医学
无线电技术
接收机工作特性
放射科
脂肪组织
对比度(视觉)
核医学
内科学
人工智能
计算机科学
作者
Xingyuan Jiang,Zhiqing Shao,Yating Chai,Yingnan Liu,Ye Li
标识
DOI:10.1088/1361-6560/ac69a7
摘要
Objective.To develop two combined clinical-radiomics models of pericoronary adipose tissue (PCAT) for the presence and characterization of non-calcified plaques on non-contrast CT scan.Approach.Altogether, 431 patients undergoing Coronary Computed Tomography Angiography from March 2019 to June 2021 who had complete data were enrolled, including 173 patients with non-calcified plaques of the right coronary artery(RCA) and 258 with no abnormality. PCAT was segmented around the proximal RCA on non-contrast CT scan (calcium score acquisition). Two best models were established by screening features and classifiers respectively using FeAture Explorer software. Model 1 distinguished normal coronary arteries from those with non-calcified plaques, and model 2 distinguished vulnerable plaques in non-calcified plaques. Performance was assessed by the area under the receiver operating characteristic curve (AUC-ROC).Main results.4 and 9 features were selected for the establishment of the radiomics model respectively through Model 1 and 2. In the test group, the AUC values, sensitivity, specificity and accuracy were 0.833%, 78.3%, 80.8%, 76.6% and 0.7467%, 75.0%, 77.8%, 73.5%, respectively. The combined model including radiomics features and independent clinical factors yielded an AUC, sensitivity, specificity and accuracy of 0.896%, 81.4%, 86.5%, 77.9% for model 1 and 0.752%, 75.0%, 77.8%, 73.5% for model 2.Significance.The combined clinical-radiomics models based on non-contrast CT images of PCAT had good diagnostic efficacy for non-calcified and vulnerable plaques.
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