MRI-based habitat radiomics combined with vision transformer for identifying vulnerable intracranial atherosclerotic plaques and predicting stroke events: a multicenter, retrospective study.

ABSTRACT:

Background

Accurate identification of high-risk vulnerable plaques and assessment of stroke risk are crucial for clinical decision-making, yet reliable non-invasive predictive tools are currently lacking. This study aimed to develop an artificial intelligence model based on high-resolution vessel wall imaging (HR-VWI) to assist in the identification of vulnerable plaques and prediction of stroke recurrence risk in patients with symptomatic intracranial atherosclerotic stenosis (sICAS).

Methods

Between June 2018 and June 2024, a retrospective collection of HR-VWI images from 1806 plaques in 726 sICAS patients across four medical institutions was conducted. K-means clustering was applied to the T1-weighted imaging (T1WI) and T1-weighted imaging with contrast enhancement (T1CE)

SUBMITTER: Gao Y 

PROVIDER: S-EPMC11999680 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature