Computational Fractional Flow Reserve From Coronary Computed Tomography Angiography—Optical Coherence Tomography Fusion Images in Assessing Functionally Significant Coronary Stenosis

Yong Joon Lee, Young Woo Kim, Jinyong Ha, Minug Kim, Giulio Guagliumi, Juan F. Granada, Seul Gee Lee, Jung Jae Lee, Yun Kyeong Cho, Hyuck Jun Yoon, Jung Hee Lee, Ung Kim, Ji Yong Jang, Seung Jin Oh, Seung Jun Lee, Sung Jin Hong, Chul Min Ahn, Byeong Keuk Kim, Hyuk Jae Chang, Young Guk KoDonghoon Choi, Myeong Ki Hong, Yangsoo Jang, Joon Sang Lee, Jung Sun Kim

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1 Citation (Scopus)

Abstract

Background: Coronary computed tomography angiography (CTA) and optical coherence tomography (OCT) provide additional functional information beyond the anatomy by applying computational fluid dynamics (CFD). This study sought to evaluate a novel approach for estimating computational fractional flow reserve (FFR) from coronary CTA-OCT fusion images. Methods: Among patients who underwent coronary CTA, 148 patients who underwent both pressure wire-based FFR measurement and OCT during angiography to evaluate intermediate stenosis in the left anterior descending artery were included from the prospective registry. Coronary CTA-OCT fusion images were created, and CFD was applied to estimate computational FFR. Based on pressure wire-based FFR as a reference, the diagnostic performance of Fusion-FFR was compared with that of CT-FFR and OCT-FFR. Results: Fusion-FFR was strongly correlated with FFR (r = 0.836, P < 0.001). Correlation between FFR and Fusion-FFR was stronger than that between FFR and CT-FFR (r = 0.682, P < 0.001; z statistic, 5.42, P < 0.001) and between FFR and OCT-FFR (r = 0.705, P < 0.001; z statistic, 4.38, P < 0.001). Area under the receiver operating characteristics curve to assess functionally significant stenosis was higher for Fusion-FFR than for CT-FFR (0.90 vs. 0.83, P = 0.024) and OCT-FFR (0.90 vs. 0.83, P = 0.043). Fusion-FFR exhibited 84.5% accuracy, 84.6% sensitivity, 84.3% specificity, 80.9% positive predictive value, and 87.5% negative predictive value. Especially accuracy, specificity, and positive predictive value were superior for Fusion-FFR than for CT-FFR (73.0%, P = 0.007; 61.4%, P < 0.001; 64.0%, P < 0.001) and OCT-FFR (75.7%, P = 0.021; 73.5%, P = 0.020; 69.9%, P = 0.012). Conclusion: CFD-based computational FFR from coronary CTA-OCT fusion images provided more accurate functional information than coronary CTA or OCT alone. Clinical Trial Registration: [www.ClinicalTrials.gov], identifier [NCT03298282].

Original languageEnglish
Article number925414
JournalFrontiers in Cardiovascular Medicine
Volume9
DOIs
Publication statusPublished - 2022 Jun 13

Bibliographical note

Funding Information:
This work was supported by the Technology Innovation Program (20010978: Development of the drug eluting bioresorbable coronary vascular stent having 100μm thick struts) funded by the Ministry of Trade, Industry and Energy (Sejong-city, South Korea), the Bio and Medical Technology Development Program (2017M3A9E9073370 and 2017M3A9E9073585) of the National Research Foundation funded by the Ministry of Science and ICT (Sejong City, South Korea), the Cardiovascular Research Center (Seoul, South Korea), and funded by research grants from Chong Kun Dang (Seoul, South Korea).

Publisher Copyright:
Copyright © 2022 Lee, Kim, Ha, Kim, Guagliumi, Granada, Lee, Lee, Cho, Yoon, Lee, Kim, Jang, Oh, Lee, Hong, Ahn, Kim, Chang, Ko, Choi, Hong, Jang, Lee and Kim.

All Science Journal Classification (ASJC) codes

  • Cardiology and Cardiovascular Medicine

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