Ischemic stroke risk assessment based on carotid plaque CT radiomics combined with Essen stroke risk score
10.3969/j.issn.1002-1671.2024.09.003
- VernacularTitle:基于颈动脉斑块CT影像组学联合Essen卒中风险评分量表在缺血性脑卒中的风险评估
- Author:
Tao ZHOU
1
;
Xiu WANG
;
Nannan SUN
;
Zhengyi XIE
;
Xiaobo FAN
;
Yuqing SUN
;
Zhuangfei MA
;
Min ZHANG
;
Ying LI
;
Shouqiang JIA
Author Information
1. 济南市人民医院影像科,山东 济南 271199
- Keywords:
carotid;
computed tomography;
Essen stroke risk score;
radiomics
- From:
Journal of Practical Radiology
2024;40(9):1408-1412
- CountryChina
- Language:Chinese
-
Abstract:
Objective To investigate a novel stroke recurrence risk prediction model,which utilized radiomics machine learning methods and specifically combined carotid computed tomography angiography(CT A)with the Essen stroke risk score(ESRS).Methods A total of 136 patients who underwent carotid CT A were analyzed retrospectively.The features of carotid plaque were extrac-ted by machine learning to construct a radiomics feature model,as well as combined with ESRS.Based on clinical outcomes at one-year follow-up,the stroke recurrence risk prediction model was constructed using the logistic regression(LR)machine learning model.To construct an effective and robust model,the dataset was divided into a training set and a validation set in a ratio of 7∶3.The performance of this model was evaluated using area under the curve(AUC)of receiver operating characteristic(ROC)curve,sensi-tivity and specificity.Results The model had strong predictive value.In the training set,AUC,sensitivity and specificity of this model were 0.903,0.796 and 0.761,respectively.In the validation set,AUC,sensitivity and specificity of this model were 0.869,0.667 and 0.850,respectively.Conclusion The stroke recurrence risk prediction model constructed based on radiomics analysis of carotid plaque characteristics in carotid CTA,in combination with the ESRS,can provide reliable predictions for stroke prognosis.
