Enhanced perfusion following exposure to radiotherapy : A theoretical investigation
Copyright: © 2024 Köry et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited..
Tumour angiogenesis leads to the formation of blood vessels that are structurally and spatially heterogeneous. Poor blood perfusion, in conjunction with increased hypoxia and oxygen heterogeneity, impairs a tumour's response to radiotherapy. The optimal strategy for enhancing tumour perfusion remains unclear, preventing its regular deployment in combination therapies. In this work, we first identify vascular architectural features that correlate with enhanced perfusion following radiotherapy, using in vivo imaging data from vascular tumours. Then, we present a novel computational model to determine the relationship between these architectural features and blood perfusion in silico. If perfusion is defined to be the proportion of vessels that support blood flow, we find that vascular networks with small mean diameters and large numbers of angiogenic sprouts show the largest increases in perfusion post-irradiation for both biological and synthetic tumours. We also identify cases where perfusion increases due to the pruning of hypoperfused vessels, rather than blood being rerouted. These results indicate the importance of considering network composition when determining the optimal irradiation strategy. In the future, we aim to use our findings to identify tumours that are good candidates for perfusion enhancement and to improve the efficacy of combination therapies.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:20 |
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| Enthalten in: |
PLoS computational biology - 20(2024), 2 vom: 27. Feb., Seite e1011252 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Köry, Jakub [VerfasserIn] |
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| Links: |
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| Anmerkungen: |
Date Completed 04.03.2024 Date Revised 04.03.2024 published: Electronic-eCollection Citation Status MEDLINE |
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| doi: |
10.1371/journal.pcbi.1011252 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| 520 | |a Copyright: © 2024 Köry et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. | ||
| 520 | |a Tumour angiogenesis leads to the formation of blood vessels that are structurally and spatially heterogeneous. Poor blood perfusion, in conjunction with increased hypoxia and oxygen heterogeneity, impairs a tumour's response to radiotherapy. The optimal strategy for enhancing tumour perfusion remains unclear, preventing its regular deployment in combination therapies. In this work, we first identify vascular architectural features that correlate with enhanced perfusion following radiotherapy, using in vivo imaging data from vascular tumours. Then, we present a novel computational model to determine the relationship between these architectural features and blood perfusion in silico. If perfusion is defined to be the proportion of vessels that support blood flow, we find that vascular networks with small mean diameters and large numbers of angiogenic sprouts show the largest increases in perfusion post-irradiation for both biological and synthetic tumours. We also identify cases where perfusion increases due to the pruning of hypoperfused vessels, rather than blood being rerouted. These results indicate the importance of considering network composition when determining the optimal irradiation strategy. In the future, we aim to use our findings to identify tumours that are good candidates for perfusion enhancement and to improve the efficacy of combination therapies | ||
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| 700 | 1 | |a Stolz, Bernadette J |e verfasserin |4 aut | |
| 700 | 1 | |a Kaeppler, Jakob |e verfasserin |4 aut | |
| 700 | 1 | |a Markelc, Bostjan |e verfasserin |4 aut | |
| 700 | 1 | |a Muschel, Ruth J |e verfasserin |4 aut | |
| 700 | 1 | |a Maini, Philip K |e verfasserin |4 aut | |
| 700 | 1 | |a Pitt-Francis, Joe M |e verfasserin |4 aut | |
| 700 | 1 | |a Byrne, Helen M |e verfasserin |4 aut | |
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