Cerebral Small Vessel Diseases, CADASIL, Hemosiderosis, intracranial hemorrhages},\n\tpages = {1404--1407},\n}\n\n

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\n \n\n \n \n \n \n \n Arterial branching and basal ganglia lacunes: A study in pure small vessel disease.\n \n \n \n\n\n \n Moreton, F. C.; During, M.; Phan, T.; Srikanth, V.; Beare, R.; Huang, X.; Jouvent, E.; Chabriat, H.; Dichgans, M.; and Muir, K. W.\n\n\n \n\n\n\n Eur Stroke J, 2(3): 264–271. September 2017.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{moreton_arterial_2017,\n\ttitle = {Arterial branching and basal ganglia lacunes: {A} study in pure small vessel disease},\n\tvolume = {2},\n\tissn = {2396-9881 (Electronic) 2396-9873 (Linking)},\n\tdoi = {10.1177/2396987317718450},\n\tabstract = {Introduction: Lacunes are defined morphologically by size and location, but radiological characteristics alone may be unable to distinguish small vessel disease aetiology from alternative mechanisms. We investigated the branching order of arterial vessels associated with basal ganglia lacunes in cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL), in order to improve the understanding of their pathogenesis in pure cerebral small vessel disease. Patients and methods: Adults with a confirmed diagnosis of CADASIL were included. A pilot study was conducted in a Scottish CADASIL cohort. The Paris-Munich CADASIL cohort was used for independent validation. Lacunes identified on T1-weighted magnetic resonance imaging scans were registered to a standard brain template. A microangiographic template of the basal ganglia vasculature was automatically overlaid onto coronal slices, and raters estimated the vessel branching order related to each lacune. Results: Of 179 lacunes, 150 (84\\%) were associated with third-order vessels. In 14 incident lacunes, 11 (79\\%) were associated with third-order vessels. In the pilot study, lacune volume was significantly lower in lacunes associated with third-order vessels (0.04 ml +/- 0.04 ml) compared to second-order vessels (0.48 +/- 0.16 ml; p {\\textless} 0.001). Discussion: In this study of CADASIL patients, most lacunes were small and associated with third-order vessel disease. This suggests that these are the vessels primarily affected in cerebral small vessel disease. Microangiographic template techniques could be used to further investigate in a general stroke population whether finding large lacunes originating from higher order vessels indicates an alternative cause of stroke. Conclusion: Lacunes in pure small vessel disease are associated with the smallest vessels in the basal ganglia.},\n\tnumber = {3},\n\tjournal = {Eur Stroke J},\n\tauthor = {Moreton, F. C. and During, M. and Phan, T. and Srikanth, V. and Beare, R. and Huang, X. and Jouvent, E. and Chabriat, H. and Dichgans, M. and Muir, K. W.},\n\tmonth = sep,\n\tyear = {2017},\n\tpmcid = {PMC6454827},\n\tpmid = {31008320},\n\tkeywords = {lacunes, cerebral autosomal dominant arteriopathy with subcortical infarcts and, Infarction, leukoencephalopathy, magnetic resonance imaging, cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy},\n\tpages = {264--271},\n}\n\n

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\n \n\n \n \n \n \n \n Microstructure of Strategic White Matter Tracts and Cognition in Memory Clinic Patients with Vascular Brain Injury.\n \n \n \n\n\n \n Biesbroek, J. M.; Leemans, A.; den Bakker, H.; Duering, M.; Gesierich, B.; Koek, H. L.; van den Berg, E.; Postma, A.; and Biessels, G. J.\n\n\n \n\n\n\n Dement Geriatr Cogn Disord, 44(5-6): 268–282. 2017.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{biesbroek_microstructure_2017,\n\ttitle = {Microstructure of {Strategic} {White} {Matter} {Tracts} and {Cognition} in {Memory} {Clinic} {Patients} with {Vascular} {Brain} {Injury}},\n\tvolume = {44},\n\tissn = {1421-9824 (Electronic) 1420-8008 (Linking)},\n\tdoi = {10.1159/000485376},\n\tabstract = {BACKGROUND: White matter injury is an important factor for cognitive impairment in memory clinic patients. We determined the added value of diffusion tensor imaging (DTI) of strategic white matter tracts in explaining variance in cognition in memory clinic patients with vascular brain injury. METHODS: We included 159 patients. Conventional MRI markers (white matter hyperintensity volume, lacunes, nonlacunar infarcts, brain atrophy, and microbleeds), and fractional anisotropy and mean diffusivity (MD) of the whole brain white matter and of 18 white matter tracts were related to cognition using linear regression and Bayesian network analysis. RESULTS: On top of all conventional MRI markers combined, MD of the whole brain white matter explained an additional 3.4\\% (p = 0.014), 7.8\\% (p {\\textless} 0.001), and 1.2\\% (p = 0.119) variance in executive functioning, speed, and memory, respectively. The Bayesian analyses of regional DTI measures identified strategic tracts for executive functioning (right superior longitudinal fasciculus), speed (left corticospinal tract), and memory (left uncinate fasciculus). MD within these tracts explained an additional 3.4\\% (p = 0.012), 3.8\\% (p = 0.007), and 2.1\\% (p = 0.041) variance in executive functioning, speed, and memory, respectively, on top of all conventional MRI and global DTI markers combined. CONCLUSION: In memory clinic patients with vascular brain injury, DTI of strategic white matter tracts has a significant added value in explaining variance in cognitive functioning.},\n\tnumber = {5-6},\n\tjournal = {Dement Geriatr Cogn Disord},\n\tauthor = {Biesbroek, J. M. and Leemans, A. and den Bakker, H. and Duering, M. and Gesierich, B. and Koek, H. L. and van den Berg, E. and Postma, A. and Biessels, G. J.},\n\tyear = {2017},\n\tpmcid = {PMC5972515},\n\tpmid = {29353280},\n\tkeywords = {Cognition, Small vessel disease, Aged, Diffusion Tensor Imaging, Female, Humans, Image Processing, Computer-Assisted, Male, Middle Aged, Aged, 80 and over, Magnetic Resonance Imaging, *Diffusion tensor imaging, *Small vessel disease, White Matter/*diagnostic imaging, Cohort Studies, Executive Function, Neuropsychological Tests, Atrophy, Diffusion tensor imaging, *Alzheimer disease, *Cognition, *Strategic white matter tract, *Vascular dementia, Anisotropy, Cerebral Infarction/diagnostic imaging, Cerebrovascular Disorders/*diagnostic imaging/*psychology, Cognition Disorders/diagnostic imaging/psychology, Memory Disorders/*diagnostic imaging/*psychology, Psychomotor Performance, White Matter, Cerebral Infarction, Cognition Disorders, Cerebrovascular Disorders, Vascular dementia, Alzheimer disease, Memory Disorders, Strategic white matter tract},\n\tpages = {268--282},\n}\n\n

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\n \n\n \n \n \n \n \n Cerebral Microbleeds and the Risk of Incident Ischemic Stroke in CADASIL (Cerebral Autosomal Dominant Arteriopathy With Subcortical Infarcts and Leukoencephalopathy).\n \n \n \n\n\n \n Puy, L.; De Guio, F.; Godin, O.; Duering, M.; Dichgans, M.; Chabriat, H.; and Jouvent, E.\n\n\n \n\n\n\n Stroke, 48(10): 2699–2703. October 2017.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{puy_cerebral_2017,\n\ttitle = {Cerebral {Microbleeds} and the {Risk} of {Incident} {Ischemic} {Stroke} in {CADASIL} ({Cerebral} {Autosomal} {Dominant} {Arteriopathy} {With} {Subcortical} {Infarcts} and {Leukoencephalopathy})},\n\tvolume = {48},\n\tissn = {1524-4628 (Electronic) 0039-2499 (Linking)},\n\tdoi = {10.1161/STROKEAHA.117.017839},\n\tabstract = {BACKGROUND AND PURPOSE: Cerebral microbleeds are associated with an increased risk of intracerebral hemorrhage. Recent data suggest that microbleeds may also predict the risk of incident ischemic stroke. However, these results were observed in elderly individuals undertaking various medications and for whom causes of microbleeds and ischemic stroke may differ. We aimed to test the relationship between the presence of microbleeds and incident stroke in CADASIL (Cerebral Autosomal Dominant Arteriopathy With Subcortical Infarcts and Leukoencephalopathy)-a severe monogenic small vessel disease known to be responsible for both highly prevalent microbleeds and a high incidence of ischemic stroke in young patients. METHODS: We assessed microbleeds on baseline MRI in all 378 patients from the Paris-Munich cohort study. Incident ischemic strokes were recorded during 54 months. Survival analyses were used to test the relationship between microbleeds and incident ischemic stroke. RESULTS: Three hundred sixty-nine patients (mean age, 51.4+/-11.4 years) were followed-up during a median time of 39 months (interquartile range, 19 months). The risk of incident ischemic stroke was higher in patients with microbleeds than in patients without (35.8\\% versus 19.6\\%, hazard ratio, 1.87; 95\\% confidence interval, 1.16-3.01; P=0.009). These results persisted after adjustment for history of ischemic stroke, age, sex, vascular risk factors, and antiplatelet agents use (hazard ratio, 1.89; 95\\% confidence interval, 1.10-3.26; P=0.02). CONCLUSIONS: The presence of microbleeds is an independent risk marker of incident ischemic stroke in CADASIL, emphasizing the need to carefully interpret MRI data.},\n\tnumber = {10},\n\tjournal = {Stroke},\n\tauthor = {Puy, L. and De Guio, F. and Godin, O. and Duering, M. and Dichgans, M. and Chabriat, H. and Jouvent, E.},\n\tmonth = oct,\n\tyear = {2017},\n\tpmid = {28842512},\n\tkeywords = {Stroke, Adult, Female, Humans, Male, Middle Aged, Prospective Studies, Incidence, Follow-Up Studies, Magnetic Resonance Imaging, *cadasil, Cerebral Hemorrhage/*diagnostic imaging/epidemiology, Risk Factors, Magnetic Resonance Imaging/methods, *ischemic stroke, cerebral microbleeds, *cerebral microbleeds, *cohort studies, *survival analysis, Brain Ischemia/*diagnostic imaging/epidemiology, CADASIL/*diagnostic imaging/epidemiology, Microvessels/*diagnostic imaging, Stroke/*diagnostic imaging/epidemiology, Cerebral Hemorrhage, Microvessels, CADASIL, Brain Ischemia, cohort studies, ischemic stroke, survival analysis},\n\tpages = {2699--2703},\n}\n\n

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\n \n\n \n \n \n \n \n Resting-State Connectivity of the Left Frontal Cortex to the Default Mode and Dorsal Attention Network Supports Reserve in Mild Cognitive Impairment.\n \n \n \n\n\n \n Franzmeier, N.; Gottler, J.; Grimmer, T.; Drzezga, A.; Araque-Caballero, M. A.; Simon-Vermot, L.; Taylor, A. N. W.; Burger, K.; Catak, C.; Janowitz, D.; Muller, C.; Duering, M.; Sorg, C.; and Ewers, M.\n\n\n \n\n\n\n Front Aging Neurosci, 9: 264. 2017.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{franzmeier_resting-state_2017,\n\ttitle = {Resting-{State} {Connectivity} of the {Left} {Frontal} {Cortex} to the {Default} {Mode} and {Dorsal} {Attention} {Network} {Supports} {Reserve} in {Mild} {Cognitive} {Impairment}},\n\tvolume = {9},\n\tissn = {1663-4365 (Print) 1663-4365 (Linking)},\n\tdoi = {10.3389/fnagi.2017.00264},\n\tabstract = {Reserve refers to the phenomenon of relatively preserved cognition in disproportion to the extent of neuropathology, e.g., in Alzheimer's disease. A putative functional neural substrate underlying reserve is global functional connectivity of the left lateral frontal cortex (LFC, Brodmann Area 6/44). Resting-state fMRI-assessed global LFC-connectivity is associated with protective factors (education) and better maintenance of memory in mild cognitive impairment (MCI). Since the LFC is a hub of the fronto-parietal control network that regulates the activity of other networks, the question arises whether LFC-connectivity to specific networks rather than the whole-brain may underlie reserve. We assessed resting-state fMRI in 24 MCI and 16 healthy controls (HC) and in an independent validation sample (23 MCI/32 HC). Seed-based LFC-connectivity to seven major resting-state networks (i.e., fronto-parietal, limbic, dorsal-attention, somatomotor, default-mode, ventral-attention, visual) was computed, reserve was quantified as residualized memory performance after accounting for age and hippocampal atrophy. In both samples of MCI, LFC-activity was anti-correlated with the default-mode network (DMN), but positively correlated with the dorsal-attention network (DAN). Greater education predicted stronger LFC-DMN-connectivity (anti-correlation) and LFC-DAN-connectivity. Stronger LFC-DMN and LFC-DAN-connectivity each predicted higher reserve, consistently in both MCI samples. No associations were detected for LFC-connectivity to other networks. These novel results extend our previous findings on global functional connectivity of the LFC, showing that LFC-connectivity specifically to the DAN and DMN, two core memory networks, enhances reserve in the memory domain in MCI.},\n\tjournal = {Front Aging Neurosci},\n\tauthor = {Franzmeier, N. and Gottler, J. and Grimmer, T. and Drzezga, A. and Araque-Caballero, M. A. and Simon-Vermot, L. and Taylor, A. N. W. and Burger, K. and Catak, C. and Janowitz, D. and Muller, C. and Duering, M. and Sorg, C. and Ewers, M.},\n\tyear = {2017},\n\tpmcid = {PMC5545597},\n\tpmid = {28824423},\n\tkeywords = {functional connectivity, cognitive reserve, frontoparietal control network, memory, mild cognitive impairment},\n\tpages = {264},\n}\n\n

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\n \n\n \n \n \n \n \n Left Frontal Hub Connectivity during Memory Performance Supports Reserve in Aging and Mild Cognitive Impairment.\n \n \n \n\n\n \n Franzmeier, N.; Hartmann, J. C.; Taylor, A. N. W.; Araque Caballero, M. A.; Simon-Vermot, L.; Buerger, K.; Kambeitz-Ilankovic, L. M.; Ertl-Wagner, B.; Mueller, C.; Catak, C.; Janowitz, D.; Stahl, R.; Dichgans, M.; Duering, M.; and Ewers, M.\n\n\n \n\n\n\n J Alzheimers Dis, 59(4): 1381–1392. 2017.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{franzmeier_left_2017,\n\ttitle = {Left {Frontal} {Hub} {Connectivity} during {Memory} {Performance} {Supports} {Reserve} in {Aging} and {Mild} {Cognitive} {Impairment}},\n\tvolume = {59},\n\tissn = {1875-8908 (Electronic) 1387-2877 (Linking)},\n\tdoi = {10.3233/JAD-170360},\n\tabstract = {Reserve in aging and Alzheimer's disease (AD) is defined as maintaining cognition at a relatively high level in the presence of neurodegeneration, an ability often associated with higher education among other life factors. Recent evidence suggests that higher resting-state functional connectivity within the frontoparietal control network, specifically the left frontal cortex (LFC) hub, contributes to higher reserve. Following up these previous resting-state fMRI findings, we probed memory-task related functional connectivity of the LFC hub as a neural substrate of reserve. In elderly controls (CN, n = 37) and patients with mild cognitive impairment (MCI, n = 17), we assessed global connectivity of the LFC hub during successful face-name association learning, using generalized psychophysiological interaction analyses. Reserve was quantified as residualized memory performance, accounted for gender and proxies of neurodegeneration (age, hippocampus atrophy, and APOE genotype). We found that greater education was associated with higher LFC-connectivity in both CN and MCI during successful memory. Furthermore, higher LFC-connectivity predicted higher residualized memory (i.e., reserve). These results suggest that higher LFC-connectivity contributes to reserve in both healthy and pathological aging.},\n\tnumber = {4},\n\tjournal = {J Alzheimers Dis},\n\tauthor = {Franzmeier, N. and Hartmann, J. C. and Taylor, A. N. W. and Araque Caballero, M. A. and Simon-Vermot, L. and Buerger, K. and Kambeitz-Ilankovic, L. M. and Ertl-Wagner, B. and Mueller, C. and Catak, C. and Janowitz, D. and Stahl, R. and Dichgans, M. and Duering, M. and Ewers, M.},\n\tyear = {2017},\n\tpmcid = {PMC5611800},\n\tpmid = {28731448},\n\tkeywords = {Aged, Female, Humans, Image Processing, Computer-Assisted, Male, Aged, 80 and over, Magnetic Resonance Imaging, Neural Pathways/diagnostic imaging, Memory, Aging, functional connectivity, Aging/*pathology, Brain Mapping, Functional Laterality, Functional Laterality/*physiology, cognitive reserve, memory, mild cognitive impairment, Apolipoproteins E/genetics, Cognitive Dysfunction/diagnostic imaging/genetics/*pathology, education, Face, Frontal Lobe/diagnostic imaging/*pathology, Memory/*physiology, Names, Nerve Net/diagnostic imaging/*pathology, Pattern Recognition, Visual/physiology, Sex Factors, task-fMRI, Frontal Lobe, Cognitive Dysfunction, Neural Pathways, Nerve Net, Apolipoproteins E, Pattern Recognition, Visual},\n\tpages = {1381--1392},\n}\n\n

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\n \n\n \n \n \n \n \n RNA-Seq Identifies Circulating miR-125a-5p, miR-125b-5p, and miR-143-3p as Potential Biomarkers for Acute Ischemic Stroke.\n \n \n \n\n\n \n Tiedt, S.; Prestel, M.; Malik, R.; Schieferdecker, N.; Duering, M.; Kautzky, V.; Stoycheva, I.; Bock, J.; Northoff, B. H.; Klein, M.; Dorn, F.; Krohn, K.; Teupser, D.; Liesz, A.; Plesnila, N.; Holdt, L. M.; and Dichgans, M.\n\n\n \n\n\n\n Circ Res, 121(8): 970–980. September 2017.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{tiedt_rna-seq_2017,\n\ttitle = {{RNA}-{Seq} {Identifies} {Circulating} {miR}-125a-5p, {miR}-125b-5p, and {miR}-143-3p as {Potential} {Biomarkers} for {Acute} {Ischemic} {Stroke}},\n\tvolume = {121},\n\tissn = {1524-4571 (Electronic) 0009-7330 (Linking)},\n\tdoi = {10.1161/CIRCRESAHA.117.311572},\n\tabstract = {RATIONALE: Currently, there are no blood-based biomarkers with clinical utility for acute ischemic stroke (IS). MicroRNAs show promise as disease markers because of their cell type-specific expression patterns and stability in peripheral blood. OBJECTIVE: To identify circulating microRNAs associated with acute IS, determine their temporal course up to 90 days post-stroke, and explore their utility as an early diagnostic marker. METHODS AND RESULTS: We used RNA sequencing to study expression changes of circulating microRNAs in a discovery sample of 20 patients with IS and 20 matched healthy control subjects. We further applied quantitative real-time polymerase chain reaction in independent samples for validation (40 patients with IS and 40 matched controls), replication (200 patients with IS, 100 healthy control subjects), and in 72 patients with transient ischemic attacks. Sampling of patient plasma was done immediately upon hospital arrival. We identified, validated, and replicated 3 differentially expressed microRNAs, which were upregulated in patients with IS compared with both healthy control subjects (miR-125a-5p [1.8-fold; P=1.5x10(-6)], miR-125b-5p [2.5-fold; P=5.6x10(-6)], and miR-143-3p [4.8-fold; P=7.8x10(-9)]) and patients with transient ischemic attack (miR-125a-5p: P=0.003; miR-125b-5p: P=0.003; miR-143-3p: P=0.005). Longitudinal analysis of expression levels up to 90 days after stroke revealed a normalization to control levels for miR-125b-5p and miR-143-3p starting at day 2 while miR-125a-5p remained elevated. Levels of all 3 microRNAs depended on platelet numbers in a platelet spike-in experiment but were unaffected by chemical hypoxia in Neuro2a cells and in experimental stroke models. In a random forest classification, miR-125a-5p, miR-125b-5p, and miR-143-3p differentiated between healthy control subjects and patients with IS with an area under the curve of 0.90 (sensitivity: 85.6\\%; specificity: 76.3\\%), which was superior to multimodal cranial computed tomography obtained for routine diagnostics (sensitivity: 72.5\\%) and previously reported biomarkers of acute IS (neuron-specific enolase: area under the curve=0.69; interleukin 6: area under the curve=0.82). CONCLUSIONS: A set of circulating microRNAs (miR-125a-5p, miR-125b-5p, and miR-143-3p) associates with acute IS and might have clinical utility as an early diagnostic marker.},\n\tnumber = {8},\n\tjournal = {Circ Res},\n\tauthor = {Tiedt, S. and Prestel, M. and Malik, R. and Schieferdecker, N. and Duering, M. and Kautzky, V. and Stoycheva, I. and Bock, J. and Northoff, B. H. and Klein, M. and Dorn, F. and Krohn, K. and Teupser, D. and Liesz, A. and Plesnila, N. and Holdt, L. M. and Dichgans, M.},\n\tmonth = sep,\n\tyear = {2017},\n\tpmid = {28724745},\n\tkeywords = {Stroke, Aged, Female, Humans, Male, Middle Aged, Aged, 80 and over, Prognosis, stroke, Reproducibility of Results, Time Factors, Case-Control Studies, biomarkers, Tomography, X-Ray Computed, *Sequence Analysis, RNA, Area Under Curve, Brain Ischemia/*blood/diagnostic imaging/genetics, Early Diagnosis, Genetic Markers, Interleukin-6/blood, microRNAs, MicroRNAs/*blood/genetics, Phosphopyruvate Hydratase/blood, Predictive Value of Tests, Real-Time Polymerase Chain Reaction, ROC Curve, Stroke/*blood/diagnostic imaging/genetics, Brain Ischemia, Interleukin-6, MicroRNAs, Phosphopyruvate Hydratase, Sequence Analysis, RNA},\n\tpages = {970--980},\n}\n\n

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\n RATIONALE: Currently, there are no blood-based biomarkers with clinical utility for acute ischemic stroke (IS). MicroRNAs show promise as disease markers because of their cell type-specific expression patterns and stability in peripheral blood. OBJECTIVE: To identify circulating microRNAs associated with acute IS, determine their temporal course up to 90 days post-stroke, and explore their utility as an early diagnostic marker. METHODS AND RESULTS: We used RNA sequencing to study expression changes of circulating microRNAs in a discovery sample of 20 patients with IS and 20 matched healthy control subjects. We further applied quantitative real-time polymerase chain reaction in independent samples for validation (40 patients with IS and 40 matched controls), replication (200 patients with IS, 100 healthy control subjects), and in 72 patients with transient ischemic attacks. Sampling of patient plasma was done immediately upon hospital arrival. We identified, validated, and replicated 3 differentially expressed microRNAs, which were upregulated in patients with IS compared with both healthy control subjects (miR-125a-5p [1.8-fold; P=1.5x10(-6)], miR-125b-5p [2.5-fold; P=5.6x10(-6)], and miR-143-3p [4.8-fold; P=7.8x10(-9)]) and patients with transient ischemic attack (miR-125a-5p: P=0.003; miR-125b-5p: P=0.003; miR-143-3p: P=0.005). Longitudinal analysis of expression levels up to 90 days after stroke revealed a normalization to control levels for miR-125b-5p and miR-143-3p starting at day 2 while miR-125a-5p remained elevated. Levels of all 3 microRNAs depended on platelet numbers in a platelet spike-in experiment but were unaffected by chemical hypoxia in Neuro2a cells and in experimental stroke models. In a random forest classification, miR-125a-5p, miR-125b-5p, and miR-143-3p differentiated between healthy control subjects and patients with IS with an area under the curve of 0.90 (sensitivity: 85.6%; specificity: 76.3%), which was superior to multimodal cranial computed tomography obtained for routine diagnostics (sensitivity: 72.5%) and previously reported biomarkers of acute IS (neuron-specific enolase: area under the curve=0.69; interleukin 6: area under the curve=0.82). CONCLUSIONS: A set of circulating microRNAs (miR-125a-5p, miR-125b-5p, and miR-143-3p) associates with acute IS and might have clinical utility as an early diagnostic marker.\n

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\n \n\n \n \n \n \n \n Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy (CADASIL) as a model of small vessel disease: update on clinical, diagnostic, and management aspects.\n \n \n \n\n\n \n Di Donato, I.; Bianchi, S.; De Stefano, N.; Dichgans, M.; Dotti, M. T.; Duering, M.; Jouvent, E.; Korczyn, A. D.; Lesnik-Oberstein, S. A.; Malandrini, A.; Markus, H. S.; Pantoni, L.; Penco, S.; Rufa, A.; Sinanovic, O.; Stojanov, D.; and Federico, A.\n\n\n \n\n\n\n BMC Med, 15(1): 41. February 2017.\n \n\n\n\n
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@article{di_donato_cerebral_2017,\n\ttitle = {Cerebral {Autosomal} {Dominant} {Arteriopathy} with {Subcortical} {Infarcts} and {Leukoencephalopathy} ({CADASIL}) as a model of small vessel disease: update on clinical, diagnostic, and management aspects},\n\tvolume = {15},\n\tissn = {1741-7015 (Electronic) 1741-7015 (Linking)},\n\tdoi = {10.1186/s12916-017-0778-8},\n\tabstract = {Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) is the most common and best known monogenic small vessel disease. Here, we review the clinical, neuroimaging, neuropathological, genetic, and therapeutic aspects based on the most relevant articles published between 1994 and 2016 and on the personal experience of the authors, all directly involved in CADASIL research and care. We conclude with some suggestions that may help in the clinical practice and management of these patients.},\n\tnumber = {1},\n\tjournal = {BMC Med},\n\tauthor = {Di Donato, I. and Bianchi, S. and De Stefano, N. and Dichgans, M. and Dotti, M. T. and Duering, M. and Jouvent, E. and Korczyn, A. D. and Lesnik-Oberstein, S. A. and Malandrini, A. and Markus, H. S. and Pantoni, L. and Penco, S. and Rufa, A. and Sinanovic, O. and Stojanov, D. and Federico, A.},\n\tmonth = feb,\n\tyear = {2017},\n\tpmcid = {PMC5324276},\n\tpmid = {28231783},\n\tkeywords = {Small vessel disease, Humans, *Small vessel disease, *cadasil, *Vascular dementia, *Genetics, *notch 3, CADASIL/*complications, Cerebral Small Vessel Diseases/*etiology/pathology, Vascular dementia, Cerebral Small Vessel Diseases, CADASIL, Genetics, NOTCH 3},\n\tpages = {41},\n}\n\n

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\n \n\n \n \n \n \n \n Left frontal cortex connectivity underlies cognitive reserve in prodromal Alzheimer disease.\n \n \n \n\n\n \n Franzmeier, N.; Duering, M.; Weiner, M.; Dichgans, M.; Ewers, M.; and Alzheimer's Disease Neuroimaging, I.\n\n\n \n\n\n\n Neurology, 88(11): 1054–1061. March 2017.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{franzmeier_left_2017-1,\n\ttitle = {Left frontal cortex connectivity underlies cognitive reserve in prodromal {Alzheimer} disease},\n\tvolume = {88},\n\tissn = {1526-632X (Electronic) 0028-3878 (Linking)},\n\tdoi = {10.1212/WNL.0000000000003711},\n\tabstract = {OBJECTIVE: To test whether higher global functional connectivity of the left frontal cortex (LFC) in Alzheimer disease (AD) is associated with more years of education (a proxy of cognitive reserve [CR]) and mitigates the association between AD-related fluorodeoxyglucose (FDG)-PET hypometabolism and episodic memory. METHODS: Forty-four amyloid-PET-positive patients with amnestic mild cognitive impairment (MCI-Abeta+) and 24 amyloid-PET-negative healthy controls (HC) were included. Voxel-based linear regression analyses were used to test the association between years of education and FDG-PET in MCI-Abeta+, controlled for episodic memory performance. Global LFC (gLFC) connectivity was computed through seed-based resting-state fMRI correlations between the LFC (seed) and each voxel in the gray matter. In linear regression analyses, education as a predictor of gLFC connectivity and the interaction of gLFC connectivity x FDG-PET hypometabolism on episodic memory were tested. RESULTS: FDG-PET metabolism in the precuneus was reduced in MCI-Abeta+ compared to HC (p = 0.028), with stronger reductions observed in MCI-Abeta+ with more years of education (p = 0.006). In MCI-Abeta+, higher gLFC connectivity was associated with more years of education (p = 0.021). At higher levels of gLFC connectivity, the association between precuneus FDG-PET hypometabolism and lower memory performance was attenuated (p = 0.027). CONCLUSIONS: Higher gLFC connectivity is a functional substrate of CR that helps to maintain episodic memory relatively well in the face of emerging FDG-PET hypometabolism in early-stage AD.},\n\tnumber = {11},\n\tjournal = {Neurology},\n\tauthor = {Franzmeier, N. and Duering, M. and Weiner, M. and Dichgans, M. and Ewers, M. and Alzheimer's Disease Neuroimaging, Initiative},\n\tmonth = mar,\n\tyear = {2017},\n\tpmcid = {PMC5384837},\n\tpmid = {28188306},\n\tkeywords = {Female, Humans, Male, Magnetic Resonance Imaging, Nerve Net/*pathology, Oxygen/blood, Neuropsychological Tests, Cognition Disorders/*etiology, Functional Laterality, Functional Laterality/*physiology, Alzheimer Disease/*complications/diagnostic imaging/*pathology, Chi-Square Distribution, Cognitive Reserve/*physiology, Epilepsy/diagnostic imaging/etiology, Fluorodeoxyglucose F18/metabolism, Frontal Lobe/diagnostic imaging/pathology, Positron-Emission Tomography, Prodromal Symptoms, Fluorodeoxyglucose F18, Cognition Disorders, Alzheimer Disease, Epilepsy, Frontal Lobe, Nerve Net, Cognitive Reserve, Oxygen},\n\tpages = {1054--1061},\n}\n\n

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\n \n\n \n \n \n \n \n Predictors and Clinical Impact of Incident Lacunes in Cerebral Autosomal Dominant Arteriopathy With Subcortical Infarcts and Leukoencephalopathy.\n \n \n \n\n\n \n Ling, Y.; De Guio, F.; Duering, M.; Jouvent, E.; Herve, D.; Godin, O.; Dichgans, M.; and Chabriat, H.\n\n\n \n\n\n\n Stroke, 48(2): 283–289. February 2017.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{ling_predictors_2017,\n\ttitle = {Predictors and {Clinical} {Impact} of {Incident} {Lacunes} in {Cerebral} {Autosomal} {Dominant} {Arteriopathy} {With} {Subcortical} {Infarcts} and {Leukoencephalopathy}},\n\tvolume = {48},\n\tissn = {1524-4628 (Electronic) 0039-2499 (Linking)},\n\tdoi = {10.1161/STROKEAHA.116.015750},\n\tabstract = {BACKGROUND AND PURPOSE: Previous studies in cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy showed that accumulation of lacunes strongly relate to clinical severity. However, the potential predictors of incident lacunes and their clinical consequences over a short time frame have not been investigated. This study aimed to determine the predictors and clinical impact of such lesions in a large cohort of patients. METHODS: Two hundred and six NOTCH3 mutation carriers (mean age, 49.5+/-10.6 years) were followed up over 3 years. Incident lacunes were identified using difference imaging from 3-dimensional T1 images. Clinical events and change in different clinical scores such as the Mattis Dementia Rating Scale, Modified Rankin Scale, Barthel index, and time to complete part A and part B of Trail Making Test were recorded. Associations were analyzed with multivariable logistic regression analysis and ANCOVA. RESULTS: Over a mean period of 3.4+/-0.7 years, incident lacunes occurred in 51 of 206 patients. Both the number of lacunes (P{\\textless}0.0001) and systolic blood pressure at baseline (P{\\textless}0.01) were independent predictors of incident lacunes during follow-up. The results were still significant after excluding patients with systolic blood pressure {\\textgreater}140 mm Hg. Incident lacunes were also associated with incident stroke and with change in time to complete Trail Making Test part B, initiation/perseveration subscale of the Mattis Dementia Rating Scale and Barthel Index over the study period. CONCLUSIONS: Systolic blood pressure and the number of prevalent lacunes are independent predictors of incident lacunes in cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy. These lesions mainly impact executive performances and functional independence over 3 years.},\n\tnumber = {2},\n\tjournal = {Stroke},\n\tauthor = {Ling, Y. and De Guio, F. and Duering, M. and Jouvent, E. and Herve, D. and Godin, O. and Dichgans, M. and Chabriat, H.},\n\tmonth = feb,\n\tyear = {2017},\n\tpmid = {28034964},\n\tkeywords = {Adult, Female, Humans, Male, Middle Aged, cerebral small vessel disease, *cerebral small vessel disease, Prospective Studies, *stroke, Incidence, Follow-Up Studies, Magnetic Resonance Imaging, stroke, *cadasil, *magnetic resonance imaging, magnetic resonance imaging, Predictive Value of Tests, *risk factor, CADASIL/*diagnostic imaging/*epidemiology, Stroke, Lacunar/*diagnostic imaging/*epidemiology, CADASIL, Stroke, Lacunar, risk factor},\n\tpages = {283--289},\n}\n\n

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\n \n\n \n \n \n \n \n Lower Magnetization Transfer Ratio in the Forceps Minor Is Associated with Poorer Gait Velocity in Older Adults.\n \n \n \n\n\n \n Seiler, S.; Pirpamer, L.; Gesierich, B.; Hofer, E.; Duering, M.; Pinter, D.; Jouvent, E.; Fazekas, F.; Mangin, J. F.; Chabriat, H.; Ropele, S.; and Schmidt, R.\n\n\n \n\n\n\n AJNR Am J Neuroradiol, 38(3): 500–506. March 2017.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{seiler_lower_2017,\n\ttitle = {Lower {Magnetization} {Transfer} {Ratio} in the {Forceps} {Minor} {Is} {Associated} with {Poorer} {Gait} {Velocity} in {Older} {Adults}},\n\tvolume = {38},\n\tissn = {1936-959X (Electronic) 0195-6108 (Linking)},\n\tdoi = {10.3174/ajnr.A5036},\n\tabstract = {BACKGROUND AND PURPOSE: Gait disturbances in the elderly are disabling and a major public health issue but are poorly understood. In this multimodal MR imaging study, we used 2 voxel-based analysis methods to assess the voxelwise relationship of magnetization transfer ratio and white matter hyperintensity location with gait velocity in older adults. MATERIALS AND METHODS: We assessed 230 community-dwelling participants of the Austrian Stroke Prevention Family Study. Every participant underwent 3T MR imaging, including magnetization transfer imaging. Voxel-based magnetization transfer ratio-symptom mapping correlated the white matter magnetization transfer ratio of each voxel with gait velocity. To assess a possible relationship between white matter hyperintensity location and gait velocity, we applied voxel-based lesion-symptom mapping. RESULTS: We found a significant association between the magnetization transfer ratio within the forceps minor and gait velocity (beta = 0.134; 95\\% CI, 0.011-0.258; P = .033), independent of demographics, general physical performance, vascular risk factors, and brain volume. White matter hyperintensities did not significantly change this association. CONCLUSIONS: Our study provides new evidence for the importance of magnetization transfer ratio changes in gait disturbances at an older age, particularly in the forceps minor. The histopathologic basis of these findings is yet to be determined.},\n\tnumber = {3},\n\tjournal = {AJNR Am J Neuroradiol},\n\tauthor = {Seiler, S. and Pirpamer, L. and Gesierich, B. and Hofer, E. and Duering, M. and Pinter, D. and Jouvent, E. and Fazekas, F. and Mangin, J. F. and Chabriat, H. and Ropele, S. and Schmidt, R.},\n\tmonth = mar,\n\tyear = {2017},\n\tpmid = {27979793},\n\tpmcid = {PMC7959982},\n\tkeywords = {Adult, Aged, Female, Humans, Male, Middle Aged, Magnetic Resonance Imaging, Magnetic Resonance Imaging/methods, Brain/diagnostic imaging/*pathology, Gait Disorders, Neurologic/diagnostic imaging/*pathology, Gait/physiology, Brain, Gait Disorders, Neurologic, Gait},\n\tpages = {500--506},\n}\n\n

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\n \n\n \n \n \n \n \n Resting-state global functional connectivity as a biomarker of cognitive reserve in mild cognitive impairment.\n \n \n \n\n\n \n Franzmeier, N.; Caballero, M. A. A.; Taylor, A. N. W.; Simon-Vermot, L.; Buerger, K.; Ertl-Wagner, B.; Mueller, C.; Catak, C.; Janowitz, D.; Baykara, E.; Gesierich, B.; Duering, M.; Ewers, M.; and Alzheimer's Disease Neuroimaging, I.\n\n\n \n\n\n\n Brain Imaging Behav, 11(2): 368–382. April 2017.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{franzmeier_resting-state_2017-1,\n\ttitle = {Resting-state global functional connectivity as a biomarker of cognitive reserve in mild cognitive impairment},\n\tvolume = {11},\n\tissn = {1931-7565 (Electronic) 1931-7557 (Linking)},\n\tdoi = {10.1007/s11682-016-9599-1},\n\tabstract = {Cognitive reserve (CR) shows protective effects in Alzheimer's disease (AD) and reduces the risk of dementia. Despite the clinical significance of CR, a clinically useful diagnostic biomarker of brain changes underlying CR in AD is not available yet. Our aim was to develop a fully-automated approach applied to fMRI to produce a biomarker associated with CR in subjects at increased risk of AD. We computed resting-state global functional connectivity (GFC), i.e. the average connectivity strength, for each voxel within the cognitive control network, which may sustain CR due to its central role in higher cognitive function. In a training sample including 43 mild cognitive impairment (MCI) subjects and 24 healthy controls (HC), we found that MCI subjects with high CR ({\\textgreater} median of years of education, CR+) showed increased frequency of high GFC values compared to MCI-CR- and HC. A summary index capturing such a surplus frequency of high GFC was computed (called GFC reserve (GFC-R) index). GFC-R discriminated MCI-CR+ vs. MCI-CR-, with the area under the ROC = 0.84. Cross-validation in an independently recruited test sample of 23 MCI subjects showed that higher levels of the GFC-R index predicted higher years of education and an alternative questionnaire-based proxy of CR, controlled for memory performance, gray matter of the cognitive control network, white matter hyperintensities, age, and gender. In conclusion, the GFC-R index that captures GFC changes within the cognitive control network provides a biomarker candidate of functional brain changes of CR in patients at increased risk of AD.},\n\tnumber = {2},\n\tjournal = {Brain Imaging Behav},\n\tauthor = {Franzmeier, N. and Caballero, M. A. A. and Taylor, A. N. W. and Simon-Vermot, L. and Buerger, K. and Ertl-Wagner, B. and Mueller, C. and Catak, C. and Janowitz, D. and Baykara, E. and Gesierich, B. and Duering, M. and Ewers, M. and Alzheimer's Disease Neuroimaging, Initiative},\n\tmonth = apr,\n\tyear = {2017},\n\tpmid = {27709513},\n\tkeywords = {Aged, Female, Humans, Male, *Alzheimer's disease, Magnetic Resonance Imaging, Biomarkers, Reproducibility of Results, *Cognitive Reserve, Magnetic Resonance Imaging/methods, Sensitivity and Specificity, Brain Mapping/methods, Brain Mapping, *Biomarker, *Global functional connectivity, *Mild cognitive impairment, *Resting-state fMRI, Cerebral Cortex/*physiopathology, Cognitive Dysfunction/*diagnostic imaging/*physiopathology, Connectome/*methods, Image Interpretation, Computer-Assisted/*methods, Nerve Net/physiopathology, Neural Pathways/physiopathology, Reference Values, Rest, Resting-state fMRI, Image Interpretation, Computer-Assisted, Alzheimer’s disease, Cerebral Cortex, Cognitive Dysfunction, Neural Pathways, Biomarker, Mild cognitive impairment, Nerve Net, Cognitive Reserve, Cognitive reserve, Connectome, Global functional connectivity},\n\tpages = {368--382},\n}\n\n

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\n \n\n \n \n \n \n \n Tract-specific white matter hyperintensities disrupt neural network function in Alzheimer's disease.\n \n \n \n\n\n \n Taylor, A. N. W.; Kambeitz-Ilankovic, L.; Gesierich, B.; Simon-Vermot, L.; Franzmeier, N.; Araque Caballero, M. A.; Muller, S.; Hesheng, L.; Ertl-Wagner, B.; Burger, K.; Weiner, M. W.; Dichgans, M.; Duering, M.; Ewers, M.; and Alzheimer's Disease Neuroimaging, I.\n\n\n \n\n\n\n Alzheimers Dement, 13(3): 225–235. March 2017.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{taylor_tract-specific_2017,\n\ttitle = {Tract-specific white matter hyperintensities disrupt neural network function in {Alzheimer}'s disease},\n\tvolume = {13},\n\tissn = {1552-5279 (Electronic) 1552-5260 (Linking)},\n\tdoi = {10.1016/j.jalz.2016.06.2358},\n\tabstract = {INTRODUCTION: White matter hyperintensities (WMHs) increase the risk of Alzheimer's disease (AD). Whether WMHs are associated with the decline of functional neural networks in AD is debated. METHOD: Resting-state functional magnetic resonance imaging and WMH were assessed in 78 subjects with increased amyloid levels on AV-45 positron emission tomography (PET) in different clinical stages of AD. We tested the association between WMH volume in major atlas-based fiber tract regions of interest (ROIs) and changes in functional connectivity (FC) between the tracts' projection areas within the default mode network (DMN). RESULTS: WMH volume within the inferior fronto-occipital fasciculus (IFOF) was the highest among all tract ROIs and associated with reduced FC in IFOF-connected DMN areas, independently of global AV-45 PET. Higher AV-45 PET contributed to reduced FC in IFOF-connected, temporal, and parietal DMN areas. CONCLUSIONS: High fiber tract WMH burden is associated with reduced FC in connected areas, thus adding to the effects of amyloid pathology on neuronal network function.},\n\tnumber = {3},\n\tjournal = {Alzheimers Dement},\n\tauthor = {Taylor, A. N. W. and Kambeitz-Ilankovic, L. and Gesierich, B. and Simon-Vermot, L. and Franzmeier, N. and Araque Caballero, M. A. and Muller, S. and Hesheng, L. and Ertl-Wagner, B. and Burger, K. and Weiner, M. W. and Dichgans, M. and Duering, M. and Ewers, M. and Alzheimer's Disease Neuroimaging, Initiative},\n\tmonth = mar,\n\tyear = {2017},\n\tpmcid = {PMC5319922},\n\tpmid = {27432800},\n\tkeywords = {Aged, Female, Humans, Image Processing, Computer-Assisted, Male, Alzheimer's disease, White Matter/diagnostic imaging/*pathology, Aged, 80 and over, Magnetic Resonance Imaging, White matter hyperintensities, Neuropsychological Tests, *Brain Mapping, Brain Mapping, Nerve Net/diagnostic imaging/*pathology, Positron-Emission Tomography, Alzheimer Disease/diagnostic imaging/*pathology/*physiopathology, Amyloid-beta, Fiber tract, Functional connectivity, Resting-state fMRI, Vascular, White Matter, Alzheimer Disease, Nerve Net},\n\tpages = {225--235},\n}\n\n

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\n \n\n \n \n \n \n \n A Novel Imaging Marker for Small Vessel Disease Based on Skeletonization of White Matter Tracts and Diffusion Histograms.\n \n \n \n\n\n \n Baykara, E.; Gesierich, B.; Adam, R.; Tuladhar, A. M.; Biesbroek, J. M.; Koek, H. L.; Ropele, S.; Jouvent, E.; Alzheimer's Disease Neuroimaging, I.; Chabriat, H.; Ertl-Wagner, B.; Ewers, M.; Schmidt, R.; de Leeuw, F. E.; Biessels, G. J.; Dichgans, M.; and Duering, M.\n\n\n \n\n\n\n Ann Neurol, 80(4): 581–92. October 2016.\n \n\n\n\n
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@article{baykara_novel_2016,\n\ttitle = {A {Novel} {Imaging} {Marker} for {Small} {Vessel} {Disease} {Based} on {Skeletonization} of {White} {Matter} {Tracts} and {Diffusion} {Histograms}},\n\tvolume = {80},\n\tissn = {1531-8249 (Electronic) 0364-5134 (Linking)},\n\tdoi = {10.1002/ana.24758},\n\tabstract = {OBJECTIVE: To establish a fully automated, robust imaging marker for cerebral small vessel disease (SVD) and related cognitive impairment that is easy to implement, reflects disease burden, and is strongly associated with processing speed, the predominantly affected cognitive domain in SVD. METHODS: We developed a novel magnetic resonance imaging marker based on diffusion tensor imaging, skeletonization of white matter tracts, and histogram analysis. The marker (peak width of skeletonized mean diffusivity [PSMD]) was assessed along with conventional SVD imaging markers. We first evaluated associations with processing speed in patients with genetically defined SVD (n = 113). Next, we validated our findings in independent samples of inherited SVD (n = 57), sporadic SVD (n = 444), and memory clinic patients with SVD (n = 105). The new marker was further applied to healthy controls (n = 241) and to patients with Alzheimer's disease (n = 153). We further conducted a longitudinal analysis and interscanner reproducibility study. RESULTS: PSMD was associated with processing speed in all study samples with SVD (p-values between 2.8 x 10(-3) and 1.8 x 10(-10) ). PSMD explained most of the variance in processing speed (R(2) ranging from 8.8\\% to 46\\%) and consistently outperformed conventional imaging markers (white matter hyperintensity volume, lacune volume, and brain volume) in multiple regression analyses. Increases in PSMD were linked to vascular but not to neurodegenerative disease. In longitudinal analysis, PSMD captured SVD progression better than other imaging markers. INTERPRETATION: PSMD is a new, fully automated, and robust imaging marker for SVD. PSMD can easily be applied to large samples and may be of great utility for both research studies and clinical use. Ann Neurol 2016;80:581-592.},\n\tnumber = {4},\n\tjournal = {Ann Neurol},\n\tauthor = {Baykara, E. and Gesierich, B. and Adam, R. and Tuladhar, A. M. and Biesbroek, J. M. and Koek, H. L. and Ropele, S. and Jouvent, E. and Alzheimer's Disease Neuroimaging, Initiative and Chabriat, H. and Ertl-Wagner, B. and Ewers, M. and Schmidt, R. and de Leeuw, F. E. and Biessels, G. J. and Dichgans, M. and Duering, M.},\n\tmonth = oct,\n\tyear = {2016},\n\tpmid = {27518166},\n\tkeywords = {Adult, Aged, Diffusion Tensor Imaging, Female, Humans, Male, Middle Aged, Aged, 80 and over, Biomarkers, Alzheimer Disease/*diagnostic imaging, Young Adult, Cerebral Small Vessel Diseases/complications/*diagnostic imaging, Cognitive Dysfunction/*diagnostic imaging/etiology/physiopathology, Diffusion Tensor Imaging/*methods/standards, Reproducibility of Results, White Matter/*diagnostic imaging, White Matter, Alzheimer Disease, Cerebral Small Vessel Diseases, Cognitive Dysfunction},\n\tpages = {581--92},\n}\n\n

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\n \n\n \n \n \n \n \n Features and Determinants of Lacune Shape: Relationship With Fiber Tracts and Perforating Arteries.\n \n \n \n\n\n \n Gesierich, B.; Duchesnay, E.; Jouvent, E.; Chabriat, H.; Schmidt, R.; Mangin, J. F.; Duering, M.; and Dichgans, M.\n\n\n \n\n\n\n Stroke, 47(5): 1258–64. May 2016.\n \n\n\n\n
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@article{gesierich_features_2016,\n\ttitle = {Features and {Determinants} of {Lacune} {Shape}: {Relationship} {With} {Fiber} {Tracts} and {Perforating} {Arteries}},\n\tvolume = {47},\n\tissn = {1524-4628 (Electronic) 0039-2499 (Linking)},\n\tdoi = {10.1161/STROKEAHA.116.012779},\n\tabstract = {BACKGROUND AND PURPOSE: Lacunes are a major manifestation of cerebral small vessel disease. Although still debated, the morphological features of lacunes may offer mechanistic insights. We systematically analyzed the shape of incident lacunes in cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy, a genetically defined small vessel disease. METHODS: A total of 88 incident lacunes from 57 patients were segmented from 3-dimensional T1 magnetic resonance images and 3 dimensionally reconstructed. Anatomic location, diameter, volume, surface area, and compactness of lacunes were assessed. The shape was analyzed using a size, orientation, and position invariant spectral shape descriptor. We further investigated the relationship with perforating arteries and fiber tracts. RESULTS: Lacunes were most abundant in the centrum semiovale and the basal ganglia. Diameter, volume, and surface area of lacunes in the basal ganglia and centrum semiovale were larger than in other brain regions. The spectral shape descriptor revealed a continuum of shapes with no evidence for distinct classes of lacunes. Shapes varied mostly in elongation and planarity. The main axis and plane of lacunes were found to align with the orientation of perforating arteries but not with fiber tracts. CONCLUSIONS: Elongation and planarity are the primary shape principles of lacunes. Their main axis and plane align with perforating arteries. Our findings add to current concepts on the mechanisms of lacunes.},\n\tnumber = {5},\n\tjournal = {Stroke},\n\tauthor = {Gesierich, B. and Duchesnay, E. and Jouvent, E. and Chabriat, H. and Schmidt, R. and Mangin, J. F. and Duering, M. and Dichgans, M.},\n\tmonth = may,\n\tyear = {2016},\n\tpmid = {27048698},\n\tkeywords = {Adult, Aged, Female, Humans, Male, Middle Aged, Magnetic Resonance Imaging, *cadasil, *cerebral small vessel diseases, *magnetic resonance imaging, White Matter/*diagnostic imaging, *neuroimaging, Aftercare, Basal Ganglia/*diagnostic imaging, CADASIL/*diagnostic imaging, neuroimaging, magnetic resonance imaging, cerebral small vessel diseases, White Matter, CADASIL, Basal Ganglia},\n\tpages = {1258--64},\n}\n\n

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\n \n\n \n \n \n \n \n APOE varepsilon2 is associated with white matter hyperintensity volume in CADASIL.\n \n \n \n\n\n \n Gesierich, B.; Opherk, C.; Rosand, J.; Gonik, M.; Malik, R.; Jouvent, E.; Herve, D.; Adib-Samii, P.; Bevan, S.; Pianese, L.; Silvestri, S.; Dotti, M. T.; De Stefano, N.; van der Grond, J.; Boon, E. M.; Pescini, F.; Rost, N.; Pantoni, L.; Oberstein, S. A.; Federico, A.; Ragno, M.; Markus, H. S.; Tournier-Lasserve, E.; Chabriat, H.; Dichgans, M.; Duering, M.; and Ewers, M.\n\n\n \n\n\n\n J Cereb Blood Flow Metab, 36(1): 199–203. January 2016.\n \n\n\n\n
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@article{gesierich_apoe_2016,\n\ttitle = {{APOE} varepsilon2 is associated with white matter hyperintensity volume in {CADASIL}},\n\tvolume = {36},\n\tissn = {1559-7016 (Electronic) 0271-678X (Linking)},\n\tdoi = {10.1038/jcbfm.2015.85},\n\tabstract = {Apolipoprotein E (APOE) increases the risk for Alzheimer's disease (varepsilon4 allele) and cerebral amyloid angiopathy (varepsilon2 and varepsilon4), but its role in small vessel disease (SVD) is debated. Here we studied the effects of APOE on white matter hyperintensity volume (WMHV) in CADASIL (cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy), a nonamyloidogenic angiopathy and inherited early-onset form of pure SVD. Four hundred and eighty-eight subjects were recruited through a multicenter consortium. Compared with APOE varepsilon3/varepsilon3, WMHV was increased in APOE varepsilon2 (P = 0.02) but not APOE varepsilon4. The results remained significant when controlled for genome-wide genetic background variation. Our findings suggest a modifying influence of APOE varepsilon2 on WMHV caused by pure SVD.},\n\tnumber = {1},\n\tjournal = {J Cereb Blood Flow Metab},\n\tauthor = {Gesierich, B. and Opherk, C. and Rosand, J. and Gonik, M. and Malik, R. and Jouvent, E. and Herve, D. and Adib-Samii, P. and Bevan, S. and Pianese, L. and Silvestri, S. and Dotti, M. T. and De Stefano, N. and van der Grond, J. and Boon, E. M. and Pescini, F. and Rost, N. and Pantoni, L. and Oberstein, S. A. and Federico, A. and Ragno, M. and Markus, H. S. and Tournier-Lasserve, E. and Chabriat, H. and Dichgans, M. and Duering, M. and Ewers, M.},\n\tmonth = jan,\n\tyear = {2016},\n\tpmcid = {PMC4758562},\n\tpmid = {25920955},\n\tkeywords = {Adult, Female, Humans, Male, Middle Aged, Magnetic Resonance Imaging, *Alleles, *Polymorphism, Single Nucleotide, Apolipoprotein E2/genetics/*metabolism, CADASIL/genetics/*metabolism/pathology, Gene Frequency/genetics, Genome-Wide Association Study, Genotype, Protein Isoforms, Regression Analysis, Risk Factors, White Matter/*pathology, White Matter, CADASIL, Polymorphism, Single Nucleotide, Alleles, Apolipoprotein E2, Gene Frequency},\n\tpages = {199--203},\n}\n\n

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\n \n\n \n \n \n \n \n The Primacy Effect in Amnestic Mild Cognitive Impairment: Associations with Hippocampal Functional Connectivity.\n \n \n \n\n\n \n Brueggen, K.; Kasper, E.; Dyrba, M.; Bruno, D.; Pomara, N.; Ewers, M.; Duering, M.; Burger, K.; and Teipel, S. J.\n\n\n \n\n\n\n Front Aging Neurosci, 8: 244. 2016.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{brueggen_primacy_2016,\n\ttitle = {The {Primacy} {Effect} in {Amnestic} {Mild} {Cognitive} {Impairment}: {Associations} with {Hippocampal} {Functional} {Connectivity}},\n\tvolume = {8},\n\tissn = {1663-4365 (Print) 1663-4365 (Linking)},\n\tdoi = {10.3389/fnagi.2016.00244},\n\tabstract = {Background: The "primacy effect," i.e., increased memory recall for the first items of a series compared to the following items, is reduced in amnestic mild cognitive impairment (aMCI). Memory task-fMRI studies demonstrated that primacy recall is associated with higher activation of the hippocampus and temporo-parietal and frontal cortical regions in healthy subjects. Functional magnetic resonance imaging (fMRI) at resting state revealed that hippocampus functional connectivity (FC) with neocortical brain areas, including regions of the default mode network (DMN), is altered in aMCI. The present study aimed to investigate whether resting state fMRI FC between the hippocampus and cortical brain regions, especially the DMN, is associated with primacy recall performance in aMCI. Methods: A number of 87 aMCI patients underwent resting state fMRI and verbal episodic memory assessment. FC between the left or right hippocampus, respectively, and all other voxels in gray matter was mapped voxel-wise and used in whole-brain regression analyses, testing whether FC values predicted delayed primacy recall score. The delayed primacy score was defined as the number of the first four words recalled on the California Verbal Learning Test. Additionally, a partial least squares (PLS) analysis was performed, using DMN regions as seeds to identify the association of their functional interactions with delayed primacy recall. Results: Voxel-based analyses indicated that delayed primacy recall was mainly (positively) associated with higher FC between the left and right hippocampus. Additionally, significant associations were found for higher FC between the left hippocampus and bilateral temporal cortex, frontal cortical regions, and for higher FC between the right hippocampus and right temporal cortex, right frontal cortical regions, left medial frontal cortex and right amygdala (p {\\textless} 0.01, uncorr.). PLS analysis revealed positive associations of delayed primacy recall with FC between regions of the DMN, including the left and right hippocampus, as well as middle cingulate cortex and thalamus (p {\\textless} 0.04). In conclusion, in the light of decreased hippocampus function in aMCI, inter-hemispheric hippocampus FC and hippocampal FC with brain regions predominantly included in the DMN may contribute to residual primacy recall in aMCI.},\n\tjournal = {Front Aging Neurosci},\n\tauthor = {Brueggen, K. and Kasper, E. and Dyrba, M. and Bruno, D. and Pomara, N. and Ewers, M. and Duering, M. and Burger, K. and Teipel, S. J.},\n\tyear = {2016},\n\tpmcid = {PMC5073133},\n\tpmid = {27818633},\n\tkeywords = {functional connectivity, Alzheimer's disease (AD), default mode network, hippocampus, mild cognitive impairment (MCI), primacy effect},\n\tpages = {244},\n}\n\n

