Why the study?
Although considered the gold standard, wire-based physiological assessments like PW-FFR and PW-iFR are not sufficiently adopted, making vFFR a potentially less invasive surrogate needing real-world validation.
Does angiography-based vessel fractional flow reserve (vFFR) accurately predict wire-based fractional flow reserve (PW-FFR) in patients undergoing coronary angiography?
Does angiography-based vessel fractional flow reserve (vFFR) accurately predict wire-based fractional flow reserve (PW-FFR) in patients undergoing coronary angiography?
Angiography-based vessel fractional flow reserve (vFFR) provides good diagnostic accuracy and correlation compared to invasive wire-based physiological assessments, offering a less invasive alternative for evaluating coronary lesions.
BACKGROUND: Although considered the gold standard, pressure wire-derived fractional flow reserve (PW-FFR) and instantaneous wave-free ratio (PW-iFR) are not sufficiently adopted. Vessel fractional flow reserve (vFFR) is a potentially less invasive surrogate. AIMS: To validate the diagnostic performance of vFFR against the wire-based physiological assessments in real-world clinical settings. METHODS: In this single-center retrospective study, we analyzed 479 patients (586 vessels) who underwent PW-FFR and vFFR in the same vessel, and evaluated the correlation between vFFR and PW-FFR using PW-FFR ≦ 0.80 as the reference. Additionally, we analyzed 378 patients (455 vessels) with vFFR, PW-FFR, and PW-iFR, and 93 patients (119 vessels) with vFFR, PW-FFR, and resting full-cycle ratio (RFR). RESULTS: The indications for coronary angiography were stable angina (92%), unstable angina (6.3%), and non-ST-elevation myocardial infarction (1.5%). The target vessels were the left anterior descending artery (61%), left circumflex artery (20%), and right coronary artery (19%). A good correlation was found between vFFR and PW-FFR (R = 0.67; p < 0.001) with a mean bias of 0.0068 ± 0.0786. vFFR demonstrated good accuracy at predicting PW-FFR ≦0.80 (area under the curve [AUC] = 0.86; 95% confidence interval [CI]: 0.83-0.89). At a vFFR cut-off value of ≦0.80, the sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy for predicting PW-FFR ≦0.80 were 78.8%, 82.5%, 77.6%, 83.5%, and 80.9%, respectively, with a Cohen's Kappa coefficient of 0.612. Similar results were observed for vFFR with PW-iFR and RFR. CONCLUSION: vFFR demonstrated good correlation and diagnostic performance compared with wire-based physiological assessments.
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Oshima et al. (2025) studied this question.
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