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 Adluru^1,2, Veena Nair¹, Daniel Chu¹, Camille Garcia-Ramos^3,4, Anusha Adluru¹, Shi-Jiang Li⁵, Andrew L Alexander^2,4, 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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