【摘要】 目的 分析多模态CT影像组学模型构建对主动脉斑块患者发生不稳定心绞痛的预测价值。方法 选取2023年1月—2023年12月齐齐哈尔医学院附属第二医院收治的236例接受多模态CT检查的主动脉斑块患者进行研究，根据随访1年是否发生不稳定心绞痛分为未发生组（200例）和发生组（36例）。将两组有差异的资料代入Logistic回归方程，确定不稳定心绞痛的影响因素，构建预测模型，并绘制受试者工作特征曲线（ROC）评估模型效能。结果 主动脉斑块位置、主动脉瓣狭窄程度、主动脉斑块CT值、主动脉根部钙化积分、主动脉钙化体积均为主动脉斑块患者发生不稳定心绞痛的影响因素，OR值均>1。通过构建列线图，绘制ROC曲线验证模型预测效能发现AUC为0.990(95%CI:0.970～1.000)。结论 构建多模态CT影像组学预测模型对主动脉斑块患者发生不稳定心绞痛的预测价值较高，能为临床筛查高危群体并采取措施提供依据。更多还原

【Abstract】 Objective To analyze the predictive value of a multimodal CT radiomics model in predicting unstable angina in patients with aortic plaques. Methods A total of 236 patients with aortic plaque who underwent multimodal CT examination in our hospital from January 2023 to December 2023 were selected for this study. Combined with 1-year follow-up, they were divided into non-occurrence group(200) and occurrence group(36), and the diff erence data between the two groups were replaced by Logistic regression equation. The influencing factors of unstable angina pectoris were determined, the predictive model was constructed, and the receiver operating characteristic curve(ROC) was drawn to evaluate the model efficacy. Results The location of aortic plaque, degree of aortic stenosis, CT value of aortic plaque, calcification score of aortic root, and volume of aortic calcification were all influential factors for the occurrence of unstable angina pectoris in patients with major arterial plaque, and the OR values were all greater than 1. By constructing a nomogram, ROC curve was drawn to verify the prediction e fficiency of the model and the AUC was found to be 0.990(95%CI: 0.970-1.000). Conclusion The multi-modality CT image omics prediction model has a high value in predicting unstable angina pectoris in patients with aortic plaque, and can provide evidence for clinical screening of high-risk groups and taking measures.更多还原