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\n Background: The \"primacy effect,\" i.e., increased memory recall for the first items of a series compared to the following items, is reduced in amnestic mild cognitive impairment (aMCI). Memory task-fMRI studies demonstrated that primacy recall is associated with higher activation of the hippocampus and temporo-parietal and frontal cortical regions in healthy subjects. Functional magnetic resonance imaging (fMRI) at resting state revealed that hippocampus functional connectivity (FC) with neocortical brain areas, including regions of the default mode network (DMN), is altered in aMCI. The present study aimed to investigate whether resting state fMRI FC between the hippocampus and cortical brain regions, especially the DMN, is associated with primacy recall performance in aMCI. Methods: A number of 87 aMCI patients underwent resting state fMRI and verbal episodic memory assessment. FC between the left or right hippocampus, respectively, and all other voxels in gray matter was mapped voxel-wise and used in whole-brain regression analyses, testing whether FC values predicted delayed primacy recall score. The delayed primacy score was defined as the number of the first four words recalled on the California Verbal Learning Test. Additionally, a partial least squares (PLS) analysis was performed, using DMN regions as seeds to identify the association of their functional interactions with delayed primacy recall. Results: Voxel-based analyses indicated that delayed primacy recall was mainly (positively) associated with higher FC between the left and right hippocampus. Additionally, significant associations were found for higher FC between the left hippocampus and bilateral temporal cortex, frontal cortical regions, and for higher FC between the right hippocampus and right temporal cortex, right frontal cortical regions, left medial frontal cortex and right amygdala (p \\textless 0.01, uncorr.). PLS analysis revealed positive associations of delayed primacy recall with FC between regions of the DMN, including the left and right hippocampus, as well as middle cingulate cortex and thalamus (p \\textless 0.04). In conclusion, in the light of decreased hippocampus function in aMCI, inter-hemispheric hippocampus FC and hippocampal FC with brain regions predominantly included in the DMN may contribute to residual primacy recall in aMCI.\n

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\n \n\n \n \n \n \n \n Prediction of 3-year clinical course in CADASIL.\n \n \n \n\n\n \n Jouvent, E.; Duchesnay, E.; Hadj-Selem, F.; De Guio, F.; Mangin, J. F.; Herve, D.; Duering, M.; Ropele, S.; Schmidt, R.; Dichgans, M.; and Chabriat, H.\n\n\n \n\n\n\n Neurology, 87(17): 1787–1795. October 2016.\n \n\n\n\n
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@article{jouvent_prediction_2016,\n\ttitle = {Prediction of 3-year clinical course in {CADASIL}},\n\tvolume = {87},\n\tissn = {1526-632X (Electronic) 0028-3878 (Linking)},\n\tdoi = {10.1212/WNL.0000000000003252},\n\tabstract = {OBJECTIVE: To obtain simple models predicting disease evolution at 3 years for a given patient with cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL). METHODS: Based on data obtained in a prospective study of 236 patients, we built and validated models predicting, at the individual level, 3-year changes in Mini-Mental State Examination (MMSE), Mattis Dementia Rating Scale (MDRS), Trail Making Test version B (TMTB), and modified Rankin Scale (mRS). These models were based on different sets of predictors obtained at baseline, including either clinical data (epidemiologic data and cardiovascular risk factors) or clinical data and quantitative MRI markers (volume of lacunes [LLV], volume of white matter hyperintensities, normalized brain volume [BPF], number of microbleeds). The Bayesian information criterion (BIC) and the coefficient of determination (R(2)) were used to determine models with the highest predictive ability and the lowest numbers of predictors. RESULTS: We obtained validated models with a demonstrated ability to predict, for a given patient, 3-year changes in MMSE, MDRS, TMTB, and mRS (R(2) on independent samples: 0.22, 0.12, 0.09, and 0.17, respectively). In all cases, the best models according to R(2) and BIC values included only the baseline values of the outcome, of BPF, and of LLV. Inclusion of other potential predictors always led to a loss of generalizability. CONCLUSIONS: The prediction of 3-year changes in MMSE, MDRS, TMTB, and mRS for a given patient with CADASIL can be obtained using simple models relying only on the initial values of the considered score, BPF, and LLV.},\n\tnumber = {17},\n\tjournal = {Neurology},\n\tauthor = {Jouvent, E. and Duchesnay, E. and Hadj-Selem, F. and De Guio, F. and Mangin, J. F. and Herve, D. and Duering, M. and Ropele, S. and Schmidt, R. and Dichgans, M. and Chabriat, H.},\n\tmonth = oct,\n\tyear = {2016},\n\tpmcid = {PMC5089530},\n\tpmid = {27694265},\n\tkeywords = {Adult, Aged, Disease Progression, Female, Humans, Male, Middle Aged, Magnetic Resonance Imaging, Young Adult, Bayes Theorem, Neuropsychological Tests, Linear Models, Predictive Value of Tests, *Bayes Theorem, *Disease Progression, *Linear Models, CADASIL/*diagnosis/genetics/*physiopathology, France, Germany, Longitudinal Studies, Mental Status Schedule, Retrospective Studies, Severity of Illness Index, CADASIL},\n\tpages = {1787--1795},\n}\n\n

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\n \n\n \n \n \n \n \n Prevalence of Amyloid Positron Emission Tomographic Positivity in Poststroke Mild Cognitive Impairment.\n \n \n \n\n\n \n Wollenweber, F. A.; Darr, S.; Muller, C.; Duering, M.; Buerger, K.; Zietemann, V.; Malik, R.; Brendel, M.; Ertl-Wagner, B.; Bartenstein, P.; Rominger, A.; and Dichgans, M.\n\n\n \n\n\n\n Stroke, 47(10): 2645–8. October 2016.\n \n\n\n\n
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@article{wollenweber_prevalence_2016,\n\ttitle = {Prevalence of {Amyloid} {Positron} {Emission} {Tomographic} {Positivity} in {Poststroke} {Mild} {Cognitive} {Impairment}},\n\tvolume = {47},\n\tissn = {1524-4628 (Electronic) 0039-2499 (Linking)},\n\tdoi = {10.1161/STROKEAHA.116.013778},\n\tabstract = {BACKGROUND AND PURPOSE: Mild cognitive impairment (MCI) is common after stroke and associated with poor outcome. However, the mechanisms underlying poststroke MCI (PS-MCI) are insufficiently understood. We performed amyloid-beta positron emission tomography (PET) in a prospective cohort of stroke survivors to determine the role of amyloid pathology in PS-MCI. METHODS: We studied 178 consecutive patients enrolled into the prospective DEDEMAS study (Determinants of Dementia After Stroke). Follow-up visits 6 months post stroke included detailed cognitive testing, standardized magnetic resonance imaging, and amyloid-beta imaging using flutemetamol ((18)F) PET. MCI was defined by the modified Petersen criteria. Amyloid-positivity was assessed visually and quantitatively. Fifty-six (31\\%) patients agreed to undergo PET imaging. RESULTS: Thirty-eight (68\\%) patients who consented to PET imaging had PS-MCI. Visual assessment revealed amyloid PET positivity in 2 (5\\%) of the 38 PS-MCI patients and in 2 (11\\%) of the 18 cognitively healthy stroke survivors. There was no correlation between flutemetamol ((18)F) standardized uptake value ratios and cognitive scores in the 56 patients. PS-MCI patients had significant cognitive impairments on executive function (P{\\textless}0.01) and memory tests (P{\\textless}0.01) when compared with cognitively healthy stroke survivors (P{\\textless}0.01). CONCLUSIONS: The prevalence of amyloid-pathology in patients with PS-MCI is not increased when compared with cognitively healthy stroke survivors and to recent estimates for cognitively healthy elderly subjects. Factors other than amyloid-pathology likely contribute to the development of PS-MCI. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier: NCT01334749.},\n\tnumber = {10},\n\tjournal = {Stroke},\n\tauthor = {Wollenweber, F. A. and Darr, S. and Muller, C. and Duering, M. and Buerger, K. and Zietemann, V. and Malik, R. and Brendel, M. and Ertl-Wagner, B. and Bartenstein, P. and Rominger, A. and Dichgans, M.},\n\tmonth = oct,\n\tyear = {2016},\n\tpmid = {27539301},\n\tkeywords = {Stroke, Aged, Female, Humans, Male, Prospective Studies, *stroke, Aged, 80 and over, Magnetic Resonance Imaging, stroke, *magnetic resonance imaging, Memory, Neuropsychological Tests, Brain/*diagnostic imaging, magnetic resonance imaging, mild cognitive impairment, Positron-Emission Tomography, *Amyloid, *mild cognitive impairment, *positron emission tomography, Amyloid beta-Peptides, Cognitive Dysfunction/*diagnostic imaging/etiology, Memory/physiology, Stroke/complications/*diagnostic imaging, amyloid, Brain, positron emission tomography, Cognitive Dysfunction, Amyloid},\n\tpages = {2645--8},\n}\n\n

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\n \n\n \n \n \n \n \n METACOHORTS for the study of vascular disease and its contribution to cognitive decline and neurodegeneration: An initiative of the Joint Programme for Neurodegenerative Disease Research.\n \n \n \n\n\n \n address: joanna. wardlaw@ed.ac.uk , M. C. E.; and Consortium, M.\n\n\n \n\n\n\n Alzheimers Dement, 12(12): 1235–1249. December 2016.\n \n\n\n\n
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@article{metacohorts_consortium_electronic_address_joanna_wardlawedacuk_metacohorts_2016,\n\ttitle = {{METACOHORTS} for the study of vascular disease and its contribution to cognitive decline and neurodegeneration: {An} initiative of the {Joint} {Programme} for {Neurodegenerative} {Disease} {Research}},\n\tvolume = {12},\n\tissn = {1552-5279 (Electronic) 1552-5260 (Linking)},\n\tdoi = {10.1016/j.jalz.2016.06.004},\n\tabstract = {Dementia is a global problem and major target for health care providers. Although up to 45\\% of cases are primarily or partly due to cerebrovascular disease, little is known of these mechanisms or treatments because most dementia research still focuses on pure Alzheimer's disease. An improved understanding of the vascular contributions to neurodegeneration and dementia, particularly by small vessel disease, is hampered by imprecise data, including the incidence and prevalence of symptomatic and clinically "silent" cerebrovascular disease, long-term outcomes (cognitive, stroke, or functional), and risk factors. New large collaborative studies with long follow-up are expensive and time consuming, yet substantial data to advance the field are available. In an initiative funded by the Joint Programme for Neurodegenerative Disease Research, 55 international experts surveyed and assessed available data, starting with European cohorts, to promote data sharing to advance understanding of how vascular disease affects brain structure and function, optimize methods for cerebrovascular disease in neurodegeneration research, and focus future research on gaps in knowledge. Here, we summarize the results and recommendations from this initiative. We identified data from over 90 studies, including over 660,000 participants, many being additional to neurodegeneration data initiatives. The enthusiastic response means that cohorts from North America, Australasia, and the Asia Pacific Region are included, creating a truly global, collaborative, data sharing platform, linked to major national dementia initiatives. Furthermore, the revised World Health Organization International Classification of Diseases version 11 should facilitate recognition of vascular-related brain damage by creating one category for all cerebrovascular disease presentations and thus accelerate identification of targets for dementia prevention.},\n\tnumber = {12},\n\tjournal = {Alzheimers Dement},\n\tauthor = {Metacohorts Consortium. Electronic address: joanna. wardlaw@ed.ac.uk and Metacohorts Consortium},\n\tmonth = dec,\n\tyear = {2016},\n\tpmcid = {PMC5399602},\n\tpmid = {27490018},\n\tkeywords = {Small vessel disease, Aged, Female, Humans, Male, Incidence, *Small vessel disease, Risk Factors, Cohort Studies, Dementia, Cerebrovascular disease, *Cerebrovascular disease, *Cognitive Dysfunction, *Dementia, *Neurodegeneration, Cohorts, Survey, *Neurodegenerative Diseases/etiology, Cerebrovascular Disorders/*complications/*epidemiology, Dementia, Vascular, Prevalence, Surveys and Questionnaires, Cerebrovascular Disorders, Cognitive Dysfunction, Neurodegenerative Diseases, Neurodegeneration, Cohorts, Survey},\n\tpages = {1235--1249},\n}\n\n

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\n \n\n \n \n \n \n \n Enhanced resting-state functional connectivity between core memory-task activation peaks is associated with memory impairment in MCI.\n \n \n \n\n\n \n Zhang, Y.; Simon-Vermot, L.; Araque Caballero, M. A.; Gesierich, B.; Taylor, A. N. W.; Duering, M.; Dichgans, M.; Ewers, M.; and Alzheimer's Disease Neuroimaging, I.\n\n\n \n\n\n\n Neurobiol Aging, 45: 43–49. September 2016.\n \n\n\n\n
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@article{zhang_enhanced_2016,\n\ttitle = {Enhanced resting-state functional connectivity between core memory-task activation peaks is associated with memory impairment in {MCI}},\n\tvolume = {45},\n\tissn = {1558-1497 (Electronic) 0197-4580 (Linking)},\n\tdoi = {10.1016/j.neurobiolaging.2016.04.018},\n\tabstract = {Resting-state functional connectivity (FC) is altered in Alzheimer's disease (AD) but its predictive value for episodic memory impairment is debated. Here, we aimed to assess whether resting-state FC in core brain regions activated during memory-task functional magnetic resonance imaging is altered and predictive of memory performance in AD and amnestic mild cognitive impairment (aMCI). Twenty-three elderly cognitively healthy controls (HC), 76 aMCI subjects, and 19 AD dementia patients were included. We computed resting-state FC between 18 meta-analytically determined peak coordinates of brain activation during successful memory retrieval. Higher FC between the parahippocampus, parietal cortex, and the middle frontal gyrus was observed in both AD and mild cognitive impairment compared to HC (false-discovery rate-corrected p {\\textless} 0.05). The increase in FC between the parahippocampus and middle frontal gyrus was associated with reduced episodic memory in aMCI, independent of amyloid-beta positron emission tomography binding and apolipoprotein E epsilon4-carrier status. In conclusion, increased parahippocampal-prefrontal FC is predictive of impaired episodic memory in aMCI and may reflect a dysfunctional change within the episodic memory-related neural network.},\n\tjournal = {Neurobiol Aging},\n\tauthor = {Zhang, Y. and Simon-Vermot, L. and Araque Caballero, M. A. and Gesierich, B. and Taylor, A. N. W. and Duering, M. and Dichgans, M. and Ewers, M. and Alzheimer's Disease Neuroimaging, Initiative},\n\tmonth = sep,\n\tyear = {2016},\n\tpmid = {27459924},\n\tkeywords = {Cognition, Aged, Female, Humans, Male, Alzheimer's disease, *Alzheimer's disease, Aged, 80 and over, Magnetic Resonance Imaging, Memory, Memory/*physiology, Predictive Value of Tests, *Mild cognitive impairment, Rest, *Compensation, *Episodic memory, *Functional connectivity, *Network, *Resting-state functional MRI, Alzheimer Disease/psychology, Brain/diagnostic imaging/physiopathology, Cognition/physiology, Cognitive Dysfunction/diagnostic imaging/*psychology, Functional Neuroimaging, Memory, Episodic, Nerve Net/diagnostic imaging/physiopathology, Rest/*physiology, Functional connectivity, Brain, Alzheimer Disease, Cognitive Dysfunction, Mild cognitive impairment, Nerve Net, Compensation, Episodic memory, Network, Resting-state functional MRI},\n\tpages = {43--49},\n}\n\n

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\n \n\n \n \n \n \n \n Determinants of iron accumulation in the normal aging brain.\n \n \n \n\n\n \n Pirpamer, L.; Hofer, E.; Gesierich, B.; De Guio, F.; Freudenberger, P.; Seiler, S.; Duering, M.; Jouvent, E.; Duchesnay, E.; Dichgans, M.; Ropele, S.; and Schmidt, R.\n\n\n \n\n\n\n Neurobiol Aging, 43: 149–55. July 2016.\n \n\n\n\n
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@article{pirpamer_determinants_2016,\n\ttitle = {Determinants of iron accumulation in the normal aging brain},\n\tvolume = {43},\n\tissn = {1558-1497 (Electronic) 0197-4580 (Linking)},\n\tdoi = {10.1016/j.neurobiolaging.2016.04.002},\n\tabstract = {In a recent postmortem study, R2* relaxometry in gray matter (GM) of the brain has been validated as a noninvasive measure for iron content in brain tissue. Iron accumulation in the normal aging brain is a common finding and relates to brain maturation and degeneration. The goal of this study was to assess the determinants of iron accumulation during brain aging. The study cohort consisted of 314 healthy community-dwelling participants of the Austrian Stroke Prevention Study. Their age ranged from 38-82 years. Quantitative magnetic resonance imaging was performed on 3T and included R2* mapping, based on a 3D multi-echo gradient echo sequence. The median of R2* values was measured in all GM regions, which were segmented automatically using FreeSurfer. We investigated 25 possible determinants for cerebral iron deposition. These included demographics, brain volume, lifestyle factors, cerebrovascular risk factors, serum levels of iron, and single nucleotide polymorphisms related to iron regulating genes (rs1800562, rs3811647, rs1799945, and rs1049296). The body mass index (BMI) was significantly related to R2* in 15/32 analyzed brain regions with the strongest correlations found in the amygdala (p = 0.0091), medial temporal lobe (p = 0.0002), and hippocampus (p {\\textless}/= 0.0001). Further associations to R2* values were found in deep GM for age and smoking. No significant associations were found for gender, GM volume, serum levels of iron, or iron-associated genetic polymorphisms. In conclusion, besides age, the BMI and smoking are the only significant determinants of brain iron accumulation in normally aging subjects. Smoking relates to iron deposition in the basal ganglia, whereas higher BMI is associated with iron content in the neocortex following an Alzheimer-like distribution.},\n\tjournal = {Neurobiol Aging},\n\tauthor = {Pirpamer, L. and Hofer, E. and Gesierich, B. and De Guio, F. and Freudenberger, P. and Seiler, S. and Duering, M. and Jouvent, E. and Duchesnay, E. and Dichgans, M. and Ropele, S. and Schmidt, R.},\n\tmonth = jul,\n\tyear = {2016},\n\tpmid = {27255824},\n\tkeywords = {Adult, Aged, Female, Humans, Male, Middle Aged, Aged, 80 and over, Magnetic Resonance Imaging, Magnetic resonance imaging, Cohort Studies, Aging, *Determinants for iron accumulation, *Magnetic resonance imaging, *Neocortex, *Normal aging brain, *R(2)* brain iron mapping, Aging/*metabolism, Body Mass Index, Brain/*diagnostic imaging/*metabolism/pathology, Iron/*metabolism, Smoking/adverse effects, Brain, Iron, Determinants for iron accumulation, Neocortex, Normal aging brain, R(2)* brain iron mapping, Smoking},\n\tpages = {149--55},\n}\n\n

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\n \n\n \n \n \n \n \n Neuronal correlates of serial position performance in amnestic mild cognitive impairment.\n \n \n \n\n\n \n Kasper, E.; Brueggen, K.; Grothe, M. J.; Bruno, D.; Pomara, N.; Unterauer, E.; Duering, M.; Ewers, M.; Teipel, S.; and Buerger, K.\n\n\n \n\n\n\n Neuropsychology, 30(8): 906–914. November 2016.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{kasper_neuronal_2016,\n\ttitle = {Neuronal correlates of serial position performance in amnestic mild cognitive impairment},\n\tvolume = {30},\n\tissn = {1931-1559 (Electronic) 0894-4105 (Linking)},\n\tdoi = {10.1037/neu0000287},\n\tabstract = {OBJECTIVES: Delayed recall of the first words of a list-the primacy position-is thought to be particularly dependent on intact memory consolidation. Hippocampal volume has been suggested as the primary neuronal correlate of delayed primacy recall in cognitively normal elderly individuals. Here, we studied the association of hippocampal volume with primacy recall in individuals with amnestic mild cognitive impairment (aMCI). METHOD: We investigated serial position performance in 88 subjects with aMCI using a 16-word list (the California Verbal Learning Test [CVLT]). Primacy and recency performance were measured during learning and delayed recall. Hippocampal volumes were automatically determined from structural MRI scans. We conducted regression analyses with bilateral hippocampal volumes as predictors and serial position indices as outcomes. RESULTS: After controlling for age, gender, and total intracranial volume, bilateral hippocampal volume was not associated with primacy recall either during learning or delayed recall. Primacy performance during learning was associated with the right inferior and middle temporal gyrus as well as the right inferior parietal cortex and supramerginal gyrus. During delayed recall, primacy performance was related to the bilateral supramarginal gyri. CONCLUSIONS: Our findings suggest a reduced primacy effect in aMCI already during learning, contrasting previous findings in normal cognitive aging. This might indicate impaired encoding and consolidation processes at an early stage of episodic memory acquisition. Furthermore, our data indicate that hippocampal volume may not be a relevant determinant of residual primacy performance in the stage of aMCI, which may rather depend on temporal and parietal neocortical networks. (PsycINFO Database Record},\n\tnumber = {8},\n\tjournal = {Neuropsychology},\n\tauthor = {Kasper, E. and Brueggen, K. and Grothe, M. J. and Bruno, D. and Pomara, N. and Unterauer, E. and Duering, M. and Ewers, M. and Teipel, S. and Buerger, K.},\n\tmonth = nov,\n\tyear = {2016},\n\tpmid = {27182709},\n\tkeywords = {Aged, Female, Humans, Aged, 80 and over, Magnetic Resonance Imaging, Regression Analysis, Neuropsychological Tests, Hippocampus, Brain Mapping, Imaging, Three-Dimensional, Memory, Episodic, Amnesia/*physiopathology/*psychology, Brain/*physiopathology, Cognitive Dysfunction/*physiopathology/*psychology, Hippocampus/physiopathology, Image Interpretation, Computer-Assisted, Mental Recall/physiology, Orientation/*physiology, Serial Learning/*physiology, Statistics as Topic, Temporal Lobe/physiopathology, Brain, Amnesia, Cognitive Dysfunction, Temporal Lobe, Mental Recall, Orientation, Serial Learning},\n\tpages = {906--914},\n}\n\n

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\n \n\n \n \n \n \n \n Reproducibility and variability of quantitative magnetic resonance imaging markers in cerebral small vessel disease.\n \n \n \n\n\n \n De Guio, F.; Jouvent, E.; Biessels, G. J.; Black, S. E.; Brayne, C.; Chen, C.; Cordonnier, C.; De Leeuw, F. E.; Dichgans, M.; Doubal, F.; Duering, M.; Dufouil, C.; Duzel, E.; Fazekas, F.; Hachinski, V.; Ikram, M. A.; Linn, J.; Matthews, P. M.; Mazoyer, B.; Mok, V.; Norrving, B.; O'Brien, J. T.; Pantoni, L.; Ropele, S.; Sachdev, P.; Schmidt, R.; Seshadri, S.; Smith, E. E.; Sposato, L. A.; Stephan, B.; Swartz, R. H.; Tzourio, C.; van Buchem, M.; van der Lugt, A.; van Oostenbrugge, R.; Vernooij, M. W.; Viswanathan, A.; Werring, D.; Wollenweber, F.; Wardlaw, J. M.; and Chabriat, H.\n\n\n \n\n\n\n J Cereb Blood Flow Metab, 36(8): 1319–37. August 2016.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{de_guio_reproducibility_2016,\n\ttitle = {Reproducibility and variability of quantitative magnetic resonance imaging markers in cerebral small vessel disease},\n\tvolume = {36},\n\tissn = {1559-7016 (Electronic) 0271-678X (Linking)},\n\tdoi = {10.1177/0271678X16647396},\n\tabstract = {Brain imaging is essential for the diagnosis and characterization of cerebral small vessel disease. Several magnetic resonance imaging markers have therefore emerged, providing new information on the diagnosis, progression, and mechanisms of small vessel disease. Yet, the reproducibility of these small vessel disease markers has received little attention despite being widely used in cross-sectional and longitudinal studies. This review focuses on the main small vessel disease-related markers on magnetic resonance imaging including: white matter hyperintensities, lacunes, dilated perivascular spaces, microbleeds, and brain volume. The aim is to summarize, for each marker, what is currently known about: (1) its reproducibility in studies with a scan-rescan procedure either in single or multicenter settings; (2) the acquisition-related sources of variability; and, (3) the techniques used to minimize this variability. Based on the results, we discuss technical and other challenges that need to be overcome in order for these markers to be reliably used as outcome measures in future clinical trials. We also highlight the key points that need to be considered when designing multicenter magnetic resonance imaging studies of small vessel disease.},\n\tnumber = {8},\n\tjournal = {J Cereb Blood Flow Metab},\n\tauthor = {De Guio, F. and Jouvent, E. and Biessels, G. J. and Black, S. E. and Brayne, C. and Chen, C. and Cordonnier, C. and De Leeuw, F. E. and Dichgans, M. and Doubal, F. and Duering, M. and Dufouil, C. and Duzel, E. and Fazekas, F. and Hachinski, V. and Ikram, M. A. and Linn, J. and Matthews, P. M. and Mazoyer, B. and Mok, V. and Norrving, B. and O'Brien, J. T. and Pantoni, L. and Ropele, S. and Sachdev, P. and Schmidt, R. and Seshadri, S. and Smith, E. E. and Sposato, L. A. and Stephan, B. and Swartz, R. H. and Tzourio, C. and van Buchem, M. and van der Lugt, A. and van Oostenbrugge, R. and Vernooij, M. W. and Viswanathan, A. and Werring, D. and Wollenweber, F. and Wardlaw, J. M. and Chabriat, H.},\n\tmonth = aug,\n\tyear = {2016},\n\tpmcid = {PMC4976752},\n\tpmid = {27170700},\n\tkeywords = {Humans, Image Processing, Computer-Assisted, cerebral small vessel disease, *cerebral small vessel disease, Magnetic Resonance Imaging, Biomarkers, Magnetic resonance imaging, Cerebral Small Vessel Diseases/*diagnostic imaging, Reproducibility of Results, lacunes, white matter hyperintensities, Magnetic Resonance Imaging/*methods, *lacunes, *white matter hyperintensities, *brain volume, Microvessels/*diagnostic imaging, *Magnetic resonance imaging, *atrophy, *marker, *microbleeds, *perivascular spaces, *repeatability, *reproducibility, *variability, Biomarkers/analysis, Brain/blood supply/*diagnostic imaging, Image Processing, Computer-Assisted/*methods, Brain, Microvessels, Cerebral Small Vessel Diseases, microbleeds, atrophy, brain volume, marker, perivascular spaces, repeatability, reproducibility, variability},\n\tpages = {1319--37},\n}\n\n

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\n \n\n \n \n \n \n \n Shape of the Central Sulcus and Disability After Subcortical Stroke: A Motor Reserve Hypothesis.\n \n \n \n\n\n \n Jouvent, E.; Sun, Z. Y.; De Guio, F.; Duchesnay, E.; Duering, M.; Ropele, S.; Dichgans, M.; Mangin, J. F.; and Chabriat, H.\n\n\n \n\n\n\n Stroke, 47(4): 1023–9. April 2016.\n \n\n\n\n
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@article{jouvent_shape_2016,\n\ttitle = {Shape of the {Central} {Sulcus} and {Disability} {After} {Subcortical} {Stroke}: {A} {Motor} {Reserve} {Hypothesis}},\n\tvolume = {47},\n\tissn = {1524-4628 (Electronic) 0039-2499 (Linking)},\n\tdoi = {10.1161/STROKEAHA.115.012562},\n\tabstract = {BACKGROUND AND PURPOSE: Both brain and cognitive reserves modulate the clinical impact of chronic brain diseases. Whether a motor reserve also modulates the relationships between stroke and disability is unknown. We aimed to determine whether the shape of the central sulcus, a marker of the development of underlying motor connections, is independently associated with disability in patients with a positive history of small subcortical ischemic stroke. METHODS: Shapes of central sulci were reconstructed from high-resolution magnetic resonance imaging and ordered without supervision according to a validated algorithm in 166 patients with a positive history of small subcortical ischemic stroke caused by CADASIL (Cerebral Autosomal Dominant Arteriopathy With Subcortical Infarcts and Leukoencephalopathy), a severe monogenic cerebral small vessel disease affecting young patients. Ordinal logistic regression modeling was used to test the relationships between modified Rankin scale, a disability scale strongly weighted toward motor disability, and sulcal shape. RESULTS: Modified Rankin scale was strongly associated with sulcal shape, independent of age, sex, and level of education (proportional odds ratio =1.19, 95\\% confidence interval =1.06-1.35; P=0.002). Results remained significant after further adjustment for brain atrophy, volume of lacunes, and volume of white matter hyperintensities of presumed vascular origin. CONCLUSIONS: The severity of disability in patients with a positive history of small subcortical ischemic stroke caused by a severe cerebral small vessel disease is related to the shape of the central sulcus, independently of the main determinants of disability. These results support the concept of a motor reserve that could modulate the clinical severity in patients with a positive history of small subcortical ischemic stroke.},\n\tnumber = {4},\n\tjournal = {Stroke},\n\tauthor = {Jouvent, E. and Sun, Z. Y. and De Guio, F. and Duchesnay, E. and Duering, M. and Ropele, S. and Dichgans, M. and Mangin, J. F. and Chabriat, H.},\n\tmonth = apr,\n\tyear = {2016},\n\tpmid = {26941259},\n\tkeywords = {Stroke, Adult, Aged, Female, Humans, Image Processing, Computer-Assisted, Male, Middle Aged, Magnetic Resonance Imaging, stroke, Cadasil, CADASIL/*pathology/physiopathology, Atrophy, Brain Mapping, Algorithms, Atrophy/pathology/physiopathology, central sulcus, cerebral cortex, Cerebral Cortex/*pathology/physiopathology, motor reserve, Recovery of Function/physiology, Stroke/*pathology/physiopathology, White Matter/*pathology/physiopathology, White Matter, Cerebral Cortex, CADASIL, Recovery of Function},\n\tpages = {1023--9},\n}\n\n

