Konstantinos Toutouzas1, Yiannis S Chatzizisis2, Maria Riga1, Andreas Giannopoulos3, Antonios P Antoniadis4, Shengxian Tu5, Yusuke Fujino6, Dimitrios Mitsouras7, Charalampos Doulaverakis8, Ioannis Tsampoulatidis8, Vassilis G Koutkias9, Konstantina Bouki10, Yingguang Li11, Ioanna Chouvarda9, Grigorios Cheimariotis9, Nicos Maglaveras9, Ioannis Kompatsiaris8, Sunao Nakamura6, Johan H C Reiber11, Frank Rybicki7, Haralambos Karvounis3, Christodoulos Stefanadis1, Dimitris Tousoulis1, George D Giannoglou3. 1. First Department of Cardiology, Hippokration Hospital, Athens University Medical School, Athens, Greece. 2. Cardiovascular Division, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; First Department of Cardiology, AHEPA University Hospital, Aristotle University Medical School, Thessaloniki, Greece. Electronic address: ychatzizisis@icloud.com. 3. First Department of Cardiology, AHEPA University Hospital, Aristotle University Medical School, Thessaloniki, Greece. 4. Cardiovascular Division, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; First Department of Cardiology, AHEPA University Hospital, Aristotle University Medical School, Thessaloniki, Greece. 5. Division of Image Processing, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands; Biomedical Instrument Institute, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China. 6. Department of Cardiology, New Tokyo Hospital, Chiba, Japan. 7. Applied Imaging Science Laboratory, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA. 8. Information Technologies Institute, Centre for Research and Technology Hellas, Thessaloniki, Greece. 9. Laboratory of Medical Informatics, Aristotle University Medical School, Thessaloniki, Greece; Institute of Applied Biosciences, Centre for Research and Technology Hellas, Thessaloniki, Greece. 10. Second Department of Cardiology, General Hospital of Nikaia, Piraeus, Greece. 11. Division of Image Processing, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands.
Abstract
BACKGROUND: Geometrically-correct 3D OCT is a new imaging modality with the potential to investigate the association of local hemodynamic microenvironment with OCT-derived high-risk features. We aimed to describe the methodology of 3D OCT and investigate the accuracy, inter- and intra-observer agreement of 3D OCT in reconstructing coronary arteries and calculating ESS, using 3D IVUS and 3D QCA as references. METHODS- RESULTS: 35 coronary artery segments derived from 30 patients were reconstructed in 3D space using 3D OCT. 3D OCT was validated against 3D IVUS and 3D QCA. The agreement in artery reconstruction among 3D OCT, 3D IVUS and 3D QCA was assessed in 3-mm-long subsegments using lumen morphometry and ESS parameters. The inter- and intra-observer agreement of 3D OCT, 3D IVUS and 3D QCA were assessed in a representative sample of 61 subsegments (n = 5 arteries). The data processing times for each reconstruction methodology were also calculated. There was a very high agreement between 3D OCT vs. 3D IVUS and 3D OCT vs. 3D QCA in terms of total reconstructed artery length and volume, as well as in terms of segmental morphometric and ESS metrics with mean differences close to zero and narrow limits of agreement (Bland-Altman analysis). 3D OCT exhibited excellent inter- and intra-observer agreement. The analysis time with 3D OCT was significantly lower compared to 3D IVUS. CONCLUSIONS: Geometrically-correct 3D OCT is a feasible, accurate and reproducible 3D reconstruction technique that can perform reliable ESS calculations in coronary arteries.
BACKGROUND: Geometrically-correct 3D OCT is a new imaging modality with the potential to investigate the association of local hemodynamic microenvironment with OCT-derived high-risk features. We aimed to describe the methodology of 3D OCT and investigate the accuracy, inter- and intra-observer agreement of 3D OCT in reconstructing coronary arteries and calculating ESS, using 3D IVUS and 3D QCA as references. METHODS- RESULTS: 35 coronary artery segments derived from 30 patients were reconstructed in 3D space using 3D OCT. 3D OCT was validated against 3D IVUS and 3D QCA. The agreement in artery reconstruction among 3D OCT, 3D IVUS and 3D QCA was assessed in 3-mm-long subsegments using lumen morphometry and ESS parameters. The inter- and intra-observer agreement of 3D OCT, 3D IVUS and 3D QCA were assessed in a representative sample of 61 subsegments (n = 5 arteries). The data processing times for each reconstruction methodology were also calculated. There was a very high agreement between 3D OCT vs. 3D IVUS and 3D OCT vs. 3D QCA in terms of total reconstructed artery length and volume, as well as in terms of segmental morphometric and ESS metrics with mean differences close to zero and narrow limits of agreement (Bland-Altman analysis). 3D OCT exhibited excellent inter- and intra-observer agreement. The analysis time with 3D OCT was significantly lower compared to 3D IVUS. CONCLUSIONS: Geometrically-correct 3D OCT is a feasible, accurate and reproducible 3D reconstruction technique that can perform reliable ESS calculations in coronary arteries.
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Authors: Yiannis S Chatzizisis; Konstantinos Toutouzas; Andreas A Giannopoulos; Maria Riga; Antonios P Antoniadis; Yusuke Fujinom; Dimitrios Mitsouras; Vassilis G Koutkias; Grigorios Cheimariotis; Charalampos Doulaverakis; Ioannis Tsampoulatidis; Ioanna Chouvarda; Ioannis Kompatsiaris; Sunao Nakamura; Frank J Rybicki; Nicos Maglaveras; Dimitris Tousoulis; George D Giannoglou Journal: Eur Heart J Cardiovasc Imaging Date: 2017-05-01 Impact factor: 6.875
Authors: Satoru Kishi; Andreas A Giannopoulos; Anji Tang; Nahoko Kato; Yiannis S Chatzizisis; Carole Dennie; Yu Horiuchi; Kengo Tanabe; João A C Lima; Frank J Rybicki; Dimitris Mitsouras Journal: Radiology Date: 2017-11-20 Impact factor: 29.146