Multivariate analysis of morphometric and quantitative magnetic resonance imaging metrics in aging and Alzheimer’s disease
Aurelie Bussy1,2, Raihaan Patel1,3, Alyssa Salaciak1, Sarah Farzin1, Stephanie Tullo1,2, Sandra Pelleieux4, Sylvia Villeneuve4,5, Judes Poirier4,5, John CS Breitner4,5, Gabriel A. Devenyi1,5, Christine L. Tardif3,6, and M. Mallar Chakravarty1,2,3,5
1Computational Brain Anatomy (CoBrA) Laboratory, Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, QC, Canada, 2Integrated Program in Neuroscience, McGill University, Montreal, QC, Canada, 3Department of Biomedical Engineering, McGill University, Montreal, QC, Canada, 4Centre for the Studies on the Prevention of AD, Douglas Mental Health University Institute, Montreal, QC, Canada, 5Department of Psychiatry, McGill University, Montreal, QC, Canada, 6McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
Morphometric and quantitative magnetic resonance imaging techniques have rarely been used simultaneously to characterise healthy aging and Alzheimer’s disease (AD) progression. Here, we are extracting four vertex-wise cortical metrics : cortical thickness, surface area, T1 value (myelin) and T2* values (iron). All these metrics were analysed using non-negative matrix factorization and linear models. Overall, cortical thinning seemed to be linked to both aging and AD progression, while decrease in myelin seemed to be a phenomenon mostly related to aging. No significant patterns of changes were seen in the prodromal phase of AD.
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