Functional Assessment of Cerebral Artery Stenosis by Angiography-Based Quantitative Flow Ratio: A Pilot Study

Front Aging Neurosci. 2022 Feb 1:14:813648. doi: 10.3389/fnagi.2022.813648. eCollection 2022.

Abstract

Background: Increasing attention has been paid to the hemodynamic evaluation of cerebral arterial stenosis. We aimed to demonstrate the performance of angiography-based quantitative flow ratio (QFR) to assess hemodynamic alterations caused by luminal stenoses, using invasive fractional pressure ratios (FPRs) as a reference standard.

Methods: Between March 2013 and December 2019, 29 patients undergoing the pressure gradient measurement of cerebral atherosclerosis were retrospectively enrolled. Wire-based FPR was defined by the arterial pressure distal to the stenotic lesion (Pd) to proximal (Pa) pressure ratios (Pd/Pa). FPR < 0.70 or FPR < 0.75 was assumed as hemodynamically significant stenosis. The new method of computing QFR from a single angiographic view, i.e., the Murray law-based QFR, was applied to the interrogated vessel. An artificial intelligence algorithm was developed to realize the automatic delineation of vascular contour.

Results: Fractional pressure ratio and QFR were assessed in 38 vessels from 29 patients. Excellent correlation and agreement were observed between QFR and FPR [r = 0.879, P < 0.001; mean difference (bias): -0.006, 95% limits of agreement: -0.198 to 0.209, respectively). Intra-observer and inter-observer reliability in QFR were excellent (intra-class correlation coefficients, 0.996 and 0.973, respectively). For predicting FPR < 0.70, the area under the receiver-operating characteristic curves (AUC) of QFR was 0.946 (95% CI, 0.820 to 0.993%). The sensitivity and specificity of QFR < 0.70 for identifying FPR < 0.70 was 88.9% (95% CI, 65.3 to 98.6%) and 85.0% (95% CI, 62.1 to 96.8%). For predicting FPR < 0.75, QFR showed similar performance with an AUC equal to 0.926.

Conclusion: Computational QFR from a single angiographic view achieved comparable results to the wire-based FPR. The excellent diagnostic performance and repeatability empower QFR with high feasibility in the functional assessment of cerebral arterial stenosis.

Keywords: artificial intelligence; cerebral arterial stenosis; fractional flow reserve; hemodynamics; quantitative flow ratio.