@article{
 title = {On the merits of non-invasive myelin imaging in epilepsy, a literature review},
 type = {article},
 year = {2020},
 pages = {108687},
 volume = {338},
 websites = {https://linkinghub.elsevier.com/retrieve/pii/S0165027020301096},
 month = {5},
 id = {51978c9c-0400-398a-945b-969ff7949a91},
 created = {2020-04-08T10:13:39.472Z},
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 profile_id = {7beca3ea-bd78-352c-ad7d-8235fb917e77},
 last_modified = {2021-08-04T12:11:55.100Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 bibtype = {article},
 author = {Drenthen, G.S. and Backes, Walter H. and Aldenkamp, Albert P. and Vermeulen, R. Jeroen and Klinkenberg, Sylvia and Jansen, Jacobus F.A.},
 doi = {10.1016/j.jneumeth.2020.108687},
 journal = {Journal of Neuroscience Methods}
}

@article{
 title = {Constructing an Axonal-Specific Myelin Developmental Graph and its Application to Childhood Absence Epilepsy},
 type = {article},
 year = {2020},
 keywords = {20,2020,6202 az maastricht,a,acceptance,accepted for publication march,address correspondence to dr,and in revised form,center,correspondence,d,department of radiology and,diffusion mri,e-mail,f,j,jacobus,jansen,maastricht university medical,march 18,maturation,mumc,myelin-water,nl,nuclear medicine,ph,po box 5800,received february 19,the netherlands,tractography,white matter},
 pages = {308-314},
 volume = {30},
 websites = {http://doi.wiley.com/10.1111/jon.12707},
 month = {4},
 day = {7},
 id = {34c7488d-9600-335b-a963-7758beed9ff5},
 created = {2020-04-15T19:06:34.135Z},
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 last_modified = {2024-09-04T05:59:50.772Z},
 read = {false},
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 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Drenthen2020b},
 private_publication = {false},
 bibtype = {article},
 author = {Drenthen, G.S. and Fonseca Wald, Eric L. A. and Backes, Walter H and Aldenkamp, Albert P and Vermeulen, R Jeroen and Debeij-van Hall, Mariette H. J. A. and Klinkenberg, Sylvia and Jansen, Jacobus F A},
 doi = {10.1111/jon.12707},
 journal = {Journal of Neuroimaging},
 number = {3}
}

