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Abstract #1386

Investigating the Diagnostic Utility of Multi-Shell Diffusion MRI and CSF Biomarkers for Mild Cognitive Impairment Classification

Alex Guo1, John Laporte1, Kavita Singh2, Zhaoyuan Gong1, Jonghyun Bae1, Keagan Bergeron1, Angelique De Rouen1, Nathan Zhang1, Noam Fox1, Dan Benjamini2, and Mustapha Bouhrara1
1Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, MD, United States, 2Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, United States

Synopsis

Keywords: Diagnosis/Prediction, Alzheimer's Disease, Biomarkers, Mild Cognitive Impairment

Motivation: While recent advances in quantitative MRI have resulted in a myriad of methods capable of examining cerebral tissue microstructure, the pre-dementia classification performances of these models have not been extensively studied.

Goal(s): To evaluate diffusion MRI biomarkers as a noninvasive diagnostic tool for early detection of Alzheimer’s disease.

Approach: We utilize multi-shell diffusion MRI from ADNI to investigate the comparative effectiveness of diffusion MRI models (MAP, SMI, NODDI, and C-NODDI) versus established CSF biomarkers in classifying mild cognitive impairment.

Results: Multi-shell diffusion biomarkers match CSF biomarker performance in MCI classification. Greater performance can be achieved when using both MRI and CSF biomarkers simultaneously.

Impact: This research highlights diffusion MRI's potential for classifying prodromal Alzheimer's disease, paving the way for non-invasive pre-dementia diagnostics. It additionally provides MRI researchers insights into the comparative classification performance of various diffusion MRI models.

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Keywords