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\n \n\n \n \n \n \n \n Genome-wide meta-analysis of cerebral white matter hyperintensities in patients with stroke.\n \n \n \n\n\n \n Traylor, M.; Zhang, C. R.; Adib-Samii, P.; Devan, W. J.; Parsons, O. E.; Lanfranconi, S.; Gregory, S.; Cloonan, L.; Falcone, G. J.; Radmanesh, F.; Fitzpatrick, K.; Kanakis, A.; Barrick, T. R.; Moynihan, B.; Lewis, C. M.; Boncoraglio, G. B.; Lemmens, R.; Thijs, V.; Sudlow, C.; Wardlaw, J.; Rothwell, P. M.; Meschia, J. F.; Worrall, B. B.; Levi, C.; Bevan, S.; Furie, K. L.; Dichgans, M.; Rosand, J.; Markus, H. S.; Rost, N.; and International Stroke Genetics, C.\n\n\n \n\n\n\n Neurology, 86(2): 146–53. January 2016.\n \n\n\n\n
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@article{traylor_genome-wide_2016,\n\ttitle = {Genome-wide meta-analysis of cerebral white matter hyperintensities in patients with stroke},\n\tvolume = {86},\n\tissn = {1526-632X (Electronic) 0028-3878 (Linking)},\n\tdoi = {10.1212/WNL.0000000000002263},\n\tabstract = {OBJECTIVE: For 3,670 stroke patients from the United Kingdom, United States, Australia, Belgium, and Italy, we performed a genome-wide meta-analysis of white matter hyperintensity volumes (WMHV) on data imputed to the 1000 Genomes reference dataset to provide insights into disease mechanisms. METHODS: We first sought to identify genetic associations with white matter hyperintensities in a stroke population, and then examined whether genetic loci previously linked to WMHV in community populations are also associated in stroke patients. Having established that genetic associations are shared between the 2 populations, we performed a meta-analysis testing which associations with WMHV in stroke-free populations are associated overall when combined with stroke populations. RESULTS: There were no associations at genome-wide significance with WMHV in stroke patients. All previously reported genome-wide significant associations with WMHV in community populations shared direction of effect in stroke patients. In a meta-analysis of the genome-wide significant and suggestive loci (p {\\textless} 5 x 10(-6)) from community populations (15 single nucleotide polymorphisms in total) and from stroke patients, 6 independent loci were associated with WMHV in both populations. Four of these are novel associations at the genome-wide level (rs72934505 [NBEAL1], p = 2.2 x 10(-8); rs941898 [EVL], p = 4.0 x 10(-8); rs962888 [C1QL1], p = 1.1 x 10(-8); rs9515201 [COL4A2], p = 6.9 x 10(-9)). CONCLUSIONS: Genetic associations with WMHV are shared in otherwise healthy individuals and patients with stroke, indicating common genetic susceptibility in cerebral small vessel disease.},\n\tnumber = {2},\n\tjournal = {Neurology},\n\tauthor = {Traylor, M. and Zhang, C. R. and Adib-Samii, P. and Devan, W. J. and Parsons, O. E. and Lanfranconi, S. and Gregory, S. and Cloonan, L. and Falcone, G. J. and Radmanesh, F. and Fitzpatrick, K. and Kanakis, A. and Barrick, T. R. and Moynihan, B. and Lewis, C. M. and Boncoraglio, G. B. and Lemmens, R. and Thijs, V. and Sudlow, C. and Wardlaw, J. and Rothwell, P. M. and Meschia, J. F. and Worrall, B. B. and Levi, C. and Bevan, S. and Furie, K. L. and Dichgans, M. and Rosand, J. and Markus, H. S. and Rost, N. and International Stroke Genetics, Consortium},\n\tmonth = jan,\n\tyear = {2016},\n\tpmcid = {PMC4731688},\n\tpmid = {26674333},\n\tkeywords = {Stroke, Humans, Genome-Wide Association Study, Risk Factors, Genetic Predisposition to Disease, *Genome-Wide Association Study, Cerebral Small Vessel Diseases/*genetics, Genetic Predisposition to Disease/*genetics, Genetic Testing/methods, Polymorphism, Single Nucleotide/*genetics, Stroke/*epidemiology/physiopathology, White Matter/*physiopathology, White Matter, Cerebral Small Vessel Diseases, Polymorphism, Single Nucleotide, Genetic Testing},\n\tpages = {146--53},\n}\n\n

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\n \n\n \n \n \n \n \n Prevalence and characteristics of migraine in CADASIL.\n \n \n \n\n\n \n Guey, S.; Mawet, J.; Herve, D.; Duering, M.; Godin, O.; Jouvent, E.; Opherk, C.; Alili, N.; Dichgans, M.; and Chabriat, H.\n\n\n \n\n\n\n Cephalalgia, 36(11): 1038–1047. October 2016.\n \n\n\n\n
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@article{guey_prevalence_2016,\n\ttitle = {Prevalence and characteristics of migraine in {CADASIL}},\n\tvolume = {36},\n\tissn = {1468-2982 (Electronic) 0333-1024 (Linking)},\n\tdoi = {10.1177/0333102415620909},\n\tabstract = {Background and objective Migraine with aura (MA) is a major symptom of cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL). We assessed the spectrum of migraine symptoms and their potential correlates in a large prospective cohort of CADASIL individuals. Methods A standardized questionnaire was used in 378 CADASIL patients for assessing headache symptoms, trigger factors, age at first attack, frequency of attacks and associated symptoms. MRI lesions and brain atrophy were quantified. Results A total of 54.5\\% of individuals had a history of migraine, mostly MA in 84\\% of them; 62.4\\% of individuals with MA were women and age at onset of MA was lower in women than in men. Atypical aura symptoms were experienced by 59.3\\% of individuals with MA, and for 19.7\\% of patients with MA the aura was never accompanied by headache. MA was the inaugural manifestation in 41\\% of symptomatic patients and an isolated symptom in 12.1\\% of individuals. Slightly higher MMSE and MDRS scores and lower Rankin score were detected in the MA group. Conclusion MA is observed in almost half of all CADASIL patients. Atypical aura symptoms are reported by more than one in two of them. MA is often inaugural, can remain isolated and is not associated with the severity of the disorder.},\n\tnumber = {11},\n\tjournal = {Cephalalgia},\n\tauthor = {Guey, S. and Mawet, J. and Herve, D. and Duering, M. and Godin, O. and Jouvent, E. and Opherk, C. and Alili, N. and Dichgans, M. and Chabriat, H.},\n\tmonth = oct,\n\tyear = {2016},\n\tpmid = {26646784},\n\tkeywords = {small vessel disease, Adult, Aged, Female, Humans, Male, Middle Aged, Comorbidity, Risk Factors, Cadasil, Cohort Studies, France, Germany, Prevalence, Age Distribution, aura, CADASIL/*diagnosis/*epidemiology, cortical spreading depression, France/epidemiology, Germany/epidemiology, migraine, Migraine with Aura/*diagnosis/*epidemiology, Sex Distribution, CADASIL, Migraine with Aura},\n\tpages = {1038--1047},\n}\n\n

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\n \n\n \n \n \n \n \n Predictors of Clinical Worsening in Cerebral Autosomal Dominant Arteriopathy With Subcortical Infarcts and Leukoencephalopathy: Prospective Cohort Study.\n \n \n \n\n\n \n Chabriat, H.; Herve, D.; Duering, M.; Godin, O.; Jouvent, E.; Opherk, C.; Alili, N.; Reyes, S.; Jabouley, A.; Zieren, N.; Guichard, J. P.; Pachai, C.; Vicaut, E.; and Dichgans, M.\n\n\n \n\n\n\n Stroke, 47(1): 4–11. January 2016.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{chabriat_predictors_2016,\n\ttitle = {Predictors of {Clinical} {Worsening} in {Cerebral} {Autosomal} {Dominant} {Arteriopathy} {With} {Subcortical} {Infarcts} and {Leukoencephalopathy}: {Prospective} {Cohort} {Study}},\n\tvolume = {47},\n\tissn = {1524-4628 (Electronic) 0039-2499 (Linking)},\n\tdoi = {10.1161/STROKEAHA.115.010696},\n\tabstract = {BACKGROUND AND PURPOSE: Predictors of clinical worsening in cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy remain unknown. This study aims to identify demographic, clinical, and magnetic resonance imaging predictors of incident strokes, incident dementia, clinical deterioration, and death in patients with this genetically proven disease. METHODS: Two hundred ninety subjects (mean age, 50.6+/-11.4 years) were assessed at baseline and followed up for 36 months. Incident clinical events were recorded, and clinical scores included the Mini Mental State Examination, Mattis Dementia Rating Scale, modified Rankin Scale, and Barthel index. The number of lacunes and microbleeds, the volume of white-matter hyperintensities, and brain parenchymal fraction were assessed on baseline magnetic resonance imaging. Data were analyzed by ANCOVA, multivariable logistic regression, and Cox proportional hazard models. RESULTS: Incident stroke occurred in 55 of 278 patients (19.8\\%). Moderate or severe disability developed in 19 of 210 (9\\%) nondisabled individuals, incident dementia in 49 of 231 (20\\%) nondemented subjects, and 4.8\\% of patients died. Active smoking, the number of lacunes, and brain parenchymal fraction independently predicted incident stroke during follow-up. Gait disturbance, dementia, and brain parenchymal fraction predicted progression toward moderate or severe disability. Active smoking, disability, and brain parenchymal fraction predicted incident dementia. Age was the only significant predictor of death. CONCLUSIONS: Clinical assessment and brain magnetic resonance imaging aid in predicting incident clinical events and clinical deterioration in cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy. There is a bidirectional relationship between dementia and moderate or severe disability in predicting each other's onset. Active smoking is a modifiable risk factor associated with clinical progression in Notch3 mutation carriers.},\n\tnumber = {1},\n\tjournal = {Stroke},\n\tauthor = {Chabriat, H. and Herve, D. and Duering, M. and Godin, O. and Jouvent, E. and Opherk, C. and Alili, N. and Reyes, S. and Jabouley, A. and Zieren, N. and Guichard, J. P. and Pachai, C. and Vicaut, E. and Dichgans, M.},\n\tmonth = jan,\n\tyear = {2016},\n\tpmid = {26578659},\n\tkeywords = {Adult, Disease Progression, Female, Humans, Male, Middle Aged, Prospective Studies, Magnetic Resonance Imaging, Cadasil, Cohort Studies, Dementia, magnetic resonance imaging, Predictive Value of Tests, *Disease Progression, CADASIL/*diagnosis/epidemiology/*psychology, cerebral small vessel diseases, Dementia/diagnosis/epidemiology/psychology, Magnetic Resonance Imaging/trends, risk factors, CADASIL, cohort studies},\n\tpages = {4--11},\n}\n\n

\n\n\n

\n BACKGROUND AND PURPOSE: Predictors of clinical worsening in cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy remain unknown. This study aims to identify demographic, clinical, and magnetic resonance imaging predictors of incident strokes, incident dementia, clinical deterioration, and death in patients with this genetically proven disease. METHODS: Two hundred ninety subjects (mean age, 50.6+/-11.4 years) were assessed at baseline and followed up for 36 months. Incident clinical events were recorded, and clinical scores included the Mini Mental State Examination, Mattis Dementia Rating Scale, modified Rankin Scale, and Barthel index. The number of lacunes and microbleeds, the volume of white-matter hyperintensities, and brain parenchymal fraction were assessed on baseline magnetic resonance imaging. Data were analyzed by ANCOVA, multivariable logistic regression, and Cox proportional hazard models. RESULTS: Incident stroke occurred in 55 of 278 patients (19.8%). Moderate or severe disability developed in 19 of 210 (9%) nondisabled individuals, incident dementia in 49 of 231 (20%) nondemented subjects, and 4.8% of patients died. Active smoking, the number of lacunes, and brain parenchymal fraction independently predicted incident stroke during follow-up. Gait disturbance, dementia, and brain parenchymal fraction predicted progression toward moderate or severe disability. Active smoking, disability, and brain parenchymal fraction predicted incident dementia. Age was the only significant predictor of death. CONCLUSIONS: Clinical assessment and brain magnetic resonance imaging aid in predicting incident clinical events and clinical deterioration in cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy. There is a bidirectional relationship between dementia and moderate or severe disability in predicting each other's onset. Active smoking is a modifiable risk factor associated with clinical progression in Notch3 mutation carriers.\n

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\n \n\n \n \n \n \n \n Consensus statement for diagnosis of subcortical small vessel disease.\n \n \n \n\n\n \n Rosenberg, G. A.; Wallin, A.; Wardlaw, J. M.; Markus, H. S.; Montaner, J.; Wolfson, L.; Iadecola, C.; Zlokovic, B. V.; Joutel, A.; Dichgans, M.; Duering, M.; Schmidt, R.; Korczyn, A. D.; Grinberg, L. T.; Chui, H. C.; and Hachinski, V.\n\n\n \n\n\n\n J Cereb Blood Flow Metab, 36(1): 6–25. January 2016.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{rosenberg_consensus_2016,\n\ttitle = {Consensus statement for diagnosis of subcortical small vessel disease},\n\tvolume = {36},\n\tissn = {1559-7016 (Electronic) 0271-678X (Linking)},\n\tdoi = {10.1038/jcbfm.2015.172},\n\tabstract = {Vascular cognitive impairment (VCI) is the diagnostic term used to describe a heterogeneous group of sporadic and hereditary diseases of the large and small blood vessels. Subcortical small vessel disease (SVD) leads to lacunar infarcts and progressive damage to the white matter. Patients with progressive damage to the white matter, referred to as Binswanger's disease (BD), constitute a spectrum from pure vascular disease to a mixture with neurodegenerative changes. Binswanger's disease patients are a relatively homogeneous subgroup with hypoxic hypoperfusion, lacunar infarcts, and inflammation that act synergistically to disrupt the blood-brain barrier (BBB) and break down myelin. Identification of this subgroup can be facilitated by multimodal disease markers obtained from clinical, cerebrospinal fluid, neuropsychological, and imaging studies. This consensus statement identifies a potential set of biomarkers based on underlying pathologic changes that could facilitate diagnosis and aid patient selection for future collaborative treatment trials.},\n\tnumber = {1},\n\tjournal = {J Cereb Blood Flow Metab},\n\tauthor = {Rosenberg, G. A. and Wallin, A. and Wardlaw, J. M. and Markus, H. S. and Montaner, J. and Wolfson, L. and Iadecola, C. and Zlokovic, B. V. and Joutel, A. and Dichgans, M. and Duering, M. and Schmidt, R. and Korczyn, A. D. and Grinberg, L. T. and Chui, H. C. and Hachinski, V.},\n\tmonth = jan,\n\tyear = {2016},\n\tpmcid = {PMC4758552},\n\tpmid = {26198175},\n\tkeywords = {Humans, Aging, Dementia, Vascular, Aging/pathology, Blood-Brain Barrier/*pathology, Capillary Permeability, Dementia, Vascular/cerebrospinal fluid/*diagnosis/immunology/pathology, Leukoaraiosis/pathology, Microvessels/*pathology, Microvessels, Leukoaraiosis, Blood-Brain Barrier},\n\tpages = {6--25},\n}\n\n

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\n \n 2015\n \n \n (4)\n \n \n

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\n \n\n \n \n \n \n \n Acute infarcts cause focal thinning in remote cortex via degeneration of connecting fiber tracts.\n \n \n \n\n\n \n Duering, M.; Righart, R.; Wollenweber, F. A.; Zietemann, V.; Gesierich, B.; and Dichgans, M.\n\n\n \n\n\n\n Neurology, 84(16): 1685–92. April 2015.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{duering_acute_2015,\n\ttitle = {Acute infarcts cause focal thinning in remote cortex via degeneration of connecting fiber tracts},\n\tvolume = {84},\n\tissn = {1526-632X (Electronic) 0028-3878 (Linking)},\n\tdoi = {10.1212/WNL.0000000000001502},\n\tabstract = {OBJECTIVE: To study remote effects distant from acute ischemic infarcts by measuring longitudinal changes of cortical thickness in connected brain regions as well as changes in microstructural integrity in connecting fiber tracts. METHODS: Thirty-two patients (mean age 71 years) underwent a standardized protocol including multimodal MRI and clinical assessment both at stroke onset and 6 months after the event. Cortex connected to acute infarcts was identified by probabilistic diffusion tensor tractography starting from the acute lesion. Changes of cortical thickness were measured using the longitudinal stream of FreeSurfer. Microstructural damage in white matter tracts was assessed by changes of mean diffusivity. RESULTS: We found focal cortical thinning specifically in areas connected to acute infarcts (p {\\textless} 0.001). Thinning was more pronounced in regions showing a high probability of connectivity to infarcts. Microstructural damage in white matter tracts connecting acute infarcts with distant cortex significantly correlated with thickness changes in that region (rho = -0.39, p = 0.028). There was no indication of an influence of cavitation status or infarct etiology on the observed changes in cortex and white matter. CONCLUSIONS: These findings identify secondary degeneration of connected white matter tracts and remote cortex as key features of acute ischemic infarcts. Our observations may have implications for the understanding of structural and functional reorganization after stroke.},\n\tnumber = {16},\n\tjournal = {Neurology},\n\tauthor = {Duering, M. and Righart, R. and Wollenweber, F. A. and Zietemann, V. and Gesierich, B. and Dichgans, M.},\n\tmonth = apr,\n\tyear = {2015},\n\tpmcid = {PMC4409580},\n\tpmid = {25809303},\n\tkeywords = {Aged, Diffusion Tensor Imaging, Female, Humans, Male, Middle Aged, Aged, 80 and over, Follow-Up Studies, Brain Infarction/*pathology, Cerebral Cortex/*pathology, Nerve Fibers, Myelinated/*pathology, Nerve Net/*pathology, Cerebral Cortex, Brain Infarction, Nerve Fibers, Myelinated, Nerve Net},\n\tpages = {1685--92},\n}\n\n

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\n \n\n \n \n \n \n \n Cysteine-sparing CADASIL mutations in NOTCH3 show proaggregatory properties in vitro.\n \n \n \n\n\n \n Wollenweber, F. A.; Hanecker, P.; Bayer-Karpinska, A.; Malik, R.; Bazner, H.; Moreton, F.; Muir, K. W.; Muller, S.; Giese, A.; Opherk, C.; Dichgans, M.; Haffner, C.; and Duering, M.\n\n\n \n\n\n\n Stroke, 46(3): 786–92. March 2015.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{wollenweber_cysteine-sparing_2015,\n\ttitle = {Cysteine-sparing {CADASIL} mutations in {NOTCH3} show proaggregatory properties in vitro},\n\tvolume = {46},\n\tissn = {1524-4628 (Electronic) 0039-2499 (Linking)},\n\tdoi = {10.1161/STROKEAHA.114.007472},\n\tabstract = {BACKGROUND AND PURPOSE: Mutations in NOTCH3 cause cerebral autosomal-dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL), the most common monogenic cause of stroke and vascular dementia. Misfolding and aggregation of NOTCH3 proteins triggered by cysteine-affecting mutations are considered to be the key disease mechanisms. However, the significance of cysteine-sparing mutations is still debated. METHODS: We studied a family with inherited small vessel disease by standardized medical history, clinical examination, MRI, ultrastructural analysis of skin biopsies, and Sanger sequencing of all NOTCH3 exons. In addition, we performed in vitro characterization of NOTCH3 variants using recombinant protein fragments and a single-particle aggregation assay. RESULTS: We identified a novel cysteine-sparing NOTCH3 mutation (D80G) in 4 family members, which was absent in a healthy sibling. All mutation carriers exhibited a CADASIL typical brain imaging and clinical phenotype, whereas skin biopsy showed inconsistent results. In vitro aggregation behavior of the D80G mutant was similar compared with cysteine-affecting mutations. This was reproduced with cysteine-sparing mutations from previously reported families having a phenotype consistent with CADASIL. CONCLUSIONS: Our findings support the view that cysteine-sparing mutations, such as D80G, might cause CADASIL with a phenotype largely indistinguishable from cysteine mutations. The in vitro aggregation analysis of atypical NOTCH3 mutations offers novel insights into pathomechanisms and might represent a tool for estimating their clinical significance.},\n\tnumber = {3},\n\tjournal = {Stroke},\n\tauthor = {Wollenweber, F. A. and Hanecker, P. and Bayer-Karpinska, A. and Malik, R. and Bazner, H. and Moreton, F. and Muir, K. W. and Muller, S. and Giese, A. and Opherk, C. and Dichgans, M. and Haffner, C. and Duering, M.},\n\tmonth = mar,\n\tyear = {2015},\n\tpmid = {25604251},\n\tkeywords = {Aged, Female, Humans, Male, cerebral small vessel disease, Magnetic Resonance Imaging, *Mutation, Biopsy, Cadasil, CADASIL/*genetics, Cysteine/*genetics, genetic testing, NOTCH3 protein, human, Protein Binding, Protein Folding, Receptor, Notch3, Receptors, Notch/*genetics, recombinant proteins, Sequence Analysis, DNA, Skin/ultrastructure, Mutation, CADASIL, Receptors, Notch, Cysteine, Skin},\n\tpages = {786--92},\n}\n\n

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\n \n\n \n \n \n \n \n R2* mapping for brain iron: associations with cognition in normal aging.\n \n \n \n\n\n \n Ghadery, C.; Pirpamer, L.; Hofer, E.; Langkammer, C.; Petrovic, K.; Loitfelder, M.; Schwingenschuh, P.; Seiler, S.; Duering, M.; Jouvent, E.; Schmidt, H.; Fazekas, F.; Mangin, J. F.; Chabriat, H.; Dichgans, M.; Ropele, S.; and Schmidt, R.\n\n\n \n\n\n\n Neurobiol Aging, 36(2): 925–32. February 2015.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{ghadery_r2_2015,\n\ttitle = {R2* mapping for brain iron: associations with cognition in normal aging},\n\tvolume = {36},\n\tissn = {1558-1497 (Electronic) 0197-4580 (Linking)},\n\tdoi = {10.1016/j.neurobiolaging.2014.09.013},\n\tabstract = {Brain iron accumulates during aging and has been associated with neurodegenerative disorders including Alzheimer's disease. Magnetic resonance (MR)-based R2* mapping enables the in vivo detection of iron content in brain tissue. We investigated if during normal brain aging iron load relates to cognitive impairment in region-specific patterns in a community-dwelling cohort of 336 healthy, middle aged, and older adults from the Austrian Stroke Prevention Family Study. MR imaging and R2* mapping in the basal ganglia and neocortex were done at 3T. Comprehensive neuropsychological testing assessed memory, executive function, and psychomotor speed. We found the highest iron concentration in the globus pallidus, and pallidal and putaminal iron was significantly and inversely associated with cognitive performance in all cognitive domains, except memory. These associations were iron load dependent. Vascular brain lesions and brain volume did not mediate the relationship between iron and cognitive performance. We conclude that higher R2*-determined iron in the basal ganglia correlates with cognitive impairment during brain aging independent of concomitant brain abnormalities. The prognostic significance of this finding needs to be determined.},\n\tnumber = {2},\n\tjournal = {Neurobiol Aging},\n\tauthor = {Ghadery, C. and Pirpamer, L. and Hofer, E. and Langkammer, C. and Petrovic, K. and Loitfelder, M. and Schwingenschuh, P. and Seiler, S. and Duering, M. and Jouvent, E. and Schmidt, H. and Fazekas, F. and Mangin, J. F. and Chabriat, H. and Dichgans, M. and Ropele, S. and Schmidt, R.},\n\tmonth = feb,\n\tyear = {2015},\n\tpmid = {25443291},\n\tkeywords = {Cognition, Aged, Female, Humans, Male, Middle Aged, Magnetic Resonance Imaging, Cohort Studies, Mri, Aging, *Magnetic Resonance Imaging, Brain Mapping/*methods, Brain Mapping, *Cognition, Iron/*metabolism, Aging/*metabolism/*psychology, All cognitive disorders/dementia, Basal Ganglia/metabolism, Brain/*metabolism, Cognitive aging, Neurodegenerative Diseases/etiology/metabolism/psychology, R2* brain iron mapping, Brain, MRI, Basal Ganglia, Iron, Neurodegenerative Diseases},\n\tpages = {925--32},\n}\n\n

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\n \n\n \n \n \n \n \n White matter edema at the early stage of cerebral autosomal-dominant arteriopathy with subcortical infarcts and leukoencephalopathy.\n \n \n \n\n\n \n De Guio, F.; Mangin, J. F.; Duering, M.; Ropele, S.; Chabriat, H.; and Jouvent, E.\n\n\n \n\n\n\n Stroke, 46(1): 258–61. January 2015.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{de_guio_white_2015,\n\ttitle = {White matter edema at the early stage of cerebral autosomal-dominant arteriopathy with subcortical infarcts and leukoencephalopathy},\n\tvolume = {46},\n\tissn = {1524-4628 (Electronic) 0039-2499 (Linking)},\n\tdoi = {10.1161/STROKEAHA.114.007018},\n\tabstract = {BACKGROUND AND PURPOSE: Recently, in a mouse model of cerebral autosomal-dominant arteriopathy with subcortical infarcts and leukoencephalopathy, a monogenic cerebral small vessel disease, intramyelinic edema was detected in the white matter (WM) early during the course of the disease. We hypothesized that if this mechanism holds true in patients, it would translate in larger WM volume. We aimed to measure WM volume in patients with cerebral autosomal-dominant arteriopathy with subcortical infarcts and leukoencephalopathy in comparison with age- and sex-matched controls, along with the ratio of cortical surface area to the volume of brain hemispheres as an indirect measure that should be reduced in patients. METHODS: Twenty patients at the early stage of the disease (Mini Mental State Examination {\\textgreater}24 and modified Rankin scale {\\textless}/=1) and 27 age- and sex-matched controls had high-quality 3-Tesla 3DT1 MRI acquisitions. Volumes of brain hemispheres and of WM were determined. The ratio of cortical surface area to the volume of brain hemispheres was evaluated as a proxy of underlying WM volume. RESULTS: Patients had larger volumes of WM than controls (patients: 479.4+/-71.7; controls: 463.9+/-44.2; P=0.03). They presented a lower cortical surface area and cortical volume leading to a lower ratio of cortical surface area to the volume of brain hemispheres (patients: 15.7+/-0.7; controls: 16.1+/-0.5; P=0.004). Volume of WM tended to be associated with that of WM hyperintensities (P=0.06). CONCLUSIONS: Patients with cerebral autosomal-dominant arteriopathy with subcortical infarcts and leukoencephalopathy have larger WM volume than age- and sex-matched controls, a finding compatible with the hypothesis of intramyelinic edema as observed recently in mice.},\n\tnumber = {1},\n\tjournal = {Stroke},\n\tauthor = {De Guio, F. and Mangin, J. F. and Duering, M. and Ropele, S. and Chabriat, H. and Jouvent, E.},\n\tmonth = jan,\n\tyear = {2015},\n\tpmid = {25370582},\n\tkeywords = {Adult, Aged, Female, Humans, Male, Middle Aged, Magnetic Resonance Imaging, White Matter/*pathology, Cadasil, Case-Control Studies, cerebral small vessel diseases, Brain Edema/*pathology, CADASIL/*pathology, edema, Organ Size, white matter diseases, White Matter, CADASIL, Brain Edema},\n\tpages = {258--61},\n}\n\n

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\n \n 2014\n \n \n (10)\n \n \n

