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

作者：Yu Gao, Ziang Li, Xiaoyang Zhai, Gang Zhang, Lan Zhang, Tingting Huang, Lin Han, Jie Wang, Ruifang Yan, Yongdong Li, Hongling Zhao, Qiuyi Zhao, Zhengqi Wei, Beichen Xie, Yancong Sun, Jianhua Zhao, Hongkai Cui · 发表于：EClinicalMedicine · 年份：2025 · DOI：10.1016/j.eclinm.2025.103186 · 被引用次数：19 · 研究领域：Cerebrovascular and Carotid Artery Diseases、Radiomics and Machine Learning in Medical Imaging、Acute Ischemic Stroke Management

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) sequences. Following feature extraction and selection, radiomic models and habitat models were constructed. Additionally, the Vision Transformer (ViT) architecture was utilized for HR-VWI image analysis to build a deep learning model. A stacking fusion strategy was employed to integrate the habitat model and ViT model, enabling effective identification of high-risk vulnerable plaques in the intracranial region and prediction of stroke recurrence risk. Model performance was evaluated using receiver operating characteristic (ROC) curves, and model comparisons were conducted using the DeLong test. Furthermore, decision curve analysis and calibration curves were utilized to assess the practicality and clini...