@article{
 title = {Spectral Diffusion Analysis of Intravoxel Incoherent Motion MRI in Cerebral Small Vessel Disease},
 type = {article},
 year = {2020},
 keywords = {MRI,cerebral small vessel disease,diffusion magnetic resonance imaging,glymphatic system},
 pages = {1170-1180},
 volume = {51},
 id = {2adf4dc2-8f71-39f9-b8a2-981ab91fa6c4},
 created = {2020-04-15T19:06:34.216Z},
 file_attached = {false},
 profile_id = {7beca3ea-bd78-352c-ad7d-8235fb917e77},
 last_modified = {2024-09-04T05:59:44.450Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Wong2020},
 private_publication = {false},
 abstract = {Background: Cerebral intravoxel incoherent motion (IVIM) imaging assumes two components. However, more compartments are likely present in pathologic tissue. We hypothesized that spectral analysis using a nonnegative least-squares (NNLS) approach can detect an additional, intermediate diffusion component, distinct from the parenchymal and microvascular components, in lesion-prone regions. Purpose: To investigate the presence of this intermediate diffusion component and its relation with cerebral small vessel disease (cSVD)-related lesions. Study Type: Prospective cross-sectional study. Population: Patients with cSVD (n = 69, median age 69.8) and controls (n = 39, median age 68.9). Field Strength/Sequence: Whole-brain inversion recovery IVIM acquisition at 3.0T. Assessment: Enlarged perivascular spaces (PVS) were rated by three raters. White matter hyperintensities (WMH) were identified on a fluid attenuated inversion recovery (FLAIR) image using a semiautomated algorithm. Statistical Tests: Relations between IVIM measures and cSVD-related lesions were studied using the Spearman's rank order correlation. Results: NNLS yielded diffusion spectra from which the intermediate volume fraction fint was apparent between parenchymal diffusion and microvasular pseudodiffusion. WMH volume and the extent of MRI-visible enlarged PVS in the basal ganglia (BG) and centrum semiovale (CSO) were correlated with fint in the WMHs, BG, and CSO, respectively. fint was 4.2 ± 1.7%, 7.0 ± 4.1% and 13.6 ± 7.7% in BG and 3.9 ± 1.3%, 4.4 ± 1.4% and 4.5 ± 1.2% in CSO for the groups with low, moderate, and high number of enlarged PVS, respectively, and increased with the extent of enlarged PVS (BG: r = 0.49, P < 0.01; CSO: r = 0.23, P = 0.02). fint in the WMHs was 27.1 ± 13.1%, and increased with the WMH volume (r = 0.57, P < 0.01). Data Conclusion: We revealed the presence of an intermediate diffusion component in lesion-prone regions of cSVD and demonstrated its relation with enlarged PVS and WMHs. In tissue with these lesions, tissue degeneration or perivascular edema can lead to more freely diffusing interstitial fluid contributing to fint. Level of Evidence: 2. Technical Efficacy: Stage 2. J. Magn. Reson. Imaging 2020;51:1170–1180.},
 bibtype = {article},
 author = {Wong, Sau May and Backes, Walter H. and Drenthen, G.S. and Zhang, C. Eleana and Voorter, Paulien H.M. and Staals, Julie and van Oostenbrugge, Robert J. and Jansen, Jacobus F.A.},
 doi = {10.1002/jmri.26920},
 journal = {Journal of Magnetic Resonance Imaging},
 number = {4}
}

Background: Cerebral intravoxel incoherent motion (IVIM) imaging assumes two components. However, more compartments are likely present in pathologic tissue. We hypothesized that spectral analysis using a nonnegative least-squares (NNLS) approach can detect an additional, intermediate diffusion component, distinct from the parenchymal and microvascular components, in lesion-prone regions. Purpose: To investigate the presence of this intermediate diffusion component and its relation with cerebral small vessel disease (cSVD)-related lesions. Study Type: Prospective cross-sectional study. Population: Patients with cSVD (n = 69, median age 69.8) and controls (n = 39, median age 68.9). Field Strength/Sequence: Whole-brain inversion recovery IVIM acquisition at 3.0T. Assessment: Enlarged perivascular spaces (PVS) were rated by three raters. White matter hyperintensities (WMH) were identified on a fluid attenuated inversion recovery (FLAIR) image using a semiautomated algorithm. Statistical Tests: Relations between IVIM measures and cSVD-related lesions were studied using the Spearman's rank order correlation. Results: NNLS yielded diffusion spectra from which the intermediate volume fraction fint was apparent between parenchymal diffusion and microvasular pseudodiffusion. WMH volume and the extent of MRI-visible enlarged PVS in the basal ganglia (BG) and centrum semiovale (CSO) were correlated with fint in the WMHs, BG, and CSO, respectively. fint was 4.2 ± 1.7%, 7.0 ± 4.1% and 13.6 ± 7.7% in BG and 3.9 ± 1.3%, 4.4 ± 1.4% and 4.5 ± 1.2% in CSO for the groups with low, moderate, and high number of enlarged PVS, respectively, and increased with the extent of enlarged PVS (BG: r = 0.49, P < 0.01; CSO: r = 0.23, P = 0.02). fint in the WMHs was 27.1 ± 13.1%, and increased with the WMH volume (r = 0.57, P < 0.01). Data Conclusion: We revealed the presence of an intermediate diffusion component in lesion-prone regions of cSVD and demonstrated its relation with enlarged PVS and WMHs. In tissue with these lesions, tissue degeneration or perivascular edema can lead to more freely diffusing interstitial fluid contributing to fint. Level of Evidence: 2. Technical Efficacy: Stage 2. J. Magn. Reson. Imaging 2020;51:1170–1180.

