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Experimental evaluation of the patient-specific haemodynamics of an aortic dissection model using particle image velocimetry

Aortic Dissection (AD) is a complex pathology that affects the aorta. Diagnosis, management and treatment remain a challenge as it is a highly patient-specific pathology and there is still a limited understanding of the fluid-mechanics phenomena underlying clinical outcomes. Although in vitro models...

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Autores principales: Franzetti, Gaia, Bonfanti, Mirko, Homer-Vanniasinkam, Shervanthi, Diaz-Zuccarini, Vanessa, Balabani, Stavroula
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9617468/
https://www.ncbi.nlm.nih.gov/pubmed/35151036
http://dx.doi.org/10.1016/j.jbiomech.2022.110963
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author Franzetti, Gaia
Bonfanti, Mirko
Homer-Vanniasinkam, Shervanthi
Diaz-Zuccarini, Vanessa
Balabani, Stavroula
author_facet Franzetti, Gaia
Bonfanti, Mirko
Homer-Vanniasinkam, Shervanthi
Diaz-Zuccarini, Vanessa
Balabani, Stavroula
author_sort Franzetti, Gaia
collection PubMed
description Aortic Dissection (AD) is a complex pathology that affects the aorta. Diagnosis, management and treatment remain a challenge as it is a highly patient-specific pathology and there is still a limited understanding of the fluid-mechanics phenomena underlying clinical outcomes. Although in vitro models can allow the accurate study of AD flow fields in physical phantoms, they are currently scarce and almost exclusively rely on over simplifying assumptions. In this work, we present the first experimental study of a patient-specific case of AD. An anatomically correct phantom was produced and combined with a state-of-the-art in vitro platform, informed by clinical data, employed to accurately reproduce personalised conditions. The complex AD haemodynamics reproduced by the platform was characterised by flow rate and pressure acquisitions as well as Particle Image Velocimetry (PIV) derived velocity fields. Clinically relevant haemodynamic indices, that can be correlated with AD prognosis – such as velocity, shear rate, turbulent kinetic energy distributions – were extracted in two regions of interest in the aortic domain. The acquired data highlighted the complex nature of the flow (e.g. recirculation regions, low shear rate in the false lumen) and was in very good agreement with the available clinical data and the CFD results of a study conducted alongside, demonstrating the accuracy of the findings. These results demonstrate that the described platform constitutes a powerful, unique tool to reproduce in vitro personalised haemodynamic conditions, which can be used to support the evaluation of surgical procedures, medical devices testing and to validate state-of-the-art numerical models.
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spelling pubmed-96174682022-10-31 Experimental evaluation of the patient-specific haemodynamics of an aortic dissection model using particle image velocimetry Franzetti, Gaia Bonfanti, Mirko Homer-Vanniasinkam, Shervanthi Diaz-Zuccarini, Vanessa Balabani, Stavroula J Biomech Article Aortic Dissection (AD) is a complex pathology that affects the aorta. Diagnosis, management and treatment remain a challenge as it is a highly patient-specific pathology and there is still a limited understanding of the fluid-mechanics phenomena underlying clinical outcomes. Although in vitro models can allow the accurate study of AD flow fields in physical phantoms, they are currently scarce and almost exclusively rely on over simplifying assumptions. In this work, we present the first experimental study of a patient-specific case of AD. An anatomically correct phantom was produced and combined with a state-of-the-art in vitro platform, informed by clinical data, employed to accurately reproduce personalised conditions. The complex AD haemodynamics reproduced by the platform was characterised by flow rate and pressure acquisitions as well as Particle Image Velocimetry (PIV) derived velocity fields. Clinically relevant haemodynamic indices, that can be correlated with AD prognosis – such as velocity, shear rate, turbulent kinetic energy distributions – were extracted in two regions of interest in the aortic domain. The acquired data highlighted the complex nature of the flow (e.g. recirculation regions, low shear rate in the false lumen) and was in very good agreement with the available clinical data and the CFD results of a study conducted alongside, demonstrating the accuracy of the findings. These results demonstrate that the described platform constitutes a powerful, unique tool to reproduce in vitro personalised haemodynamic conditions, which can be used to support the evaluation of surgical procedures, medical devices testing and to validate state-of-the-art numerical models. Elsevier Science 2022-03 /pmc/articles/PMC9617468/ /pubmed/35151036 http://dx.doi.org/10.1016/j.jbiomech.2022.110963 Text en © 2022 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Franzetti, Gaia
Bonfanti, Mirko
Homer-Vanniasinkam, Shervanthi
Diaz-Zuccarini, Vanessa
Balabani, Stavroula
Experimental evaluation of the patient-specific haemodynamics of an aortic dissection model using particle image velocimetry
title Experimental evaluation of the patient-specific haemodynamics of an aortic dissection model using particle image velocimetry
title_full Experimental evaluation of the patient-specific haemodynamics of an aortic dissection model using particle image velocimetry
title_fullStr Experimental evaluation of the patient-specific haemodynamics of an aortic dissection model using particle image velocimetry
title_full_unstemmed Experimental evaluation of the patient-specific haemodynamics of an aortic dissection model using particle image velocimetry
title_short Experimental evaluation of the patient-specific haemodynamics of an aortic dissection model using particle image velocimetry
title_sort experimental evaluation of the patient-specific haemodynamics of an aortic dissection model using particle image velocimetry
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9617468/
https://www.ncbi.nlm.nih.gov/pubmed/35151036
http://dx.doi.org/10.1016/j.jbiomech.2022.110963
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