Enhanced perfusion following exposure to radiotherapy: a theoretical investigation

Köry, J. , Narain, V., Stolz, B. J., Kaeppler, J., Markelc, B., Muschel, R. J., Maini, P. K., Pitt-Francis, J. M. and Byrne, H. M. (2024) Enhanced perfusion following exposure to radiotherapy: a theoretical investigation. PLoS Computational Biology, 20(2), e1011252. (doi: 10.1371/journal.pcbi.1011252) (PMID:38363799) (PMCID:PMC10903964)

Abstract

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.

• Item Type: Articles
• Additional Information: JK acknowledges support from Cancer Research UK (CRUK) Grants No. C5255/A18085 and No. C5255/A15935. VN acknowledges support from Cancer Research UK (CRUK) Grant No. C2195/A31281. BJS and HMB are members of the Centre for Topological Data Analysis and this research was funded in whole or in part by EPSRC EP/R018472/1. BJS is further supported by the L’Oréal-UNESCO UK and Ireland For Women in Science Rising Talent Programme. HMB and PKM would further like to thank the Isaac Newton Institute for Mathematical Sciences, Cambridge, for support and hospitality during the programme Mathematics of Movement where work on the completion of this paper was undertaken. This work was supported by EPSRC grant no EP/R014604/1. BM acknowledges support from People Programme (Marie Curie Actions) of the European Union’s Seventh Framework Programme (FP7/2007- 2013) under REA grant agreement No 625631, Medical Research Council (MRC) - UKRI (Grant number: C5255/A18085), Cancer Research UK (CRUK) grant numbers C5255/A18085 and C5255/A15935, through the CRUK Oxford Centre, and the Slovenian Research Agency (Grant numbers:P3-0003, J3-2529).
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Koery, Dr Jakub

Creator Roles

Köry, J.: Conceptualization, Formal analysis, Investigation, Methodology, Software, Writing – original draft, Writing – review and editing

• Authors: Köry, J., Narain, V., Stolz, B. J., Kaeppler, J., Markelc, B., Muschel, R. J., Maini, P. K., Pitt-Francis, J. M., and Byrne, H. M.
• College/School: College of Science and Engineering > School of Mathematics and Statistics > Mathematics
• Journal Name: PLoS Computational Biology
• Publisher: Public Library of Science
• ISSN: 1553-734X
• ISSN (Online): 1553-7358
• Published Online: 16 February 2024
• Copyright Holders: Copyright © 2024 Köry et al.
• First Published: First published in PLoS Computational Biology 20(2): e1011252
• Publisher Policy: Reproduced under a Creative Commons License

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