@article{
 title = {Correction to: Towards a Better Understanding of Cognitive Deficits in Absence Epilepsy: a Systematic Review and Meta-Analysis (Neuropsychology Review, (2019), 29, 4, (421-449), 10.1007/s11065-019-09419-2)},
 type = {article},
 year = {2020},
 volume = {30},
 id = {34e94c6e-b249-3070-a6eb-fc7d0ffc2f5d},
 created = {2019-12-30T23:59:00.000Z},
 file_attached = {false},
 profile_id = {7beca3ea-bd78-352c-ad7d-8235fb917e77},
 last_modified = {2021-03-02T12:36:13.526Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {true},
 abstract = {© 2019, The Author(s). Due to an error during the editorial phase, a correction regarding Fig. 2 is added to the original article: “Towards a Better Understanding of Cognitive Deficits in Absence Epilepsy: a Systematic Review and Meta-Analysis”. Please see below correct Fig. 2.},
 bibtype = {article},
 author = {Fonseca Wald, E.L.A. and Hendriksen, J.G.M. and Drenthen, G.S. and Kuijk, S.M.J.V. and Aldenkamp, A.P. and Vles, J.S.H. and Vermeulen, R.J. and Debeij van Hall, M.H.J.A. and Klinkenberg, S.},
 doi = {10.1007/s11065-019-09425-4},
 journal = {Neuropsychology Review},
 number = {1}
}

© 2019, The Author(s). Due to an error during the editorial phase, a correction regarding Fig. 2 is added to the original article: “Towards a Better Understanding of Cognitive Deficits in Absence Epilepsy: a Systematic Review and Meta-Analysis”. Please see below correct Fig. 2.

@article{
 title = {Applicability and reproducibility of 2D multi-slice GRASE myelin water fraction with varying acquisition acceleration},
 type = {article},
 year = {2019},
 keywords = {myelin water fraction},
 pages = {333-339},
 volume = {195},
 month = {7},
 publisher = {Elsevier Ltd},
 id = {07ef1f77-e845-3346-94a6-51952726e662},
 created = {2019-08-05T07:42:30.944Z},
 file_attached = {false},
 profile_id = {7beca3ea-bd78-352c-ad7d-8235fb917e77},
 last_modified = {2024-09-04T05:59:42.526Z},
 read = {true},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Drenthen2019d},
 private_publication = {false},
 bibtype = {article},
 author = {Drenthen, G.S. and Backes, Walter H and Aldenkamp, Albert P and Jansen, Jacobus F.A.},
 doi = {10.1016/j.neuroimage.2019.04.011},
 journal = {NeuroImage}
}

@article{
 title = {Towards a Better Understanding of Cognitive Deficits in Absence Epilepsy: a Systematic Review and Meta-Analysis},
 type = {article},
 year = {2019},
 keywords = {Absence epilepsy,Cognition,Meta-analysis,Systematic review,absence epilepsy,cognition,meta-analysis,systematic review},
 websites = {http://link.springer.com/10.1007/s11065-019-09419-2},
 month = {11},
 publisher = {Neuropsychology Review},
 day = {27},
 id = {af312efc-19a1-35a1-8603-5033457197b1},
 created = {2019-12-06T09:24:39.781Z},
 file_attached = {false},
 profile_id = {7beca3ea-bd78-352c-ad7d-8235fb917e77},
 last_modified = {2021-08-04T12:11:55.000Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 bibtype = {article},
 author = {Fonseca Wald, Eric L. A. and Hendriksen, Jos G M and Drenthen, G.S. and Kuijk, Sander M J V and Aldenkamp, Albert P and Vles, Johan S H and Vermeulen, R Jeroen and Debeij-van Hall, Mariette H. J. A. and Klinkenberg, Sylvia},
 doi = {10.1007/s11065-019-09419-2},
 journal = {Neuropsychology Review}
}

