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Abstract #3667

Multivariate MR Biomarkers Predict Cognitive Decline in Mouse Models of Alzheimer’s Disease

Alexandra Badea1, Robert J Anderson1, Russell Dibb1, Yi Qi1, Natalie A Delpratt1, Hongjiang Wei2, Chunlei Liu2, William C Wetsel3, Brian B Avants4, and Carol A Colton5

1Radiology, Duke University Medical Center, Durham, NC, United States, 2University of California, Berkeley, CA, NC, United States, 3Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC, United States, 4BIOGEN, Cambridge, MA, United States, 5Neurology, Duke University Medical Center, Durham, NC, United States

We propose a multivariate approach for characterizing mouse models of Alzheimer’s disease (AD), which integrates imaging and behavior in a joint analysis. We used manganese enhanced MRI (MEMRI) to identify brain areas associated with reduced performance in a spatial memory task. We quantified genotype differences based on morphometry, T1 weighted (T1W) signal and quantitative susceptibility maps (QSM). We find that the integration of multiple imaging biomarkers is a better predictor of cognitive decline, relative to using single biomarkers in isolation.

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