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

Autor: 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 Ko, Donghoon Choi, Myeong-Ki Hong, Yangsoo Jang, Joon Sang Lee, Jung-Sun Kim
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Frontiers in Cardiovascular Medicine, Vol 9 (2022)
Druh dokumentu: article
ISSN: 2297-055X
DOI: 10.3389/fcvm.2022.925414
Popis: BackgroundCoronary 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.MethodsAmong 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.ResultsFusion-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).ConclusionCFD-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].
Databáze: Directory of Open Access Journals