@article{
 title = {A new analysis approach for T 2 relaxometry myelin water quantification: Orthogonal Matching Pursuit},
 type = {article},
 year = {2018},
 keywords = {2018 the authors magnetic,access article under the,by wiley periodicals,commons attribution,distribution,distribution in any medium,in medicine,inc,myelin water fraction,noderivs license,noncommercial,nonnegative least squares,on behalf of international,orthogonal matching pursuit,provided,resonance in medicine published,society for magnetic resonance,t 2 relaxometry,terms of the creative,this is an open,which permits use and},
 pages = {3292–3303},
 volume = {81},
 websites = {https://onlinelibrary.wiley.com/doi/abs/10.1002/mrm.27600},
 month = {11},
 day = {16},
 id = {934a7a32-e8fa-3d2a-9859-47dcc1f89dc0},
 created = {2019-08-05T07:42:31.342Z},
 file_attached = {false},
 profile_id = {7beca3ea-bd78-352c-ad7d-8235fb917e77},
 last_modified = {2021-08-04T12:11:54.997Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Drenthen2018},
 source_type = {article},
 private_publication = {false},
 bibtype = {article},
 author = {Drenthen, G.S. and Backes, Walter H. and Aldenkamp, Albert P. and Op ’t Veld, Giel J. and Jansen, Jacobus F. A.},
 doi = {10.1002/mrm.27600},
 journal = {Magnetic Resonance in Medicine},
 number = {5}
}

@article{
 title = {Structural covariance networks relate to the severity of epilepsy with focal-onset seizures},
 type = {article},
 year = {2018},
 keywords = {Cognition,Cortical thickness,Epilepsy,Magnetic resonance imaging,Seizures,Structural covarience networks,magnetic resonance imaging},
 pages = {861-867},
 volume = {20},
 websites = {https://doi.org/10.1016/j.nicl.2018.09.023},
 publisher = {Elsevier},
 id = {10468b59-2085-395f-97ab-55f5459ee13c},
 created = {2019-08-05T07:42:31.376Z},
 file_attached = {false},
 profile_id = {7beca3ea-bd78-352c-ad7d-8235fb917e77},
 last_modified = {2021-08-04T12:11:55.179Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Drenthen2019},
 source_type = {article},
 notes = {<b>From Duplicate 1 (<i>Structural covariance networks relate to the severity of epilepsy with focal-onset seizures</i> - Drenthen, Gerhard S; Backes, Walter H; Rouhl, Rob P W; Vlooswijk, Marielle C G; Majoie, Marian H J M; Hofman, Paul A M; Aldenkamp, Albert P; Jansen, Jacobus F A)<br/></b><br/>I've read abstract},
 folder_uuids = {17c8aa2e-4ed1-4e35-b279-0a987cbf22b9},
 private_publication = {false},
 abstract = {© 2018 The Authors Purpose: The brains of patients with epilepsy may exhibit various morphological abnormalities, which are often not directly visible on structural MR images, as they may be focally subtle or related to a more large-scale inconspicuous disorganization of brain structures. To explore the relation between structural brain organization and epilepsy characteristics, including severity and cognitive co-morbidity, we determined structural covariance networks (SCNs). SCNs represent interregional correlations of morphologic measures, for instance in terms of cortical thickness, between various large-scale distributed brain regions. Methods: Thirty-eight patients with focal seizures of all subtypes and 21 healthy controls underwent structural MRI, neurological, and IQ assessment. Cortical thickness was derived from the structural MRIs using FreeSurfer. Subsequently, SCNs were constructed on a group-level based on correlations of the cortical thicknesses between various brain regions. Individual SCNs for the epilepsy patients were extracted by adding the respective patient to the control group prior to the SCN construction (i.e. add-one-patient approach). Calculated network measures, i.e. path length, clustering coefficient and betweenness centrality were correlated with characteristics related to the severity of epilepsy, including seizure history and age at onset of epilepsy, and cognitive performance. Results: Stronger clustering in the individual SCN was associated with a higher number of focal to bilateral tonic-clonic seizures during life time, a younger age at onset, and lower cognitive performance. The path length of the individual SCN was not related to the severity of epilepsy or cognitive performance. Higher betweenness centrality of the left cuneus and lower betweenness centrality of the right rostral middle frontal gyrus were associated with increased drug load and younger age at onset, respectively. Conclusions: These results indicate that the correlations between interregional variations of cortical thickness reflect disease characteristics or responses to the disease and deficits in patients with epilepsy with focal seizures.},
 bibtype = {article},
 author = {Drenthen, G.S. and Backes, Walter H and Rouhl, Rob P W and Vlooswijk, M.C.G. and Majoie, Marian H J and Hofman, Paul A M and Aldenkamp, Albert P and Jansen, J.F.A.},
 doi = {10.1016/j.nicl.2018.09.023},
 journal = {NeuroImage: Clinical},
 number = {2018}
}

