Angiographic Lesion Morphology Provides Incremental Value to Generalize Quantitative Flow Ratio for Predicting Myocardial Ischemia

Jie Zhang; Na Zhao; Bo Xu; Lihua Xie; Weihua Yin; Yunqiang An; Hankun Yan; Yitong Yu; Bin Lu

doi:10.3389/fcvm.2022.872498

Angiographic Lesion Morphology Provides Incremental Value to Generalize Quantitative Flow Ratio for Predicting Myocardial Ischemia

Front Cardiovasc Med. 2022 Jun 6:9:872498. doi: 10.3389/fcvm.2022.872498. eCollection 2022.

Authors

Jie Zhang¹, Na Zhao¹, Bo Xu², Lihua Xie², Weihua Yin¹, Yunqiang An¹, Hankun Yan¹, Yitong Yu¹, Bin Lu¹

Affiliations

¹ Department of Radiology, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
² Department of Cardiology, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.

Abstract

Aim: The quantitative flow ratio (QFR) is favorable for functional assessment of coronary artery stenosis without pressure wires and induction of hyperemia. The aim of this study was to explore whether angiographic lesion morphology provides incremental value to generalize QFR for predicting myocardial ischemia in unselected patients.

Methods: This study was a substudy to the CT-FFR CHINA trial, referring 345 participants from five centers with suspected coronary artery disease on coronary CT angiography for diagnostic invasive coronary angiography (ICA). Fractional flow reserve (FFR) was measured in all vessels with 30-90% diameter stenosis. QFR was calculated in 186 lesions from 159 participants in a blinded manner. In addition, parameters to characterize lesion features were recorded or measured, including left anterior descending arteries (LADs)-involved lesions, side branch located at stenotic lesion (BL), multiple lesions (ML), minimal lumen diameter (MLD), reference lumen diameter (RLD), percent diameter stenosis (%DS), lesion length (LL), and LL/MLD⁴. Logistic regression was used to construct two kinds of models by combining single or two lesion parameters with the QFR. The performances of these models were compared with that of QFR on a per-vessel level.

Results: A total of 148 participants (mean age: 59.5 years; 101 men) with 175 coronary arteries were included for final analysis. In total, 81 (46%) vessels were considered hemodynamically significant. QFR correctly classified 82.29% of the vessels using FFR with a cutoff of 0.80 as reference standard. The area under the receiver operating characteristic curve (AUC) of QFR was 0.86 with a sensitivity, specificity, positive predictive value, and negative predictive value of 80.25, 84.04, 81.25, and 83.16%, respectively. The combined models (QFR + LAD + MLD, QFR + LAD + %DS, QFR + BL + MLD, and QFR + BL + %DS) outperformed QFR with higher AUCs (0.91 vs. 0.86, P = 0.02; 0.91 vs. 0.86, P = 0.02; 0.91 vs. 0.86, P = 0.02; 0.90 vs. 0.86, P = 0.03, respectively). Compared with QFR, the sensitivity of the combined models (QFR + BL and QFR + MLD) was improved (91.36 vs. 80.25%, 91.36 vs. 80.25%, respectively, both P < 0.05) without compromised specificity or accuracy.

Conclusion: Combined with angiographic lesion parameters, QFR can be optimized for predicting myocardial ischemia in unselected patients.

Keywords: fractional flow reserve; invasive coronary angiography; lesion morphology; myocardial ischemia; quantitative flow ratio.