Change in Computed Tomography-Derived Fractional Flow Reserve Across the Lesion Improve the Diagnostic Performance of Functional Coronary Stenosis

Hankun Yan; Yang Gao; Na Zhao; Wenlei Geng; Zhihui Hou; Yunqiang An; Jie Zhang; Bin Lu

doi:10.3389/fcvm.2021.788703

Change in Computed Tomography-Derived Fractional Flow Reserve Across the Lesion Improve the Diagnostic Performance of Functional Coronary Stenosis

Front Cardiovasc Med. 2022 Jan 13:8:788703. doi: 10.3389/fcvm.2021.788703. eCollection 2021.

Authors

Hankun Yan¹, Yang Gao¹, Na Zhao¹, Wenlei Geng¹, Zhihui Hou¹, Yunqiang An¹, Jie Zhang¹, Bin Lu¹

Affiliation

¹ Department of Radiology, Fu Wai Hospital, National Center for Cardiovascular Diseases, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China.

Abstract

Aims: This study sought to evaluate the diagnostic performance of change in computed tomography-derived fractional flow reserve (CT-FFR) across the lesion (ΔCT-FFR) for identifying ischemia lesions with FFR as the reference standard. Methods: Patients who underwent coronary CT angiography (CCTA) and FFR measurement within 1 week from December 2018 to December 2019 were retrospectively enrolled. CT-FFR within 2 cm distal to the lesion, ΔCT-FFR and plaque characteristics were analyzed. The diagnostic accuracy of CCTA (coronary stenosis ≥ 50%), CT-FFR ≤ 0.80, and ΔCT-FFR ≥ 0.15 (based on the largest Youden index) were assessed with FFR as the reference standard. The relationship between plaque characteristics and ΔCT-FFR was analyzed. Results: The specificity of ΔCT-FFR and CT-FFR were 70.8 and 67.4%, respectively, which were both higher than CCTA (39.3%) (both P < 0.001), while there were no statistical significance in sensitivity among the three (84.5, 77.4, 88.1%, respectively; P = 0.08). The area under the curves (AUCs) of ΔCT-FFR and CT-FFR were 0.803 and 0.743, respectively, which were both higher than that of CCTA (0.637) (both P < 0.05), and the AUC of ΔCT-FFR was higher than that of CT-FFR (P < 0.001). Multivariable analysis showed that low-attenuation plaque (LAP) volume (odds ratio [OR], 1.006) and plaque length (OR, 1.021) were independently correlated with ΔCT-FFR (both P < 0.05). Conclusions: CT-FFR and ΔCT-FFR and here especially the ΔCT-FFR could improve the diagnostic performance of ischemia compared with CCTA alone. LAP volume and plaque length were the independent risk factors of ΔCT-FFR.

Keywords: computed tomography-derived fractional flow reserve; coronary artery disease; coronary computed tomography angiography; fractional flow reserve; machine-learning.