Wood Gregory, Pedersen Alexandra Uglebjerg, Nørgaard Bjarne Linde, Frederiksen Christian Alcaraz, Jensen Jesper Møller, Kunze Karl-Philipp, Neji Radhouene, Wetzl Jens, Prieto Claudia, Botnar René M, Kim Won Yong
Department of Cardiology, Aarhus University Hospital, Palle Juul-Jensens Boulevard 99, Aarhus 8200, Denmark.
Department of Clinical Medicine, Aarhus University, Palle Juul-Jensens Boulevard 99, Aarhus 8200, Denmark.
Eur Heart J Imaging Methods Pract. 2025 Mar 27;3(1):qyaf037. doi: 10.1093/ehjimp/qyaf037. eCollection 2025 Jan.
Clinical implementation of coronary magnetic resonance angiography (CMRA) is limited due to variability in image quality. A protocol utilizing an image navigator (iNAV) integrated with automated scan planning has been developed to facilitate consistent diagnostic image quality. The aim of this study was to evaluate the agreement of automated iNAV CMRA compared with coronary computed tomography angiography (CCTA) using Coronary Artery Disease-Reporting and Data System (CAD-RADS) to classify coronary artery disease (CAD).
Ninety-five individuals underwent automated iNAV CMRA at a resolution of 0.7 mm with a deep learning-assisted automated scan planning and trigger-delay detection protocol. CMRA and CCTA data sets were analysed using CAD-RADS to classify the per-patient severity of CAD. Additionally, the accuracy of both imaging modalities in predicting referral for invasive coronary angiography (ICA) and coronary revascularization was assessed. CMRA classification for CAD-RADS ≥ 1, ≥2, ≥3, and ≥4 agreed with CCTA for 80%, 73%, 63%, and 70% of cases, respectively. The area under the receiver operating characteristic curves with CAD-RADS ≥ 4 and ≥3 for CMRA and CCTA were comparable in predicting ICA referral (0.75 vs. 0.70, = 0.687, and 0.70 vs. 0.70, = 0.945) and revascularization (0.72 vs. 0.74, = 0.811, and 0.68 vs. 0.76, = 0.089).
A novel automated iNAV CMRA protocol was implemented, investigating individuals at risk of CAD. Using the CAD-RADS classification, there was moderate to good agreement between CMRA and CCTA. In patients with CAD-RADS ≥ 4 and ≥3, CMRA was as effective as CCTA in predicting ICA referral and revascularization.
由于图像质量的变异性，冠状动脉磁共振血管造影（CMRA）的临床应用受到限制。已开发出一种利用与自动扫描规划集成的图像导航器（iNAV）的方案，以促进获得一致的诊断图像质量。本研究的目的是使用冠状动脉疾病报告和数据系统（CAD-RADS）对冠状动脉疾病（CAD）进行分类，评估自动iNAV CMRA与冠状动脉计算机断层扫描血管造影（CCTA）的一致性。
95名个体接受了分辨率为0.7 mm的自动iNAV CMRA检查，采用深度学习辅助的自动扫描规划和触发延迟检测方案。使用CAD-RADS分析CMRA和CCTA数据集，以对每位患者的CAD严重程度进行分类。此外，评估了两种成像方式在预测侵入性冠状动脉造影（ICA）转诊和冠状动脉血运重建方面的准确性。CAD-RADS≥1、≥2、≥3和≥4的CMRA分类分别与CCTA在80%、73%、63%和70%的病例中一致。在预测ICA转诊方面，CMRA和CCTA的CAD-RADS≥4和≥3时的受试者操作特征曲线下面积具有可比性（0.75对0.70，P = 0.687，以及0.70对0.70，P = 0.945），在预测血运重建方面也具有可比性（0.72对0.74，P = 0.811，以及0.68对0.76，P = 0.089）。
实施了一种新型的自动iNAV CMRA方案，对有CAD风险的个体进行研究。使用CAD-RADS分类，CMRA和CCTA之间存在中度至良好的一致性。在CAD-RADS≥4和≥3的患者中，CMRA在预测ICA转诊和血运重建方面与CCTA一样有效。
