Abstract #2695

Multivariate analysis of morphometric and quantitative magnetic resonance imaging metrics in aging and Alzheimer’s disease

Aurelie Bussy^1,2, Raihaan Patel^1,3, Alyssa Salaciak¹, Sarah Farzin¹, Stephanie Tullo^1,2, Sandra Pelleieux⁴, Sylvia Villeneuve^4,5, Judes Poirier^4,5, John CS Breitner^4,5, Gabriel A. Devenyi^1,5, Christine L. Tardif^3,6, and M. Mallar Chakravarty^1,2,3,5

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

Synopsis

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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