The value of radiomics-based hyperdense middle cerebral artery sign in predicting hemorrhagic transformation in acute ischemic stroke patients undergoing endovascular treatment

医学 列线图 逻辑回归 接收机工作特性 冲程(发动机) 队列 无线电技术 曲线下面积 放射科 回顾性队列研究 大脑中动脉 内科学 缺血 机械工程 工程类
作者
Chundan Gong,Yun Liu,Wei Ma,Yang Jing,Li Liu,Yan Huang,Jinlin Yang,Chen Feng,Yuan Fang,Weidong Fang
出处
期刊:Frontiers in Neurology [Frontiers Media]
卷期号:15: 1492089-1492089 被引量:2
标识
DOI:10.3389/fneur.2024.1492089
摘要

Objective To establish and validate a model based on hyperdense middle cerebral artery sign (HMCAS) radiomics features for predicting hemorrhagic transformation (HT) in patients with acute ischemic stroke (AIS) after endovascular treatment (EVT). Methods Patients with AIS who presented with HMCAS on non-contrast computed tomography (NCCT) at admission and underwent EVT at three comprehensive hospitals between June 2020 and January 2024 were recruited for this retrospective study. A radiomics model was constructed using the HMCAS radiomics features most strongly associated with HT. In addition, clinical and radiological independent factors associated with HT were identified. Subsequently, a combined model incorporating radiomics features and independent risk factors was developed via multivariate logistic regression and presented as a nomogram. The models were evaluated via receiver operating characteristic curve, calibration curve, and decision curve analysis. Results Of the 118 patients, 71 (60.17%) developed HT. The area under the curve (AUC) of the radiomics model was 0.873 (95% CI 0.797–0.935) in the training cohort and 0.851 (95%CI 0.721–0.942) in the test cohort. The Alberta Stroke Program Early CT score (ASPECTS) was the only independent predictor among 24 clinical and 4 radiological variables. The combined model further improved the predictive performance, with an AUC of 0.911 (95%CI 0.850–0.960) in the training cohort and 0.877 (95%CI 0.753–0.960) in the test cohort. Decision curve analysis demonstrated that the combined model had greater clinical utility for predicting HT. Conclusion HMCAS-based radiomics is expected to be a reliable tool for predicting HT risk stratification in AIS patients after EVT.
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