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Bridging cell-scale simulations and radiologic images to explain short-time intratumoral oxygen fluctuations

Radiologic images provide a way to monitor tumor development and its response to therapies in a longitudinal and minimally invasive fashion. However, they operate on a macroscopic scale (average value per voxel) and are not able to capture microscopic scale (cell-level) phenomena. Nevertheless, to e...

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Autores principales: Kingsley, Jessica L., Costello, James R., Raghunand, Natarajan, Rejniak, Katarzyna A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8341701/
https://www.ncbi.nlm.nih.gov/pubmed/34310608
http://dx.doi.org/10.1371/journal.pcbi.1009206
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author Kingsley, Jessica L.
Costello, James R.
Raghunand, Natarajan
Rejniak, Katarzyna A.
author_facet Kingsley, Jessica L.
Costello, James R.
Raghunand, Natarajan
Rejniak, Katarzyna A.
author_sort Kingsley, Jessica L.
collection PubMed
description Radiologic images provide a way to monitor tumor development and its response to therapies in a longitudinal and minimally invasive fashion. However, they operate on a macroscopic scale (average value per voxel) and are not able to capture microscopic scale (cell-level) phenomena. Nevertheless, to examine the causes of frequent fast fluctuations in tissue oxygenation, models simulating individual cells’ behavior are needed. Here, we provide a link between the average data values recorded for radiologic images and the cellular and vascular architecture of the corresponding tissues. Using hybrid agent-based modeling, we generate a set of tissue morphologies capable of reproducing oxygenation levels observed in radiologic images. We then use these in silico tissues to investigate whether oxygen fluctuations can be explained by changes in vascular oxygen supply or by modulations in cellular oxygen absorption. Our studies show that intravascular changes in oxygen supply reproduce the observed fluctuations in tissue oxygenation in all considered regions of interest. However, larger-magnitude fluctuations cannot be recreated by modifications in cellular absorption of oxygen in a biologically feasible manner. Additionally, we develop a procedure to identify plausible tissue morphologies for a given temporal series of average data from radiology images. In future applications, this approach can be used to generate a set of tissues comparable with radiology images and to simulate tumor responses to various anti-cancer treatments at the tissue-scale level.
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spelling pubmed-83417012021-08-06 Bridging cell-scale simulations and radiologic images to explain short-time intratumoral oxygen fluctuations Kingsley, Jessica L. Costello, James R. Raghunand, Natarajan Rejniak, Katarzyna A. PLoS Comput Biol Research Article Radiologic images provide a way to monitor tumor development and its response to therapies in a longitudinal and minimally invasive fashion. However, they operate on a macroscopic scale (average value per voxel) and are not able to capture microscopic scale (cell-level) phenomena. Nevertheless, to examine the causes of frequent fast fluctuations in tissue oxygenation, models simulating individual cells’ behavior are needed. Here, we provide a link between the average data values recorded for radiologic images and the cellular and vascular architecture of the corresponding tissues. Using hybrid agent-based modeling, we generate a set of tissue morphologies capable of reproducing oxygenation levels observed in radiologic images. We then use these in silico tissues to investigate whether oxygen fluctuations can be explained by changes in vascular oxygen supply or by modulations in cellular oxygen absorption. Our studies show that intravascular changes in oxygen supply reproduce the observed fluctuations in tissue oxygenation in all considered regions of interest. However, larger-magnitude fluctuations cannot be recreated by modifications in cellular absorption of oxygen in a biologically feasible manner. Additionally, we develop a procedure to identify plausible tissue morphologies for a given temporal series of average data from radiology images. In future applications, this approach can be used to generate a set of tissues comparable with radiology images and to simulate tumor responses to various anti-cancer treatments at the tissue-scale level. Public Library of Science 2021-07-26 /pmc/articles/PMC8341701/ /pubmed/34310608 http://dx.doi.org/10.1371/journal.pcbi.1009206 Text en © 2021 Kingsley et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Kingsley, Jessica L.
Costello, James R.
Raghunand, Natarajan
Rejniak, Katarzyna A.
Bridging cell-scale simulations and radiologic images to explain short-time intratumoral oxygen fluctuations
title Bridging cell-scale simulations and radiologic images to explain short-time intratumoral oxygen fluctuations
title_full Bridging cell-scale simulations and radiologic images to explain short-time intratumoral oxygen fluctuations
title_fullStr Bridging cell-scale simulations and radiologic images to explain short-time intratumoral oxygen fluctuations
title_full_unstemmed Bridging cell-scale simulations and radiologic images to explain short-time intratumoral oxygen fluctuations
title_short Bridging cell-scale simulations and radiologic images to explain short-time intratumoral oxygen fluctuations
title_sort bridging cell-scale simulations and radiologic images to explain short-time intratumoral oxygen fluctuations
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8341701/
https://www.ncbi.nlm.nih.gov/pubmed/34310608
http://dx.doi.org/10.1371/journal.pcbi.1009206
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