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An image-based approach for the estimation of arterial local stiffness in vivo
The analysis of mechanobiology of arterial tissues remains an important topic of research for cardiovascular pathologies evaluation. In the current state of the art, the gold standard to characterize the tissue mechanical behavior is represented by experimental tests, requiring the harvesting of ex-...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9923115/ https://www.ncbi.nlm.nih.gov/pubmed/36793441 http://dx.doi.org/10.3389/fbioe.2023.1096196 |
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author | Celi, Simona Gasparotti, Emanuele Capellini, Katia Bardi, Francesco Scarpolini, Martino Andrea Cavaliere, Carlo Cademartiri, Filippo Vignali, Emanuele |
author_facet | Celi, Simona Gasparotti, Emanuele Capellini, Katia Bardi, Francesco Scarpolini, Martino Andrea Cavaliere, Carlo Cademartiri, Filippo Vignali, Emanuele |
author_sort | Celi, Simona |
collection | PubMed |
description | The analysis of mechanobiology of arterial tissues remains an important topic of research for cardiovascular pathologies evaluation. In the current state of the art, the gold standard to characterize the tissue mechanical behavior is represented by experimental tests, requiring the harvesting of ex-vivo specimens. In recent years though, image-based techniques for the in vivo estimation of arterial tissue stiffness were presented. The aim of this study is to define a new approach to provide local distribution of arterial stiffness, estimated as the linearized Young’s Modulus, based on the knowledge of in vivo patient-specific imaging data. In particular, the strain and stress are estimated with sectional contour length ratios and a Laplace hypothesis/inverse engineering approach, respectively, and then used to calculate the Young’s Modulus. After describing the method, this was validated by using a set of Finite Element simulations as input. In particular, idealized cylinder and elbow shapes plus a single patient-specific geometry were simulated. Different stiffness distributions were tested for the simulated patient-specific case. After the validation from Finite Element data, the method was then applied to patient-specific ECG-gated Computed Tomography data by also introducing a mesh morphing approach to map the aortic surface along the cardiac phases. The validation process revealed satisfactory results. In the simulated patient-specific case, root mean square percentage errors below 10% for the homogeneous distribution and below 20% for proximal/distal distribution of stiffness. The method was then successfully used on the three ECG-gated patient-specific cases. The resulting distributions of stiffness exhibited significant heterogeneity, nevertheless the resulting Young’s moduli were always contained within the 1–3 MPa range, which is in line with literature. |
format | Online Article Text |
id | pubmed-9923115 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-99231152023-02-14 An image-based approach for the estimation of arterial local stiffness in vivo Celi, Simona Gasparotti, Emanuele Capellini, Katia Bardi, Francesco Scarpolini, Martino Andrea Cavaliere, Carlo Cademartiri, Filippo Vignali, Emanuele Front Bioeng Biotechnol Bioengineering and Biotechnology The analysis of mechanobiology of arterial tissues remains an important topic of research for cardiovascular pathologies evaluation. In the current state of the art, the gold standard to characterize the tissue mechanical behavior is represented by experimental tests, requiring the harvesting of ex-vivo specimens. In recent years though, image-based techniques for the in vivo estimation of arterial tissue stiffness were presented. The aim of this study is to define a new approach to provide local distribution of arterial stiffness, estimated as the linearized Young’s Modulus, based on the knowledge of in vivo patient-specific imaging data. In particular, the strain and stress are estimated with sectional contour length ratios and a Laplace hypothesis/inverse engineering approach, respectively, and then used to calculate the Young’s Modulus. After describing the method, this was validated by using a set of Finite Element simulations as input. In particular, idealized cylinder and elbow shapes plus a single patient-specific geometry were simulated. Different stiffness distributions were tested for the simulated patient-specific case. After the validation from Finite Element data, the method was then applied to patient-specific ECG-gated Computed Tomography data by also introducing a mesh morphing approach to map the aortic surface along the cardiac phases. The validation process revealed satisfactory results. In the simulated patient-specific case, root mean square percentage errors below 10% for the homogeneous distribution and below 20% for proximal/distal distribution of stiffness. The method was then successfully used on the three ECG-gated patient-specific cases. The resulting distributions of stiffness exhibited significant heterogeneity, nevertheless the resulting Young’s moduli were always contained within the 1–3 MPa range, which is in line with literature. Frontiers Media S.A. 2023-01-30 /pmc/articles/PMC9923115/ /pubmed/36793441 http://dx.doi.org/10.3389/fbioe.2023.1096196 Text en Copyright © 2023 Celi, Gasparotti, Capellini, Bardi, Scarpolini, Cavaliere, Cademartiri and Vignali. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Bioengineering and Biotechnology Celi, Simona Gasparotti, Emanuele Capellini, Katia Bardi, Francesco Scarpolini, Martino Andrea Cavaliere, Carlo Cademartiri, Filippo Vignali, Emanuele An image-based approach for the estimation of arterial local stiffness in vivo |
title | An image-based approach for the estimation of arterial local stiffness in vivo
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title_full | An image-based approach for the estimation of arterial local stiffness in vivo
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title_fullStr | An image-based approach for the estimation of arterial local stiffness in vivo
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title_full_unstemmed | An image-based approach for the estimation of arterial local stiffness in vivo
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title_short | An image-based approach for the estimation of arterial local stiffness in vivo
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title_sort | image-based approach for the estimation of arterial local stiffness in vivo |
topic | Bioengineering and Biotechnology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9923115/ https://www.ncbi.nlm.nih.gov/pubmed/36793441 http://dx.doi.org/10.3389/fbioe.2023.1096196 |
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