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dc.contributor.authorSmith, Edward AK
dc.contributor.authorHenthorn, Nicholas
dc.contributor.authorWarmenhoven, John
dc.contributor.authorIngram, Samuel
dc.contributor.authorAitkenhead, Adam H
dc.contributor.authorRichardson, JC
dc.contributor.authorSitch, Peter
dc.contributor.authorChadwick, Amy
dc.contributor.authorUnderwood, Tracy
dc.contributor.authorMerchant, Michael J
dc.contributor.authorBurnet, Neil G
dc.contributor.authorKirkby, Norman
dc.contributor.authorKirkby, Karen J
dc.contributor.authorMackay, Ranald I
dc.date.accessioned2020-01-29T15:17:51Z
dc.date.available2020-01-29T15:17:51Z
dc.date.issued2019en
dc.identifier.citationSmith 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.en
dc.identifier.pmid31882690en
dc.identifier.doi10.1038/s41598-019-56258-5en
dc.identifier.urihttp://hdl.handle.net/10541/622685
dc.description.abstractThere 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.en
dc.language.isoenen
dc.relation.urlhttps://dx.doi.org/10.1038/s41598-019-56258-5en
dc.titleIn silico models of DNA damage and repair in proton treatment planning: a proof of concepten
dc.typeArticleen
dc.contributor.departmentDivision of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.en
dc.identifier.journalScientific Reportsen
dc.description.noteen]
refterms.dateFOA2020-02-03T15:37:37Z


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