Papafaklis Michail I, Muramatsu Takashi, Ishibashi Yuki, Lakkas Lampros S, Nakatani Shimpei, Bourantas Christos V, Ligthart Jurgen, Onuma Yoshinobu, Echavarria-Pinto Mauro, Tsirka Georgia, Kotsia Anna, Nikas Dimitrios N, Mogabgab Owen, van Geuns Robert-Jan, Naka Katerina K, Fotiadis Dimitrios I, Brilakis Emmanouil S, Garcia-Garcia Héctor M, Escaned Javier, Zijlstra Felix, Michalis Lampros K, Serruys Patrick W
Department of Cardiology, Medical School, University of Ioannina, Ioannina, Greece.
EuroIntervention. 2014 Sep;10(5):574-83. doi: 10.4244/EIJY14M07_01.
To develop a simplified approach of virtual functional assessment of coronary stenosis from routine angiographic data and test it against fractional flow reserve using a pressure wire (wire-FFR).
Three-dimensional quantitative coronary angiography (3D-QCA) was performed in 139 vessels (120 patients) with intermediate lesions assessed by wire-FFR (reference standard: ≤0.80). The 3D-QCA models were processed with computational fluid dynamics (CFD) to calculate the lesion-specific pressure gradient (ΔP) and construct the ΔP-flow curve, from which the virtual functional assessment index (vFAI) was derived. The discriminatory power of vFAI for ischaemia- producing lesions was high (area under the receiver operator characteristic curve [AUC]: 92% [95% CI: 86-96%]). Diagnostic accuracy, sensitivity and specificity for the optimal vFAI cut-point (≤0.82) were 88%, 90% and 86%, respectively. Virtual-FAI demonstrated superior discrimination against 3D-QCA-derived % area stenosis (AUC: 78% [95% CI: 70- 84%]; p<0.0001 compared to vFAI). There was a close correlation (r=0.78, p<0.0001) and agreement of vFAI compared to wire-FFR (mean difference: -0.0039±0.085, p=0.59).
We developed a fast and simple CFD-powered virtual haemodynamic assessment model using only routine angiography and without requiring any invasive physiology measurements/hyperaemia induction. Virtual-FAI showed a high diagnostic performance and incremental value to QCA for predicting wire-FFR; this "less invasive" approach could have important implications for patient management and cost.
从常规血管造影数据开发一种简化的冠状动脉狭窄虚拟功能评估方法，并使用压力导丝（导丝血流储备分数，wire-FFR）与血流储备分数进行对比测试。
对139支血管（120例患者）进行三维定量冠状动脉造影（3D-QCA），这些血管存在通过导丝血流储备分数评估的中度病变（参考标准：≤0.80）。对3D-QCA模型进行计算流体动力学（CFD）处理，以计算病变特异性压力梯度（ΔP）并构建ΔP-流量曲线，从中得出虚拟功能评估指数（vFAI）。vFAI对缺血性病变的鉴别能力很高（受试者操作特征曲线下面积[AUC]：92%[95%CI：86-96%]）。对于最佳vFAI切点（≤0.82），诊断准确性、敏感性和特异性分别为88%、90%和86%。虚拟功能评估指数对3D-QCA得出的狭窄面积百分比显示出更好的鉴别能力（AUC：78%[95%CI：70-84%]；与vFAI相比，p<0.0001）。vFAI与导丝血流储备分数密切相关（r=0.78，p<0.0001）且一致性良好（平均差异：-0.0039±0.085，p=0.59）。
我们开发了一种快速且简单的由CFD驱动的虚拟血流动力学评估模型，仅使用常规血管造影，无需任何有创生理学测量/充血诱导。虚拟功能评估指数在预测导丝血流储备分数方面显示出较高的诊断性能和相对于QCA的增量价值；这种“侵入性较小”的方法可能对患者管理和成本具有重要意义。
