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Combining radiation with hyperthermia : a multiscale model informed by in vitro experiments
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dc.contributor.author | Brüningk, Sarah | |
dc.contributor.author | Powathil, Gibin | |
dc.contributor.author | Ziegenhein, Peter | |
dc.contributor.author | Ijaz, Jannat | |
dc.contributor.author | Rivens, Ian | |
dc.contributor.author | Nill, S. | |
dc.contributor.author | Chaplain, Mark Andrew Joseph | |
dc.contributor.author | Oelfke, Uwe | |
dc.contributor.author | ter Haar, Gail | |
dc.date.accessioned | 2018-01-23T15:30:09Z | |
dc.date.available | 2018-01-23T15:30:09Z | |
dc.date.issued | 2018-01 | |
dc.identifier.citation | Brüningk , S , Powathil , G , Ziegenhein , P , Ijaz , J , Rivens , I , Nill , S , Chaplain , M A J , Oelfke , U & ter Haar , G 2018 , ' Combining radiation with hyperthermia : a multiscale model informed by in vitro experiments ' , Journal of the Royal Society Interface , vol. 15 , no. 38 , 20170681 . https://doi.org/10.1098/rsif.2017.0681 | en |
dc.identifier.issn | 1742-5689 | |
dc.identifier.other | PURE: 251701594 | |
dc.identifier.other | PURE UUID: 409af595-10e3-4826-bc82-17363a0f4550 | |
dc.identifier.other | Scopus: 85048537315 | |
dc.identifier.other | ORCID: /0000-0001-5727-2160/work/55378908 | |
dc.identifier.other | WOS: 000423770900011 | |
dc.identifier.uri | https://hdl.handle.net/10023/12590 | |
dc.description | Funding: Cancer Research UK. Research at The Institute of Cancer Research is supported by Cancer Research UK under Programme C33589/A19727. Peter Ziegenhein is supported by Cancer Research UK under Programme C33589/A19908. | en |
dc.description.abstract | Combined radiotherapy and hyperthermia offer great potential for the successful treatment of radio-resistant tumours through thermo-radiosensitization. Tumour response heterogeneity, due to intrinsic, or micro-environmentally induced factors, may greatly influence treatment outcome, but is difficult to account for using traditional treatment planning approaches. Systems oncology simulation, using mathematical models designed to predict tumour growth and treatment response, provides a powerful tool for analysis and optimization of combined treatments. We present a framework that simulates such combination treatments on a cellular level. This multiscale hybrid cellular automaton simulates large cell populations (up to 107 cells) in vitro, while allowing individual cell-cycle progression, and treatment response by modelling radiation-induced mitotic cell death, and immediate cell kill in response to heating. Based on a calibration using a number of experimental growth, cell cycle and survival datasets for HCT116 cells, model predictions agreed well (R2 > 0.95) with experimental data within the range of (thermal and radiation) doses tested (0–40 CEM43, 0–5 Gy). The proposed framework offers flexibility for modelling multimodality treatment combinations in different scenarios. It may therefore provide an important step towards the modelling of personalized therapies using a virtual patient tumour. | |
dc.format.extent | 11 | |
dc.language.iso | eng | |
dc.relation.ispartof | Journal of the Royal Society Interface | en |
dc.rights | Copyright 2018 The Author(s). Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited. | en |
dc.subject | Hybrid multiscale model | en |
dc.subject | Radiotherapy | en |
dc.subject | Hyperthermia | en |
dc.subject | Cell-cycle | en |
dc.subject | Cancer | en |
dc.subject | Tumour | en |
dc.subject | QA Mathematics | en |
dc.subject | QH301 Biology | en |
dc.subject | RC0254 Neoplasms. Tumors. Oncology (including Cancer) | en |
dc.subject | E-DAS | en |
dc.subject | SDG 3 - Good Health and Well-being | en |
dc.subject.lcc | QA | en |
dc.subject.lcc | QH301 | en |
dc.subject.lcc | RC0254 | en |
dc.title | Combining radiation with hyperthermia : a multiscale model informed by in vitro experiments | en |
dc.type | Journal article | en |
dc.description.version | Publisher PDF | en |
dc.contributor.institution | University of St Andrews. Applied Mathematics | en |
dc.identifier.doi | https://doi.org/10.1098/rsif.2017.0681 | |
dc.description.status | Peer reviewed | en |
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