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Abstract #3056

Multi-shell DTI diffusion MRI Based Graph Theory Measures for Prediction of Cognitive Impairment in the Alzheimer’s Disease Connectome Project

Timothy Jaehyun Choi1, Nagesh Adluru1,2, Veena Nair1, Daniel Chu1, Camille Garcia-Ramos3,4, Anusha Adluru1, Shi-Jiang Li5, Andrew L Alexander2,4, Barbara Bendlin6, and Vivek Prabhakaran1
1Department of Radiology, University of Wisconsin-Madison, Madison, WI, United States, 2Waisman Center, University of Wisconsin-Madison, Madison, WI, United States, 3Department of Neurology, University of Wisconsin-Madison, Madison, WI, United States, 4Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, United States, 5Medical College of Wisconsin, Milwaukee, WI, United States, 6Department of Medicine, University of Wisconsin-Madison, Madison, WI, United States

Synopsis

Keywords: Alzheimer's Disease, Brain ConnectivityThe prevalence of Alzheimer’s Dementia (AD) is on the rise, with an estimated economic burden to the US rivaling that of diabetes. Graph theory (GT) offers topological measures that can be used to detect connectivity changes due to aging and AD related processes. We aim to investigate the utility of GT measures based on multi-shell diffusion MRI (ms-dMRI) in discriminating aging individuals with cognitive impairment (CI) from healthy controls, and to find any intrinsic differences within the cognitively impaired subjects by clustering on the GT measures.

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