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\n \n\n \n \n \n \n \n Strategic white matter tracts for processing speed deficits in age-related small vessel disease.\n \n \n \n\n\n \n Duering, M.; Gesierich, B.; Seiler, S.; Pirpamer, L.; Gonik, M.; Hofer, E.; Jouvent, E.; Duchesnay, E.; Chabriat, H.; Ropele, S.; Schmidt, R.; and Dichgans, M.\n\n\n \n\n\n\n Neurology, 82(22): 1946–50. June 2014.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{duering_strategic_2014,\n\ttitle = {Strategic white matter tracts for processing speed deficits in age-related small vessel disease},\n\tvolume = {82},\n\tissn = {1526-632X (Electronic) 0028-3878 (Linking)},\n\tdoi = {10.1212/WNL.0000000000000475},\n\tabstract = {OBJECTIVE: Cerebral small vessel disease is the most common cause of vascular cognitive impairment and typically manifests with slowed processing speed. We investigated the impact of lesion location on processing speed in age-related small vessel disease. METHODS: A total of 584 community-dwelling elderly underwent brain MRI followed by segmentation of white matter hyperintensities. Processing speed was determined by the timed measure of the Trail Making Test part B. The impact of the location of white matter hyperintensities was assessed by voxel-based lesion-symptom mapping and graph-based statistical models on regional lesion volumes in major white matter tracts. RESULTS: Voxel-based lesion-symptom mapping identified multiple voxel clusters where the presence of white matter hyperintensities was associated with slower performance on the Trail Making Test part B. Clusters were located bilaterally in the forceps minor and anterior thalamic radiation. Region of interest-based Bayesian network analyses on lesion volumes within major white matter tracts depicted the same tracts as direct predictors for an impaired Trail Making Test part B performance. CONCLUSIONS: Our findings highlight damage to frontal interhemispheric and thalamic projection fiber tracts harboring frontal-subcortical neuronal circuits as a predictor for processing speed performance in age-related small vessel disease.},\n\tnumber = {22},\n\tjournal = {Neurology},\n\tauthor = {Duering, M. and Gesierich, B. and Seiler, S. and Pirpamer, L. and Gonik, M. and Hofer, E. and Jouvent, E. and Duchesnay, E. and Chabriat, H. and Ropele, S. and Schmidt, R. and Dichgans, M.},\n\tmonth = jun,\n\tyear = {2014},\n\tpmcid = {PMC4105258},\n\tpmid = {24793184},\n\tkeywords = {Aged, Female, Humans, Male, Middle Aged, Brain Mapping/instrumentation/methods, Brain/blood supply/*pathology/physiopathology, Cerebral Small Vessel Diseases/complications/*pathology/physiopathology, Cognition Disorders/etiology/*pathology/physiopathology, Leukoencephalopathies/etiology/*pathology/physiopathology, Trail Making Test, Brain Mapping, Brain, Cognition Disorders, Cerebral Small Vessel Diseases, Leukoencephalopathies},\n\tpages = {1946--50},\n}\n\n

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\n \n\n \n \n \n \n \n Magnetization transfer ratio relates to cognitive impairment in normal elderly.\n \n \n \n\n\n \n Seiler, S.; Pirpamer, L.; Hofer, E.; Duering, M.; Jouvent, E.; Fazekas, F.; Mangin, J. F.; Chabriat, H.; Dichgans, M.; Ropele, S.; and Schmidt, R.\n\n\n \n\n\n\n Front Aging Neurosci, 6: 263. 2014.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{seiler_magnetization_2014,\n\ttitle = {Magnetization transfer ratio relates to cognitive impairment in normal elderly},\n\tvolume = {6},\n\tissn = {1663-4365 (Print) 1663-4365 (Linking)},\n\tdoi = {10.3389/fnagi.2014.00263},\n\tabstract = {Magnetization transfer imaging (MTI) can detect microstructural brain tissue changes and may be helpful in determining age-related cerebral damage. We investigated the association between the magnetization transfer ratio (MTR) in gray and white matter (WM) and cognitive functioning in 355 participants of the Austrian stroke prevention family study (ASPS-Fam) aged 38-86 years. MTR maps were generated for the neocortex, deep gray matter structures, WM hyperintensities, and normal appearing WM (NAWM). Adjusted mixed models determined whole brain and lobar cortical MTR to be directly and significantly related to performance on tests of memory, executive function, and motor skills. There existed an almost linear dose-effect relationship. MTR of deep gray matter structures and NAWM correlated to executive functioning. All associations were independent of demographics, vascular risk factors, focal brain lesions, and cortex volume. Further research is needed to understand the basis of this association at the tissue level, and to determine the role of MTR in predicting cognitive decline and dementia.},\n\tjournal = {Front Aging Neurosci},\n\tauthor = {Seiler, S. and Pirpamer, L. and Hofer, E. and Duering, M. and Jouvent, E. and Fazekas, F. and Mangin, J. F. and Chabriat, H. and Dichgans, M. and Ropele, S. and Schmidt, R.},\n\tyear = {2014},\n\tpmcid = {PMC4174770},\n\tpmid = {25309438},\n\tkeywords = {cerebrovascular disease, dementia, magnetic resonance imaging, cognitive aging, magnetization transfer imaging, microstructural tissue damage},\n\tpages = {263},\n}\n\n

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\n \n\n \n \n \n \n \n In vivo high-resolution 7 Tesla MRI shows early and diffuse cortical alterations in CADASIL.\n \n \n \n\n\n \n De Guio, F.; Reyes, S.; Vignaud, A.; Duering, M.; Ropele, S.; Duchesnay, E.; Chabriat, H.; and Jouvent, E.\n\n\n \n\n\n\n PLoS One, 9(8): e106311. 2014.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{de_guio_vivo_2014,\n\ttitle = {In vivo high-resolution 7 {Tesla} {MRI} shows early and diffuse cortical alterations in {CADASIL}},\n\tvolume = {9},\n\tissn = {1932-6203 (Electronic) 1932-6203 (Linking)},\n\tdoi = {10.1371/journal.pone.0106311},\n\tabstract = {BACKGROUND AND PURPOSE: Recent data suggest that early symptoms may be related to cortex alterations in CADASIL (Cerebral Autosomal-Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy), a monogenic model of cerebral small vessel disease (SVD). The aim of this study was to investigate cortical alterations using both high-resolution T2* acquisitions obtained with 7 Tesla MRI and structural T1 images with 3 Tesla MRI in CADASIL patients with no or only mild symptomatology (modified Rankin's scale {\\textless}/=1 and Mini Mental State Examination (MMSE) {\\textgreater}/=24). METHODS: Complete reconstructions of the cortex using 7 Tesla T2* acquisitions with 0.7 mm isotropic resolution were obtained in 11 patients (52.1+/-13.2 years, 36\\% male) and 24 controls (54.8+/-11.0 years, 42\\% male). Seven Tesla T2* within the cortex and cortical thickness and morphology obtained from 3 Tesla images were compared between CADASIL and control subjects using general linear models. RESULTS: MMSE, brain volume, cortical thickness and global sulcal morphology did not differ between groups. By contrast, T2* measured by 7 Tesla MRI was significantly increased in frontal, parietal, occipital and cingulate cortices in patients after correction for multiple testing. These changes were not related to white matter lesions, lacunes or microhemorrhages in patients having no brain atrophy compared to controls. CONCLUSIONS: Seven Tesla MRI, by contrast to state of the art post-processing of 3 Tesla acquisitions, shows diffuse T2* alterations within the cortical mantle in CADASIL whose origin remains to be determined.},\n\tnumber = {8},\n\tjournal = {PLoS One},\n\tauthor = {De Guio, F. and Reyes, S. and Vignaud, A. and Duering, M. and Ropele, S. and Duchesnay, E. and Chabriat, H. and Jouvent, E.},\n\tyear = {2014},\n\tpmcid = {PMC4148432},\n\tpmid = {25165824},\n\tkeywords = {Adult, Female, Humans, Male, Middle Aged, Magnetic Resonance Imaging, Cerebral Cortex/*pathology, Case-Control Studies, Magnetic Resonance Imaging/*methods, CADASIL/*pathology, Organ Size, Cerebral Cortex, CADASIL},\n\tpages = {e106311},\n}\n\n

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\n \n\n \n \n \n \n \n Loss of venous integrity in cerebral small vessel disease: a 7-T MRI study in cerebral autosomal-dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL).\n \n \n \n\n\n \n De Guio, F.; Vignaud, A.; Ropele, S.; Duering, M.; Duchesnay, E.; Chabriat, H.; and Jouvent, E.\n\n\n \n\n\n\n Stroke, 45(7): 2124–6. July 2014.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{de_guio_loss_2014,\n\ttitle = {Loss of venous integrity in cerebral small vessel disease: a 7-{T} {MRI} study in cerebral autosomal-dominant arteriopathy with subcortical infarcts and leukoencephalopathy ({CADASIL})},\n\tvolume = {45},\n\tissn = {1524-4628 (Electronic) 0039-2499 (Linking)},\n\tdoi = {10.1161/STROKEAHA.114.005726},\n\tabstract = {BACKGROUND AND PURPOSE: Previous pathological studies in humans or in animal models have shown alterations of small arteries and veins within white matter lesions in cerebral small vessel disease. We aimed to evaluate in vivo, the integrity of the cerebral venous network using high-resolution MRI both within and outside white matter hyperintensities in cerebral autosomal-dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL). METHODS: High-resolution T2*-weighted images were obtained at 7-T in 13 CADASIL patients with no or only mild symptoms and 13 age- and sex-matched controls. Macroscopic veins were automatically counted in the centrum semiovale and compared between patients and controls. In addition, T2* was compared between groups in the normal-appearing white matter. RESULTS: Vein density was found lower in CADASIL patients compared with that in controls (-14.6\\% in patients, P{\\textless}0.001). This was detected both within and outside white matter hyperintensities. Mean T2*, that is presumably inversely related to the venous density, was also found increased in normal-appearing white matter of patients (+7.2\\%, P=0.006). All results were independent from the extent of white matter hyperintensities. CONCLUSIONS: A significant reduction in the number of visible veins was observed in the centrum semiovale of CADASIL patients both within and outside white matter hyperintensities, together with an increase of T2* in the normal-appearing white matter. Additional studies are needed to decipher the exact implication of such vasculature changes in the appearance of white matter lesions.},\n\tnumber = {7},\n\tjournal = {Stroke},\n\tauthor = {De Guio, F. and Vignaud, A. and Ropele, S. and Duering, M. and Duchesnay, E. and Chabriat, H. and Jouvent, E.},\n\tmonth = jul,\n\tyear = {2014},\n\tpmid = {24867926},\n\tkeywords = {Adult, Aged, Female, Humans, Male, Middle Aged, Magnetic Resonance Imaging, Cadasil, CADASIL/*pathology/physiopathology, magnetic resonance imaging, Cerebral Veins/*pathology/physiopathology, Cerebrum/*pathology/physiopathology, Magnetic Resonance Imaging/*instrumentation/methods, veins, CADASIL, Cerebral Veins, Cerebrum},\n\tpages = {2124--6},\n}\n\n

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\n \n\n \n \n \n \n \n ADC histograms from routine DWI for longitudinal studies in cerebral small vessel disease: a field study in CADASIL.\n \n \n \n\n\n \n Gunda, B.; Porcher, R.; Duering, M.; Guichard, J. P.; Mawet, J.; Jouvent, E.; Dichgans, M.; and Chabriat, H.\n\n\n \n\n\n\n PLoS One, 9(5): e97173. 2014.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{gunda_adc_2014,\n\ttitle = {{ADC} histograms from routine {DWI} for longitudinal studies in cerebral small vessel disease: a field study in {CADASIL}},\n\tvolume = {9},\n\tissn = {1932-6203 (Electronic) 1932-6203 (Linking)},\n\tdoi = {10.1371/journal.pone.0097173},\n\tabstract = {Diffusion tensor imaging (DTI) histogram metrics are correlated with clinical parameters in cerebral small vessel diseases (cSVD). Whether ADC histogram parameters derived from simple diffusion weighted imaging (DWI) can provide relevant markers for long term studies of cSVD remains unknown. CADASIL patients were evaluated by DWI and DTI in a large cohort study over a 6-year period. ADC histogram parameters were compared to those derived from mean diffusivity (MD) histograms in 280 patients using intra-class correlation and Bland-Altman plots. Impact of image corrections applied to ADC maps was assessed and a mixed effect model was used for analyzing the effects of scanner upgrades. The results showed that ADC histogram parameters are strongly correlated to MD histogram parameters and that image corrections have only limited influence on these results. Unexpectedly, scanner upgrades were found to have major effects on diffusion measures with DWI or DTI that can be even larger than those related to patients' characteristics. These data support that ADC histograms from daily used DWI can provide relevant parameters for assessing cSVD, but the variability related to scanner upgrades as regularly performed in clinical centers should be determined precisely for longitudinal and multicentric studies using diffusion MRI in cSVD.},\n\tnumber = {5},\n\tjournal = {PLoS One},\n\tauthor = {Gunda, B. and Porcher, R. and Duering, M. and Guichard, J. P. and Mawet, J. and Jouvent, E. and Dichgans, M. and Chabriat, H.},\n\tyear = {2014},\n\tpmcid = {PMC4018248},\n\tpmid = {24819368},\n\tkeywords = {Diffusion Magnetic Resonance Imaging, Female, Humans, Image Processing, Computer-Assisted, Male, Cohort Studies, *Image Processing, Computer-Assisted, Longitudinal Studies, *Diffusion Magnetic Resonance Imaging, CADASIL/*diagnosis, Probability, CADASIL},\n\tpages = {e97173},\n}\n\n

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\n \n\n \n \n \n \n \n Genome-wide genotyping demonstrates a polygenic risk score associated with white matter hyperintensity volume in CADASIL.\n \n \n \n\n\n \n Opherk, C.; Gonik, M.; Duering, M.; Malik, R.; Jouvent, E.; Herve, D.; Adib-Samii, P.; Bevan, S.; Pianese, L.; Silvestri, S.; Dotti, M. T.; De Stefano, N.; Liem, M.; Boon, E. M.; Pescini, F.; Pachai, C.; Bracoud, L.; Muller-Myhsok, B.; Meitinger, T.; Rost, N.; Pantoni, L.; Lesnik Oberstein, S.; Federico, A.; Ragno, M.; Markus, H. S.; Tournier-Lasserve, E.; Rosand, J.; Chabriat, H.; and Dichgans, M.\n\n\n \n\n\n\n Stroke, 45(4): 968–72. April 2014.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{opherk_genome-wide_2014,\n\ttitle = {Genome-wide genotyping demonstrates a polygenic risk score associated with white matter hyperintensity volume in {CADASIL}},\n\tvolume = {45},\n\tissn = {1524-4628 (Electronic) 0039-2499 (Linking)},\n\tdoi = {10.1161/STROKEAHA.113.004461},\n\tabstract = {BACKGROUND AND PURPOSE: White matter hyperintensities (WMH) on MRI are a quantitative marker for sporadic cerebral small vessel disease and are highly heritable. To date, large-scale genetic studies have identified only a single locus influencing WMH burden. This might in part relate to biological heterogeneity of sporadic WMH. The current study searched for genetic modifiers of WMH volume in cerebral autosomal-dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL), a monogenic small vessel disease. METHODS: We performed a genome-wide association study to identify quantitative trait loci for WMH volume by combining data from 517 CADASIL patients collected through 7 centers across Europe. WMH volumes were centrally analyzed and quantified on fluid attenuated inversion recovery images. Genotyping was performed using the Affymetrix 6.0 platform. Individuals were assigned to 2 distinct genetic clusters (cluster 1 and cluster 2) based on their genetic background. RESULTS: Four hundred sixty-six patients entered the final genome-wide association study analysis. The phenotypic variance of WMH burden in CADASIL explained by all single nucleotide polymorphisms in cluster 1 was 0.85 (SE=0.21), suggesting a substantial genetic contribution. Using cluster 1 as derivation and cluster 2 as a validation sample, a polygenic score was significantly associated with WMH burden (P=0.001) after correction for age, sex, and vascular risk factors. No single nucleotide polymorphism reached genome-wide significance. CONCLUSIONS: We found a polygenic score to be associated with WMH volume in CADASIL subjects. Our findings suggest that multiple variants with small effects influence WMH burden in CADASIL. The identification of these variants and the biological pathways involved will provide insights into the pathophysiology of white matter disease in CADASIL and possibly small vessel disease in general.},\n\tnumber = {4},\n\tjournal = {Stroke},\n\tauthor = {Opherk, C. and Gonik, M. and Duering, M. and Malik, R. and Jouvent, E. and Herve, D. and Adib-Samii, P. and Bevan, S. and Pianese, L. and Silvestri, S. and Dotti, M. T. and De Stefano, N. and Liem, M. and Boon, E. M. and Pescini, F. and Pachai, C. and Bracoud, L. and Muller-Myhsok, B. and Meitinger, T. and Rost, N. and Pantoni, L. and Lesnik Oberstein, S. and Federico, A. and Ragno, M. and Markus, H. S. and Tournier-Lasserve, E. and Rosand, J. and Chabriat, H. and Dichgans, M.},\n\tmonth = apr,\n\tyear = {2014},\n\tpmid = {24578207},\n\tkeywords = {Adult, Aged, Female, Humans, Male, Middle Aged, Magnetic Resonance Imaging, Genome-Wide Association Study, Risk Factors, Cadasil, Genetic Predisposition to Disease, *Genome-Wide Association Study, cerebral small vessel diseases, *Models, Genetic, CADASIL/epidemiology/*genetics/pathology, Genetic Predisposition to Disease/epidemiology/*genetics, genetics, genome-wide association study, Hypertension/epidemiology/genetics/pathology, leukoaraiosis, Leukoencephalopathies/epidemiology/*genetics/pathology, Quantitative Trait Loci, CADASIL, Leukoencephalopathies, Hypertension, Models, Genetic},\n\tpages = {968--72},\n}\n\n

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\n \n\n \n \n \n \n \n Dilated perivascular spaces in small-vessel disease: a study in CADASIL.\n \n \n \n\n\n \n Yao, M.; Herve, D.; Jouvent, E.; Duering, M.; Reyes, S.; Godin, O.; Guichard, J. P.; Dichgans, M.; and Chabriat, H.\n\n\n \n\n\n\n Cerebrovasc Dis, 37(3): 155–63. 2014.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{yao_dilated_2014,\n\ttitle = {Dilated perivascular spaces in small-vessel disease: a study in {CADASIL}},\n\tvolume = {37},\n\tissn = {1421-9786 (Electronic) 1015-9770 (Linking)},\n\tdoi = {10.1159/000356982},\n\tabstract = {BACKGROUND AND AIM: Dilated perivascular spaces (dPVS) have previously been associated with aging and hypertension-related cerebral microangiopathy. However, their risk factors, radiological features and clinical relevance have been poorly evaluated in CADASIL (cerebral autosomal-dominant arteriopathy with subcortical infarcts and leukoencephalopathy), a unique model to investigate the pathophysiology of ischemic small-vessel disease. The purpose of this study was to investigate these different aspects in a large cohort of patients with this disorder. METHODS: Demographic and MRI data of 344 patients from a prospective cohort study were analyzed. The severity of dPVS was evaluated separately in the anterior temporal lobes, subinsular areas, basal ganglia and white matter, using validated semiquantitative scales. Logistic and multiple linear regression models were used to determine the risk factors associated with the severity of dPVS in these different regions and their relationships with cognition, disability and the MRI markers of the disease (white matter hyperintensities (WMH) lacunar infarcts, microbleeds and brain parenchymal fraction (BPF)). RESULTS: The severity of dPVS was found to increase with age regardless of cerebral area (p{\\textless}0.001). In contrast with dPVS in other locations, the severity of dPVS in the temporal lobes or subinsular areas was also found strongly and specifically related to the extent of WMH (p{\\textless}0.001). Conversely, no significant association was detected with lacunar volume, number of microbleeds or BPF. A high degree of dPVS in the white matter was associated with lower cognitive performances independently of age and other MRI markers of the disease including BPF (p{\\textless}/=0.04). CONCLUSIONS: In CADASIL, the progression of the hereditary microangiopathy with aging may promote the dilation of perivascular spaces throughout the whole brain but with variable extent according to cerebral location. In temporal lobes and subinsular areas, dPVS are common MRI features and may share a similar pathogenesis with the extension of WMH during the course of the disease. dPVS may also participate in the development of cognitive decline in this model of small-vessel disease, and their large number in white matter may alert clinicians to a higher risk of cognitive decline in CADASIL.},\n\tnumber = {3},\n\tjournal = {Cerebrovasc Dis},\n\tauthor = {Yao, M. and Herve, D. and Jouvent, E. and Duering, M. and Reyes, S. and Godin, O. and Guichard, J. P. and Dichgans, M. and Chabriat, H.},\n\tyear = {2014},\n\tpmid = {24503815},\n\tkeywords = {Adult, Aged, Female, Humans, Male, Middle Aged, Prospective Studies, Aged, 80 and over, Magnetic Resonance Imaging, Young Adult, Risk Factors, Brain/*pathology, Imaging, Three-Dimensional, Severity of Illness Index, Organ Size, Basal Ganglia/pathology, CADASIL/complications/*pathology/psychology, Cerebral Hemorrhage/etiology/pathology, Cognition Disorders/etiology, Dilatation, Pathologic/etiology, Stroke, Lacunar/etiology/pathology, Temporal Lobe/pathology, Brain, Cognition Disorders, Cerebral Hemorrhage, Temporal Lobe, CADASIL, Stroke, Lacunar, Basal Ganglia, Dilatation, Pathologic},\n\tpages = {155--63},\n}\n\n

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\n BACKGROUND AND AIM: Dilated perivascular spaces (dPVS) have previously been associated with aging and hypertension-related cerebral microangiopathy. However, their risk factors, radiological features and clinical relevance have been poorly evaluated in CADASIL (cerebral autosomal-dominant arteriopathy with subcortical infarcts and leukoencephalopathy), a unique model to investigate the pathophysiology of ischemic small-vessel disease. The purpose of this study was to investigate these different aspects in a large cohort of patients with this disorder. METHODS: Demographic and MRI data of 344 patients from a prospective cohort study were analyzed. The severity of dPVS was evaluated separately in the anterior temporal lobes, subinsular areas, basal ganglia and white matter, using validated semiquantitative scales. Logistic and multiple linear regression models were used to determine the risk factors associated with the severity of dPVS in these different regions and their relationships with cognition, disability and the MRI markers of the disease (white matter hyperintensities (WMH) lacunar infarcts, microbleeds and brain parenchymal fraction (BPF)). RESULTS: The severity of dPVS was found to increase with age regardless of cerebral area (p\\textless0.001). In contrast with dPVS in other locations, the severity of dPVS in the temporal lobes or subinsular areas was also found strongly and specifically related to the extent of WMH (p\\textless0.001). Conversely, no significant association was detected with lacunar volume, number of microbleeds or BPF. A high degree of dPVS in the white matter was associated with lower cognitive performances independently of age and other MRI markers of the disease including BPF (p\\textless/=0.04). CONCLUSIONS: In CADASIL, the progression of the hereditary microangiopathy with aging may promote the dilation of perivascular spaces throughout the whole brain but with variable extent according to cerebral location. In temporal lobes and subinsular areas, dPVS are common MRI features and may share a similar pathogenesis with the extension of WMH during the course of the disease. dPVS may also participate in the development of cognitive decline in this model of small-vessel disease, and their large number in white matter may alert clinicians to a higher risk of cognitive decline in CADASIL.\n

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\n \n\n \n \n \n \n \n Decreased T1 contrast between gray matter and normal-appearing white matter in CADASIL.\n \n \n \n\n\n \n De Guio, F.; Reyes, S.; Duering, M.; Pirpamer, L.; Chabriat, H.; and Jouvent, E.\n\n\n \n\n\n\n AJNR Am J Neuroradiol, 35(1): 72–6. January 2014.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{de_guio_decreased_2014,\n\ttitle = {Decreased {T1} contrast between gray matter and normal-appearing white matter in {CADASIL}},\n\tvolume = {35},\n\tissn = {1936-959X (Electronic) 0195-6108 (Linking)},\n\tdoi = {10.3174/ajnr.A3639},\n\tabstract = {BACKGROUND AND PURPOSE: CADASIL is the most frequent hereditary small-vessel disease of the brain. The clinical impact of various MR imaging markers has been repeatedly studied in this disorder, but alterations of contrast between gray matter and normal-appearing white matter remain unknown. The aim of this study was to evaluate the contrast alterations between gray matter and normal-appearing white matter on T1-weighted images in patients with CADASIL compared with healthy subjects. MATERIALS AND METHODS: Contrast between gray matter and normal-appearing white matter was assessed by using histogram analyses of 3D T1 high-resolution MR imaging in 23 patients with CADASIL at the initial stage of the disease (Mini-Mental State Examination score {\\textgreater} 24 and modified Rankin scale score {\\textless}/= 1; mean age, 53.5 +/- 11.1 years) and 30 age- and sex-matched controls. RESULTS: T1 contrast between gray matter and normal-appearing white matter was significantly reduced in patients compared with age- and sex-matched controls (patients: 1.35 +/- 0.08 versus controls: 1.43 +/- 0.04, P {\\textless} 10(-5)). This reduction was mainly driven by a signal decrease in normal-appearing white matter. Contrast loss was strongly related to the volume of white matter hyperintensities. CONCLUSIONS: Conventional 3D T1 imaging shows significant loss of contrast between gray matter and normal-appearing white matter in CADASIL. This probably reflects tissue changes in normal-appearing white matter outside signal abnormalities on T2 or FLAIR sequences. These contrast alterations should be taken into account for image interpretation and postprocessing.},\n\tnumber = {1},\n\tjournal = {AJNR Am J Neuroradiol},\n\tauthor = {De Guio, F. and Reyes, S. and Duering, M. and Pirpamer, L. and Chabriat, H. and Jouvent, E.},\n\tmonth = jan,\n\tyear = {2014},\n\tpmid = {23868154},\n\tpmcid = {PMC7966464},\n\tkeywords = {Adult, Aged, Female, Humans, Male, Middle Aged, Magnetic Resonance Imaging, Nerve Fibers, Myelinated/*pathology, Magnetic Resonance Imaging/*methods, Brain/*pathology, CADASIL/*pathology, Neurons/*pathology, Brain, CADASIL, Nerve Fibers, Myelinated, Neurons},\n\tpages = {72--6},\n}\n\n

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\n \n\n \n \n \n \n \n White matter pathology and disconnection in the frontal lobe in cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL).\n \n \n \n\n\n \n Craggs, L. J.; Yamamoto, Y.; Ihara, M.; Fenwick, R.; Burke, M.; Oakley, A. E.; Roeber, S.; Duering, M.; Kretzschmar, H.; and Kalaria, R. N.\n\n\n \n\n\n\n Neuropathol Appl Neurobiol, 40(5): 591–602. August 2014.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{craggs_white_2014,\n\ttitle = {White matter pathology and disconnection in the frontal lobe in cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy ({CADASIL})},\n\tvolume = {40},\n\tissn = {1365-2990 (Electronic) 0305-1846 (Linking)},\n\tdoi = {10.1111/nan.12073},\n\tabstract = {BACKGROUND: Magnetic resonance imaging indicates diffuse white matter (WM) changes are associated with cognitive impairment in cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL). We examined whether the distribution of axonal abnormalities is related to microvascular pathology in the underlying WM. METHODS: We used post-mortem brains from CADASIL subjects and similar age cognitively normal controls to examine WM axonal changes, microvascular pathology, and glial reaction in up to 16 different regions extending rostro-caudally through the cerebrum. Using unbiased stereological methods, we estimated length densities of affected axons immunostained with neurofilament antibody SMI32. Standard immunohistochemistry was used to assess amyloid precursor protein immunoreactivity per WM area. To relate WM changes to microvascular pathology, we also determined the sclerotic index (SI) in WM arterioles. RESULTS: The degree of WM pathology consistently scored higher across all brain regions in CADASIL subjects (P{\\textless}0.01) with the WM underlying the primary motor cortex exhibiting the most severe change. SMI32 immunoreactive axons in CADASIL were invariably increased compared with controls (P{\\textless}0.01), with most prominent axonal abnormalities observed in the frontal WM (P{\\textless}0.05). The SIs of arterioles in CADASIL were increased by 25-45\\% throughout the regions assessed, with the highest change in the mid-frontal region (P=0.000). CONCLUSIONS: Our results suggest disruption of either cortico-cortical or subcortical-cortical networks in the WM of the frontal lobe that may explain motor deficits and executive dysfunction in CADASIL. Widespread WM axonal changes arise from differential stenosis and sclerosis of arterioles in the WM of CADASIL subjects, possibly affecting some axons of projection neurones connecting to targets in the subcortical structures.},\n\tnumber = {5},\n\tjournal = {Neuropathol Appl Neurobiol},\n\tauthor = {Craggs, L. J. and Yamamoto, Y. and Ihara, M. and Fenwick, R. and Burke, M. and Oakley, A. E. and Roeber, S. and Duering, M. and Kretzschmar, H. and Kalaria, R. N.},\n\tmonth = aug,\n\tyear = {2014},\n\tpmcid = {PMC4282433},\n\tpmid = {23844775},\n\tkeywords = {cognitive impairment, Adult, Aged, Female, Humans, Male, Middle Aged, Axons, stroke, Cadasil, white matter changes, Amyloid beta-Protein Precursor/metabolism, Axons/metabolism/*pathology, Brain/metabolism/pathology, CADASIL/metabolism/*pathology, disconnection, Frontal Lobe/metabolism/*pathology, Nerve Net/pathology, vascular dementia, White Matter/blood supply/metabolism/*pathology, Brain, White Matter, Frontal Lobe, Amyloid beta-Protein Precursor, CADASIL, Nerve Net},\n\tpages = {591--602},\n}\n\n

