Department of Cardiology, The Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China.
Department of Thoracic Surgery, Nanchong Central Hospital, Nanchong, China.
Sci Rep. 2024 Aug 23;14(1):19643. doi: 10.1038/s41598-024-70218-8.
To assess whether the radiomics signature of pericoronary adipose tissue (PCAT) from coronary computed tomography angiography (CCTA) can distinguish between perimenopausal women with coronary heart disease (CHD) and those without coronary artery disease (CAD). This single-center retrospective case-control study comprised 140 perimenopausal women with CHD presenting with chest pain who underwent CCTA within 48 h of admission. They were matched with 140 control patients presenting with chest pain but without CAD, based on age, risk factors, radiation dose and CT tube voltage. For all participants, PCAT around the proximal right coronary artery was segmented, from which radiomics features and the fat attenuation index (FAI) were extracted and analyzed. Subsequently, corresponding models were developed and internally validated using Bootstrap methods. Model performance was assessed through measures of identification, calibration, and clinical utility. Using logistic regression analysis, an integrated model that combines clinical features, fat attenuation index and radiomics parameters demonstrated enhanced discrimination ability for perimenopausal CHD (area under the curve [AUC]: 0.80, 95% confidence interval [CI]:0.740-0.845). This model outperformed both the combination of clinical features and PCAT attenuation (AUC 0.67, 95% CI 0.602-0.727) and the use of clinical features alone (AUC 0.66, 95% CI 0.603-0.732). Calibration curves for the three predictive models indicated satisfactory fit (all p > 0.05). Moreover, decision curve analysis demonstrated that the integrated model offered greater clinical benefit compared to the other two models. The CCTA-based radiomics signature derived from the PCAT model outperforms the FAI model in differentiating perimenopausal CHD patients from non-CAD individuals. Integrating PCAT radiomics with the FAI could enhance the diagnostic accuracy for perimenopausal CHD.
评估冠状动脉计算机断层血管造影（CCTA）中冠状动脉周围脂肪组织（PCAT）的放射组学特征是否可以区分围绝经期冠心病（CHD）和无冠状动脉疾病（CAD）的患者。这项单中心回顾性病例对照研究纳入了 140 名因胸痛而在入院后 48 小时内接受 CCTA 的围绝经期 CHD 患者。根据年龄、危险因素、辐射剂量和 CT 管电压，与 140 名有胸痛但无 CAD 的对照患者进行匹配。对所有参与者，对近端右冠状动脉周围的 PCAT 进行分割，从其中提取并分析放射组学特征和脂肪衰减指数（FAI）。随后，使用 Bootstrap 方法开发并内部验证相应的模型。通过识别、校准和临床实用性的措施评估模型性能。使用逻辑回归分析，结合临床特征、脂肪衰减指数和放射组学参数的综合模型对围绝经期 CHD 具有增强的鉴别能力（曲线下面积 [AUC]：0.80，95%置信区间 [CI]：0.740-0.845）。该模型优于临床特征和 PCAT 衰减的组合（AUC 0.67，95%CI 0.602-0.727）和单独使用临床特征（AUC 0.66，95%CI 0.603-0.732）。三种预测模型的校准曲线表明拟合良好（均 p>0.05）。此外，决策曲线分析表明，与其他两种模型相比，综合模型提供了更大的临床获益。基于 CCTA 的 PCAT 模型的放射组学特征在区分围绝经期 CHD 患者和非 CAD 个体方面优于 FAI 模型。整合 PCAT 放射组学和 FAI 可以提高围绝经期 CHD 的诊断准确性。
