In silico models of DNA damage and repair in proton treatment planning: a proof of concept
Authors
Smith, Edward AKHenthorn, Nicholas
Warmenhoven, John
Ingram, Samuel
Aitkenhead, Adam H
Richardson, JC
Sitch, Peter
Chadwick, Amy
Underwood, Tracy
Merchant, Michael J
Burnet, Neil G
Kirkby, Norman
Kirkby, Karen J
Mackay, Ranald I
Affiliation
Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.Issue Date
2019
Metadata
Show full item recordAbstract
There is strong in vitro cell survival evidence that the relative biological effectiveness (RBE) of protons is variable, with dependence on factors such as linear energy transfer (LET) and dose. This is coupled with the growing in vivo evidence, from post-treatment image change analysis, of a variable RBE. Despite this, a constant RBE of 1.1 is still applied as a standard in proton therapy. However, there is a building clinical interest in incorporating a variable RBE. Recently, correlations summarising Monte Carlo-based mechanistic models of DNA damage and repair with absorbed dose and LET have been published as the Manchester mechanistic (MM) model. These correlations offer an alternative path to variable RBE compared to the more standard phenomenological models. In this proof of concept work, these correlations have been extended to acquire RBE-weighted dose distributions and calculated, along with other RBE models, on a treatment plan. The phenomenological and mechanistic models for RBE have been shown to produce comparable results with some differences in magnitude and relative distribution. The mechanistic model found a large RBE for misrepair, which phenomenological models are unable to do. The potential of the MM model to predict multiple endpoints presents a clear advantage over phenomenological models.Citation
Smith EAK, Henthorn NT, Warmenhoven JW, Ingram SP, Aitkenhead AH, Richardson JC, et al. In Silico Models of DNA Damage and Repair in Proton Treatment Planning: A Proof of Concept. Sci Rep. 2019;9(1):19870.Journal
Scientific ReportsDOI
10.1038/s41598-019-56258-5PubMed ID
31882690Additional Links
https://dx.doi.org/10.1038/s41598-019-56258-5Type
ArticleLanguage
enae974a485f413a2113503eed53cd6c53
10.1038/s41598-019-56258-5
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