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\n \n\n \n \n \n \n \n The Determinants of Dementia After Stroke (DEDEMAS) Study: protocol and pilot data.\n \n \n \n\n\n \n Wollenweber, F. A.; Zietemann, V.; Rominger, A.; Opherk, C.; Bayer-Karpinska, A.; Gschwendtner, A.; Coloma Andrews, L.; Burger, K.; Duering, M.; and Dichgans, M.\n\n\n \n\n\n\n Int J Stroke, 9(3): 387–92. April 2014.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{wollenweber_determinants_2014,\n\ttitle = {The {Determinants} of {Dementia} {After} {Stroke} ({DEDEMAS}) {Study}: protocol and pilot data},\n\tvolume = {9},\n\tissn = {1747-4949 (Electronic) 1747-4930 (Linking)},\n\tdoi = {10.1111/ijs.12092},\n\tabstract = {RATIONALE: About 20\\% of stroke patients develop dementia within a few months after their event, but the determinants and mechanisms of poststroke dementia are insufficiently understood. AIMS: To identify and characterize the determinants of cognitive impairment poststroke. DESIGN: Observational prospective study in patients with acute stroke and no prior dementia. Six hundred subjects will be characterized by detailed interview, standardized clinical examinations, biometric measures (intima-media thickness, waist-hip ratio, and ankle-brachial index), multimodal imaging (magnetic resonance imaging, fluorodeoxyglucose-positron emission tomography (FDG-PET), amyloid-positron emission tomography (amyloid-PET), and retinal imaging), analysis of biomarkers derived from blood and cerebrospinal fluid, and detailed cognitive testing at repeat time points. Patients will be followed for five-years with a total of five personal visits and three telephone interviews. STUDY OUTCOMES: Primary end-point is the occurrence of poststroke dementia. Secondary end-points include poststroke cognitive impairment-no dementia, stroke recurrence, and death. Predictive factors for poststroke dementia will be identified by multiple Cox proportional-hazards model. RESULTS: Baseline characteristics of the first 71 patients (study inclusion between May 2011 and August 2012) are as follows: median age, 70 years (interquartile range, 65-75); female gender, 25 (35\\%); median National Institutes of Health Stroke Scale at admission, 2 (1-4); and etiological stroke subtypes according to TOAST classification, 15\\% large artery disease, 18\\% small vessel disease, 35\\% cardioembolic, and 32\\% undetermined or multiple competing etiologies. DISCUSSION: This study will provide insights into the mechanisms of poststroke dementia and hold the potential to identify novel diagnostic markers and targets for preventive therapies. The study is registered at http://www.clinicaltrials.gov (NCT01334749) and will be extended as a multicenter study starting 2013.},\n\tnumber = {3},\n\tjournal = {Int J Stroke},\n\tauthor = {Wollenweber, F. A. and Zietemann, V. and Rominger, A. and Opherk, C. and Bayer-Karpinska, A. and Gschwendtner, A. and Coloma Andrews, L. and Burger, K. and Duering, M. and Dichgans, M.},\n\tmonth = apr,\n\tyear = {2014},\n\tpmid = {23834337},\n\tkeywords = {Stroke, Aged, Female, Humans, Male, Magnetic Resonance Imaging, Cohort Studies, Neuropsychological Tests, Dementia, Positron-Emission Tomography, Amyloid/metabolism, Ankle Brachial Index, Carotid Intima-Media Thickness, Dementia/*diagnosis/*etiology/therapy, Fluorodeoxyglucose F18, Neurologic Examination, Pilot Projects, poststroke dementia, poststroke dementia epidemiology, Retina/pathology, stroke-related outcomes, Stroke/*complications, Treatment Outcome, Waist-Hip Ratio, Amyloid, Retina},\n\tpages = {387--92},\n}\n\n

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\n RATIONALE: About 20% of stroke patients develop dementia within a few months after their event, but the determinants and mechanisms of poststroke dementia are insufficiently understood. AIMS: To identify and characterize the determinants of cognitive impairment poststroke. DESIGN: Observational prospective study in patients with acute stroke and no prior dementia. Six hundred subjects will be characterized by detailed interview, standardized clinical examinations, biometric measures (intima-media thickness, waist-hip ratio, and ankle-brachial index), multimodal imaging (magnetic resonance imaging, fluorodeoxyglucose-positron emission tomography (FDG-PET), amyloid-positron emission tomography (amyloid-PET), and retinal imaging), analysis of biomarkers derived from blood and cerebrospinal fluid, and detailed cognitive testing at repeat time points. Patients will be followed for five-years with a total of five personal visits and three telephone interviews. STUDY OUTCOMES: Primary end-point is the occurrence of poststroke dementia. Secondary end-points include poststroke cognitive impairment-no dementia, stroke recurrence, and death. Predictive factors for poststroke dementia will be identified by multiple Cox proportional-hazards model. RESULTS: Baseline characteristics of the first 71 patients (study inclusion between May 2011 and August 2012) are as follows: median age, 70 years (interquartile range, 65-75); female gender, 25 (35%); median National Institutes of Health Stroke Scale at admission, 2 (1-4); and etiological stroke subtypes according to TOAST classification, 15% large artery disease, 18% small vessel disease, 35% cardioembolic, and 32% undetermined or multiple competing etiologies. DISCUSSION: This study will provide insights into the mechanisms of poststroke dementia and hold the potential to identify novel diagnostic markers and targets for preventive therapies. The study is registered at http://www.clinicaltrials.gov (NCT01334749) and will be extended as a multicenter study starting 2013.\n

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\n \n\n \n \n \n \n \n Incident lacunes preferentially localize to the edge of white matter hyperintensities: insights into the pathophysiology of cerebral small vessel disease.\n \n \n \n\n\n \n Duering, M.; Csanadi, E.; Gesierich, B.; Jouvent, E.; Herve, D.; Seiler, S.; Belaroussi, B.; Ropele, S.; Schmidt, R.; Chabriat, H.; and Dichgans, M.\n\n\n \n\n\n\n Brain, 136(Pt 9): 2717–26. September 2013.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{duering_incident_2013,\n\ttitle = {Incident lacunes preferentially localize to the edge of white matter hyperintensities: insights into the pathophysiology of cerebral small vessel disease},\n\tvolume = {136},\n\tissn = {1460-2156 (Electronic) 0006-8950 (Linking)},\n\tdoi = {10.1093/brain/awt184},\n\tabstract = {White matter hyperintensities and lacunes are among the most frequent abnormalities on brain magnetic resonance imaging. They are commonly related to cerebral small vessel disease and associated with both stroke and dementia. We examined the spatial relationships between incident lacunes and white matter hyperintensities and related these findings to information on vascular anatomy to study possible mechanistic links between the two lesion types. Two hundred and seventy-six patients with cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL), a genetically defined small vessel disease with mutations in the NOTCH3 gene were followed with magnetic resonance imaging over a total of 633 patient years. Using difference images and Jacobian maps from registered images we identified 104 incident lacunes. The majority (n = 95; 91.3\\%) of lacunes developed at the edge of a white matter hyperintensity whereas few lacunes were found to develop fully within (n = 6; 5.8\\%) or outside (n = 3; 2.9\\%) white matter hyperintensities. Adding information on vascular anatomy revealed that the majority of incident lacunes developed proximal to a white matter hyperintensity along the course of perforating vessels supplying the respective brain region. We further studied the spatial relationship between prevalent lacunes and white matter hyperintensities both in 365 patients with CADASIL and in 588 elderly subjects from the Austrian Stroke Prevention Study. The results were consistent with the results for incident lacunes. Lesion prevalence maps in different disease stages showed a spread of lesions towards subcortical regions in both cohorts. Our findings suggest that the mechanisms of lacunes and white matter hyperintensities are intimately connected and identify the edge of white matter hyperintensities as a predilection site for lacunes. Our observations further support and refine the concept of the white matter hyperintensity penumbra.},\n\tnumber = {Pt 9},\n\tjournal = {Brain},\n\tauthor = {Duering, M. and Csanadi, E. and Gesierich, B. and Jouvent, E. and Herve, D. and Seiler, S. and Belaroussi, B. and Ropele, S. and Schmidt, R. and Chabriat, H. and Dichgans, M.},\n\tmonth = sep,\n\tyear = {2013},\n\tpmid = {23864274},\n\tkeywords = {Adult, Aged, Disease Progression, Female, Humans, Male, Middle Aged, cerebral small vessel disease, Magnetic Resonance Imaging, Young Adult, Receptor, Notch3, CADASIL/*complications/epidemiology, Cohort Studies, lacunes, Leukoencephalopathies/*epidemiology/*etiology/genetics, Nerve Fibers, Myelinated/pathology, pathomechanisms, Receptors, Notch/genetics, small vessel stroke, Stroke, Lacunar/*epidemiology/*etiology/pathology, white matter hyperintensities, CADASIL, Leukoencephalopathies, Nerve Fibers, Myelinated, Receptors, Notch, Stroke, Lacunar},\n\tpages = {2717--26},\n}\n\n

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\n \n\n \n \n \n \n \n Identification of a strategic brain network underlying processing speed deficits in vascular cognitive impairment.\n \n \n \n\n\n \n Duering, M.; Gonik, M.; Malik, R.; Zieren, N.; Reyes, S.; Jouvent, E.; Herve, D.; Gschwendtner, A.; Opherk, C.; Chabriat, H.; and Dichgans, M.\n\n\n \n\n\n\n Neuroimage, 66: 177–83. February 2013.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{duering_identification_2013,\n\ttitle = {Identification of a strategic brain network underlying processing speed deficits in vascular cognitive impairment},\n\tvolume = {66},\n\tissn = {1095-9572 (Electronic) 1053-8119 (Linking)},\n\tdoi = {10.1016/j.neuroimage.2012.10.084},\n\tabstract = {Patients with vascular cognitive impairment (VCI) commonly exhibit deficits in processing speed. This has been attributed to a disruption of frontal-subcortical neuronal circuits by ischemic lesions, but the exact mechanisms and underlying anatomical structures are poorly understood. We set out to identify a strategic brain network for processing speed by applying graph-based data-mining techniques to MRI lesion maps from patients with small vessel disease. We studied 235 patients with CADASIL, a genetic small vessel disease causing pure VCI. Using a probabilistic atlas in standard space we first determined the regional volumes of white matter hyperintensities (WMH) and lacunar lesions (LL) within major white matter tracts. Conditional dependencies between the regional lesion volumes and processing speed were then examined using Bayesian network analysis. Exploratory analysis identified a network of five imaging variables as the best determinant of processing speed. The network included LL in the left anterior thalamic radiation and the left cingulum as well as WMH in the left forceps minor, the left parahippocampal white matter and the left corticospinal tract. Together these variables explained 34\\% of the total variance in the processing speed score. Structural equation modeling confirmed the findings obtained from the Bayesian models. In summary, using graph-based models we identified a strategic brain network having the highest predictive value for processing speed in our cohort of patients with pure small vessel disease. Our findings confirm and extend previous results showing a role of frontal-subcortical neuronal circuits, in particular dorsolateral prefrontal and cingulate circuits, in VCI.},\n\tjournal = {Neuroimage},\n\tauthor = {Duering, M. and Gonik, M. and Malik, R. and Zieren, N. and Reyes, S. and Jouvent, E. and Herve, D. and Gschwendtner, A. and Opherk, C. and Chabriat, H. and Dichgans, M.},\n\tmonth = feb,\n\tyear = {2013},\n\tpmid = {23153965},\n\tkeywords = {Small vessel disease, Adult, Aged, Female, Humans, Male, Middle Aged, Magnetic Resonance Imaging, Young Adult, Bayes Theorem, Brain/*pathology/physiopathology, CADASIL/*pathology/physiopathology, Lacunar lesions, Neural Pathways/*pathology/physiopathology, Processing speed, Vascular cognitive impairment, White matter hyperintensities, Brain, CADASIL, Neural Pathways},\n\tpages = {177--83},\n}\n\n

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\n \n\n \n \n \n \n \n Education modifies the relation of vascular pathology to cognitive function: cognitive reserve in cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy.\n \n \n \n\n\n \n Zieren, N.; Duering, M.; Peters, N.; Reyes, S.; Jouvent, E.; Herve, D.; Gschwendtner, A.; Mewald, Y.; Opherk, C.; Chabriat, H.; and Dichgans, M.\n\n\n \n\n\n\n Neurobiol Aging, 34(2): 400–7. February 2013.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{zieren_education_2013,\n\ttitle = {Education modifies the relation of vascular pathology to cognitive function: cognitive reserve in cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy},\n\tvolume = {34},\n\tissn = {1558-1497 (Electronic) 0197-4580 (Linking)},\n\tdoi = {10.1016/j.neurobiolaging.2012.04.019},\n\tabstract = {A clinical impact of cognitive reserve (CR) has been demonstrated in Alzheimer's disease, whereas its role in vascular cognitive impairment (VCI) is largely unknown. In this study, we investigated the impact of CR in patients with cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL), a genetic variant of pure VCI. A total of 247 NOTCH3 mutation carriers from a two-center study were investigated using detailed neuropsychological and neuroimaging protocols. CR was operationalized as years of formal education. Brain pathology was assessed by MRI using normalized brain volume and lacunar lesion volume as proxies. Multivariate analyses were done for each structural measure with scores of processing speed, executive function, and memory as dependent variables. Additional linear regression models were conducted with interaction terms for education x brain volume and education x lacunar lesion volume. Education had an independent impact on cognitive performance in subjects with mild and moderate degrees of brain pathology, whereas there was no significant influence of education on cognition in patients with severe MRI changes. This interaction was found for processing speed, the cognitive domain most impaired in our patients. Our findings demonstrate an interaction of education and brain pathology in regard to cognitive impairment: the effect of education seems most pronounced in early disease stages but may ultimately be overwhelmed by the pathological changes. The results extend the concept of CR to VCI.},\n\tnumber = {2},\n\tjournal = {Neurobiol Aging},\n\tauthor = {Zieren, N. and Duering, M. and Peters, N. and Reyes, S. and Jouvent, E. and Herve, D. and Gschwendtner, A. and Mewald, Y. and Opherk, C. and Chabriat, H. and Dichgans, M.},\n\tmonth = feb,\n\tyear = {2013},\n\tpmid = {22626524},\n\tkeywords = {Cognition, Adult, Aged, Female, Humans, Male, Middle Aged, Prospective Studies, Magnetic Resonance Imaging, Brain/*pathology/physiopathology, *Cognitive Reserve, CADASIL/*pathology/physiopathology/psychology, Educational Status, Executive Function, Memory, Neuropsychological Tests, Brain, CADASIL, Cognitive Reserve},\n\tpages = {400--7},\n}\n\n

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\n \n\n \n \n \n \n \n Impact of regional cortical and subcortical changes on processing speed in cerebral small vessel disease.\n \n \n \n\n\n \n Righart, R.; Duering, M.; Gonik, M.; Jouvent, E.; Reyes, S.; Herve, D.; Chabriat, H.; and Dichgans, M.\n\n\n \n\n\n\n Neuroimage Clin, 2: 854–61. 2013.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{righart_impact_2013,\n\ttitle = {Impact of regional cortical and subcortical changes on processing speed in cerebral small vessel disease},\n\tvolume = {2},\n\tissn = {2213-1582 (Print) 2213-1582 (Linking)},\n\tdoi = {10.1016/j.nicl.2013.06.006},\n\tabstract = {Slowed processing speed is common in elderly subjects and frequently related to cerebral small vessel disease. Previous studies have demonstrated associations between processing speed and subcortical ischemic lesions as well as cortical alterations but the precise functional-anatomical relationships remain poorly understood. Here we assessed the impact of both cortical and subcortical changes on processing speed by measuring regional cortical thickness and regional lesion volumes within distinct white-matter tracts. To limit confounding effects from age-related pathologies we studied patients with CADASIL, a genetic small vessel disease. General linear model analysis revealed significant associations between cortical thickness in the medial frontal and occipito-temporal cortex and processing speed. Bayesian network analysis showed a robust conditional dependency between the volume of lacunar lesions in the left anterior thalamic radiation and cortical thickness of the left medial frontal cortex, and between thickness of the left medial frontal cortex and processing speed, whereas there was no direct dependency between lesion volumes in the left anterior thalamic radiation and processing speed. Our results suggest that the medial frontal cortex has an intermediate position between lacunar lesions in the anterior thalamic radiation and deficits in processing speed. In contrast, we did not observe such a relationship for the occipito-temporal region. These findings reinforce the key role of frontal-subcortical circuits in cognitive impairment resulting from cerebral small vessel disease.},\n\tjournal = {Neuroimage Clin},\n\tauthor = {Righart, R. and Duering, M. and Gonik, M. and Jouvent, E. and Reyes, S. and Herve, D. and Chabriat, H. and Dichgans, M.},\n\tyear = {2013},\n\tpmcid = {PMC3777834},\n\tpmid = {24179837},\n\tkeywords = {Small vessel disease, Lacunar lesions, Processing speed, ATR, anterior thalamic radiation, Cortical thickness, LL, lacunar lesions, Medial frontal cortex, MFC, medial frontal cortex, OTC, occipito-temporal cortex, SVD, small vessel disease, WMH, white-matter hyperintensities},\n\tpages = {854--61},\n}\n\n

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\n \n\n \n \n \n \n \n Neuroimaging standards for research into small vessel disease and its contribution to ageing and neurodegeneration.\n \n \n \n\n\n \n Wardlaw, J. M.; Smith, E. E.; Biessels, G. J.; Cordonnier, C.; Fazekas, F.; Frayne, R.; Lindley, R. I.; O'Brien, J. T.; Barkhof, F.; Benavente, O. R.; Black, S. E.; Brayne, C.; Breteler, M.; Chabriat, H.; Decarli, C.; de Leeuw, F. E.; Doubal, F.; Duering, M.; Fox, N. C.; Greenberg, S.; Hachinski, V.; Kilimann, I.; Mok, V.; Oostenbrugge, R.; Pantoni, L.; Speck, O.; Stephan, B. C.; Teipel, S.; Viswanathan, A.; Werring, D.; Chen, C.; Smith, C.; van Buchem, M.; Norrving, B.; Gorelick, P. B.; Dichgans, M.; and for ReportIng Vascular changes on nEuroimaging , S. T.\n\n\n \n\n\n\n Lancet Neurol, 12(8): 822–38. August 2013.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{wardlaw_neuroimaging_2013,\n\ttitle = {Neuroimaging standards for research into small vessel disease and its contribution to ageing and neurodegeneration},\n\tvolume = {12},\n\tissn = {1474-4465 (Electronic) 1474-4422 (Linking)},\n\tdoi = {10.1016/S1474-4422(13)70124-8},\n\tabstract = {Cerebral small vessel disease (SVD) is a common accompaniment of ageing. Features seen on neuroimaging include recent small subcortical infarcts, lacunes, white matter hyperintensities, perivascular spaces, microbleeds, and brain atrophy. SVD can present as a stroke or cognitive decline, or can have few or no symptoms. SVD frequently coexists with neurodegenerative disease, and can exacerbate cognitive deficits, physical disabilities, and other symptoms of neurodegeneration. Terminology and definitions for imaging the features of SVD vary widely, which is also true for protocols for image acquisition and image analysis. This lack of consistency hampers progress in identifying the contribution of SVD to the pathophysiology and clinical features of common neurodegenerative diseases. We are an international working group from the Centres of Excellence in Neurodegeneration. We completed a structured process to develop definitions and imaging standards for markers and consequences of SVD. We aimed to achieve the following: first, to provide a common advisory about terms and definitions for features visible on MRI; second, to suggest minimum standards for image acquisition and analysis; third, to agree on standards for scientific reporting of changes related to SVD on neuroimaging; and fourth, to review emerging imaging methods for detection and quantification of preclinical manifestations of SVD. Our findings and recommendations apply to research studies, and can be used in the clinical setting to standardise image interpretation, acquisition, and reporting. This Position Paper summarises the main outcomes of this international effort to provide the STandards for ReportIng Vascular changes on nEuroimaging (STRIVE).},\n\tnumber = {8},\n\tjournal = {Lancet Neurol},\n\tauthor = {Wardlaw, J. M. and Smith, E. E. and Biessels, G. J. and Cordonnier, C. and Fazekas, F. and Frayne, R. and Lindley, R. I. and O'Brien, J. T. and Barkhof, F. and Benavente, O. R. and Black, S. E. and Brayne, C. and Breteler, M. and Chabriat, H. and Decarli, C. and de Leeuw, F. E. and Doubal, F. and Duering, M. and Fox, N. C. and Greenberg, S. and Hachinski, V. and Kilimann, I. and Mok, V. and Oostenbrugge, Rv and Pantoni, L. and Speck, O. and Stephan, B. C. and Teipel, S. and Viswanathan, A. and Werring, D. and Chen, C. and Smith, C. and van Buchem, M. and Norrving, B. and Gorelick, P. B. and Dichgans, M. and S. Tandards for ReportIng Vascular changes on nEuroimaging},\n\tmonth = aug,\n\tyear = {2013},\n\tpmcid = {PMC3714437},\n\tpmid = {23867200},\n\tkeywords = {Female, Humans, Image Processing, Computer-Assisted, Male, Neuroimaging, Aging, *Aging, Cerebral Small Vessel Diseases/classification/complications/*diagnosis, Guidelines as Topic, International Cooperation, Neurodegenerative Diseases/*diagnosis, Neuroimaging/classification/*methods/*standards, Terminology as Topic, Cerebral Small Vessel Diseases, Neurodegenerative Diseases},\n\tpages = {822--38},\n}\n\n

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\n \n\n \n \n \n \n \n Incident subcortical infarcts induce focal thinning in connected cortical regions.\n \n \n \n\n\n \n Duering, M.; Righart, R.; Csanadi, E.; Jouvent, E.; Herve, D.; Chabriat, H.; and Dichgans, M.\n\n\n \n\n\n\n Neurology, 79(20): 2025–8. November 2012.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{duering_incident_2012,\n\ttitle = {Incident subcortical infarcts induce focal thinning in connected cortical regions},\n\tvolume = {79},\n\tissn = {1526-632X (Electronic) 0028-3878 (Linking)},\n\tdoi = {10.1212/WNL.0b013e3182749f39},\n\tabstract = {OBJECTIVE: Brain atrophy is common in subcortical ischemic vascular disease, but the underlying mechanisms are poorly understood. We set out to examine the effects of incident subcortical infarcts on cortical morphology. METHODS: A total of 276 subjects with cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy, an inherited small vessel disease, were enrolled in a prospective study. Incident subcortical infarcts were identified on follow-up magnetic resonance scans after 18, 36, and 54 months using difference images. Probabilistic fiber tracking and cortical thickness measurements were applied to study the longitudinal relationship between incident infarcts and connected cortical areas. Cortical thickness was assessed before and after infarction using FreeSurfer software. Focal cortical thinning was defined as change of cortical thickness in the connected region of interest exceeding the global change of cortical thickness. RESULTS: Nine subjects had a single incident infarct during the follow-up and were suitable for analysis. There was a strong correlation between the probability of connectivity and mean focal cortical thinning (p = 0.0039). In all subjects, there was focal cortical thinning in cortical regions with high probability of connectivity with the incident infarct. This pattern was not observed when using control tractography seeds. CONCLUSIONS: Our findings provide in vivo evidence for secondary cortical neurodegeneration after subcortical ischemia as a mechanism for brain atrophy in cerebrovascular disease.},\n\tnumber = {20},\n\tjournal = {Neurology},\n\tauthor = {Duering, M. and Righart, R. and Csanadi, E. and Jouvent, E. and Herve, D. and Chabriat, H. and Dichgans, M.},\n\tmonth = nov,\n\tyear = {2012},\n\tpmid = {23054230},\n\tkeywords = {Adult, Female, Humans, Image Processing, Computer-Assisted, Male, Middle Aged, Prospective Studies, Incidence, Follow-Up Studies, Magnetic Resonance Imaging, Nerve Fibers, Myelinated/*pathology, CADASIL/complications, Cerebral Cortex/blood supply/*pathology, Cerebral Infarction/etiology/*pathology, Leukoencephalopathies/pathology, Oxygen/blood, Statistics, Nonparametric, Time Factors, Cerebral Infarction, Cerebral Cortex, CADASIL, Leukoencephalopathies, Nerve Fibers, Myelinated, Oxygen},\n\tpages = {2025--8},\n}\n\n

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\n \n\n \n \n \n \n \n NIHSS scores in ischemic small vessel disease: a study in CADASIL.\n \n \n \n\n\n \n Yao, M.; Herve, D.; Allili, N.; Jouvent, E.; Duering, M.; Dichgans, M.; and Chabriat, H.\n\n\n \n\n\n\n Cerebrovasc Dis, 34(5-6): 419–23. 2012.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{yao_nihss_2012,\n\ttitle = {{NIHSS} scores in ischemic small vessel disease: a study in {CADASIL}},\n\tvolume = {34},\n\tissn = {1421-9786 (Electronic) 1015-9770 (Linking)},\n\tdoi = {10.1159/000345067},\n\tabstract = {BACKGROUND: The National Institutes of Health Stroke Scale (NIHSS) is widely used to measure neurological deficits, evaluate the effectiveness of treatment and predict outcome in acute ischemic stroke. It has also been used to measure the residual neurological deficit at the chronic stage after ischemic events. However, the value of NIHSS in ischemic cerebral small vessel disease has not been specifically evaluated. The purpose of this study was to investigate the link between the NIHSS score and clinical severity in a large population of subjects with CADASIL (cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy), a unique model to investigate the pathophysiology and natural history of ischemic small vessel disease. METHODS: Demographic and clinical data of 220 patients with one or more lacunar infarcts confirmed by MRI examination and enrolled from a prospective cohort study were analyzed. Detailed neurological examinations, including evaluation of the NIHSS and modified Rankin Scale score (mRS) for evaluating the clinical severity, were performed in all subjects. The sensitivity, specificity, positive and negative predictive values of various NIHSS thresholds to capture the absence of significant disability (mRS {\\textless}3) were calculated. General linear models, controlling for age, educational level and different clinical manifestations frequently observed in CADASIL, were used to evaluate the relationships between NIHSS and clinical severity. RESULTS: In the whole cohort, 45 (20.5\\%) subjects presented with mRS {\\textgreater}/=3, but only 16 (7.3\\%) had NIHSS {\\textgreater}5. All but 1 subject with NIHSS {\\textgreater}5 showed mRS {\\textgreater}/=3. NIHSS {\\textless}/=5 had an 85.3\\% positive predictive value for no or slight disability with only 33.3\\% specificity. The NIHSS, MMSE score and presence or absence of gait disturbances were found to be strongly and independently correlated with disability (all p {\\textless} 0.001). Altogether, they accounted for 73\\% of the variance of mRS in contrast with the NIHSS alone accounting for only 50\\% of this variance. Among patients with NIHSS {\\textless}/=5, subjects with mRS {\\textgreater}/=3 showed a lower MMSE score than those with mRS {\\textless}3 (p {\\textless} 0.001). All patients with NIHSS {\\textless}/=5 but with mRS {\\textgreater}/=3 presented either with gait disturbances or MMSE score {\\textless}25. CONCLUSIONS: The present results suggest that the NIHSS cannot reflect the extent of neurological deficit and clinical severity in subjects with lacunar infarctions in the context of a chronic and diffuse small vessel disease. A specific and global neurological scale, including the assessment of cognitive and gait performances, should be developed for ischemic cerebral microangiopathy.},\n\tnumber = {5-6},\n\tjournal = {Cerebrovasc Dis},\n\tauthor = {Yao, M. and Herve, D. and Allili, N. and Jouvent, E. and Duering, M. and Dichgans, M. and Chabriat, H.},\n\tyear = {2012},\n\tpmid = {23221354},\n\tkeywords = {Adult, Aged, Disease Progression, Female, Humans, Male, Middle Aged, Prospective Studies, Magnetic Resonance Imaging, Cohort Studies, Neuropsychological Tests, Magnetic Resonance Imaging/methods, Sensitivity and Specificity, Severity of Illness Index, CADASIL/*diagnosis, Brain Ischemia/*diagnosis, Cerebral Small Vessel Diseases/*diagnosis, National Institutes of Health (U.S.), United States, Cerebral Small Vessel Diseases, CADASIL, Brain Ischemia},\n\tpages = {419--23},\n}\n\n

