In Silico Models of DNA Damage and Repair in Proton Treatment Planning: A Proof of Concept

Edward Smith, Nicholas Henthorn, John Warmenhoven, Samuel Ingram, Adam Aitkenhead, Jenny Richardson, Amy Chadwick, Tracy Underwood, Mike Merchant, Neil Burnet, Norman Kirkby, Karen Kirkby, Ranald Mackay

Research output: Contribution to journalArticlepeer-review

Abstract

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.
Original languageEnglish
JournalScientific Reports
DOIs
Publication statusPublished - 27 Dec 2019

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