Mohee Kevin, Mynard Jonathan P, Dhunnoo Gauravsingh, Davies Rhodri, Nithiarasu Perumal, Halcox Julian P, Obaid Daniel R
Department of Cardiology, Swansea Bay University Health Board, Morriston Hospital, Swansea, UK.
Heart Research, Murdoch Children's Research Institute, Parkville, VIC, Australia.
JRSM Cardiovasc Dis. 2020 Nov 5;9:2048004020967578. doi: 10.1177/2048004020967578. eCollection 2020 Jan-Dec.
Fractional flow reserve (FFR) improves assessment of the physiological significance of coronary lesions compared with conventional angiography. However, it is an invasive investigation. We tested the performance of a virtual FFR (1D-vFFR) using routine angiographic images and a rapidly performed reduced order computational model.
Quantitative coronary angiography (QCA) was performed in 102 with coronary lesions assessed by invasive FFR. A 1D-vFFR for each lesion was created using reduced order (one-dimensional) computational flow modelling derived from conventional angiographic images and patient specific estimates of coronary flow. The diagnostic accuracy of 1D-vFFR and QCA derived stenosis was compared against the gold standard of invasive FFR using area under the receiver operator characteristic curve (AUC).
QCA revealed the mean coronary stenosis diameter was 44% ± 12% and lesion length 13 ± 7 mm. Following angiography calculation of the 1DvFFR took less than one minute. Coronary stenosis (QCA) had a significant but weak correlation with FFR (r = -0.2, p = 0.04) and poor diagnostic performance to identify lesions with FFR <0.80 (AUC 0.39, p = 0.09), (sensitivity - 58% and specificity - 26% at a QCA stenosis of 50%). In contrast, 1D-vFFR had a better correlation with FFR (r = 0.32, p = 0.01) and significantly better diagnostic performance (AUC 0.67, p = 0.007), (sensitivity - 92% and specificity - 29% at a 1D-vFFR of 0.7).
1D-vFFR improves the determination of functionally significant coronary lesions compared with conventional angiography without requiring a pressure-wire or hyperaemia induction. It is fast enough to influence immediate clinical decision-making but requires further clinical evaluation.
与传统血管造影相比，血流储备分数（FFR）可改善对冠状动脉病变生理意义的评估。然而，它是一种侵入性检查。我们使用常规血管造影图像和快速执行的降阶计算模型测试了虚拟FFR（1D-vFFR）的性能。
对102例有冠状动脉病变的患者进行了定量冠状动脉造影（QCA），并通过侵入性FFR对病变进行评估。使用从传统血管造影图像和患者特定冠状动脉血流估计得出的降阶（一维）计算血流模型，为每个病变创建一个1D-vFFR。使用受试者操作特征曲线下面积（AUC），将1D-vFFR和QCA得出的狭窄的诊断准确性与侵入性FFR的金标准进行比较。
QCA显示冠状动脉狭窄的平均直径为44%±12%，病变长度为13±7mm。血管造影后计算1DvFFR耗时不到一分钟。冠状动脉狭窄（QCA）与FFR有显著但较弱的相关性（r = -0.2，p = 0.04），对识别FFR<0.80的病变的诊断性能较差（AUC 0.39，p = 0.09），（在QCA狭窄为50%时，敏感性为58%，特异性为26%）。相比之下，1D-vFFR与FFR的相关性更好（r = 0.32，p = 0.01），诊断性能显著更好（AUC 0.67，p = 0.007），（在1D-vFFR为0.7时，敏感性为92%，特异性为29%）。
与传统血管造影相比，1D-vFFR无需压力导丝或充血诱导即可改善对功能性显著冠状动脉病变的判定。它速度足够快，足以影响即时临床决策，但需要进一步的临床评估。