© 2018 The Authors Purpose: The brains of patients with epilepsy may exhibit various morphological abnormalities, which are often not directly visible on structural MR images, as they may be focally subtle or related to a more large-scale inconspicuous disorganization of brain structures. To explore the relation between structural brain organization and epilepsy characteristics, including severity and cognitive co-morbidity, we determined structural covariance networks (SCNs). SCNs represent interregional correlations of morphologic measures, for instance in terms of cortical thickness, between various large-scale distributed brain regions. Methods: Thirty-eight patients with focal seizures of all subtypes and 21 healthy controls underwent structural MRI, neurological, and IQ assessment. Cortical thickness was derived from the structural MRIs using FreeSurfer. Subsequently, SCNs were constructed on a group-level based on correlations of the cortical thicknesses between various brain regions. Individual SCNs for the epilepsy patients were extracted by adding the respective patient to the control group prior to the SCN construction (i.e. add-one-patient approach). Calculated network measures, i.e. path length, clustering coefficient and betweenness centrality were correlated with characteristics related to the severity of epilepsy, including seizure history and age at onset of epilepsy, and cognitive performance. Results: Stronger clustering in the individual SCN was associated with a higher number of focal to bilateral tonic-clonic seizures during life time, a younger age at onset, and lower cognitive performance. The path length of the individual SCN was not related to the severity of epilepsy or cognitive performance. Higher betweenness centrality of the left cuneus and lower betweenness centrality of the right rostral middle frontal gyrus were associated with increased drug load and younger age at onset, respectively. Conclusions: These results indicate that the correlations between interregional variations of cortical thickness reflect disease characteristics or responses to the disease and deficits in patients with epilepsy with focal seizures.

@article{
 title = {Altered neurotransmitter metabolism in adolescents with high-functioning autism},
 type = {article},
 year = {2016},
 pages = {44-49},
 volume = {256},
 websites = {https://linkinghub.elsevier.com/retrieve/pii/S0925492715301633},
 month = {10},
 id = {5265410c-2522-36f1-8430-5d9a162fd5e4},
 created = {2020-04-08T10:14:00.199Z},
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 profile_id = {7beca3ea-bd78-352c-ad7d-8235fb917e77},
 last_modified = {2021-08-04T12:11:55.405Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 bibtype = {article},
 author = {Drenthen, G.S. and Barendse, Evelien M. and Aldenkamp, Albert P. and van Veenendaal, Tamar M. and Puts, Nicolaas A.J. and Edden, Richard A.E. and Zinger, Svitlana and Thoonen, Geert and Hendriks, Marc P.H. and Kessels, Roy P.C. and Jansen, Jacobus F.A.},
 doi = {10.1016/j.pscychresns.2016.09.007},
 journal = {Psychiatry Research: Neuroimaging}
}