Patient-specific computational simulation of coronary artery bifurcation stenting
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 p...
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Nature Portfolio
2021
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oai:doaj.org-article:11ba697b208a48099e110b8621286a7b2021-12-02T18:50:51ZPatient-specific computational simulation of coronary artery bifurcation stenting10.1038/s41598-021-95026-22045-2322https://doaj.org/article/11ba697b208a48099e110b8621286a7b2021-08-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-95026-2https://doaj.org/toc/2045-2322Abstract 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.Shijia ZhaoWei WuSaurabhi SamantBehram KhanGhassan S. KassabYusuke WatanabeYoshinobu MurasatoMohammadali SharzeheeJanaki MakadiaDaniel ZoltyAnastasios PanagopoulosFrancesco BurzottaFrancesco MigliavaccaThomas W. JohnsonThierry LefevreJens Flensted LassenEmmanouil S. BrilakisDeepak L. BhattGeorge DangasClaudio ChiastraGoran StankovicYves LouvardYiannis S. ChatzizisisNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-17 (2021) |
| institution |
DOAJ |
| collection |
DOAJ |
| language |
EN |
| topic |
Medicine R Science Q |
| spellingShingle |
Medicine R Science Q Shijia Zhao Wei Wu Saurabhi Samant Behram Khan Ghassan S. Kassab Yusuke Watanabe Yoshinobu Murasato Mohammadali Sharzehee Janaki Makadia Daniel Zolty Anastasios Panagopoulos Francesco Burzotta Francesco Migliavacca Thomas W. Johnson Thierry Lefevre Jens Flensted Lassen Emmanouil S. Brilakis Deepak L. Bhatt George Dangas Claudio Chiastra Goran Stankovic Yves Louvard Yiannis S. Chatzizisis Patient-specific computational simulation of coronary artery bifurcation stenting |
| description |
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. |
| format |
article |
| author |
Shijia Zhao Wei Wu Saurabhi Samant Behram Khan Ghassan S. Kassab Yusuke Watanabe Yoshinobu Murasato Mohammadali Sharzehee Janaki Makadia Daniel Zolty Anastasios Panagopoulos Francesco Burzotta Francesco Migliavacca Thomas W. Johnson Thierry Lefevre Jens Flensted Lassen Emmanouil S. Brilakis Deepak L. Bhatt George Dangas Claudio Chiastra Goran Stankovic Yves Louvard Yiannis S. Chatzizisis |
| author_facet |
Shijia Zhao Wei Wu Saurabhi Samant Behram Khan Ghassan S. Kassab Yusuke Watanabe Yoshinobu Murasato Mohammadali Sharzehee Janaki Makadia Daniel Zolty Anastasios Panagopoulos Francesco Burzotta Francesco Migliavacca Thomas W. Johnson Thierry Lefevre Jens Flensted Lassen Emmanouil S. Brilakis Deepak L. Bhatt George Dangas Claudio Chiastra Goran Stankovic Yves Louvard Yiannis S. Chatzizisis |
| author_sort |
Shijia Zhao |
| title |
Patient-specific computational simulation of coronary artery bifurcation stenting |
| title_short |
Patient-specific computational simulation of coronary artery bifurcation stenting |
| title_full |
Patient-specific computational simulation of coronary artery bifurcation stenting |
| title_fullStr |
Patient-specific computational simulation of coronary artery bifurcation stenting |
| title_full_unstemmed |
Patient-specific computational simulation of coronary artery bifurcation stenting |
| title_sort |
patient-specific computational simulation of coronary artery bifurcation stenting |
| publisher |
Nature Portfolio |
| publishDate |
2021 |
| url |
https://doaj.org/article/11ba697b208a48099e110b8621286a7b |
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