Year-by-year White Matter Hyperintensity Probabilistic Atlases based on China Aging Cohort and its Application to Cognitive Decline Evaluation

Motivation: As frequently observed in older populations, white matter hyperintensity (WMH) appears a risk factor for cognitive decline. Goal(s): To construct normative WMH probabilistic atlases for quantifying its spatiotemporal progression and for disease detection. Approach: We released the first set of such atlases and related trajectories, based on a large cohort of the Chinese typical aging population, with AI techniques. Results: We validated its clinical usefulness by comparing cognitive impairment groups with the atlases, as a new tool for early Alzheimer’s disease evaluation. We also found that the WMH in deep, rather than periventricular, white matter moderated aging-induced general cognitive ability reduction. Impact: Given normative curves summarizing WHM progression in Chinese typical aging population, clinicians can better assess abnormalities related to cerebral small-vessel diseases, detect high-risk individuals who will develop cognitive decline in the future, and conduct large-scale community screening for older population.