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Abstract #3764

T2-Weighted MRI Increases Machine Learning Accuracy in Alzheimer's Disease

L. Z. Diaz-de-Grenu1, G. B. Williams1, J. Acosta-Cabronero1, J. M. Pereira1, P. J. Nestor1

1Clinical Neurosciences, University of Cambridge, Cambridge, Cambridgeshire, United Kingdom

Support vector machines (SVM) using T1-weighted images offer moderate accuracy in diagnosing Alzheimers disease (AD). Recent work suggests, however, that T2-weighted scans may contain more pathologically relevant information. This study, therefore, tested if T2 data could improve SVM classification. T1 and T2 were compared in whole-brain images and regions of interest (ROI) known to be affected in AD. An ROI focused on the mesial temporal lobe (known to be atrophic) yielded similar accuracy for T1 and T2 (both 88.5%), however adding ROIs known to be rich in beta-amyloid improved diagnostic accuracy (92.3%) but only when using T2 data.