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\n BACKGROUND: The National Institutes of Health Stroke Scale (NIHSS) is widely used to measure neurological deficits, evaluate the effectiveness of treatment and predict outcome in acute ischemic stroke. It has also been used to measure the residual neurological deficit at the chronic stage after ischemic events. However, the value of NIHSS in ischemic cerebral small vessel disease has not been specifically evaluated. The purpose of this study was to investigate the link between the NIHSS score and clinical severity in a large population of subjects with CADASIL (cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy), a unique model to investigate the pathophysiology and natural history of ischemic small vessel disease. METHODS: Demographic and clinical data of 220 patients with one or more lacunar infarcts confirmed by MRI examination and enrolled from a prospective cohort study were analyzed. Detailed neurological examinations, including evaluation of the NIHSS and modified Rankin Scale score (mRS) for evaluating the clinical severity, were performed in all subjects. The sensitivity, specificity, positive and negative predictive values of various NIHSS thresholds to capture the absence of significant disability (mRS \\textless3) were calculated. General linear models, controlling for age, educational level and different clinical manifestations frequently observed in CADASIL, were used to evaluate the relationships between NIHSS and clinical severity. RESULTS: In the whole cohort, 45 (20.5%) subjects presented with mRS \\textgreater/=3, but only 16 (7.3%) had NIHSS \\textgreater5. All but 1 subject with NIHSS \\textgreater5 showed mRS \\textgreater/=3. NIHSS \\textless/=5 had an 85.3% positive predictive value for no or slight disability with only 33.3% specificity. The NIHSS, MMSE score and presence or absence of gait disturbances were found to be strongly and independently correlated with disability (all p \\textless 0.001). Altogether, they accounted for 73% of the variance of mRS in contrast with the NIHSS alone accounting for only 50% of this variance. Among patients with NIHSS \\textless/=5, subjects with mRS \\textgreater/=3 showed a lower MMSE score than those with mRS \\textless3 (p \\textless 0.001). All patients with NIHSS \\textless/=5 but with mRS \\textgreater/=3 presented either with gait disturbances or MMSE score \\textless25. CONCLUSIONS: The present results suggest that the NIHSS cannot reflect the extent of neurological deficit and clinical severity in subjects with lacunar infarctions in the context of a chronic and diffuse small vessel disease. A specific and global neurological scale, including the assessment of cognitive and gait performances, should be developed for ischemic cerebral microangiopathy.\n

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\n \n\n \n \n \n \n \n Extensive white matter hyperintensities may increase brain volume in cerebral autosomal-dominant arteriopathy with subcortical infarcts and leukoencephalopathy.\n \n \n \n\n\n \n Yao, M.; Jouvent, E.; During, M.; Godin, O.; Herve, D.; Guichard, J. P.; Zhu, Y. C.; Gschwendtner, A.; Opherk, C.; Dichgans, M.; and Chabriat, H.\n\n\n \n\n\n\n Stroke, 43(12): 3252–7. December 2012.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{yao_extensive_2012,\n\ttitle = {Extensive white matter hyperintensities may increase brain volume in cerebral autosomal-dominant arteriopathy with subcortical infarcts and leukoencephalopathy},\n\tvolume = {43},\n\tissn = {1524-4628 (Electronic) 0039-2499 (Linking)},\n\tdoi = {10.1161/STROKEAHA.112.664854},\n\tabstract = {BACKGROUND AND PURPOSE: The extent of white matter hyperintensities (WMH) is associated with cerebral atrophy in elderly people. WMH is a radiological hallmark of cerebral autosomal-dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL), but their relationship with brain volume remains poorly understood. The association between WMH and brain volume was analyzed in a large population of patients with CADASIL. METHODS: Demographic and MRI data of 278 patients recruited from a prospective cohort study were analyzed. Volumes of WMH and lacunar infarcts, number of cerebral microbleeds, and brain parenchymal fraction were measured. Multivariate analysis was used to study the impact of WMH on brain volume at baseline. RESULTS: In univariate analyses, brain parenchymal fraction was negatively associated with age, male sex, and all MRI markers. Multiple regression modeling showed that brain parenchymal fraction was inversely related to age, number of cerebral microbleeds, and normalized volume of lacunar infarcts but positively related to normalized volume of WMH (P{\\textless}0.001). This positive relationship was independent of the presence/absence of lacunar infarcts or of cerebral microbleeds. Subgroup analysis showed that this association was significant in subjects having normalized volume of WMH {\\textgreater}/=6.13 or brain parenchymal fraction {\\textgreater}/=86.37\\% (median values, both P{\\textless}/=0.001). CONCLUSIONS: The results of the present study suggest that extensive WMH may be associated with increase of brain volume in CADASIL. In this disorder, WMH may be related not only to loss of white matter components, but also to a global increase of water content in the cerebral tissue.},\n\tnumber = {12},\n\tjournal = {Stroke},\n\tauthor = {Yao, M. and Jouvent, E. and During, M. and Godin, O. and Herve, D. and Guichard, J. P. and Zhu, Y. C. and Gschwendtner, A. and Opherk, C. and Dichgans, M. and Chabriat, H.},\n\tmonth = dec,\n\tyear = {2012},\n\tpmid = {23185048},\n\tkeywords = {Adult, Aged, Female, Humans, Male, Middle Aged, Prospective Studies, Magnetic Resonance Imaging, Young Adult, Age Factors, *Magnetic Resonance Imaging, Atrophy, CADASIL/*pathology, Brain/metabolism/*pathology, Cerebral Hemorrhage/pathology, Leukoencephalopathies/*pathology, Stroke, Lacunar/*pathology, Water/metabolism, Brain, Cerebral Hemorrhage, Water, CADASIL, Leukoencephalopathies, Stroke, Lacunar},\n\tpages = {3252--7},\n}\n\n

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\n \n\n \n \n \n \n \n White-matter lesions without lacunar infarcts in CADASIL.\n \n \n \n\n\n \n Benisty, S.; Reyes, S.; Godin, O.; Herve, D.; Zieren, N.; Jouvent, E.; Zhu, Y.; During, M.; Dichgans, M.; and Chabriat, H.\n\n\n \n\n\n\n J Alzheimers Dis, 29(4): 903–11. 2012.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{benisty_white-matter_2012,\n\ttitle = {White-matter lesions without lacunar infarcts in {CADASIL}},\n\tvolume = {29},\n\tissn = {1875-8908 (Electronic) 1387-2877 (Linking)},\n\tdoi = {10.3233/JAD-2012-111784},\n\tabstract = {To better characterize the clinical spectrum related to white-matter hyperintensities (WMH) in small vessel disease, 66 patients with WMH but without any lacunar infarct were selected out of a cohort of 248 CADASIL individuals. Characteristics of these patients were compared to those of patients with lacunar infarcts. Relationships between the normalized volume of WMH (nWMH), presence of microhemorrhages, brain parenchymal fraction (BPF). and cognitive performances were assessed. The Trail Making Test (TMT) A and B times, Mattis Dementia Rating Scale (MDRS) total score, attention subscore, verbal fluency score and delayed memory recall were significantly correlated with nWMH but not with BPF. Presence of microhemorrhages was associated with worse TMT B time and attention MDRS subscore after adjustment for WMH. All subjects had Mini-Mental Status Examination scores {\\textgreater}/=24 and presented with no or only mild disability. These results suggest that CADASIL patients with isolated WMH can present with executive and attention deficit but not with severe disability and that additional lesions are needed to cause significant disability and/or dementia.},\n\tnumber = {4},\n\tjournal = {J Alzheimers Dis},\n\tauthor = {Benisty, S. and Reyes, S. and Godin, O. and Herve, D. and Zieren, N. and Jouvent, E. and Zhu, Y. and During, M. and Dichgans, M. and Chabriat, H.},\n\tyear = {2012},\n\tpmid = {22330818},\n\tkeywords = {Adult, Aged, Female, Humans, Image Processing, Computer-Assisted, Male, Middle Aged, Magnetic Resonance Imaging, Young Adult, Nerve Fibers, Myelinated/*pathology, Trail Making Test, Cohort Studies, Brain/*pathology, Cognition Disorders/etiology, CADASIL/complications/*pathology, Psychiatric Status Rating Scales, Stroke, Lacunar/pathology, Brain, Cognition Disorders, CADASIL, Nerve Fibers, Myelinated, Stroke, Lacunar},\n\tpages = {903--11},\n}\n\n

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\n \n\n \n \n \n \n \n Cortical folding influences migraine aura symptoms in CADASIL.\n \n \n \n\n\n \n Jouvent, E.; Mangin, J. F.; Herve, D.; During, M.; Dichgans, M.; and Chabriat, H.\n\n\n \n\n\n\n J Neurol Neurosurg Psychiatry, 83(2): 213–6. February 2012.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{jouvent_cortical_2012,\n\ttitle = {Cortical folding influences migraine aura symptoms in {CADASIL}},\n\tvolume = {83},\n\tissn = {1468-330X (Electronic) 0022-3050 (Linking)},\n\tdoi = {10.1136/jnnp-2011-300825},\n\tabstract = {OBJECTIVE: Migraine with aura is a hallmark of cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL). In contrast with the majority of CADASIL patients, some affected subjects never experience visual symptoms during their attacks of migraine with aura. The aim of this study was to determine whether specific morphology of the primary visual cortex is associated with the absence of visual symptoms during migraine aura in CADASIL. METHODS: Patients from a large cohort of CADASIL patients, aged {\\textless}45 years, and with a modified Rankin's scale {\\textless}/=1 were included in the study. Width and depth of the calcarine sulcus in the primary visual cortex as well as cortical thickness in its neighbourhood were compared between patients with visual and those with non-visual migraine auras. RESULTS: 31 patients had visual symptoms (VA group) while nine reported only non-visual symptoms (NVA group) during their migraine auras. Asymmetry index of the calcarine sulcal depth largely differed between the NVA group and the VA group (0.22+/-0.1 vs -0.004+/-0.2; p=1.7x10(-6)). The width of the right calcarine sulcus was significantly lower in the VA group (p=0.04) and cortical thickness was larger in the NVA group (p=0.03). CONCLUSION: The absence of visual symptoms during migraine auras was associated with a profound asymmetry of the primary visual cortex. Aura symptoms seem to be linked to the morphology of the primary visual cortex in CADASIL. This finding potentially reflects more general relationships between spreading depression and cortex morphology in migraine with aura.},\n\tnumber = {2},\n\tjournal = {J Neurol Neurosurg Psychiatry},\n\tauthor = {Jouvent, E. and Mangin, J. F. and Herve, D. and During, M. and Dichgans, M. and Chabriat, H.},\n\tmonth = feb,\n\tyear = {2012},\n\tpmid = {22072703},\n\tkeywords = {Adult, Aged, Female, Humans, Male, Middle Aged, Prospective Studies, Magnetic Resonance Imaging, Young Adult, Cerebral Cortex/*pathology, Cohort Studies, Functional Laterality, CADASIL/complications/*pathology, Data Interpretation, Statistical, Migraine with Aura/etiology/*pathology, Vision Disorders/etiology, Cerebral Cortex, CADASIL, Migraine with Aura, Vision Disorders},\n\tpages = {213--6},\n}\n\n

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\n \n\n \n \n \n \n \n Effects of gender on the phenotype of CADASIL.\n \n \n \n\n\n \n Gunda, B.; Herve, D.; Godin, O.; Bruno, M.; Reyes, S.; Alili, N.; Opherk, C.; Jouvent, E.; During, M.; Bousser, M. G.; Dichgans, M.; and Chabriat, H.\n\n\n \n\n\n\n Stroke, 43(1): 137–41. January 2012.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{gunda_effects_2012,\n\ttitle = {Effects of gender on the phenotype of {CADASIL}},\n\tvolume = {43},\n\tissn = {1524-4628 (Electronic) 0039-2499 (Linking)},\n\tdoi = {10.1161/STROKEAHA.111.631028},\n\tabstract = {BACKGROUND AND PURPOSE: In the general population, migraine, cerebrovascular diseases, and vascular dementia differ in many aspects between men and women. CADASIL is considered a unique model to investigate migraine with aura, stroke, and dementia related to ischemic small vessel disease. This study aims to evaluate the effect of gender on the main clinical and neuroimaging characteristics of CADASIL. METHODS: Cross-sectional data from 313 CADASIL patients including various clinical and cognitive scores and MRI parameters were compared between men and women, and between those younger and older than the median age of the population corresponding to the usual age of menopause (51 years). RESULTS: At younger than 51 years, migraine with aura was 50\\% more prevalent in women and stroke was 75\\% more prevalent in men. After the fifth decade, men had higher National Institutes of Health Stroke Scale and Rankin scores than women and more severe executive dysfunction, although global cognitive scores were similar. Age at first stroke, the number of stroke events, and the prevalence of dementia and psychiatric symptoms did not differ between men and women. Brain volume was lower in men with a trend for a larger volume of lacunar infarcts. CONCLUSIONS: In CADASIL, migraine with aura is more frequent in women and stroke is more frequent in men before the age of menopause. This difference seems to vanish after this age limit but may result in a higher degree of cognitive impairment and cerebral atrophy in men at the late stage of the disease. The presumable role of ovarian hormones in these gender-related differences remains to be explored.},\n\tnumber = {1},\n\tjournal = {Stroke},\n\tauthor = {Gunda, B. and Herve, D. and Godin, O. and Bruno, M. and Reyes, S. and Alili, N. and Opherk, C. and Jouvent, E. and During, M. and Bousser, M. G. and Dichgans, M. and Chabriat, H.},\n\tmonth = jan,\n\tyear = {2012},\n\tpmid = {22033996},\n\tkeywords = {Stroke, Adult, Female, Humans, Male, Middle Aged, Executive Function, Age Factors, Phenotype, Sex Factors, *Phenotype, Brain Ischemia/*genetics/physiopathology/psychology, CADASIL/*diagnosis/genetics/physiopathology/psychology, Cross-Sectional Studies, Migraine with Aura/*genetics/physiopathology/psychology, Stroke/*genetics/physiopathology/psychology, CADASIL, Brain Ischemia, Migraine with Aura},\n\tpages = {137--41},\n}\n\n

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\n \n\n \n \n \n \n \n Longitudinal changes of cortical morphology in CADASIL.\n \n \n \n\n\n \n Jouvent, E.; Mangin, J. F.; Duchesnay, E.; Porcher, R.; During, M.; Mewald, Y.; Guichard, J. P.; Herve, D.; Reyes, S.; Zieren, N.; Dichgans, M.; and Chabriat, H.\n\n\n \n\n\n\n Neurobiol Aging, 33(5): 1002 e29–36. May 2012.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{jouvent_longitudinal_2012,\n\ttitle = {Longitudinal changes of cortical morphology in {CADASIL}},\n\tvolume = {33},\n\tissn = {1558-1497 (Electronic) 0197-4580 (Linking)},\n\tdoi = {10.1016/j.neurobiolaging.2011.09.013},\n\tabstract = {In CADASIL (Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leucoencephalopathy), a genetic model of subcortical ischemic vascular dementia (SIVD), clinical status was previously found related to cortex morphology. In the present report, alterations of cortex morphology and their links to clinical worsening were investigated in 190 CADASIL patients followed during 24.4 months. Linear models were used to test relationships between: (1) clinical worsening and changes of depth of cortical sulci and of cortical thickness; (2) alterations of cortical morphology and changes of volume of white matter hyperintensities (WMH(v)) and of lacunar lesions (LL(v)). Reduction of sulcal depth was independently associated with increased time to complete trail making test A and B (p {\\textless} 0.0001 and p = 0.004) and that of cortical thickness to increased disability (modified Rankin's scale, p = 0.008), while brain atrophy was only related to global cognitive worsening (Mattis dementia rating scale, p = 0.002). The impact of volume of lacunar lesions on cortical alterations was larger than that of volume of white matter hyperintensities. Cortical alterations, mainly related to lacunar lesions, evolve parallel to clinical worsening. These results further support the eventual role of cortical alterations in subcortical ischemic vascular dementia.},\n\tnumber = {5},\n\tjournal = {Neurobiol Aging},\n\tauthor = {Jouvent, E. and Mangin, J. F. and Duchesnay, E. and Porcher, R. and During, M. and Mewald, Y. and Guichard, J. P. and Herve, D. and Reyes, S. and Zieren, N. and Dichgans, M. and Chabriat, H.},\n\tmonth = may,\n\tyear = {2012},\n\tpmid = {22000857},\n\tkeywords = {Adult, Aged, Disease Progression, Female, Humans, Male, Middle Aged, Aged, 80 and over, Follow-Up Studies, Magnetic Resonance Imaging, Cerebral Cortex/*pathology, Nerve Fibers, Myelinated/pathology, Magnetic Resonance Imaging/methods, Atrophy, Models, Neurological, Longitudinal Studies, Dementia, Vascular, CADASIL/*pathology, Dementia, Vascular/*pathology, Cerebral Cortex, CADASIL, Nerve Fibers, Myelinated},\n\tpages = {1002 e29--36},\n}\n\n

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\n \n 2011\n \n \n (5)\n \n \n

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\n \n\n \n \n \n \n \n Strategic role of frontal white matter tracts in vascular cognitive impairment: a voxel-based lesion-symptom mapping study in CADASIL.\n \n \n \n\n\n \n Duering, M.; Zieren, N.; Herve, D.; Jouvent, E.; Reyes, S.; Peters, N.; Pachai, C.; Opherk, C.; Chabriat, H.; and Dichgans, M.\n\n\n \n\n\n\n Brain, 134(Pt 8): 2366–75. August 2011.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{duering_strategic_2011,\n\ttitle = {Strategic role of frontal white matter tracts in vascular cognitive impairment: a voxel-based lesion-symptom mapping study in {CADASIL}},\n\tvolume = {134},\n\tissn = {1460-2156 (Electronic) 0006-8950 (Linking)},\n\tdoi = {10.1093/brain/awr169},\n\tabstract = {Cerebral small vessel disease is the most common cause of vascular cognitive impairment. It typically manifests with lacunar infarcts and ischaemic white matter lesions. However, little is known about how these lesions relate to the cognitive symptoms. Previous studies have found a poor correlation between the burden of ischaemic lesions and cognitive symptoms, thus leaving much of the variance in cognitive performance unexplained. The objective of the current study was to investigate the relationship between the location of subcortical ischaemic lesions and cognitive symptoms in small vessel disease. We applied a voxel-based lesion-symptom mapping approach to data from 215 patients with CADASIL, a genetically defined small vessel disease with mutations in the NOTCH3 gene. All patients were examined by magnetic resonance imaging and comprehensive neuropsychological testing. Lacunar lesions and white matter lesions were segmented on three-dimensional T(1) and fluid-attenuated inversion recovery sequences, respectively. One hundred and forty-five subjects had a total of 854 lacunar lesions (range 1-13 per individual). The normalized volume of white matter hyperintensities ranged from 0.0425\\% to 21.5\\% of the intracranial cavity. Significant clusters for cognitive performance were detected for both lacunar lesions and white matter hyperintensities. The most prominent results were obtained on a compound score for processing speed, the predominantly affected cognitive domain in this group of patients. Strategic locations included the anterior parts of the thalamus, the genu and anterior limb of the internal capsule, the anterior corona radiata and the genu of the corpus callosum. By combining the lesion-symptom mapping data with information from a probabilistic white matter atlas we found that the majority of the processing speed clusters projected on the anterior thalamic radiation and the forceps minor. In multivariate models that included demographic parameters, brain atrophy and the volume of ischaemic lesions, regional volumes of lacunar lesions and white matter hyperintensities in the anterior thalamic radiation predicted performance in processing speed tasks, whereas there was no independent contribution of the global volume of ischaemic lesions. These observations emphasize the importance of lesion location for both lacunar and ischaemic white matter lesions. Our findings further highlight the anterior thalamic radiation as a major anatomical structure impacting on processing speed. Together these findings provide strong support for a central role of frontal-subcortical circuits in cerebral small vessel disease and vascular cognitive impairment.},\n\tnumber = {Pt 8},\n\tjournal = {Brain},\n\tauthor = {Duering, M. and Zieren, N. and Herve, D. and Jouvent, E. and Reyes, S. and Peters, N. and Pachai, C. and Opherk, C. and Chabriat, H. and Dichgans, M.},\n\tmonth = aug,\n\tyear = {2011},\n\tpmid = {21764819},\n\tkeywords = {Adult, Female, Humans, Male, Middle Aged, Magnetic Resonance Imaging, Regression Analysis, Nerve Fibers, Myelinated/*pathology, Cohort Studies, Neuropsychological Tests, *Brain Mapping, CADASIL/*complications/*pathology, Cognition Disorders/*etiology, Frontal Lobe/*pathology, Imaging, Three-Dimensional/methods, Magnetic Resonance Imaging/methods, Brain Mapping, Imaging, Three-Dimensional, Cognition Disorders, Frontal Lobe, CADASIL, Nerve Fibers, Myelinated},\n\tpages = {2366--75},\n}\n\n

\n\n\n

\n Cerebral small vessel disease is the most common cause of vascular cognitive impairment. It typically manifests with lacunar infarcts and ischaemic white matter lesions. However, little is known about how these lesions relate to the cognitive symptoms. Previous studies have found a poor correlation between the burden of ischaemic lesions and cognitive symptoms, thus leaving much of the variance in cognitive performance unexplained. The objective of the current study was to investigate the relationship between the location of subcortical ischaemic lesions and cognitive symptoms in small vessel disease. We applied a voxel-based lesion-symptom mapping approach to data from 215 patients with CADASIL, a genetically defined small vessel disease with mutations in the NOTCH3 gene. All patients were examined by magnetic resonance imaging and comprehensive neuropsychological testing. Lacunar lesions and white matter lesions were segmented on three-dimensional T(1) and fluid-attenuated inversion recovery sequences, respectively. One hundred and forty-five subjects had a total of 854 lacunar lesions (range 1-13 per individual). The normalized volume of white matter hyperintensities ranged from 0.0425% to 21.5% of the intracranial cavity. Significant clusters for cognitive performance were detected for both lacunar lesions and white matter hyperintensities. The most prominent results were obtained on a compound score for processing speed, the predominantly affected cognitive domain in this group of patients. Strategic locations included the anterior parts of the thalamus, the genu and anterior limb of the internal capsule, the anterior corona radiata and the genu of the corpus callosum. By combining the lesion-symptom mapping data with information from a probabilistic white matter atlas we found that the majority of the processing speed clusters projected on the anterior thalamic radiation and the forceps minor. In multivariate models that included demographic parameters, brain atrophy and the volume of ischaemic lesions, regional volumes of lacunar lesions and white matter hyperintensities in the anterior thalamic radiation predicted performance in processing speed tasks, whereas there was no independent contribution of the global volume of ischaemic lesions. These observations emphasize the importance of lesion location for both lacunar and ischaemic white matter lesions. Our findings further highlight the anterior thalamic radiation as a major anatomical structure impacting on processing speed. Together these findings provide strong support for a central role of frontal-subcortical circuits in cerebral small vessel disease and vascular cognitive impairment.\n

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\n \n\n \n \n \n \n \n Co-aggregate formation of CADASIL-mutant NOTCH3: a single-particle analysis.\n \n \n \n\n\n \n Duering, M.; Karpinska, A.; Rosner, S.; Hopfner, F.; Zechmeister, M.; Peters, N.; Kremmer, E.; Haffner, C.; Giese, A.; Dichgans, M.; and Opherk, C.\n\n\n \n\n\n\n Hum Mol Genet, 20(16): 3256–65. August 2011.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{duering_co-aggregate_2011,\n\ttitle = {Co-aggregate formation of {CADASIL}-mutant {NOTCH3}: a single-particle analysis},\n\tvolume = {20},\n\tissn = {1460-2083 (Electronic) 0964-6906 (Linking)},\n\tdoi = {10.1093/hmg/ddr237},\n\tabstract = {CADASIL (cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy) is the most common monogenic cause of stroke and vascular dementia. Accumulation and deposition of the NOTCH3 (N3) extracellular domain in small blood vessels has been recognized as a central pathological feature of the disease. Recent experiments suggested enhanced formation of higher order multimers for mutant N3 compared with wild-type (WT). However, the mechanisms and consequences of N3 multimerization are still poorly understood, in part because of the lack of an appropriate in vitro aggregation assay. We therefore developed and validated a robust assay based on recombinant N3 fragments purified from cell culture supernatants. Using single-molecule analysis techniques such as scanning for intensely fluorescent targets and single-particle fluorescence resonance energy transfer, we show that spontaneous aggregation is limited to CADASIL-mutant N3, recapitulating a central aspect of CADASIL pathology in vitro. N3 aggregation requires no co-factor and is facilitated by sulfhydryl crosslinking. Although WT N3 does not exhibit multimerization itself, it can participate in aggregates of mutant N3. Furthermore, we demonstrate that thrombospondin-2, a known interaction partner of N3, co-aggregates with mutant N3. Sequestration of WT N3 and other proteins into aggregates represents a potentially important disease mechanism. These findings in combination with a new assay for single-molecule aggregation analysis provide novel opportunities for the development of therapeutic strategies.},\n\tnumber = {16},\n\tjournal = {Hum Mol Genet},\n\tauthor = {Duering, M. and Karpinska, A. and Rosner, S. and Hopfner, F. and Zechmeister, M. and Peters, N. and Kremmer, E. and Haffner, C. and Giese, A. and Dichgans, M. and Opherk, C.},\n\tmonth = aug,\n\tyear = {2011},\n\tpmid = {21628316},\n\tkeywords = {Humans, Reproducibility of Results, CADASIL/*genetics, Receptor, Notch3, Cross-Linking Reagents/pharmacology, Electrophoresis, Polyacrylamide Gel, Epidermal Growth Factor/metabolism, HEK293 Cells, Maleimides/metabolism, Mutant Proteins/chemistry/metabolism, Mutation/*genetics, Protein Multimerization/drug effects, Protein Structure, Quaternary, Receptors, Notch/*chemistry/*metabolism, Recombinant Proteins/metabolism, Sulfhydryl Reagents/metabolism, Thrombospondins/metabolism, Mutation, CADASIL, Receptors, Notch, Epidermal Growth Factor, Protein Multimerization, Cross-Linking Reagents, Maleimides, Mutant Proteins, Recombinant Proteins, Sulfhydryl Reagents, Thrombospondins},\n\tpages = {3256--65},\n}\n\n

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\n \n\n \n \n \n \n \n Carotid atherosclerotic markers in CADASIL.\n \n \n \n\n\n \n Mawet, J.; Vahedi, K.; Aout, M.; Vicaut, E.; Duering, M.; Touboul, P. J.; Dichgans, M.; and Chabriat, H.\n\n\n \n\n\n\n Cerebrovasc Dis, 31(3): 246–52. 2011.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{mawet_carotid_2011,\n\ttitle = {Carotid atherosclerotic markers in {CADASIL}},\n\tvolume = {31},\n\tissn = {1421-9786 (Electronic) 1015-9770 (Linking)},\n\tdoi = {10.1159/000321932},\n\tabstract = {PURPOSE: Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) is a cerebral small vessel disease caused by mutations of the NOTCH3 gene. Marked variations in disease severity have raised the hypothesis that non-genetic factors may modulate the expressivity of the phenotype. The aim of the current study was to evaluate whether atherosclerosis, assessed by carotid duplex ultrasonography, is associated with variations in the clinical and MRI phenotype of CADASIL. METHODS: Data from 144 consecutive patients enrolled in an ongoing prospective cohort study were collected. Degree of disability was assessed by the modified Rankin Scale, that of cognitive impairment by the Mattis Dementia Rating Scale (MDRS). The total volume of the brain, of lacunar lesions and of white matter hyperintensities, the number of cerebral microhemorrhages, and parameters derived from histograms of apparent diffusion coefficient were measured on cerebral MRI. Atherosclerosis was evaluated by B-mode ultrasonography of carotid arteries. Both the carotid intima-media thickness (cIMT) and the presence of carotid plaques or stenosis were recorded. RESULTS: Higher cIMT was found to be independently associated with lower MDRS scores when this score was less than the quartile limit (p = 0.02). Only a trend for a positive association was detected between cIMT and the Rankin score (p = 0.06). There was no significant association between carotid markers and the occurrence of stroke or MRI parameters except for diffusion data. The mean and peak values of MRI diffusion histograms were found positively associated with the presence of plaques (p {\\textless} 0.01). CONCLUSION: The results suggest that the severity of atherosclerosis may relate to cognitive decline in CADASIL and that this effect is possibly related to the degree of microstructural cerebral tissue lesions. Longitudinal studies are needed to confirm these results.},\n\tnumber = {3},\n\tjournal = {Cerebrovasc Dis},\n\tauthor = {Mawet, J. and Vahedi, K. and Aout, M. and Vicaut, E. and Duering, M. and Touboul, P. J. and Dichgans, M. and Chabriat, H.},\n\tyear = {2011},\n\tpmid = {21178349},\n\tkeywords = {Cognition, Adult, Aged, Diffusion Magnetic Resonance Imaging, Female, Humans, Male, Middle Aged, Prospective Studies, Biomarkers/blood, Prognosis, Biomarkers, Young Adult, Risk Factors, Neuropsychological Tests, Brain/pathology, Linear Models, Phenotype, Predictive Value of Tests, Severity of Illness Index, CADASIL/complications/*diagnosis/pathology/psychology, Carotid Artery Diseases/complications/*diagnosis/diagnostic imaging/psychology, Carotid Artery, Common/diagnostic imaging, Cognition Disorders/etiology/psychology, Disability Evaluation, Odds Ratio, Paris, Risk Assessment, Ultrasonography, Doppler, Duplex, Brain, Cognition Disorders, CADASIL, Carotid Artery Diseases, Carotid Artery, Common},\n\tpages = {246--52},\n}\n\n

