NIHR Biomedical Research Centre and British Heart Foundation Centre of Excellence, School of Cardiovascular Medicine and Sciences, St Thomas' Campus, King's College London, London, United Kingdom.
EuroIntervention. 2020 Sep 18;16(7):577-583. doi: 10.4244/EIJ-D-19-00635.
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.
分数血流储备（FFR）、瞬时无波比（iFR）和静息远端冠状动脉至主动脉压（Pd/Pa）等生理指标越来越多地用于指导血运重建。然而，在连续冠状动脉疾病中可靠地评估个体狭窄仍然是一个未满足的需求。本研究旨在比较传统的基于压力的指标、参考多普勒阻力指数（充血性狭窄阻力[hSR]）和最近描述的数学校正模型，以预测连续疾病中个体狭窄的贡献。
对 54 例连续疾病患者进行静息和充血压力导丝回撤。对于每个狭窄部位，通过每个指数的跨病变梯度测量 FFR、iFR 和 Pd/Pa，并从充血性拉回数据中通过数学方法预测 FFRpred（FFRpred）。通过伴随狭窄的 PCI 或在无大病变分支中进行测量，评估每个指数的“真实”狭窄意义。在 27 例患者中，还测量了多普勒平均峰值流速（APV）以计算 hSR（hSR=∆P/APV，其中 ∆P=跨病变压力梯度）。FFR 低估了个体狭窄的严重程度，与累积 FFR 呈反比（r=0.5，p<0.001）。FFR、iFR 和 Pd/Pa 的平均误差分别为 33%、20%和 24%，FFRpred 的平均误差为 14%（p<0.001）。基于 FFR 0.80、iFR 0.89 和 Pd/Pa 0.91 阈值的狭窄误分类率没有显著差异（分别为 17%、24%和 20%），但高于 FFRpred（p<0.001）。表观和真实 hSR 相关性很强（r=0.87，p<0.001，平均误差 0.19±0.3），只有 7%的狭窄被误分类。
在存在连续疾病的情况下，使用充血和静息压力基指标，个体狭窄的严重程度被显著低估。hSR 错误较少，但优化多普勒信号的挑战限制了其临床应用。一种基于数学校正模型，使用充血性压力导丝拉回的数据，产生与 hSR 相似的准确性，优于传统的基于压力的指标。
