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BioPARR: A software system for estimating the rupture potential index for abdominal aortic aneurysms

An abdominal aortic aneurysm (AAA) is a permanent and irreversible dilation of the lower region of the aorta. It is a symptomless condition that, if left untreated, can expand until rupture. Despite ongoing efforts, an efficient tool for accurate estimation of AAA rupture risk is still not available...

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Autores principales: Joldes, Grand Roman, Miller, Karol, Wittek, Adam, Forsythe, Rachael O., Newby, David E., Doyle, Barry J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5498605/
https://www.ncbi.nlm.nih.gov/pubmed/28680081
http://dx.doi.org/10.1038/s41598-017-04699-1
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author Joldes, Grand Roman
Miller, Karol
Wittek, Adam
Forsythe, Rachael O.
Newby, David E.
Doyle, Barry J.
author_facet Joldes, Grand Roman
Miller, Karol
Wittek, Adam
Forsythe, Rachael O.
Newby, David E.
Doyle, Barry J.
author_sort Joldes, Grand Roman
collection PubMed
description An abdominal aortic aneurysm (AAA) is a permanent and irreversible dilation of the lower region of the aorta. It is a symptomless condition that, if left untreated, can expand until rupture. Despite ongoing efforts, an efficient tool for accurate estimation of AAA rupture risk is still not available. Furthermore, a lack of standardisation across current approaches and specific obstacles within computational workflows limit the translation of existing methods to the clinic. This paper presents BioPARR (Biomechanics based Prediction of Aneurysm Rupture Risk), a software system to facilitate the analysis of AAA using a finite element analysis based approach. Except semi-automatic segmentation of the AAA and intraluminal thrombus (ILT) from medical images, the entire analysis is performed automatically. The system is modular and easily expandable, allows the extraction of information from images of different modalities (e.g. CT and MRI) and the simulation of different modelling scenarios (e.g. with/without thrombus). The software uses contemporary methods that eliminate the need for patient-specific material properties, overcoming perhaps the key limitation to all previous patient-specific analysis methods. The software system is robust, free, and will allow researchers to perform comparative evaluation of AAA using a standardised approach. We report preliminary data from 48 cases.
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spelling pubmed-54986052017-07-10 BioPARR: A software system for estimating the rupture potential index for abdominal aortic aneurysms Joldes, Grand Roman Miller, Karol Wittek, Adam Forsythe, Rachael O. Newby, David E. Doyle, Barry J. Sci Rep Article An abdominal aortic aneurysm (AAA) is a permanent and irreversible dilation of the lower region of the aorta. It is a symptomless condition that, if left untreated, can expand until rupture. Despite ongoing efforts, an efficient tool for accurate estimation of AAA rupture risk is still not available. Furthermore, a lack of standardisation across current approaches and specific obstacles within computational workflows limit the translation of existing methods to the clinic. This paper presents BioPARR (Biomechanics based Prediction of Aneurysm Rupture Risk), a software system to facilitate the analysis of AAA using a finite element analysis based approach. Except semi-automatic segmentation of the AAA and intraluminal thrombus (ILT) from medical images, the entire analysis is performed automatically. The system is modular and easily expandable, allows the extraction of information from images of different modalities (e.g. CT and MRI) and the simulation of different modelling scenarios (e.g. with/without thrombus). The software uses contemporary methods that eliminate the need for patient-specific material properties, overcoming perhaps the key limitation to all previous patient-specific analysis methods. The software system is robust, free, and will allow researchers to perform comparative evaluation of AAA using a standardised approach. We report preliminary data from 48 cases. Nature Publishing Group UK 2017-07-05 /pmc/articles/PMC5498605/ /pubmed/28680081 http://dx.doi.org/10.1038/s41598-017-04699-1 Text en © The Author(s) 2017 Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Joldes, Grand Roman
Miller, Karol
Wittek, Adam
Forsythe, Rachael O.
Newby, David E.
Doyle, Barry J.
BioPARR: A software system for estimating the rupture potential index for abdominal aortic aneurysms
title BioPARR: A software system for estimating the rupture potential index for abdominal aortic aneurysms
title_full BioPARR: A software system for estimating the rupture potential index for abdominal aortic aneurysms
title_fullStr BioPARR: A software system for estimating the rupture potential index for abdominal aortic aneurysms
title_full_unstemmed BioPARR: A software system for estimating the rupture potential index for abdominal aortic aneurysms
title_short BioPARR: A software system for estimating the rupture potential index for abdominal aortic aneurysms
title_sort bioparr: a software system for estimating the rupture potential index for abdominal aortic aneurysms
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5498605/
https://www.ncbi.nlm.nih.gov/pubmed/28680081
http://dx.doi.org/10.1038/s41598-017-04699-1
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