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\n \n\n \n \n \n \n \n Internal carotid artery dissection and ischemic cerebral infarction in the setting of essential thrombocythemia.\n \n \n \n\n\n \n Freilinger, T.; Saam, T.; Duering, M.; Dichgans, M.; and Peters, N.\n\n\n \n\n\n\n Clin Appl Thromb Hemost, 17(6): E138–40. December 2011.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{freilinger_internal_2011,\n\ttitle = {Internal carotid artery dissection and ischemic cerebral infarction in the setting of essential thrombocythemia},\n\tvolume = {17},\n\tissn = {1938-2723 (Electronic) 1076-0296 (Linking)},\n\tdoi = {10.1177/1076029610391651},\n\tabstract = {Cervical artery dissection (CAD) is an important etiology of stroke in young adults. Its etiology is incompletely understood. Here, we report a young woman who presented with acute ischemic stroke in the setting of internal carotid artery (ICA) dissection and essential thrombocythemia (ET). We present a review of previous cases with comorbidity of CAD and ET and discuss the pathophysiological implications of this co-occurrence. In particular, we speculate that ET may increase the susceptibility of cervical vessels to spontaneous dissection, for example, by disturbing the microcirculation within the vessel wall.},\n\tnumber = {6},\n\tjournal = {Clin Appl Thromb Hemost},\n\tauthor = {Freilinger, T. and Saam, T. and Duering, M. and Dichgans, M. and Peters, N.},\n\tmonth = dec,\n\tyear = {2011},\n\tpmid = {21159702},\n\tkeywords = {Adult, Female, Humans, Carotid Artery, Internal, Dissection/*blood, Cerebral Infarction/*blood, Thrombocythemia, Essential/*complications, Cerebral Infarction, Carotid Artery, Internal, Dissection, Thrombocythemia, Essential},\n\tpages = {E138--40},\n}\n\n

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\n \n\n \n \n \n \n \n Verbal memory impairment in subcortical ischemic vascular disease: a descriptive analysis in CADASIL.\n \n \n \n\n\n \n Epelbaum, S.; Benisty, S.; Reyes, S.; O'Sullivan, M.; Jouvent, E.; During, M.; Herve, D.; Opherk, C.; Hernandez, K.; Kurtz, A.; Viswanathan, A.; Bousser, M. G.; Dichgans, M.; and Chabriat, H.\n\n\n \n\n\n\n Neurobiol Aging, 32(12): 2172–82. December 2011.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{epelbaum_verbal_2011,\n\ttitle = {Verbal memory impairment in subcortical ischemic vascular disease: a descriptive analysis in {CADASIL}},\n\tvolume = {32},\n\tissn = {1558-1497 (Electronic) 0197-4580 (Linking)},\n\tdoi = {10.1016/j.neurobiolaging.2009.12.018},\n\tabstract = {In the elderly, the high prevalence of Alzheimer's disease neuropathology presents a major challenge to the investigation of memory decline in common diseases such as small vessel disease. CADASIL represents a unique clinical model to determine the spectrum of memory impairment in subcortical ischemic vascular dementia (SIVD). One hundred and forty CADASIL patients underwent detailed clinical, neuropsychological and imaging analyses. The Free and Cued Selective Reminding Test was used as a measure of verbal memory. Forty-four out of 140 CADASIL patients (31.4\\%) presented with memory impairment according to this test. Eight out of 44 (18.2\\%) subjects with memory impairment matched the definition of the amnestic syndrome of hippocampal type. While alterations in spontaneous recall were related to the severity of subcortical ischemic lesions, the profile of memory impairment, particularly the sensitivity to cueing was found related to other factors such as hippocampal atrophy.},\n\tnumber = {12},\n\tjournal = {Neurobiol Aging},\n\tauthor = {Epelbaum, S. and Benisty, S. and Reyes, S. and O'Sullivan, M. and Jouvent, E. and During, M. and Herve, D. and Opherk, C. and Hernandez, K. and Kurtz, A. and Viswanathan, A. and Bousser, M. G. and Dichgans, M. and Chabriat, H.},\n\tmonth = dec,\n\tyear = {2011},\n\tpmid = {20149485},\n\tkeywords = {Adult, Female, Humans, Male, Middle Aged, Magnetic Resonance Imaging, Magnetic Resonance Imaging/methods, Dementia, Vascular, Mental Recall/physiology, *Verbal Learning/physiology, Brain Ischemia/diagnosis/epidemiology/psychology, CADASIL/*diagnosis/*epidemiology/psychology, Dementia, Vascular/diagnosis/epidemiology/psychology, Memory Disorders/*diagnosis/*epidemiology/psychology, CADASIL, Brain Ischemia, Memory Disorders, Mental Recall, Verbal Learning},\n\tpages = {2172--82},\n}\n\n

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\n \n 2010\n \n \n (3)\n \n \n

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\n \n\n \n \n \n \n \n Reversible cerebral vasoconstriction syndrome associated with hormone therapy for intrauterine insemination.\n \n \n \n\n\n \n Freilinger, T.; Schmidt, C.; Duering, M.; Linn, J.; Straube, A.; and Peters, N.\n\n\n \n\n\n\n Cephalalgia, 30(9): 1127–32. September 2010.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{freilinger_reversible_2010,\n\ttitle = {Reversible cerebral vasoconstriction syndrome associated with hormone therapy for intrauterine insemination},\n\tvolume = {30},\n\tissn = {1468-2982 (Electronic) 0333-1024 (Linking)},\n\tdoi = {10.1177/0333102409360675},\n\tabstract = {INTRODUCTION: Reversible cerebral vasoconstriction syndrome (RCVS) comprises a heterogeneous group of acute neurological diseases which are characterized by thunderclap headache and evidence of reversible multifocal constriction of cerebral arteries. A number of precipitating factors have been described in the literature, including recent childbirth and use of vasoactive substances. CASE DESCRIPTION: Here we present the case of a female patient with RCVS which occurred in the setting of hormonal ovarian stimulation for intrauterine insemination. DISCUSSION: This case possibly contributes to the understanding of the pathophysiological mechanisms underlying reversible cerebral vasoconstriction.},\n\tnumber = {9},\n\tjournal = {Cephalalgia},\n\tauthor = {Freilinger, T. and Schmidt, C. and Duering, M. and Linn, J. and Straube, A. and Peters, N.},\n\tmonth = sep,\n\tyear = {2010},\n\tpmid = {20713563},\n\tkeywords = {Adult, Female, Humans, Magnetic Resonance Imaging, Cerebrovascular Circulation, Cerebrovascular Circulation/*drug effects, Chorionic Gonadotropin/*adverse effects, Follicle Stimulating Hormone/*adverse effects, Headache Disorders, Primary/*chemically induced/pathology, Magnetic Resonance Angiography, Ovulation Induction/adverse effects, Vasoconstriction/*drug effects, Vasospasm, Intracranial/*chemically induced/pathology, Chorionic Gonadotropin, Follicle Stimulating Hormone, Headache Disorders, Primary, Ovulation Induction, Vasoconstriction, Vasospasm, Intracranial},\n\tpages = {1127--32},\n}\n\n

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\n \n\n \n \n \n \n \n Confluent thalamic hyperintensities in CADASIL.\n \n \n \n\n\n \n Jacqmin, M.; Herve, D.; Viswanathan, A.; Guichard, J. P.; During, M.; Dichgans, M.; and Chabriat, H.\n\n\n \n\n\n\n Cerebrovasc Dis, 30(3): 308–13. August 2010.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{jacqmin_confluent_2010,\n\ttitle = {Confluent thalamic hyperintensities in {CADASIL}},\n\tvolume = {30},\n\tissn = {1421-9786 (Electronic) 1015-9770 (Linking)},\n\tdoi = {10.1159/000319607},\n\tabstract = {BACKGROUND: CADASIL is responsible for diffuse hyperintensities in the white matter on FLAIR images. These lesions are often associated with focal lesions in the basal ganglia such as lacunar infarctions. The prevalence and significance of diffuse or confluent thalamic hyperintensities (CTH) remain unknown. METHODS: The frequency of hyperintensities on FLAIR images in the thalamus was assessed in 147 CADASIL patients, and signal abnormalities on both FLAIR and T(1)-weighted images were categorized as focal/punctuate or diffuse/confluent by the same reader. The areas of increased diffusion were also analyzed on apparent diffusion coefficient maps. The association of CTH with vascular risk factors, the main clinical manifestations of the disease and MRI markers (brain parenchymal fraction, volume of white matter hyperintensities, volume of lacunar infarcts and number of microbleeds) was analyzed with generalized linear regression models. RESULTS: CTH were detected in 12\\% of the CADASIL subjects in association with hypointensities on T(1)-weighted images. CTH corresponded to areas of increased diffusion on apparent diffusion coefficient maps. CTH were found significantly associated with age and independently related to the volume of white matter hyperintensities but not to that of lacunar infarctions or to cerebral atrophy after adjustment for age and sex. No significant association was found between CTH and global cognitive performances. CONCLUSION: CTH are observed on FLAIR images in a sizeable proportion of CADASIL patients. They are mainly related to the extent of white matter hyperintensities and do not correlate with cognitive decline. Demyelination and/or loss of glial cells appear to be the most plausible cause of these confluent signal changes in the thalamus.},\n\tnumber = {3},\n\tjournal = {Cerebrovasc Dis},\n\tauthor = {Jacqmin, M. and Herve, D. and Viswanathan, A. and Guichard, J. P. and During, M. and Dichgans, M. and Chabriat, H.},\n\tmonth = aug,\n\tyear = {2010},\n\tpmid = {20664266},\n\tkeywords = {Adult, Female, Humans, Male, Middle Aged, Magnetic Resonance Imaging, Retrospective Studies, Prevalence, CADASIL/*pathology, Basal Ganglia/pathology, Brain Infarction/pathology, Cell Nucleus/*pathology, Thalamus/*pathology, CADASIL, Brain Infarction, Basal Ganglia, Thalamus, Cell Nucleus},\n\tpages = {308--13},\n}\n\n

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\n \n\n \n \n \n \n \n Impact of MRI markers in subcortical vascular dementia: a multi-modal analysis in CADASIL.\n \n \n \n\n\n \n Viswanathan, A.; Godin, O.; Jouvent, E.; O'Sullivan, M.; Gschwendtner, A.; Peters, N.; Duering, M.; Guichard, J. P.; Holtmannspotter, M.; Dufouil, C.; Pachai, C.; Bousser, M. G.; Dichgans, M.; and Chabriat, H.\n\n\n \n\n\n\n Neurobiol Aging, 31(9): 1629–36. September 2010.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{viswanathan_impact_2010,\n\ttitle = {Impact of {MRI} markers in subcortical vascular dementia: a multi-modal analysis in {CADASIL}},\n\tvolume = {31},\n\tissn = {1558-1497 (Electronic) 0197-4580 (Linking)},\n\tdoi = {10.1016/j.neurobiolaging.2008.09.001},\n\tabstract = {CADASIL is an arteriopathy caused by mutations of the Notch3 gene. White matter hyperintensities (WMH), lacunar lesions (LL), cerebral microhemorrhages (CM), brain atrophy and tissue microstructural changes are detected on MRI. Using an integrated multi-modal approach, we examined the relative impact of lesion burden and location of these MRI markers on cognitive impairment and disability. Multi-modal imaging was performed on 147 patients from a two-center cohort study. Volume of LL, WMH and number of CM was determined. Whole brain mean apparent diffusion coefficient (mean-ADC) and brain parenchymal fraction (BPF) were measured. In multivariate models accounting for lesion burden and location, volume of LL, mean-ADC, and BPF each had an independent influence on global cognitive function and disability. BPF explained the largest portion of the variation in cognitive and disability scores (35-38\\%). Brain atrophy has the strongest independent influence on clinical impairment in CADASIL when all MRI markers in the disease are considered together. The results suggest that the clinical impact of cerebral tissue loss plays a principal role in this genetic model of subcortical ischemic vascular dementia.},\n\tnumber = {9},\n\tjournal = {Neurobiol Aging},\n\tauthor = {Viswanathan, A. and Godin, O. and Jouvent, E. and O'Sullivan, M. and Gschwendtner, A. and Peters, N. and Duering, M. and Guichard, J. P. and Holtmannspotter, M. and Dufouil, C. and Pachai, C. and Bousser, M. G. and Dichgans, M. and Chabriat, H.},\n\tmonth = sep,\n\tyear = {2010},\n\tpmid = {18926602},\n\tkeywords = {Female, Humans, Male, Middle Aged, Magnetic Resonance Imaging, Reproducibility of Results, Sensitivity and Specificity, Magnetic Resonance Imaging/*methods, Multivariate Analysis, Brain/*pathology, Image Interpretation, Computer-Assisted/*methods, France, Germany, Image Interpretation, Computer-Assisted, CADASIL/*pathology, Image Enhancement/methods, Brain, Image Enhancement, CADASIL},\n\tpages = {1629--36},\n}\n\n

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\n \n 2009\n \n \n (3)\n \n \n

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\n \n\n \n \n \n \n \n CADASIL mutations enhance spontaneous multimerization of NOTCH3.\n \n \n \n\n\n \n Opherk, C.; Duering, M.; Peters, N.; Karpinska, A.; Rosner, S.; Schneider, E.; Bader, B.; Giese, A.; and Dichgans, M.\n\n\n \n\n\n\n Hum Mol Genet, 18(15): 2761–7. August 2009.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{opherk_cadasil_2009,\n\ttitle = {{CADASIL} mutations enhance spontaneous multimerization of {NOTCH3}},\n\tvolume = {18},\n\tissn = {1460-2083 (Electronic) 0964-6906 (Linking)},\n\tdoi = {10.1093/hmg/ddp211},\n\tabstract = {Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) is the most common monogenic cause of stroke and vascular dementia. Disease-causing mutations invariably affect cysteine residues within epidermal growth factor-like repeat domains in the extracellular domain of the NOTCH3 receptor (N3(ECD)). The biochemical and histopathological hallmark of CADASIL is the accumulation of N3(ECD) at the cell surface of vascular smooth muscle cells which degenerate over the course of the disease. The molecular mechanisms leading to N3(ECD) accumulation remain unknown. Here we show that both wild-type and CADASIL-mutated N3(ECD) spontaneously form oligomers and higher order multimers in vitro and that multimerization is mediated by disulfide bonds. Using single-molecule analysis techniques ('scanning for intensely fluorescent targets'), we demonstrate that CADASIL-associated mutations significantly enhance multimerization compared with wild-type. Taken together, our results for the first time provide experimental evidence for N3 self-association and strongly argue for a neomorphic effect of CADASIL mutations in disease pathogenesis.},\n\tnumber = {15},\n\tjournal = {Hum Mol Genet},\n\tauthor = {Opherk, C. and Duering, M. and Peters, N. and Karpinska, A. and Rosner, S. and Schneider, E. and Bader, B. and Giese, A. and Dichgans, M.},\n\tmonth = aug,\n\tyear = {2009},\n\tpmid = {19417009},\n\tkeywords = {Humans, *Mutation, Protein Binding, Receptor, Notch3, *Protein Multimerization, CADASIL/*genetics/metabolism, Cell Line, Receptors, Notch/*chemistry/*genetics/metabolism, Mutation, CADASIL, Receptors, Notch, Protein Multimerization},\n\tpages = {2761--7},\n}\n\n

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\n \n\n \n \n \n \n \n Ischemic stroke of the cortical \"hand knob\" area: stroke mechanisms and prognosis.\n \n \n \n\n\n \n Peters, N.; Muller-Schunk, S.; Freilinger, T.; During, M.; Pfefferkorn, T.; and Dichgans, M.\n\n\n \n\n\n\n J Neurol, 256(7): 1146–51. July 2009.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{peters_ischemic_2009,\n\ttitle = {Ischemic stroke of the cortical "hand knob" area: stroke mechanisms and prognosis},\n\tvolume = {256},\n\tissn = {1432-1459 (Electronic) 0340-5354 (Linking)},\n\tdoi = {10.1007/s00415-009-5104-8},\n\tabstract = {Cortical ischemic stroke affecting the precentral "hand knob" area is a rare but well known stroke entity. To date, little is known about the underlying stroke mechanisms and the prognosis. Twenty-nine patients admitted to our service between 2003 and 2007 were included in the study on the basis of an acute ischemic infarct of the cortical "hand knob" area confirmed by diffusion-weighted magnetic resonance imaging with contralateral hand paresis. For all patients clinical, epidemiological as well as imaging data at the time point of admission were analysed retrospectively and follow-up data on all patients was obtained. The majority (n = 21/72\\%) had an isolated infarct of the cortical "hand knob" area. In 23 (79\\%) patients it was a first ever stroke. Ten patients (34\\%) had ipsilateral extracranial stenosis of the internal carotid artery (ICA), whereas potential cardiac embolic sources were less frequent (n = 4/14\\%). No patient exhibited ipsilateral MCA stenosis. All but two patients (93\\%) had marked atherosclerotic alterations of the ICA. Hypertension was the most prevalent vascular risk factor (n = 23/79\\%). At follow-up (mean 25.0 months, range 0.4-47.4 months) no patient had died and only one (3\\%) experienced a recurrent stroke. The majority of patients (79\\%) reported improvement of hand paresis, 17 (59\\%) were asymptomatic (modified Rankin score = 0). Only one patient was significantly disabled due to a recurrent stroke. In conclusion, ischemic infarcts affecting the cortical "hand knob" area are frequently associated with atherosclerotic changes of the carotid artery, suggesting an arterio-arterial thrombembolic stroke mechanism. It mostly reflects first ever ischemic stroke, and follow-up data suggest a rather benign course.},\n\tnumber = {7},\n\tjournal = {J Neurol},\n\tauthor = {Peters, N. and Muller-Schunk, S. and Freilinger, T. and During, M. and Pfefferkorn, T. and Dichgans, M.},\n\tmonth = jul,\n\tyear = {2009},\n\tpmid = {19353229},\n\tkeywords = {Stroke, Aged, Female, Humans, Male, Middle Aged, Magnetic Resonance Imaging, Prognosis, Nerve Fibers, Myelinated/pathology, Retrospective Studies, Recovery of Function/physiology, Brain Ischemia/pathology/*physiopathology/rehabilitation, Carotid Stenosis/*complications/pathology/physiopathology, Hand/innervation/*physiopathology, Intracranial Arteriosclerosis/complications/pathology/physiopathology, Motor Cortex/blood supply/pathology/*physiopathology, Paresis/pathology/physiopathology/rehabilitation, Recurrence, Stroke Rehabilitation, Stroke/pathology/*physiopathology, Intracranial Arteriosclerosis, Nerve Fibers, Myelinated, Motor Cortex, Brain Ischemia, Recovery of Function, Paresis, Carotid Stenosis, Hand},\n\tpages = {1146--51},\n}\n\n

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\n \n\n \n \n \n \n \n Hippocampal volume is an independent predictor of cognitive performance in CADASIL.\n \n \n \n\n\n \n O'Sullivan, M.; Ngo, E.; Viswanathan, A.; Jouvent, E.; Gschwendtner, A.; Saemann, P. G.; Duering, M.; Pachai, C.; Bousser, M. G.; Chabriat, H.; and Dichgans, M.\n\n\n \n\n\n\n Neurobiol Aging, 30(6): 890–7. June 2009.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{osullivan_hippocampal_2009,\n\ttitle = {Hippocampal volume is an independent predictor of cognitive performance in {CADASIL}},\n\tvolume = {30},\n\tissn = {1558-1497 (Electronic) 0197-4580 (Linking)},\n\tdoi = {10.1016/j.neurobiolaging.2007.09.002},\n\tabstract = {Recent evidence suggests that hippocampal changes are present in vascular cognitive impairment but their importance and relationship with ischaemic mechanisms remain controversial. To investigate these issues we performed MRI and cognitive assessment in a large cohort (n=144) of patients with CADASIL, a hereditary small vessel disease and model of pure vascular cognitive impairment. Dementia status was ascribed according to DSM-IV and global cognitive function assessed with the Minimental State Examination (MMSE) and Mattis Dementia Rating Scale (MDRS). Hippocampal volume (HV) correlated with age (r=-0.33, p{\\textless}0.001), brain volume (r=0.39, p{\\textless}0.001) and lacunar lesion volume (r=-0.23, p=0.008), but not white matter lesions or microhaemorrhages. HV was reduced in dementia (2272+/-333 mm(3) versus 2642+/-349 mm(3), p{\\textless}0.001) in the whole cohort and the subgroup progressing to dementia before age 60. HV correlated with MMSE (r=0.30, p{\\textless}0.001), MDRS (r=0.40, p{\\textless}0.001) and in a multivariate model predicted cognition independent of typical vascular lesions and whole brain atrophy. These findings strengthen the view that hippocampal atrophy is an important pathway of cognitive impairment in vascular as well as degenerative disease.},\n\tnumber = {6},\n\tjournal = {Neurobiol Aging},\n\tauthor = {O'Sullivan, M. and Ngo, E. and Viswanathan, A. and Jouvent, E. and Gschwendtner, A. and Saemann, P. G. and Duering, M. and Pachai, C. and Bousser, M. G. and Chabriat, H. and Dichgans, M.},\n\tmonth = jun,\n\tyear = {2009},\n\tpmcid = {PMC3085992},\n\tpmid = {17963999},\n\tkeywords = {Cognition, Female, Humans, Male, Middle Aged, Magnetic Resonance Imaging, Reproducibility of Results, Hippocampus, Sensitivity and Specificity, Magnetic Resonance Imaging/*methods, Imaging, Three-Dimensional, *Cognition, Statistics as Topic, Organ Size, CADASIL/complications/*diagnosis/*pathology, Cognition Disorders/*diagnosis, Hippocampus/*pathology, Imaging, Three-Dimensional/*methods, Cognition Disorders, CADASIL},\n\tpages = {890--7},\n}\n\n

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\n \n 2005\n \n \n (2)\n \n \n

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\n \n\n \n \n \n \n \n Mean age of onset in familial Alzheimer's disease is determined by amyloid beta 42.\n \n \n \n\n\n \n Duering, M.; Grimm, M. O.; Grimm, H. S.; Schroder, J.; and Hartmann, T.\n\n\n \n\n\n\n Neurobiol Aging, 26(6): 785–8. June 2005.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{duering_mean_2005,\n\ttitle = {Mean age of onset in familial {Alzheimer}'s disease is determined by amyloid beta 42},\n\tvolume = {26},\n\tissn = {0197-4580 (Print) 0197-4580 (Linking)},\n\tdoi = {10.1016/j.neurobiolaging.2004.08.002},\n\tabstract = {More than 130 known mutations in the presenilin-1 (PS1) gene result in familial Alzheimer's disease (FAD) with a mutation specific age of disease onset. These mutations increase amyloid beta 42 (A beta42) levels, and this increase has been validated in recent years as one pathogenic factor in FAD. However, further malfunctions of mutant presenilin-1 are discussed as well. In order to assess the weight of A beta42 regarding the pathogenesis of FAD, we expressed mutant forms of PS1 (30-65 years onset age) in COS-7 cells and analyzed amyloid beta levels by a novel ELISA. We found a strong correlation (r = 0.98; p{\\textless}0.001) between the A beta40/42-ratio and mean age of disease onset indicating a substantial extent of A beta42 contribution to FAD pathology. Our data strongly suggest that A beta42 is the decisive factor for age of onset in FAD.},\n\tnumber = {6},\n\tjournal = {Neurobiol Aging},\n\tauthor = {Duering, M. and Grimm, M. O. and Grimm, H. S. and Schroder, J. and Hartmann, T.},\n\tmonth = jun,\n\tyear = {2005},\n\tpmid = {15718035},\n\tkeywords = {Adult, Aged, Humans, Middle Aged, Age of Onset, Aging/*genetics/*metabolism, Alzheimer Disease/*genetics/*metabolism, Amyloid beta-Peptides/*genetics/*metabolism, Animals, Cercopithecus aethiops, COS Cells, Genetic Predisposition to Disease/genetics, Membrane Proteins/*genetics/*metabolism, Peptide Fragments/*genetics/*metabolism, Presenilin-1, Rats, Aging, Genetic Predisposition to Disease, Amyloid beta-Peptides, Alzheimer Disease, Peptide Fragments, Chlorocebus aethiops, Membrane Proteins},\n\tpages = {785--8},\n}\n\n

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\n \n\n \n \n \n \n \n Regulation of cholesterol and sphingomyelin metabolism by amyloid-beta and presenilin.\n \n \n \n\n\n \n Grimm, M. O.; Grimm, H. S.; Patzold, A. J.; Zinser, E. G.; Halonen, R.; Duering, M.; Tschape, J. A.; De Strooper, B.; Muller, U.; Shen, J.; and Hartmann, T.\n\n\n \n\n\n\n Nat Cell Biol, 7(11): 1118–23. November 2005.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

@article{grimm_regulation_2005,\n\ttitle = {Regulation of cholesterol and sphingomyelin metabolism by amyloid-beta and presenilin},\n\tvolume = {7},\n\tissn = {1465-7392 (Print) 1465-7392 (Linking)},\n\tdoi = {10.1038/ncb1313},\n\tabstract = {Amyloid beta peptide (Abeta) has a key role in the pathological process of Alzheimer's disease (AD), but the physiological function of Abeta and of the amyloid precursor protein (APP) is unknown. Recently, it was shown that APP processing is sensitive to cholesterol and other lipids. Hydroxymethylglutaryl-CoA reductase (HMGR) and sphingomyelinases (SMases) are the main enzymes that regulate cholesterol biosynthesis and sphingomyelin (SM) levels, respectively. We show that control of cholesterol and SM metabolism involves APP processing. Abeta42 directly activates neutral SMase and downregulates SM levels, whereas Abeta40 reduces cholesterol de novo synthesis by inhibition of HMGR activity. This process strictly depends on gamma-secretase activity. In line with altered Abeta40/42 generation, pathological presenilin mutations result in increased cholesterol and decreased SM levels. Our results demonstrate a biological function for APP processing and also a functional basis for the link that has been observed between lipids and Alzheimer's disease (AD).},\n\tnumber = {11},\n\tjournal = {Nat Cell Biol},\n\tauthor = {Grimm, M. O. and Grimm, H. S. and Patzold, A. J. and Zinser, E. G. and Halonen, R. and Duering, M. and Tschape, J. A. and De Strooper, B. and Muller, U. and Shen, J. and Hartmann, T.},\n\tmonth = nov,\n\tyear = {2005},\n\tpmid = {16227967},\n\tkeywords = {Humans, Animals, Cercopithecus aethiops, COS Cells, Presenilin-1, Mice, Amyloid beta-Peptides, *Lipid Metabolism, Amyloid beta-Peptides/analysis/metabolism/*physiology, Amyloid beta-Protein Precursor/metabolism/*physiology, Amyloid Precursor Protein Secretases, Aspartic Acid Endopeptidases, Cells, Cultured, Cholesterol/*metabolism, Endopeptidases/metabolism, Gene Expression Regulation, Membrane Proteins/metabolism/physiology, Peptide Fragments/*analysis/metabolism, Presenilin-2, Sphingomyelin Phosphodiesterase/metabolism, Sphingomyelins/*metabolism, Amyloid beta-Protein Precursor, Peptide Fragments, Chlorocebus aethiops, Membrane Proteins, Cholesterol, Endopeptidases, Lipid Metabolism, Sphingomyelin Phosphodiesterase, Sphingomyelins},\n\tpages = {1118--23},\n}\n\n

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