Deep-learning-enabled brain hemodynamic mapping using resting-state fMRI.

ABSTRACT: Cerebrovascular disease is a leading cause of death globally. Prevention and early intervention are known to be the most effective forms of its management. Non-invasive imaging methods hold great promises for early stratification, but at present lack the sensitivity for personalized prognosis. Resting-state functional magnetic resonance imaging (rs-fMRI), a powerful tool previously used for mapping neural activity, is available in most hospitals. Here we show that rs-fMRI can be used to map cerebral hemodynamic function and delineate impairment. By exploiting time variations in breathing pattern during rs-fMRI, deep learning enables reproducible mapping of cerebrovascular reactivity (CVR) and bolus arrival time (BAT) of the human brain using resting-state CO₂ fluctuations as a n

SUBMITTER: Hou X 

PROVIDER: S-EPMC10284915 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature