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AngioMT: An in silico platform for digital sensing of oxygen transport through heterogenous microvascular networks
Measuring the capacity of microvascular networks in delivering soluble oxygen and nutrients to its organs is essential in health, disease, and surgical interventions. Here, a finite element method-based oxygen transport program, AngioMT, is designed and validated to predict spatial oxygen distributi...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9881947/ https://www.ncbi.nlm.nih.gov/pubmed/36711826 http://dx.doi.org/10.1101/2023.01.09.523275 |
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author | Mathur, Tanmay Tronolone, James J. Jain, Abhishek |
author_facet | Mathur, Tanmay Tronolone, James J. Jain, Abhishek |
author_sort | Mathur, Tanmay |
collection | PubMed |
description | Measuring the capacity of microvascular networks in delivering soluble oxygen and nutrients to its organs is essential in health, disease, and surgical interventions. Here, a finite element method-based oxygen transport program, AngioMT, is designed and validated to predict spatial oxygen distribution and other physiologically relevant transport metrics within both the vascular network and the surrounding tissue. The software processes acquired images of microvascular networks and produces a digital mesh which is used to predict vessel and tissue oxygenation. The image-to-physics translation by AngioMT correlated with results from commercial software, however only AngioMT could provide predictions within the solid tissue in addition to vessel oxygenation. AngioMT predictions were sensitive and positively correlated to spatial heterogeneity and extent of vascularization of 500 different vascular networks formed with variable vasculogenic conditions. The predictions of AngioMT cross-correlate with experimentally-measured oxygen distributions in vivo. The computational power of the software is increased by including calculations of higher order reaction mechanisms, and the program includes defining additional organ and tissue structures for a more physiologically relevant analysis of tissue oxygenation in complex co-cultured systems, or in vivo. AngioMT may serve as a digital performance measuring tool of vascular networks in microcirculation, experimental models of vascularized tissues and organs, and in clinical applications, such as organ transplants. |
format | Online Article Text |
id | pubmed-9881947 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Cold Spring Harbor Laboratory |
record_format | MEDLINE/PubMed |
spelling | pubmed-98819472023-01-28 AngioMT: An in silico platform for digital sensing of oxygen transport through heterogenous microvascular networks Mathur, Tanmay Tronolone, James J. Jain, Abhishek bioRxiv Article Measuring the capacity of microvascular networks in delivering soluble oxygen and nutrients to its organs is essential in health, disease, and surgical interventions. Here, a finite element method-based oxygen transport program, AngioMT, is designed and validated to predict spatial oxygen distribution and other physiologically relevant transport metrics within both the vascular network and the surrounding tissue. The software processes acquired images of microvascular networks and produces a digital mesh which is used to predict vessel and tissue oxygenation. The image-to-physics translation by AngioMT correlated with results from commercial software, however only AngioMT could provide predictions within the solid tissue in addition to vessel oxygenation. AngioMT predictions were sensitive and positively correlated to spatial heterogeneity and extent of vascularization of 500 different vascular networks formed with variable vasculogenic conditions. The predictions of AngioMT cross-correlate with experimentally-measured oxygen distributions in vivo. The computational power of the software is increased by including calculations of higher order reaction mechanisms, and the program includes defining additional organ and tissue structures for a more physiologically relevant analysis of tissue oxygenation in complex co-cultured systems, or in vivo. AngioMT may serve as a digital performance measuring tool of vascular networks in microcirculation, experimental models of vascularized tissues and organs, and in clinical applications, such as organ transplants. Cold Spring Harbor Laboratory 2023-01-10 /pmc/articles/PMC9881947/ /pubmed/36711826 http://dx.doi.org/10.1101/2023.01.09.523275 Text en https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use. |
spellingShingle | Article Mathur, Tanmay Tronolone, James J. Jain, Abhishek AngioMT: An in silico platform for digital sensing of oxygen transport through heterogenous microvascular networks |
title | AngioMT: An in silico platform for digital sensing of oxygen transport through heterogenous microvascular networks |
title_full | AngioMT: An in silico platform for digital sensing of oxygen transport through heterogenous microvascular networks |
title_fullStr | AngioMT: An in silico platform for digital sensing of oxygen transport through heterogenous microvascular networks |
title_full_unstemmed | AngioMT: An in silico platform for digital sensing of oxygen transport through heterogenous microvascular networks |
title_short | AngioMT: An in silico platform for digital sensing of oxygen transport through heterogenous microvascular networks |
title_sort | angiomt: an in silico platform for digital sensing of oxygen transport through heterogenous microvascular networks |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9881947/ https://www.ncbi.nlm.nih.gov/pubmed/36711826 http://dx.doi.org/10.1101/2023.01.09.523275 |
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