A Predictive Model for the Risk of Stroke in ICAS patients based on ASL and High-resolution MRI

Motivation: Ischemic stroke patients with Intracranial atherosclerotic stenosis (ICAS) have more severe symptoms than TIA patients, and the risk of stroke recurrence is higher. Goal(s): To accurately predict the risk of ischemic stroke in patients with symptomatic intracranial atherosclerosis (sICAS). Approach: The prediction model of ischemic stroke in patients with sICAS was established based on high-resolution magnetic resonance imaging (HR-MRI) and arterial spin labeling (ASL). Results: The nomogram constructed based on plaque characteristics of HR-MRI and presence of 2.5s-ATA in ASL imaging can accurately predict ischemic stroke in sICAS patients, providing great help to the risk stratification of stroke decision-making. Impact: The nomogram integrating plaque characteristics of HR-MRI with presence of 2.5s-ATA in ASL imaging can accurately predicts ischemic stroke in sICAS, supporting risk stratification for stroke decision-making. It also offers a foundation for early risk assessment and intervention in TIA.