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Optical coherence tomography-based machine learning for predicting fractional flow reserve in intermediate coronary stenosis: a feasibility study

 Jung-Joon Cha  ;  Tran Dinh Son  ;  Jinyong Ha  ;  Jung-Sun Kim  ;  Sung-Jin Hong  ;  Chul-Min Ahn  ;  Byeong-Keuk Kim  ;  Young-Guk Ko  ;  Donghoon Choi  ;  Myeong-Ki Hong  ;  Yangsoo Jang 
 SCIENTIFIC REPORTS, Vol.10(1) : 20421, 2020-12 
Journal Title
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Machine learning approaches using intravascular optical coherence tomography (OCT) to predict fractional flow reserve (FFR) have not been investigated. Both OCT and FFR data were obtained for left anterior descending artery lesions in 125 patients. Training and testing groups were partitioned in the ratio of 5:1. The OCT-based machine learning-FFR was derived for the testing group and compared with wire-based FFR in terms of ischemia diagnosis (FFR ≤ 0.8). The OCT-based machine learning-FFR showed good correlation (r = 0.853, P < 0.001) with the wire-based FFR. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of the OCT-based machine learning-FFR for the testing group were 100%, 92.9%, 87.5%, 100%, and 95.2%, respectively. The OCT-based machine learning-FFR can be used to simultaneously acquire information on both image and functional modalities using one procedure, suggesting that it may provide optimized treatments for intermediate coronary artery stenosis.
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1. College of Medicine (의과대학) > Dept. of Internal Medicine (내과학교실) > 1. Journal Papers
Yonsei Authors
Ko, Young Guk(고영국) ORCID logo https://orcid.org/0000-0001-7748-5788
Kim, Byeong Keuk(김병극) ORCID logo https://orcid.org/0000-0003-2493-066X
Kim, Jung Sun(김중선) ORCID logo https://orcid.org/0000-0003-2263-3274
Ahn, Chul-Min(안철민) ORCID logo https://orcid.org/0000-0002-7071-4370
Jang, Yang Soo(장양수) ORCID logo https://orcid.org/0000-0002-2169-3112
Choi, Dong Hoon(최동훈) ORCID logo https://orcid.org/0000-0002-2009-9760
Hong, Myeong Ki(홍명기) ORCID logo https://orcid.org/0000-0002-2090-2031
Hong, Sung Jin(홍성진) ORCID logo https://orcid.org/0000-0003-4893-039X
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