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Patient-specific simulations for planning treatment in congenital heart disease

Patient-specific computational models have been extensively developed over the last decades and applied to investigate a wide range of cardiovascular problems. However, translation of these technologies into clinical applications, such as planning of medical procedures, has been limited to a few sin...

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Autores principales: Capelli, Claudio, Sauvage, Emilie, Giusti, Giuliano, Bosi, Giorgia M., Ntsinjana, Hopewell, Carminati, Mario, Derrick, Graham, Marek, Jan, Khambadkone, Sachin, Taylor, Andrew M., Schievano, Silvia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5740223/
https://www.ncbi.nlm.nih.gov/pubmed/29285347
http://dx.doi.org/10.1098/rsfs.2017.0021
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author Capelli, Claudio
Sauvage, Emilie
Giusti, Giuliano
Bosi, Giorgia M.
Ntsinjana, Hopewell
Carminati, Mario
Derrick, Graham
Marek, Jan
Khambadkone, Sachin
Taylor, Andrew M.
Schievano, Silvia
author_facet Capelli, Claudio
Sauvage, Emilie
Giusti, Giuliano
Bosi, Giorgia M.
Ntsinjana, Hopewell
Carminati, Mario
Derrick, Graham
Marek, Jan
Khambadkone, Sachin
Taylor, Andrew M.
Schievano, Silvia
author_sort Capelli, Claudio
collection PubMed
description Patient-specific computational models have been extensively developed over the last decades and applied to investigate a wide range of cardiovascular problems. However, translation of these technologies into clinical applications, such as planning of medical procedures, has been limited to a few single case reports. Hence, the use of patient-specific models is still far from becoming a standard of care in clinical practice. The aim of this study is to describe our experience with a modelling framework that allows patient-specific simulations to be used for prediction of clinical outcomes. A cohort of 12 patients with congenital heart disease who were referred for percutaneous pulmonary valve implantation, stenting of aortic coarctation and surgical repair of double-outlet right ventricle was included in this study. Image data routinely acquired for clinical assessment were post-processed to set up patient-specific models and test device implantation and surgery. Finite-element and computational fluid dynamics analyses were run to assess feasibility of each intervention and provide some guidance. Results showed good agreement between simulations and clinical decision including feasibility, device choice and fluid-dynamic parameters. The promising results of this pilot study support translation of computer simulations as tools for personalization of cardiovascular treatments.
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spelling pubmed-57402232017-12-28 Patient-specific simulations for planning treatment in congenital heart disease Capelli, Claudio Sauvage, Emilie Giusti, Giuliano Bosi, Giorgia M. Ntsinjana, Hopewell Carminati, Mario Derrick, Graham Marek, Jan Khambadkone, Sachin Taylor, Andrew M. Schievano, Silvia Interface Focus Articles Patient-specific computational models have been extensively developed over the last decades and applied to investigate a wide range of cardiovascular problems. However, translation of these technologies into clinical applications, such as planning of medical procedures, has been limited to a few single case reports. Hence, the use of patient-specific models is still far from becoming a standard of care in clinical practice. The aim of this study is to describe our experience with a modelling framework that allows patient-specific simulations to be used for prediction of clinical outcomes. A cohort of 12 patients with congenital heart disease who were referred for percutaneous pulmonary valve implantation, stenting of aortic coarctation and surgical repair of double-outlet right ventricle was included in this study. Image data routinely acquired for clinical assessment were post-processed to set up patient-specific models and test device implantation and surgery. Finite-element and computational fluid dynamics analyses were run to assess feasibility of each intervention and provide some guidance. Results showed good agreement between simulations and clinical decision including feasibility, device choice and fluid-dynamic parameters. The promising results of this pilot study support translation of computer simulations as tools for personalization of cardiovascular treatments. The Royal Society 2018-02-06 2017-12-15 /pmc/articles/PMC5740223/ /pubmed/29285347 http://dx.doi.org/10.1098/rsfs.2017.0021 Text en © 2018 The Authors. http://creativecommons.org/licenses/by/4.0/ Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.
spellingShingle Articles
Capelli, Claudio
Sauvage, Emilie
Giusti, Giuliano
Bosi, Giorgia M.
Ntsinjana, Hopewell
Carminati, Mario
Derrick, Graham
Marek, Jan
Khambadkone, Sachin
Taylor, Andrew M.
Schievano, Silvia
Patient-specific simulations for planning treatment in congenital heart disease
title Patient-specific simulations for planning treatment in congenital heart disease
title_full Patient-specific simulations for planning treatment in congenital heart disease
title_fullStr Patient-specific simulations for planning treatment in congenital heart disease
title_full_unstemmed Patient-specific simulations for planning treatment in congenital heart disease
title_short Patient-specific simulations for planning treatment in congenital heart disease
title_sort patient-specific simulations for planning treatment in congenital heart disease
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5740223/
https://www.ncbi.nlm.nih.gov/pubmed/29285347
http://dx.doi.org/10.1098/rsfs.2017.0021
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