The human brain holds many clues about a person’s long-term health — in fact, research shows that a person’s brain age is a more useful and accurate predictor of health risks and future disease than their birth date. Now, a new artificial intelligence (AI) model that analyzes magnetic resonance imaging (MRI) brain scans developed by USC researchers could be used to accurately capture cognitive decline linked to neurodegenerative diseases like Alzheimer’s much earlier than previous methods.
Brain aging is considered a reliable biomarker for neurodegenerative disease risk. Such risk increases when a person’s brain exhibits features that appear “older” than expected for someone of that person’s age. By tapping into the deep learning capability of the team’s novel AI model to analyze the scans, the researchers can detect subtle brain anatomy markers that are otherwise very difficult to detect and that correlate with cognitive decline. Their findings, published on Tuesday, January 2, in the journal Proceedings of the National Academy of Sciences, offer an unprecedented glimpse into human cognition.
“Our study harnesses the power of deep learning to identify areas of the brain that are aging in ways that reflect a cognitive decline that may lead to Alzheimer’s,” said Andrei Irimia, assistant professor of gerontology, biomedical engineering, quantitative & computational biology and neuroscience at the USC Leonard Davis School of Gerontology and corresponding author of the study.
Wellness Secrets of a SuperAger 
How interesting! There is actually a similar AI-analysis test on the market already–the NeuroQuant MRI. While the neurologist read the MRI as normal, the AI’s volumetric assessment suggested I have Alzheimer’s. Based on the areas of atrophy and edema, they can determine which type of Alzheimer’s disease one has.
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Very interesting. Thanks for sharing.
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