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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2021
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oai:doaj.org-article:9d01d26f380147d1b97a378225982f6d2021-12-02T19:57:22ZBridging cell-scale simulations and radiologic images to explain short-time intratumoral oxygen fluctuations.1553-734X1553-735810.1371/journal.pcbi.1009206https://doaj.org/article/9d01d26f380147d1b97a378225982f6d2021-07-01T00:00:00Zhttps://doi.org/10.1371/journal.pcbi.1009206https://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358Radiologic 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.Jessica L KingsleyJames R CostelloNatarajan RaghunandKatarzyna A RejniakPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 17, Iss 7, p e1009206 (2021) |
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Biology (General) QH301-705.5 |
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Biology (General) QH301-705.5 Jessica L Kingsley James R Costello Natarajan Raghunand Katarzyna A Rejniak Bridging cell-scale simulations and radiologic images to explain short-time intratumoral oxygen fluctuations. |
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. |
format |
article |
author |
Jessica L Kingsley James R Costello Natarajan Raghunand Katarzyna A Rejniak |
author_facet |
Jessica L Kingsley James R Costello Natarajan Raghunand Katarzyna A Rejniak |
author_sort |
Jessica L Kingsley |
title |
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_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_sort |
bridging cell-scale simulations and radiologic images to explain short-time intratumoral oxygen fluctuations. |
publisher |
Public Library of Science (PLoS) |
publishDate |
2021 |
url |
https://doaj.org/article/9d01d26f380147d1b97a378225982f6d |
work_keys_str_mv |
AT jessicalkingsley bridgingcellscalesimulationsandradiologicimagestoexplainshorttimeintratumoraloxygenfluctuations AT jamesrcostello bridgingcellscalesimulationsandradiologicimagestoexplainshorttimeintratumoraloxygenfluctuations AT natarajanraghunand bridgingcellscalesimulationsandradiologicimagestoexplainshorttimeintratumoraloxygenfluctuations AT katarzynaarejniak bridgingcellscalesimulationsandradiologicimagestoexplainshorttimeintratumoraloxygenfluctuations |
_version_ |
1718375855969796096 |