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基于三维定量冠状动脉造影的计算血流储备分数软件的验证:FAST 研究。

Validation of a three-dimensional quantitative coronary angiography-based software to calculate fractional flow reserve: the FAST study.

机构信息

Department of Cardiology, Thoraxcenter, Erasmus Medical Center, Rotterdam, the Netherlands.

出版信息

EuroIntervention. 2020 Sep 18;16(7):591-599. doi: 10.4244/EIJ-D-19-00466.

Abstract

AIMS

The aim of this study was to validate novel software to calculate vessel fractional flow reserve (vFFR) based on 3D-QCA and to assess inter-observer variability in patients who underwent routine preprocedural FFR assessment for intermediate coronary artery stenosis.

METHODS AND RESULTS

In vitro validation was performed in an experimental model. Clinical validation was performed in an observational, retrospective, single-centre cohort study. A total of 100 patients presenting with stable angina or non-ST-segment elevation myocardial infarction and an indication to perform FFR between January 2016 and October 2016 were included. vFFR was calculated based on the aortic root pressure along with two angiographic projections and validated against pressure wire-derived FFR. Mean FFR and vFFR were 0.82±0.08 and 0.84±0.07, respectively. A good linear correlation was found between FFR and vFFR (r=0.89; p<0.001). Assessment of vFFR had a low inter-observer variability (r=0.95; p<0.001). The diagnostic accuracy of vFFR in identifying lesions with an FFR ≤0.80 was higher as compared with 3D-QCA: AUC 0.93 (95% CI: 0.88-0.97) vs 0.66 (95% CI: 0.55-0.77), respectively.

CONCLUSIONS

The 3D-QCA-derived vFFR has a high linear correlation to invasively measured FFR, a high diagnostic accuracy to detect FFR ≤0.80 and a low inter-observer variability.

摘要

目的

本研究旨在验证一种基于 3D-QCA 计算血管分数流量储备(vFFR)的新型软件,并评估对接受常规 FFR 评估的中度冠状动脉狭窄患者进行的观察者间变异性。

方法和结果

在实验模型中进行了体外验证。在观察性、回顾性、单中心队列研究中进行了临床验证。共纳入 100 例因稳定型心绞痛或非 ST 段抬高型心肌梗死且需要进行 FFR 检查的患者,这些患者的检查时间为 2016 年 1 月至 2016 年 10 月。vFFR 基于主动脉根部压力以及两个血管造影投影进行计算,并与压力导丝衍生的 FFR 进行验证。平均 FFR 和 vFFR 分别为 0.82±0.08 和 0.84±0.07。FFR 和 vFFR 之间存在良好的线性相关性(r=0.89;p<0.001)。vFFR 的评估具有较低的观察者间变异性(r=0.95;p<0.001)。与 3D-QCA 相比,vFFR 识别 FFR ≤0.80 病变的诊断准确性更高:AUC 为 0.93(95%CI:0.88-0.97)和 0.66(95%CI:0.55-0.77)。

结论

3D-QCA 衍生的 vFFR 与有创测量的 FFR 具有高度的线性相关性,对检测 FFR ≤0.80 具有较高的诊断准确性,并且观察者间变异性较低。

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