@article{for_the_alzheimers_disease_neuroimaging_initiative_automatically_2019,
	title = {Automatically computed rating scales from {MRI} for patients with cognitive disorders},
	volume = {29},
	issn = {0938-7994, 1432-1084},
	url = {http://link.springer.com/10.1007/s00330-019-06067-1},
	doi = {10.1007/s00330-019-06067-1},
	abstract = {Objectives The aims of this study were to examine whether visual MRI rating scales used in diagnostics of cognitive disorders can be estimated computationally and to compare the visual rating scales with their computed counterparts in differential diagnostics. Methods A set of volumetry and voxel-based morphometry imaging biomarkers was extracted from T1-weighted and FLAIR images. A regression model was developed for estimating visual rating scale values from a combination of imaging biomarkers. We studied three visual rating scales: medial temporal lobe atrophy (MTA), global cortical atrophy (GCA), and white matter hyperintensities (WMHs) measured by the Fazekas scale. Images and visual ratings from the Amsterdam Dementia Cohort (ADC) (N = 513) were used to develop the models and cross-validate them. The PredictND (N = 672) and ADNI (N = 752) cohorts were used for independent validation to test generalizability.},
	language = {en},
	number = {9},
	urldate = {2019-08-05},
	journal = {European Radiology},
	author = {{for the Alzheimer’s Disease Neuroimaging Initiative} and Koikkalainen, Juha R. and Rhodius-Meester, Hanneke F. M. and Frederiksen, Kristian S. and Bruun, Marie and Hasselbalch, Steen G. and Baroni, Marta and Mecocci, Patrizia and Vanninen, Ritva and Remes, Anne and Soininen, Hilkka and van Gils, Mark and van der Flier, Wiesje M. and Scheltens, Philip and Barkhof, Frederik and Erkinjuntti, Timo and Lötjönen, Jyrki M. P.},
	month = sep,
	year = {2019},
	pages = {4937--4947},
}

{"_id":"kJZPJQGNEw7wa4zmA","bibbaseid":"forthealzheimersdiseaseneuroimaginginitiative-koikkalainen-rhodiusmeester-frederiksen-bruun-hasselbalch-baroni-mecocci-etal-automaticallycomputedratingscalesfrommriforpatientswithcognitivedisorders-2019","authorIDs":[],"author_short":["for the Alzheimer’s Disease Neuroimaging Initiative","Koikkalainen, J. R.","Rhodius-Meester, H. F. M.","Frederiksen, K. S.","Bruun, M.","Hasselbalch, S. G.","Baroni, M.","Mecocci, P.","Vanninen, R.","Remes, A.","Soininen, H.","van Gils, M.","van der Flier, W. M.","Scheltens, P.","Barkhof, F.","Erkinjuntti, T.","Lötjönen, J. M. P."],"bibdata":{"bibtype":"article","type":"article","title":"Automatically computed rating scales from MRI for patients with cognitive disorders","volume":"29","issn":"0938-7994, 1432-1084","url":"http://link.springer.com/10.1007/s00330-019-06067-1","doi":"10.1007/s00330-019-06067-1","abstract":"Objectives The aims of this study were to examine whether visual MRI rating scales used in diagnostics of cognitive disorders can be estimated computationally and to compare the visual rating scales with their computed counterparts in differential diagnostics. Methods A set of volumetry and voxel-based morphometry imaging biomarkers was extracted from T1-weighted and FLAIR images. A regression model was developed for estimating visual rating scale values from a combination of imaging biomarkers. We studied three visual rating scales: medial temporal lobe atrophy (MTA), global cortical atrophy (GCA), and white matter hyperintensities (WMHs) measured by the Fazekas scale. Images and visual ratings from the Amsterdam Dementia Cohort (ADC) (N = 513) were used to develop the models and cross-validate them. The PredictND (N = 672) and ADNI (N = 752) cohorts were used for independent validation to test generalizability.","language":"en","number":"9","urldate":"2019-08-05","journal":"European Radiology","author":[{"firstnames":[],"propositions":[],"lastnames":["for the Alzheimer’s Disease Neuroimaging