Abstract #4496

Identifying Early Diffusion MRI Biomarkers in 2-month-old 3xTg-AD mice via the Elastic Net

Maria de Fatima Falangola^1,2, Bryan Granger³, Joshua Voltin^1,2, Paul J. Nietert⁴, Stefano Berto^1,3, and Jens H. Jensen^1,2,5

¹Department of Neuroscience, Medical University of South Carolina, Charleston, SC, United States, ²Center for Biomedical Imaging, Medical University of South Carolina, Charleston, SC, United States, ³Bioinformatics Core, Medical University of South Carolina, Charleston, SC, United States, ⁴Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, United States, ⁵Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, United States

Synopsis

Keywords: DWI/DTI/DKI, DWI/DTI/DKI

Motivation: To establish diffusion MRI (dMRI) biomarkers for early detection of Alzheimer's disease (AD).

Goal(s): To investigate the effectiveness of dMRI metrics in classifying 3xTg-AD mice using elastic net (EN).

Approach: Multiple dMRI metrics were measured in several brain regions of 2-month-old 3xTg-AD and control mice, and an EN logistic regression model was applied to determine the best predictor for classifying mouse group genotype.

Results: The EN model yielded an accuracy of 0.95, sensitivity of 0.96, and specificity of 0.94. The fractional anisotropies of the ventral hippocampus, corpus callosum, and cingulate cortex were identified as the three best dMRI metrics for classifying 3xTg-AD mice.

Impact: Diffusion MRI can accurately distinguish 3xTg-AD mice from control mice at 2 months, which is prior to the development of amyloid plaques and tau pathology. This demonstrates dMRI’s high sensitivity to microstructural changes occurring early in the disease process.

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