P2720Diagnostic accuracy of Quantitative Flow Ratio (QFR) and Vessel Fractional Flow Reserve (vFFR) compared to Fractional Flow Reserve (FFR) based on 7.5 frames/second coronary angiography

Background

Fractional flow reserve (FFR) is the gold standard for the physiological assessment of intermediate coronary artery lesions. Recently, several novel methods for computation of FFR based on 3-dimensional quantitative coronary angiography have been developed. These techniques allow analyses to be performed retrospectively and do not require induction of hyperaemia. The development and validation of these techniques are based on good quality coronary angiography with high frames per second (15 fps) acquisition. The diagnostic accuracy of Quantitative Flow Ratio (QFR) and Vessel Fractional Flow Reserve (vFFR) in real world “radiation-save mode” coronary angiography has not been studied.

Purpose

To validate the accuracy of QFR and vFFR compared to FFR based on a series of coronary angiography acquired at 7.5 fps.

Methods

We retrospectively analyzed 134 vessels (102 patients) with intermediate coronary artery stenosis (30–90%) in whom an FFR measurement had been performed. All the coronary angiography were acquired at 7.5 fps. 33 vessels (20 patients) were excluded from the study due to unsuitable coronary anatomy, invalid FFR measurements, poor image quality and lack of 2 projections ≥25° apart. A total of 101 vessels (82 patients) were included in the final analysis. Contrast-QFR (cQFR), fixed-QFR (fQFR) and vFFR analysis were performed in these vessels by two independent trained experts blinded to the FFR readings. FFR measurements at hyperaemic steady state was taken as the gold standard reference.

Results

Good intra- and inter-observer reliability was noted for fQFR, cQFR and vFFR analysis (intra-observer mean difference for fQFR: 0.016±0.060, p=0.066; cQFR: 0.009±0.053, p=0.230; vFFR: 0.008±0.040, p=0.175; inter-observer mean difference for fQFR: 0.001±0.036, p=0.847; cQFR: −0.001±0.049; p=0.910, vFFR: −0.005±0.037, p=0.393). fQFR and cQFR showed good correlation with FFR (r=0.694, p<0.001 and r=0.674, p<0.001, respectively) while vFFR showed moderate correlation with FFR (r=0.388, p<0.001). Similarly, fQFR and cQFR showed good accuracy for the detection of functionally significant coronary stenosis (fQFR AUC 0.882 (95% CI 0.803–0.938) and cQFR AUC 0.886 (95% CI 0.807–0.940)) while vFFR showed moderate accuracy with AUC 0.719 (95% CI 0.621–0.804). For identifying functionally significant stenosis (FFR ≤0.80), the overall diagnostic accuracy were 81.2%, 85.2%, 75.3% for fQFR, cQFR and vFFR, repectively. The sensitivity and specificity were 72.7%, 89.9% (fQFR); 83.5%, 31.8% (cQFR) and 68.2%, 87.3% (vFFR).

Conclusion

Functional assessment of intermediate coronary stenosis based on 7.5 fps angiography-derived computational modelling is feasible. Our study shows that fQFR and cQFR have a better diagnostic accuracy for detecting functionally significant coronary stenosis compared to vFFR. At the lower radiation-save mode 7.5 fps angiography, cQFR does not appear to provide additional diagnostic accuracy compared to fQFR.