Initiative"],"suffixes":[]},{"propositions":[],"lastnames":["Koikkalainen"],"firstnames":["Juha","R."],"suffixes":[]},{"propositions":[],"lastnames":["Rhodius-Meester"],"firstnames":["Hanneke","F.","M."],"suffixes":[]},{"propositions":[],"lastnames":["Frederiksen"],"firstnames":["Kristian","S."],"suffixes":[]},{"propositions":[],"lastnames":["Bruun"],"firstnames":["Marie"],"suffixes":[]},{"propositions":[],"lastnames":["Hasselbalch"],"firstnames":["Steen","G."],"suffixes":[]},{"propositions":[],"lastnames":["Baroni"],"firstnames":["Marta"],"suffixes":[]},{"propositions":[],"lastnames":["Mecocci"],"firstnames":["Patrizia"],"suffixes":[]},{"propositions":[],"lastnames":["Vanninen"],"firstnames":["Ritva"],"suffixes":[]},{"propositions":[],"lastnames":["Remes"],"firstnames":["Anne"],"suffixes":[]},{"propositions":[],"lastnames":["Soininen"],"firstnames":["Hilkka"],"suffixes":[]},{"propositions":["van"],"lastnames":["Gils"],"firstnames":["Mark"],"suffixes":[]},{"propositions":["van","der"],"lastnames":["Flier"],"firstnames":["Wiesje","M."],"suffixes":[]},{"propositions":[],"lastnames":["Scheltens"],"firstnames":["Philip"],"suffixes":[]},{"propositions":[],"lastnames":["Barkhof"],"firstnames":["Frederik"],"suffixes":[]},{"propositions":[],"lastnames":["Erkinjuntti"],"firstnames":["Timo"],"suffixes":[]},{"propositions":[],"lastnames":["Lötjönen"],"firstnames":["Jyrki","M.","P."],"suffixes":[]}],"month":"September","year":"2019","pages":"4937–4947","bibtex":"@article{for_the_alzheimers_disease_neuroimaging_initiative_automatically_2019,\n\ttitle = {Automatically computed rating scales from {MRI} for patients with cognitive disorders},\n\tvolume = {29},\n\tissn = {0938-7994, 1432-1084},\n\turl = {http://link.springer.com/10.1007/s00330-019-06067-1},\n\tdoi = {10.1007/s00330-019-06067-1},\n\tabstract = {Objectives The aims of this study were to examine whether visual MRI rating scales used in diagnostics of cognitive disorders can be estimated computationally and to compare the visual rating scales with their computed counterparts in differential diagnostics. Methods A set of volumetry and voxel-based morphometry imaging biomarkers was extracted from T1-weighted and FLAIR images. A regression model was developed for estimating visual rating scale values from a combination of imaging biomarkers. We studied three visual rating scales: medial temporal lobe atrophy (MTA), global cortical atrophy (GCA), and white matter hyperintensities (WMHs) measured by the Fazekas scale. Images and visual ratings from the Amsterdam Dementia Cohort (ADC) (N = 513) were used to develop the models and cross-validate them. The PredictND (N = 672) and ADNI (N = 752) cohorts were used for independent validation to test generalizability.},\n\tlanguage = {en},\n\tnumber = {9},\n\turldate = {2019-08-05},\n\tjournal = {European Radiology},\n\tauthor = {{for the Alzheimer’s Disease Neuroimaging Initiative} and Koikkalainen, Juha R. and Rhodius-Meester, Hanneke F. M. and Frederiksen, Kristian S. and Bruun, Marie and Hasselbalch, Steen G. and Baroni, Marta and Mecocci, Patrizia and Vanninen, Ritva and Remes, Anne and Soininen, Hilkka and van Gils, Mark and van der Flier, Wiesje M. and Scheltens, Philip and Barkhof, Frederik and Erkinjuntti, Timo and Lötjönen, Jyrki M. P.},\n\tmonth = sep,\n\tyear = {2019},\n\tpages = {4937--4947},\n}\n","author_short":["for the Alzheimer’s Disease Neuroimaging Initiative","Koikkalainen, J. R.","Rhodius-Meester, H. F. M.","Frederiksen, K. S.","Bruun, M.","Hasselbalch, S. G.","Baroni, M.","Mecocci, P.","Vanninen, R.","Remes, A.","Soininen, H.","van Gils, M.","van der Flier, W. M.","Scheltens, P.","Barkhof, F.","Erkinjuntti, T.","Lötjönen, J. M. P."],"key":"for_the_alzheimers_disease_neuroimaging_initiative_automatically_2019","id":"for_the_alzheimers_disease_neuroimaging_initiative_automatically_2019","bibbaseid":"forthealzheimersdiseaseneuroimaginginitiative-koikkalainen-rhodiusmeester-frederiksen-bruun-hasselbalch-baroni-mecocci-etal-automaticallycomputedratingscalesfrommriforpatientswithcognitivedisorders-2019","role":"author","urls":{"Paper":"http://link.springer.com/10.1007/s00330-019-06067-1"},"downloads":0},"bibtype":"article","biburl":"https://api.zotero.org/users/1776321/collections/CP6U8EPU/items?key=ALZwiC6nIlAY3QRwaV7XW896&format=bibtex&limit=100","creationDate":"2021-02-10T14:40:46.156Z","downloads":0,"keywords":[],"search_terms":["automatically","computed","rating","scales","mri","patients","cognitive","disorders","for the alzheimer’s disease neuroimaging initiative","koikkalainen","rhodius-meester","frederiksen","bruun","hasselbalch","baroni","mecocci","vanninen","remes","soininen","van gils","van der flier","scheltens","barkhof","erkinjuntti","lötjönen"],"title":"Automatically computed rating scales from MRI for patients with cognitive disorders","year":2019,"dataSources":["vteSnKe4pWxunW3j6"]}