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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