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Virtual TEVAR: Overcoming the Roadblocks of In-Silico Tools for Aortic Dissection Treatment
The use of in silico tools for the interventional planning of complex vascular conditions, such as Aortic Dissections has been often limited by high computational cost, involving long timescales for accurate results to be produced and low numbers of patients, precluding the use of statistical analys...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Ivyspring International Publisher
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6299687/ https://www.ncbi.nlm.nih.gov/pubmed/30613306 http://dx.doi.org/10.7150/thno.30753 |
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author | Diaz-Zuccarini, Vanessa Bonfanti, Mirko Franzetti, Gaia Balabani, Stavroula |
author_facet | Diaz-Zuccarini, Vanessa Bonfanti, Mirko Franzetti, Gaia Balabani, Stavroula |
author_sort | Diaz-Zuccarini, Vanessa |
collection | PubMed |
description | The use of in silico tools for the interventional planning of complex vascular conditions, such as Aortic Dissections has been often limited by high computational cost, involving long timescales for accurate results to be produced and low numbers of patients, precluding the use of statistical analyses to inform individual-level models. In the paper [Theranostics 2018; 8(20):5758-5771. doi:10.7150/thno.28944], Chen et al. proposed a novel algorithm to compute patient-specific 'virtual TEVAR' that will help clinicians to approach individual treatment and decision-making based on objective and quantifiable metrics and validated on a cohort of 66 patients in real time. This research will significantly impact the field and has the potential to transform the way clinical interventions will be approached in the future. |
format | Online Article Text |
id | pubmed-6299687 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Ivyspring International Publisher |
record_format | MEDLINE/PubMed |
spelling | pubmed-62996872019-01-04 Virtual TEVAR: Overcoming the Roadblocks of In-Silico Tools for Aortic Dissection Treatment Diaz-Zuccarini, Vanessa Bonfanti, Mirko Franzetti, Gaia Balabani, Stavroula Theranostics Editorial The use of in silico tools for the interventional planning of complex vascular conditions, such as Aortic Dissections has been often limited by high computational cost, involving long timescales for accurate results to be produced and low numbers of patients, precluding the use of statistical analyses to inform individual-level models. In the paper [Theranostics 2018; 8(20):5758-5771. doi:10.7150/thno.28944], Chen et al. proposed a novel algorithm to compute patient-specific 'virtual TEVAR' that will help clinicians to approach individual treatment and decision-making based on objective and quantifiable metrics and validated on a cohort of 66 patients in real time. This research will significantly impact the field and has the potential to transform the way clinical interventions will be approached in the future. Ivyspring International Publisher 2018-12-07 /pmc/articles/PMC6299687/ /pubmed/30613306 http://dx.doi.org/10.7150/thno.30753 Text en © Ivyspring International Publisher This is an open access article distributed under the terms of the Creative Commons Attribution (CC BY-NC) license (https://creativecommons.org/licenses/by-nc/4.0/). See http://ivyspring.com/terms for full terms and conditions. |
spellingShingle | Editorial Diaz-Zuccarini, Vanessa Bonfanti, Mirko Franzetti, Gaia Balabani, Stavroula Virtual TEVAR: Overcoming the Roadblocks of In-Silico Tools for Aortic Dissection Treatment |
title | Virtual TEVAR: Overcoming the Roadblocks of In-Silico Tools for Aortic Dissection Treatment |
title_full | Virtual TEVAR: Overcoming the Roadblocks of In-Silico Tools for Aortic Dissection Treatment |
title_fullStr | Virtual TEVAR: Overcoming the Roadblocks of In-Silico Tools for Aortic Dissection Treatment |
title_full_unstemmed | Virtual TEVAR: Overcoming the Roadblocks of In-Silico Tools for Aortic Dissection Treatment |
title_short | Virtual TEVAR: Overcoming the Roadblocks of In-Silico Tools for Aortic Dissection Treatment |
title_sort | virtual tevar: overcoming the roadblocks of in-silico tools for aortic dissection treatment |
topic | Editorial |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6299687/ https://www.ncbi.nlm.nih.gov/pubmed/30613306 http://dx.doi.org/10.7150/thno.30753 |
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