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Efficiently Simulating an Endograft Deployment: A Methodology for Detailed CFD Analyses

Numerical models of endografts for the simulation of endovascular aneurysm repair are increasingly important in the improvement of device designs and patient outcomes. Nevertheless, current finite element analysis (FEA) models of complete endograft devices come at a high computational cost, requirin...

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Autores principales: Kyriakou, Faidon, Maclean, Craig, Dempster, William, Nash, David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7505889/
https://www.ncbi.nlm.nih.gov/pubmed/32394221
http://dx.doi.org/10.1007/s10439-020-02519-8
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author Kyriakou, Faidon
Maclean, Craig
Dempster, William
Nash, David
author_facet Kyriakou, Faidon
Maclean, Craig
Dempster, William
Nash, David
author_sort Kyriakou, Faidon
collection PubMed
description Numerical models of endografts for the simulation of endovascular aneurysm repair are increasingly important in the improvement of device designs and patient outcomes. Nevertheless, current finite element analysis (FEA) models of complete endograft devices come at a high computational cost, requiring days of runtime, therefore restricting their applicability. In the current study, an efficient FEA model of the Anaconda™ endograft (Terumo Aortic, UK) was developed, able to yield results in just over 4 h, an order of magnitude less than similar models found in the literature. The model was used to replicate a physical device that was deployed in a 3D printed aorta and comparison of the two shapes illustrated a less than 5 mm placement error of the model in the regions of interest, consistent with other more computationally intensive models in the literature. Furthermore, the final goal of the study was to utilize the deployed fabric model in a hemodynamic analysis that would incorporate realistic fabric folds, a feature that is almost always omitted in similar simulations. By successfully exporting the deployed graft geometry into a flow analysis, it was illustrated that the inclusion of fabric wrinkles enabled clinically significant flow patterns such as flow stagnation and recirculation to be detected, paving the way for this modelling methodology to be used in future for stent design optimisation. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s10439-020-02519-8) contains supplementary material, which is available to authorized users.
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spelling pubmed-75058892020-10-05 Efficiently Simulating an Endograft Deployment: A Methodology for Detailed CFD Analyses Kyriakou, Faidon Maclean, Craig Dempster, William Nash, David Ann Biomed Eng Original Article Numerical models of endografts for the simulation of endovascular aneurysm repair are increasingly important in the improvement of device designs and patient outcomes. Nevertheless, current finite element analysis (FEA) models of complete endograft devices come at a high computational cost, requiring days of runtime, therefore restricting their applicability. In the current study, an efficient FEA model of the Anaconda™ endograft (Terumo Aortic, UK) was developed, able to yield results in just over 4 h, an order of magnitude less than similar models found in the literature. The model was used to replicate a physical device that was deployed in a 3D printed aorta and comparison of the two shapes illustrated a less than 5 mm placement error of the model in the regions of interest, consistent with other more computationally intensive models in the literature. Furthermore, the final goal of the study was to utilize the deployed fabric model in a hemodynamic analysis that would incorporate realistic fabric folds, a feature that is almost always omitted in similar simulations. By successfully exporting the deployed graft geometry into a flow analysis, it was illustrated that the inclusion of fabric wrinkles enabled clinically significant flow patterns such as flow stagnation and recirculation to be detected, paving the way for this modelling methodology to be used in future for stent design optimisation. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s10439-020-02519-8) contains supplementary material, which is available to authorized users. Springer International Publishing 2020-05-11 2020 /pmc/articles/PMC7505889/ /pubmed/32394221 http://dx.doi.org/10.1007/s10439-020-02519-8 Text en © The Author(s) 2020 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/.
spellingShingle Original Article
Kyriakou, Faidon
Maclean, Craig
Dempster, William
Nash, David
Efficiently Simulating an Endograft Deployment: A Methodology for Detailed CFD Analyses
title Efficiently Simulating an Endograft Deployment: A Methodology for Detailed CFD Analyses
title_full Efficiently Simulating an Endograft Deployment: A Methodology for Detailed CFD Analyses
title_fullStr Efficiently Simulating an Endograft Deployment: A Methodology for Detailed CFD Analyses
title_full_unstemmed Efficiently Simulating an Endograft Deployment: A Methodology for Detailed CFD Analyses
title_short Efficiently Simulating an Endograft Deployment: A Methodology for Detailed CFD Analyses
title_sort efficiently simulating an endograft deployment: a methodology for detailed cfd analyses
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7505889/
https://www.ncbi.nlm.nih.gov/pubmed/32394221
http://dx.doi.org/10.1007/s10439-020-02519-8
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