Department of Radiology, Chaoyang Hospital, Capital Medical University, Beijing, 100020, China.
Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing, 210029, Jiangsu, China.
Eur Radiol. 2023 Dec;33(12):8513-8520. doi: 10.1007/s00330-023-09809-4. Epub 2023 Jul 18.
To determine the value of combining conventional plaque parameters and radiomics features derived from coronary computed tomography angiography (CCTA) for predicting coronary plaque progression.
Clinical data and CCTA images of 400 patients who underwent at least two CCTA examinations between January 2009 and August 2020 were analyzed retrospectively. Diameter stenosis, total plaque volume and burden, calcified plaque volume and burden, noncalcified plaque volume and burden (NCPB), pericoronary fat attenuation index (FAI), and other conventional plaque parameters were recorded. The patients were assigned to a training cohort (n = 280) and a validation cohort (n = 120) in a 7:3 ratio using a stratified random splitting method. The area under the receiver operating characteristics curve (AUC) was used to evaluate the predictive abilities of conventional parameters (model 1), radiomics features (model 2), and their combination (model 3).
FAI and NCPB were identified as independent risk factors for coronary plaque progression in the training cohort. Both model 2 (training cohort AUC: 0.814, p < 0.001; validation cohort AUC: 0.729, p = 0.288) and model 3 (training cohort AUC: 0.824, p < 0.001; validation cohort AUC: 0.758, p = 0.042) had better diagnostic performances in predicting plaque progression than model 1 (training cohort AUC: 0.646; validation cohort AUC: 0.654). Moreover, model 3 was slightly higher than model 2, although not statistically significant.
The combination of conventional coronary plaque parameters and CCTA-derived radiomics features had a better ability to predict plaque progression than conventional parameters alone.
The conventional coronary plaque characteristics such as noncalcified plaque burden, pericoronary fat attenuation index, and radiomics features derived from CCTA can identify plaques prone to progression, which is helpful for further clinical decision-making of coronary artery disease.
• FAI and NCPB were identified as independent risk factors for predicting plaque progression. • Coronary plaque radiomics features were more advantageous than conventional parameters in predicting plaque progression. • The combination of conventional coronary plaque parameters and radiomics features could significantly improve the predictive ability of plaque progression over conventional parameters alone.
确定联合应用冠状动脉 CT 血管造影（CCTA）得出的常规斑块参数和放射组学特征来预测冠状动脉斑块进展的价值。
回顾性分析了 2009 年 1 月至 2020 年 8 月期间至少接受了两次 CCTA 检查的 400 例患者的临床数据和 CCTA 图像。记录了管腔直径狭窄率、总斑块体积和负荷、钙化斑块体积和负荷、非钙化斑块体积和负荷（NCPB）、冠状动脉周围脂肪衰减指数（FAI）和其他常规斑块参数。采用分层随机分割法，将患者按 7:3 的比例分为训练队列（n=280）和验证队列（n=120）。采用受试者工作特征曲线下面积（AUC）评估常规参数（模型 1）、放射组学特征（模型 2）及其联合应用（模型 3）的预测能力。
在训练队列中，FAI 和 NCPB 被确定为冠状动脉斑块进展的独立危险因素。模型 2（训练队列 AUC：0.814，p<0.001；验证队列 AUC：0.729，p=0.288）和模型 3（训练队列 AUC：0.824，p<0.001；验证队列 AUC：0.758，p=0.042）在预测斑块进展方面的诊断性能均优于模型 1（训练队列 AUC：0.646；验证队列 AUC：0.654）。此外，模型 3略优于模型 2，但无统计学意义。
联合应用常规冠状动脉斑块参数和 CCTA 衍生的放射组学特征预测斑块进展的能力优于单纯应用常规参数。
从 CCTA 得出的非钙化斑块负荷、冠状动脉周围脂肪衰减指数和放射组学特征等常规冠状动脉斑块特征可识别易进展斑块，有助于进一步制定冠状动脉疾病的临床决策。
FAI 和 NCPB 被确定为预测斑块进展的独立危险因素。
冠状动脉斑块放射组学特征在预测斑块进展方面优于常规参数。
联合应用常规冠状动脉斑块参数和放射组学特征可显著提高预测斑块进展的能力，优于单纯应用常规参数。
