Diagnostic performance of virtual fractional flow reserve derived from routine coronary angiography using segmentation free reduced order (1-dimensional) flow modelling.

ABSTRACT: Introduction: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. Methods: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). Results: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). Conclusions: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.

SUBMITTER: Mohee K 

PROVIDER: S-EPMC7656870 | biostudies-literature | 2020 Jan-Dec

REPOSITORIES: biostudies-literature