Gutberlet Matthias, Krieghoff Christian, Gohmann Robin
Abteilung für Diagnostische und Interventionelle Radiologie / Professur für Kardiologische Bildgebung, Herzzentrum Leipzig - Universität Leipzig, Strümpellstraße 39, 04289, Leipzig, Deutschland.
Leipzig Heart Institute (LHI), Leipzig, Deutschland.
Herz. 2020 Aug;45(5):431-440. doi: 10.1007/s00059-020-04944-w.
Coronary computed tomography angiography (CCTA) is already of great importance for the primary diagnostic testing for coronary artery disease (CAD) due to its high negative predictive value (NPV) and high sensitivity but, however, limited specificity. The specificity of invasive coronary angiography (ICA) could be increased by integrating the fractional flow reserve (FFR) into the invasive workflow with proof of the hemodynamic relevance of a morphologically detected coronary stenosis. New noninvasive methods of FFR calculations in CT based on computational fluid dynamics (CFD) or machine learning (ML) demonstrate very encouraging results; however, the widespread use of FFR is mainly determined by the image quality and the resulting capabilities of coronary artery segmentation, which could be insufficient in up to 7-12% of CCTAs to calculate FFR, although a morphological assessment is still possible in most cases. Furthermore, FFR cannot be used in total coronary artery occlusion, e.g. to assess the amount of collateral flow. Therefore, FFR calculation alone is not the game changer in diagnosing chronic coronary syndrome (CCS), but the additional use of FFR together with CCTA can be beneficial in ambiguous cases. Additionally, only one commercially available FFR solution exists on the market with an off-site solution, which limits its acute benefits. Several on-site FFR solutions for scientific evaluation exist but can so far only be used for scientific purposes and are not available for clinical use; however, the calculation of FFR from CCTA data is certainly a meaningful supplement to the purely morphological assessment of the coronary arteries. The value of CCTA for the primary diagnosis of CCS in a clinical scenario will be improved when on-site FFR solutions become commercially available.
冠状动脉计算机断层扫描血管造影（CCTA）因其高阴性预测值（NPV）和高敏感性，在冠状动脉疾病（CAD）的初步诊断检测中已具有重要意义，但其特异性有限。通过将血流储备分数（FFR）整合到侵入性流程中，并证明形态学检测到的冠状动脉狭窄具有血流动力学相关性，可以提高侵入性冠状动脉造影（ICA）的特异性。基于计算流体动力学（CFD）或机器学习（ML）的CT中FFR计算的新无创方法显示出非常令人鼓舞的结果；然而，FFR的广泛应用主要取决于图像质量和由此产生的冠状动脉分割能力，在高达7%-12%的CCTA中，这些能力可能不足以计算FFR，尽管在大多数情况下仍可进行形态学评估。此外，FFR不能用于完全冠状动脉闭塞，例如评估侧支循环血流量。因此，仅FFR计算并不是诊断慢性冠状动脉综合征（CCS）的改变游戏规则的方法，但在不明确的病例中，将FFR与CCTA一起使用可能有益。此外，市场上只有一种可商购的带有场外解决方案的FFR产品，这限制了其急性应用的益处。有几种用于科学评估的现场FFR解决方案，但到目前为止只能用于科学目的，不能用于临床；然而，从CCTA数据计算FFR无疑是对冠状动脉单纯形态学评估的有意义补充。当现场FFR解决方案上市时，可以提高CCTA在临床场景中对CCS初步诊断的价值。
