Brain age in healthy individuals and across multiple neurological disorders

Motivation: Understanding brain age of healthy people and patients with neurological diseases is crucial for clinical application. Goal(s): To characterize people with advanced brain age and explore brain aging patterns across neurological disorders. Approach: Through a predicted brain age model using deep learning, we investigated the correlations between advanced brain aging and age-related deterioration in healthy individuals, and explored the correlation with clinical variables across neurological disorders. Results: Healthy individuals with advanced brain aging have higher white matter hyperintensity burdens and lower brain region volumes. Brain age increases in patients with neurological disorders and has more cognitive decline and physical disability. Impact: The brain age model using deep learning enables identifying individuals at risk for advanced brain aging in the normal-aging population and shows advanced brain aging across neurological diseases, which can be a biomarker for cognitive impairment and/or physical disability.