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Abstract #5057

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

Ling Li1, Min Tang1, Xuejiao Yan1, Yu Wen1, Kai Ai2, Xiaoyan Lei1, and Xiaoling Zhang1
1Shaanxi Provincial People's Hospital, xi an, China, 2Philips Healthcare, Xi an, China

Synopsis

Keywords: Stroke, Vessel Wall, Intracranial atherosclerosis, transient ischemic attack, stroke, prediction model

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.

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