title: Anatomical MRI and DTI in the diagnosis of Alzheimer's disease: a European multicenter study.
abstract: Diffusion tensor imaging (DTI) detects microstructural changes of the cerebral white matter in Alzheimer's disease (AD). The use of DTI for the diagnosis of AD in a multicenter setting has not yet been investigated. We used voxel-based analysis of fractional anisotropy, mean diffusivity, and grey matter volumes from multimodal magnetic resonance imaging data of 137 AD patients and 143 healthy elderly controls collected across 9 different scanners. We compared different univariate analysis approaches to model the effect of scanner, including a linear model across all scans with a scanner covariate, a random effects model with scanner as a random variable as well as a voxel-based meta-analysis. We found significant reduction of fractional anisotropy and significant increase of mean diffusivity in core areas of AD pathology including corpus callosum, medial and lateral temporal lobes, as well as fornix, cingulate gyrus, precuneus, and prefrontal lobe white matter. Grey matter atrophy was most pronounced in medial and lateral temporal lobe as well as parietal and prefrontal association cortex. The effects of group were spatially more restricted with random effects modeling of scanner effects compared to simple pooled analysis. All three analysis approaches yielded similar accuracy of group separation in block-wise cross-validated logistic regression. Our results suggest similar effects of center on group separation based on different analysis approaches and confirm a typical pattern of cortical and subcortical microstructural changes in AD using a large multimodal multicenter data set.
authors.affiliation: Department of Psychiatry, University of Rostock, Rostock, Germany. stefan.teipel@med.uni-rostock.de
authors.forename: Stefan J
authors.initials: SJ
authors.lastname: Teipel
authors.forename: Martin
authors.initials: M
authors.lastname: Wegrzyn
authors.forename: Thomas
authors.initials: T
authors.lastname: Meindl
authors.forename: Giovanni
authors.initials: G
authors.lastname: Frisoni
authors.forename: Arun L W
authors.initials: AL
authors.lastname: Bokde
authors.forename: Andreas
authors.initials: A
authors.lastname: Fellgiebel
authors.forename: Massimo
authors.initials: M
authors.lastname: Filippi
authors.forename: Harald
authors.initials: H
authors.lastname: Hampel
authors.forename: Stefan
authors.initials: S
authors.lastname: Klöppel
authors.forename: Karlheinz
authors.initials: K
authors.lastname: Hauenstein
authors.forename: Michael
authors.initials: M
authors.lastname: Ewers
mesh_terms: D000368:Aged; D000465:Algorithms; D000544:Alzheimer Disease / Q000175:diagnosis* / Q000473:pathology / Q000523:psychology; D001921:Brain / Q000473:pathology; D003627:Data Interpretation, Statistical; D056324:Diffusion Tensor Imaging / Q000295:instrumentation / Q000379:methods*; D004522:Educational Status; D005060:Europe; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging / Q000295:instrumentation / Q000379:methods*; D008297:Male; D008875:Middle Aged; D009483:Neuropsychological Tests; D012189:Retrospective Studies; D012959:Socioeconomic Factors