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...

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Bibliographic Details
Main Author: Meaney, Cameron (Author)
Other Authors: Massachusetts Institute of Technology. Department of Physics (Contributor)
Format: Article
Language:English
Published: Public Library of Science (PLoS), 2020-04-01T10:51:22Z.
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Online Access:Get fulltext
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100 1 0 |a Meaney, Cameron  |e author 
100 1 0 |a Massachusetts Institute of Technology. Department of Physics  |e contributor 
245 0 0 |a Spatial optimization for radiation therapy of brain tumours 
260 |b Public Library of Science (PLoS),   |c 2020-04-01T10:51:22Z. 
856 |z Get fulltext  |u https://hdl.handle.net/1721.1/124467 
520 |a 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. 
520 |a National Science Foundation (U.S.) (Grant DMR-1708280) 
546 |a en 
690 |a General Biochemistry, Genetics and Molecular Biology 
690 |a General Agricultural and Biological Sciences 
690 |a General Medicine 
655 7 |a Article 
773 |t 10.1371/journal.pone.0217354 
773 |t PLoS one