Cited 2 times in
Computational Fractional Flow Reserve From Coronary Computed Tomography Angiography-Optical Coherence Tomography Fusion Images in Assessing Functionally Significant Coronary Stenosis
DC Field | Value | Language |
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dc.contributor.author | 김중선 | - |
dc.contributor.author | 이용준 | - |
dc.contributor.author | 이승준 | - |
dc.contributor.author | 홍성진 | - |
dc.contributor.author | 안철민 | - |
dc.contributor.author | 김병극 | - |
dc.contributor.author | 장혁재 | - |
dc.contributor.author | 고영국 | - |
dc.contributor.author | 최동훈 | - |
dc.contributor.author | 홍명기 | - |
dc.contributor.author | 장양수 | - |
dc.contributor.author | 김중선 | - |
dc.date.accessioned | 2022-08-23T00:09:16Z | - |
dc.date.available | 2022-08-23T00:09:16Z | - |
dc.date.issued | 2022-06 | - |
dc.identifier.uri | https://ir.ymlib.yonsei.ac.kr/handle/22282913/189282 | - |
dc.description.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]. | - |
dc.description.statementOfResponsibility | open | - |
dc.format | application/pdf | - |
dc.language | English | - |
dc.publisher | Frontiers Media S.A. | - |
dc.relation.isPartOf | FRONTIERS IN CARDIOVASCULAR MEDICINE | - |
dc.rights | CC BY-NC-ND 2.0 KR | - |
dc.title | Computational Fractional Flow Reserve From Coronary Computed Tomography Angiography-Optical Coherence Tomography Fusion Images in Assessing Functionally Significant Coronary Stenosis | - |
dc.type | Article | - |
dc.contributor.college | College of Medicine (의과대학) | - |
dc.contributor.department | Dept. of Internal Medicine (내과학교실) | - |
dc.contributor.googleauthor | Yong-Joon Lee | - |
dc.contributor.googleauthor | Young Woo Kim | - |
dc.contributor.googleauthor | Jinyong Ha | - |
dc.contributor.googleauthor | Minug Kim | - |
dc.contributor.googleauthor | Giulio Guagliumi | - |
dc.contributor.googleauthor | Juan F Granada | - |
dc.contributor.googleauthor | Seul-Gee Lee | - |
dc.contributor.googleauthor | Jung-Jae Lee | - |
dc.contributor.googleauthor | Yun-Kyeong Cho | - |
dc.contributor.googleauthor | Hyuck Jun Yoon | - |
dc.contributor.googleauthor | Jung Hee Lee | - |
dc.contributor.googleauthor | Ung Kim | - |
dc.contributor.googleauthor | Ji-Yong Jang | - |
dc.contributor.googleauthor | Seung-Jin Oh | - |
dc.contributor.googleauthor | Seung-Jun Lee | - |
dc.contributor.googleauthor | Sung-Jin Hong | - |
dc.contributor.googleauthor | Chul-Min Ahn | - |
dc.contributor.googleauthor | Byeong-Keuk Kim | - |
dc.contributor.googleauthor | Hyuk-Jae Chang | - |
dc.contributor.googleauthor | Young-Guk Ko | - |
dc.contributor.googleauthor | Donghoon Choi | - |
dc.contributor.googleauthor | Myeong-Ki Hong | - |
dc.contributor.googleauthor | Yangsoo Jang | - |
dc.contributor.googleauthor | Joon Sang Lee | - |
dc.contributor.googleauthor | Jung-Sun Kim | - |
dc.identifier.doi | 10.3389/fcvm.2022.925414 | - |
dc.contributor.localId | A00961 | - |
dc.contributor.localId | A02984 | - |
dc.relation.journalcode | J04002 | - |
dc.identifier.eissn | 2297-055X | - |
dc.identifier.pmid | 35770218 | - |
dc.subject.keyword | computational fluid dynamics (CFD) | - |
dc.subject.keyword | coronary computed tomography angiography (coronary CTA) | - |
dc.subject.keyword | fractional flow reserve (FFR) | - |
dc.subject.keyword | fusion image | - |
dc.subject.keyword | optical coherence tomography (OCT) | - |
dc.contributor.alternativeName | Kim, Jung Sun | - |
dc.contributor.affiliatedAuthor | 김중선 | - |
dc.contributor.affiliatedAuthor | 이용준 | - |
dc.citation.volume | 9 | - |
dc.citation.startPage | 925414 | - |
dc.identifier.bibliographicCitation | FRONTIERS IN CARDIOVASCULAR MEDICINE, Vol.9 : 925414, 2022-06 | - |
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