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Zhao, Shijia; Wu, Wei; Samant, Saurabhi; Khan, Behram; Kassab, Ghassan S.; Watanabe, Yusuke; Murasato, Yoshinobu; Sharzehee, Mohammadali; Makadia, Janaki; Zolty, Daniel; Panagopoulos, Anastasios; Burzotta, Francesco; Migliavacca, Francesco; Johnson, Thomas W.; Lefevre, Thierry; Lassen, Jens Flensted; Brilakis, Emmanouil S.; Bhatt, Deepak L.; Dangas, George; Chiastra, Claudio; Stankovic, Goran; Louvard, Yves; Chatzizisis, Yiannis S.
Scientific reports, 08/2021, Volume: 11, Issue: 1Journal Article
Abstract Patient-specific and lesion-specific computational simulation of bifurcation stenting is an attractive approach to achieve individualized pre-procedural planning that could improve outcomes. The objectives of this work were to describe and validate a novel platform for fully computational patient-specific coronary bifurcation stenting. Our computational stent simulation platform was trained using n = 4 patient-specific bench bifurcation models (n = 17 simulations), and n = 5 clinical bifurcation cases (training group, n = 23 simulations). The platform was blindly tested in n = 5 clinical bifurcation cases (testing group, n = 29 simulations). A variety of stent platforms and stent techniques with 1- or 2-stents was used. Post-stenting imaging with micro-computed tomography (μCT) for bench group and optical coherence tomography (OCT) for clinical groups were used as reference for the training and testing of computational coronary bifurcation stenting. There was a very high agreement for mean lumen diameter (MLD) between stent simulations and post-stenting μCT in bench cases yielding an overall bias of 0.03 (− 0.28 to 0.34) mm. Similarly, there was a high agreement for MLD between stent simulation and OCT in clinical training group bias 0.08 (− 0.24 to 0.41) mm, and clinical testing group bias 0.08 (− 0.29 to 0.46) mm. Quantitatively and qualitatively stent size and shape in computational stenting was in high agreement with clinical cases, yielding an overall bias of < 0.15 mm. Patient-specific computational stenting of coronary bifurcations is a feasible and accurate approach. Future clinical studies are warranted to investigate the ability of computational stenting simulations to guide decision-making in the cardiac catheterization laboratory and improve clinical outcomes.
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