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Abstract #3188

A novel MRI classifier of arteriolar sclerosis in aging: Prediction of pathology and cognitive decline

Nazanin Makkinejad1, Arnold M. Evia2, Ashish Tamhane2, David A. Bennett2,3, Julie A. Schneider2,3,4, and Konstantinos Arfanakis1,2,5

1Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL, United States, 2Rush Alzheimer's Disease Center, Rush University, Chicago, IL, United States, 3Department of Neurological Sciences, Rush University, Chicago, IL, United States, 4Department of Pathology, Rush University, Chicago, IL, United States, 5Department of Diagnostic Radiology, Rush University, Chicago, IL, United States

Arteriolar sclerosis is one of the main pathologies of small vessel disease, is common in the aging brain, and has been associated with lower cognitive performance and higher risk of dementia. Definitive diagnosis of arteriolar sclerosis is only possible at autopsy. In this work, an MRI-based classifier of arteriolar sclerosis was developed, by first training a classifier on ex-vivo MRI and pathology data and then translating it in-vivo, and was evaluated in a large community cohort of older adults.

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