Abstract

Physiological indices such as fractional flow reserve (FFR), instantaneous wave-free ratio (iFR) and resting distal coronary to aortic pressure (Pd/Pa) are increasingly used to guide revascularisation. However, reliable assessment of individual stenoses in serial coronary disease remains an unmet need. This study aimed to compare conventional pressure-based indices, a reference Doppler-based resistance index (hyperaemic stenosis resistance [hSR]) and a recently described mathematical correction model to predict the contribution of individual stenoses in serial disease. Resting and hyperaemic pressure wire pullbacks were performed in 54 patients with serial disease. For each stenosis, FFR, iFR, and Pd/Pa were measured by the translesional gradient in each index and the predicted FFR (FFRpred) derived mathematically from hyperaemic pullback data. "True" stenosis significance by each index was assessed following PCI of the accompanying stenosis or measurements made in a large disease-free branch. In 27 patients, Doppler average peak flow velocity (APV) was also measured to calculate hSR (hSR=∆P/APV, where ∆P=translesional pressure gradient). FFR underestimated individual stenosis severity, inversely proportional to cumulative FFR (r=0.5, p<0.001). Mean errors for FFR, iFR and Pd/Pa were 33%, 20% and 24%, respectively, and 14% for FFRpred (p<0.001). Stenosis misclassification rates based on FFR 0.80, iFR 0.89 and Pd/Pa 0.91 thresholds were not significantly different (17%, 24% and 20%, respectively) but were higher than FFRpred (11%, p<0.001). Apparent and true hSR correlated strongly (r=0.87, p<0.001, mean error 0.19±0.3), with only 7% of stenoses misclassified. Individual stenosis severity is significantly underestimated in the presence of serial disease, using both hyperaemic and resting pressure-based indices. hSR is less prone to error but challenges in optimising Doppler signals limit clinical utility. A mathematical correction model, using data from hyperaemic pressure wire pullback, produces similar accuracy to hSR and is superior to conventional pressure-based indices.

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