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. Bennett^2,3, Julie A. Schneider^2,3,4, and Konstantinos Arfanakis^1,2,5

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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