Department of Radiology, German Air Force Center of Aerospace Medicine, Cologne, Germany.
Institute for Diagnostic and Interventional Radiology, Hospital Porz am Rhein, Cologne, Germany.
Rofo. 2024 Dec;196(12):1253-1261. doi: 10.1055/a-2271-0887. Epub 2024 Apr 17.
The aim of our work was to demonstrate the importance of artificial intelligence-based analysis of fractional flow reserves of computed tomographically detected coronary artery stenosis with regard to their hemodynamic relevance in patients with unclear chest pain and suspected stable coronary heart disease with a low to medium pre-test probability.
The collective of our retrospective analysis includes 63 patients in whom coronary artery stenosis was detected by volume computed tomographic examination in "one beat, whole heart" mode in the period from March to October 2022. In these patients, the fractional flow reserve was also determined by computed tomography, which was modulated by the use of artificial intelligence.
The calculated values of the fractional flow reserve and the degrees of stenosis determined by computed tomography showed a moderate and significant negative correlation for all three coronary vascular territories (LAD/CX/RCA) (correlation coefficient rho = 0.54/0.54/0.6; p < 0.01 respectively). In just over a third (37.6 %) of all stenoses classified as high-grade by computed tomography, the assessment of hemodynamic relevance by calculating the fractional flow reserve deviated from the severity of the stenosis diagnosed by computed tomography, while the results in the peripheral areas "no stenosis/vascular occlusion" were 100 % consistent in each case.
The present results of this work illustrate that the calculation of the fractional flow reserve based on artificial intelligence as a supplement to volume computed tomography of the heart can make a decisive contribution to further therapy planning by increasing the specificity of the purely morphological method by the physiological aspect.
· Calculation of fractional flow reserve is a useful addition to computed tomography of the heart.. · It provides possibility to dispense with unnecessary further diagnostics by increasing specificity.. · The combination of both procedures leads to therapy optimization for patients..
· Noblé H, Mühlbauer N, Ehling J et al. The value of AI-based analysis of fractional flow reserve of volume computed tomographically detected coronary artery stenosis with regard to their hemodynamic relevance. Fortschr Röntgenstr 2024; 196: 1253 - 1261.
我们工作的目的是展示基于人工智能的计算机断层扫描检测冠状动脉狭窄的分流量储备分析的重要性，因为其在胸痛不明确且疑似稳定型冠心病且低至中度预测试概率的患者中具有血流动力学相关性。
我们的回顾性分析共纳入 2022 年 3 月至 10 月期间在“一次心跳，全心”模式下通过容积计算机断层检查检测到冠状动脉狭窄的 63 例患者。在这些患者中，还通过计算机断层扫描确定了分流量储备，该储备通过人工智能进行了调制。
所有三个冠状动脉血管区域（LAD/CX/RCA）的计算分流量储备值和计算机断层扫描确定的狭窄程度均呈中度显著负相关（相关系数 rho = 0.54/0.54/0.6；分别 p < 0.01）。在所有计算机断层扫描分类为高度狭窄的狭窄中，超过三分之一（37.6%）的狭窄，通过计算分流量储备来评估血流动力学相关性与计算机断层扫描诊断的狭窄严重程度存在差异，而在周边区域“无狭窄/血管闭塞”的情况下，每个病例的结果均完全一致。
本工作的结果表明，基于人工智能的分流量储备计算作为心脏容积计算机断层扫描的补充，可以通过增加形态学方法的生理学方面的特异性，对进一步的治疗计划做出决定性贡献。
· 分流量储备的计算是心脏计算机断层扫描的有用补充。
· 通过增加特异性，可以避免不必要的进一步诊断。
· 两种程序的结合可优化患者的治疗。
· Noblé H, Mühlbauer N, Ehling J 等。基于人工智能的计算机断层扫描检测冠状动脉狭窄的分流量储备分析的价值及其血流动力学相关性。放射进展 2024；196：1253-1261.
