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Spatial optimization for radiation therapy of brain tumours
Glioblastomas are the most common primary brain tumours. They are known for their highly aggressive growth and invasion, leading to short survival times. Treatments for glioblastomas commonly involve a combination of surgical intervention, chemotherapy, and external beam radiation therapy (XRT). Pre...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6599149/ https://www.ncbi.nlm.nih.gov/pubmed/31251755 http://dx.doi.org/10.1371/journal.pone.0217354 |
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author | Meaney, Cameron Stastna, Marek Kardar, Mehran Kohandel, Mohammad |
author_facet | Meaney, Cameron Stastna, Marek Kardar, Mehran Kohandel, Mohammad |
author_sort | Meaney, Cameron |
collection | PubMed |
description | Glioblastomas are the most common primary brain tumours. They are known for their highly aggressive growth and invasion, leading to short survival times. Treatments for glioblastomas commonly involve a combination of surgical intervention, chemotherapy, and external beam radiation therapy (XRT). Previous works have not only successfully modelled the natural growth of glioblastomas in vivo, but also show potential for the prediction of response to radiation prior to treatment. This suggests that the efficacy of XRT can be optimized before treatment in order to yield longer survival times. However, while current efforts focus on optimal scheduling of radiotherapy treatment, they do not include a similarly sophisticated spatial optimization. In an effort to improve XRT, we present a method for the spatial optimization of radiation profiles. We expand upon previous results in the general problem and examine the more physically reasonable cases of 1-step and 2-step radiation profiles during the first and second XRT fractions. The results show that by including spatial optimization in XRT, while retaining a constant prescribed total dose amount, we are able to increase the total cell kill from the clinically-applied uniform case. |
format | Online Article Text |
id | pubmed-6599149 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-65991492019-07-12 Spatial optimization for radiation therapy of brain tumours Meaney, Cameron Stastna, Marek Kardar, Mehran Kohandel, Mohammad PLoS One Research Article Glioblastomas are the most common primary brain tumours. They are known for their highly aggressive growth and invasion, leading to short survival times. Treatments for glioblastomas commonly involve a combination of surgical intervention, chemotherapy, and external beam radiation therapy (XRT). Previous works have not only successfully modelled the natural growth of glioblastomas in vivo, but also show potential for the prediction of response to radiation prior to treatment. This suggests that the efficacy of XRT can be optimized before treatment in order to yield longer survival times. However, while current efforts focus on optimal scheduling of radiotherapy treatment, they do not include a similarly sophisticated spatial optimization. In an effort to improve XRT, we present a method for the spatial optimization of radiation profiles. We expand upon previous results in the general problem and examine the more physically reasonable cases of 1-step and 2-step radiation profiles during the first and second XRT fractions. The results show that by including spatial optimization in XRT, while retaining a constant prescribed total dose amount, we are able to increase the total cell kill from the clinically-applied uniform case. Public Library of Science 2019-06-28 /pmc/articles/PMC6599149/ /pubmed/31251755 http://dx.doi.org/10.1371/journal.pone.0217354 Text en © 2019 Meaney et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://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 Meaney, Cameron Stastna, Marek Kardar, Mehran Kohandel, Mohammad Spatial optimization for radiation therapy of brain tumours |
title | Spatial optimization for radiation therapy of brain tumours |
title_full | Spatial optimization for radiation therapy of brain tumours |
title_fullStr | Spatial optimization for radiation therapy of brain tumours |
title_full_unstemmed | Spatial optimization for radiation therapy of brain tumours |
title_short | Spatial optimization for radiation therapy of brain tumours |
title_sort | spatial optimization for radiation therapy of brain tumours |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6599149/ https://www.ncbi.nlm.nih.gov/pubmed/31251755 http://dx.doi.org/10.1371/journal.pone.0217354 |
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