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目的:探讨基于CT平扫冠状动脉周围（简称冠周）脂肪的影像组学模型对非钙化斑块的诊断价值。方法:回顾性分析461例2019年8月1日至2020年7月31日苏州大学附属第一医院放射科行冠状动脉CT血管造影（CCTA）患者的影像学资料。CCTA检出206例（355支）冠状动脉有非钙化斑块，255例（510支）冠状动脉未见异常。于CT平扫［钙化积分（CCS）序列］图像对冠周脂肪进行感兴趣区（ROI）勾画。选取距冠状动脉开口处10 mm起始的长为40 mm的冠状动脉进行冠状动脉ROI勾画并自动生成冠周脂肪ROI，随后进行冠周脂肪衰减指数（FAI）以及影像组学参数的提取。将865支冠状动脉按7∶3的比例分为训练组（n n=606）和测试组（n n=259）并进行组学建模，运用受试者工作特征（ROC）曲线分析评估FAI值以及组学模型对于非钙化斑块的诊断效能。n 结果:从基于平扫的冠周脂肪的图像中共提取1 692个特征，使用最大相关最小冗余（mRMR）和最小绝对收缩与选择算子（LASSO）进行特征筛选后，筛选出14个特征用于影像组学模型的建立。模型在测试组中鉴别非钙化斑块患者和冠状动脉未见异常者的准确度、灵敏度、特异度和曲线下面积（AUC）分别为70.3%、63.2%、75.2%和0.75。结论:基于平扫冠周脂肪影像组学模型对非钙化斑块具有较好的诊断效能。“,”Objective:To investigate the diagnostic value of radiomics model based on plain CT scan of peripheral coronary artery adipose tissue for non-calcified plaque.Methods:The image data of 461 patients undergoing coronary CT angiography (CCTA) in the Department of Radiology of the First Affiliated Hospital of Suzhou University from August 1,2019 to July 31,2020 were retrospectively analyzed. Two hundred and six cases (355 branches) with non-calcified plaques, and 255 cases (510 branches) with no coronary artery disease were detected by CCTA. The regions of interest (ROI) of the pericoronary adipose tissue were segmented on the plain CT scan images (coronary calcification score (CCS) sequence). The coronary ROI was determined by selecting the coronary artery with a length of 40 mm and starting at 10 mm from the opening of the coronary artery, and the pericoronary adipose ROI was generated automatically. The pericoronary fat attenuation index (FAI) was then performed, and the radiomics features were extracted. The 865 coronary arteries were divided into the training group (n n=606) and the testing group (n n=259) at a ratio of 7∶3, and the radiomics model was carried out. The receiver operating characteristic (ROC) analysis was used to assess the FAI value and the diagnostic efficacy of the radiomics model for non-calcified plaque.n Results:A total of 1 692 features were extracted from images of pericoronary adipose based on plain scan. All features were screened by using max-relevance and min-redundancy (mRMR) and least absolute shrinkage and selection operator (LASSO), and 14 features were selected for the establishment of the radiomics model. The accuracy, sensitivity, specificity and area under the curve (AUC) of the model in distinguishing patients with non-calcified plaque and those without coronary stenosis in the testing group were 70.3%, 63.2%, 75.2% and 0.75, respectively.Conclusion:The radiomics model based on plain CT scan of the pericoronary adipose tissue had good diagnostic efficacy for non-calcified plaque.