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A three‐dimensional method for morphological analysis and flow velocity estimation in microvasculature on‐a‐chip
Three‐dimensional (3D) imaging techniques (e.g., confocal microscopy) are commonly used to visualize in vitro models, especially microvasculature on‐a‐chip. Conversely, 3D analysis is not the standard method to extract quantitative information from those models. We developed the μVES algorithm to an...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley & Sons, Inc.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10487341/ https://www.ncbi.nlm.nih.gov/pubmed/37693050 http://dx.doi.org/10.1002/btm2.10557 |
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author | Rota, Alberto Possenti, Luca Offeddu, Giovanni S. Senesi, Martina Stucchi, Adelaide Venturelli, Irene Rancati, Tiziana Zunino, Paolo Kamm, Roger D. Costantino, Maria Laura |
author_facet | Rota, Alberto Possenti, Luca Offeddu, Giovanni S. Senesi, Martina Stucchi, Adelaide Venturelli, Irene Rancati, Tiziana Zunino, Paolo Kamm, Roger D. Costantino, Maria Laura |
author_sort | Rota, Alberto |
collection | PubMed |
description | Three‐dimensional (3D) imaging techniques (e.g., confocal microscopy) are commonly used to visualize in vitro models, especially microvasculature on‐a‐chip. Conversely, 3D analysis is not the standard method to extract quantitative information from those models. We developed the μVES algorithm to analyze vascularized in vitro models leveraging 3D data. It computes morphological parameters (geometry, diameter, length, tortuosity, eccentricity) and intravascular flow velocity. μVES application to microfluidic vascularized in vitro models shows that they successfully replicate functional features of the microvasculature in vivo in terms of intravascular fluid flow velocity. However, wall shear stress is lower compared to in vivo references. The morphological analysis also highlights the model's physiological similarities (vessel length and tortuosity) and shortcomings (vessel radius and surface‐over‐volume ratio). The addition of the third dimension in our analysis produced significant differences in the metrics assessed compared to 2D estimations. It enabled the computation of new indices, such as vessel eccentricity. These μVES capabilities can find application in analyses of different in vitro vascular models, as well as in vivo and ex vivo microvasculature. |
format | Online Article Text |
id | pubmed-10487341 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | John Wiley & Sons, Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-104873412023-09-09 A three‐dimensional method for morphological analysis and flow velocity estimation in microvasculature on‐a‐chip Rota, Alberto Possenti, Luca Offeddu, Giovanni S. Senesi, Martina Stucchi, Adelaide Venturelli, Irene Rancati, Tiziana Zunino, Paolo Kamm, Roger D. Costantino, Maria Laura Bioeng Transl Med Regular Issue Articles Three‐dimensional (3D) imaging techniques (e.g., confocal microscopy) are commonly used to visualize in vitro models, especially microvasculature on‐a‐chip. Conversely, 3D analysis is not the standard method to extract quantitative information from those models. We developed the μVES algorithm to analyze vascularized in vitro models leveraging 3D data. It computes morphological parameters (geometry, diameter, length, tortuosity, eccentricity) and intravascular flow velocity. μVES application to microfluidic vascularized in vitro models shows that they successfully replicate functional features of the microvasculature in vivo in terms of intravascular fluid flow velocity. However, wall shear stress is lower compared to in vivo references. The morphological analysis also highlights the model's physiological similarities (vessel length and tortuosity) and shortcomings (vessel radius and surface‐over‐volume ratio). The addition of the third dimension in our analysis produced significant differences in the metrics assessed compared to 2D estimations. It enabled the computation of new indices, such as vessel eccentricity. These μVES capabilities can find application in analyses of different in vitro vascular models, as well as in vivo and ex vivo microvasculature. John Wiley & Sons, Inc. 2023-06-11 /pmc/articles/PMC10487341/ /pubmed/37693050 http://dx.doi.org/10.1002/btm2.10557 Text en © 2023 The Authors. Bioengineering & Translational Medicine published by Wiley Periodicals LLC on behalf of American Institute of Chemical Engineers. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Regular Issue Articles Rota, Alberto Possenti, Luca Offeddu, Giovanni S. Senesi, Martina Stucchi, Adelaide Venturelli, Irene Rancati, Tiziana Zunino, Paolo Kamm, Roger D. Costantino, Maria Laura A three‐dimensional method for morphological analysis and flow velocity estimation in microvasculature on‐a‐chip |
title | A three‐dimensional method for morphological analysis and flow velocity estimation in microvasculature on‐a‐chip |
title_full | A three‐dimensional method for morphological analysis and flow velocity estimation in microvasculature on‐a‐chip |
title_fullStr | A three‐dimensional method for morphological analysis and flow velocity estimation in microvasculature on‐a‐chip |
title_full_unstemmed | A three‐dimensional method for morphological analysis and flow velocity estimation in microvasculature on‐a‐chip |
title_short | A three‐dimensional method for morphological analysis and flow velocity estimation in microvasculature on‐a‐chip |
title_sort | three‐dimensional method for morphological analysis and flow velocity estimation in microvasculature on‐a‐chip |
topic | Regular Issue Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10487341/ https://www.ncbi.nlm.nih.gov/pubmed/37693050 http://dx.doi.org/10.1002/btm2.10557 |
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