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Abstract #1940

MRI Shape Analysis Predicts Progression from Mild Cognitive Impairment to Alzheimer's Disease

Donald Louis Collins1, Vladimir Fonov1, Simon Duchesne2,3

1McConnell Brain Imaging Center, Montreal Neurological Institute, Montreal, QC, Canada; 2Centre de Recherche Universit Laval - Robert Giffard, Quebec, Canada; 3Dpt. de Radiologie, Facult de Mdecine, Universit Laval, Quebec, Canada

A method is presented to predict conversion from mild cognitive impairment to Alzheimers disease using shape analysis of baseline T1w MRI data. Using 100 MCI subjects from the ADNI database, PCA analysis of deformation fields required to register to a minimum deformation template is used to build a shape model of the aging brain. LDA of the eigenvalues is used to build a classifier to identify converters and non-converters. Testing with 100 additional MCI subjects demonstrates accuracies of 65% at 12 months and 64% at 24 months. Adding baseline HC volume increases accuracy to 73% and 69%, respectively.