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Computational Fluid Dynamics Support for Fontan Planning in Minutes, Not Hours: The Next Step in Clinical Pre-Interventional Simulations
Computational fluid dynamics (CFD) modeling may aid in planning of invasive interventions in Fontan patients. Clinical application of current CFD techniques is however limited by complexity and long computation times. Therefore, we validated a “lean” CFD method to magnetic resonance imaging (MRI) an...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9622535/ https://www.ncbi.nlm.nih.gov/pubmed/34961904 http://dx.doi.org/10.1007/s12265-021-10198-6 |
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author | Frieberg, Petter Aristokleous, Nicolas Sjöberg, Pia Töger, Johannes Liuba, Petru Carlsson, Marcus |
author_facet | Frieberg, Petter Aristokleous, Nicolas Sjöberg, Pia Töger, Johannes Liuba, Petru Carlsson, Marcus |
author_sort | Frieberg, Petter |
collection | PubMed |
description | Computational fluid dynamics (CFD) modeling may aid in planning of invasive interventions in Fontan patients. Clinical application of current CFD techniques is however limited by complexity and long computation times. Therefore, we validated a “lean” CFD method to magnetic resonance imaging (MRI) and an “established” CFD method, ultimately aiming to reduce complexity to enable predictive CFD during ongoing interventions. Fifteen Fontan patients underwent MRI for CFD modeling. The differences between lean and established approach, in hepatic and total flow percentage to the left pulmonary artery (%LPA), power loss and relative wall shear stress area were 1.5 ± 4.0%, -0.17 ± 1.1%, -0.055 ± 0.092 mW and 1.1 ± 1.4%. Compared with MRI, the lean and established method showed a bias in %LPA of -1.9 ± 3.4% and -1.8 ± 3.1%. Computation time was for the lean and established approach 3.0 ± 2.0 min and 7.0 ± 3.4 h, respectively. We conclude that the proposed lean method provides fast and reliable results for future CFD support during interventions. GRAPHICAL ABSTRACT: [Image: see text] |
format | Online Article Text |
id | pubmed-9622535 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-96225352022-11-02 Computational Fluid Dynamics Support for Fontan Planning in Minutes, Not Hours: The Next Step in Clinical Pre-Interventional Simulations Frieberg, Petter Aristokleous, Nicolas Sjöberg, Pia Töger, Johannes Liuba, Petru Carlsson, Marcus J Cardiovasc Transl Res Original Article Computational fluid dynamics (CFD) modeling may aid in planning of invasive interventions in Fontan patients. Clinical application of current CFD techniques is however limited by complexity and long computation times. Therefore, we validated a “lean” CFD method to magnetic resonance imaging (MRI) and an “established” CFD method, ultimately aiming to reduce complexity to enable predictive CFD during ongoing interventions. Fifteen Fontan patients underwent MRI for CFD modeling. The differences between lean and established approach, in hepatic and total flow percentage to the left pulmonary artery (%LPA), power loss and relative wall shear stress area were 1.5 ± 4.0%, -0.17 ± 1.1%, -0.055 ± 0.092 mW and 1.1 ± 1.4%. Compared with MRI, the lean and established method showed a bias in %LPA of -1.9 ± 3.4% and -1.8 ± 3.1%. Computation time was for the lean and established approach 3.0 ± 2.0 min and 7.0 ± 3.4 h, respectively. We conclude that the proposed lean method provides fast and reliable results for future CFD support during interventions. GRAPHICAL ABSTRACT: [Image: see text] Springer US 2021-12-27 2022 /pmc/articles/PMC9622535/ /pubmed/34961904 http://dx.doi.org/10.1007/s12265-021-10198-6 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Original Article Frieberg, Petter Aristokleous, Nicolas Sjöberg, Pia Töger, Johannes Liuba, Petru Carlsson, Marcus Computational Fluid Dynamics Support for Fontan Planning in Minutes, Not Hours: The Next Step in Clinical Pre-Interventional Simulations |
title | Computational Fluid Dynamics Support for Fontan Planning in Minutes, Not Hours: The Next Step in Clinical Pre-Interventional Simulations |
title_full | Computational Fluid Dynamics Support for Fontan Planning in Minutes, Not Hours: The Next Step in Clinical Pre-Interventional Simulations |
title_fullStr | Computational Fluid Dynamics Support for Fontan Planning in Minutes, Not Hours: The Next Step in Clinical Pre-Interventional Simulations |
title_full_unstemmed | Computational Fluid Dynamics Support for Fontan Planning in Minutes, Not Hours: The Next Step in Clinical Pre-Interventional Simulations |
title_short | Computational Fluid Dynamics Support for Fontan Planning in Minutes, Not Hours: The Next Step in Clinical Pre-Interventional Simulations |
title_sort | computational fluid dynamics support for fontan planning in minutes, not hours: the next step in clinical pre-interventional simulations |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9622535/ https://www.ncbi.nlm.nih.gov/pubmed/34961904 http://dx.doi.org/10.1007/s12265-021-10198-6 |
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