Ebaid Noha Yahia, Khalifa Dalia Nabil, Ragheb Ahmad Sabry, Abdelsamie Magdy Mohamad, Alsowey Ahmed Mohamed
Department of Radiology, Faculty of Medicine, Zagazig University, Zagazig, Egypt.
Department of Cardiology, Faculty of Medicine, Zagazig University, Zagazig, Egypt.
Int J Gen Med. 2021 Nov 2;14:7503-7514. doi: 10.2147/IJGM.S336662. eCollection 2021.
The coronary artery disease reporting and data system (CAD-RADS) is intended to standardize the reporting of CCTA and the subsequent management guidelines of CAD. The present study was conducted to investigate the validation of CAD-RADS and the application of coronary calcium grading in CAD management.
The current study is a single-center prospective study that involved 177 participants with chest pain who were submitted to coronary CT angiography (CCTA). Two reviewers independently assessed CCTA results and gave each patient a CAD-RADS category. The reference standard for determining the clinical utility of CAD-RADS was invasive coronary angiography (ICA). The inter-reviewer agreement (IRA) was tested using the intra-class correlation (ICC).
The study enrolled 111 cases with non-significant CAD and 66 cases with significant CAD based on ICA findings. According to the reviewer, the CAD-RADS had a sensitivity, specificity, and accuracy of 90.9 to 100%, 89.2 to 94.6%, and 93.16 to 93.2%, respectively, for predicting severe CAD. The IRA for CAD-RADS categories was excellent (ICC = 0.960). The best cut-off value for predicting severe CAD was CAD-RADS > 3. Significant relation between Ca and severe CAD (p<0.001) was detected.
The current study provides a good understanding of CAD-RADS as a standard tool with high diagnostic accuracy.
冠状动脉疾病报告与数据系统(CAD-RADS)旨在规范CCTA报告及后续CAD管理指南。本研究旨在探讨CAD-RADS的有效性以及冠状动脉钙化分级在CAD管理中的应用。
本研究为单中心前瞻性研究,纳入177例因胸痛接受冠状动脉CT血管造影(CCTA)的患者。两名阅片者独立评估CCTA结果,并为每位患者指定一个CAD-RADS类别。确定CAD-RADS临床效用的参考标准为有创冠状动脉造影(ICA)。采用组内相关系数(ICC)检验阅片者间一致性(IRA)。
根据ICA结果,本研究纳入111例非显著性CAD患者和66例显著性CAD患者。根据阅片者的判断标准,CAD-RADS预测严重CAD的敏感性、特异性和准确性分别为90.9%至100%、89.2%至94.6%和93.16%至93.2%。CAD-RADS类别的IRA极佳(ICC = 0.960)。预测严重CAD的最佳截断值为CAD-RADS > 3。检测到Ca与严重CAD之间存在显著相关性(p<0.001)。
本研究有助于深入理解CAD-RADS作为一种具有高诊断准确性的标准工具的作用。