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

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.

Clinically relevant nanodosimetric simulation of DNA damage complexity from photons and protons

Relative Biological Effectiveness (RBE), the ratio of doses between radiation modalities to produce the same biological endpoint, is a controversial and important topic in proton therapy. A number of phenomenological models incorporate variable RBE as a function of Linear Energy Transfer (LET), though a lack of mechanistic description limits their applicability. In this work we take a different approach, using a track structure model employing fundamental physics and chemistry to make predictions of proton and photon induced DNA damage, the first step in the mechanism of radiation-induced cell death. We apply this model to a proton therapy clinical case showing, for the first time, predictions of DNA damage on a patient treatment plan. Our model predictions are for an idealised cell and are applied to an ependymoma case, at this stage without any cell specific parameters. By comparing to similar predictions for photons, we present a voxel-wise RBE of DNA damage complexity. This RBE of damage complexity shows similar trends to the expected RBE for cell kill, implying that damage complexity is an important factor in DNA repair and therefore biological effect.

Relative Biological Effectiveness (RBE) is a controversial and important topic in proton therapy. This work uses Monte Carlo simulations of DNA damage for protons and photons to probe this phenomenon, providing a plausible mechanistic understanding.

Modelling the throughput capacity of a single-accelerator multitreatment room proton therapy centre

OBJECTIVE

We describe a model for evaluating the throughput capacity of a single-accelerator multitreatment room proton therapy centre with the aims of (1) providing quantitative estimates of the throughput and waiting times and (2) providing insight into the sensitivity of the system to various physical parameters.

METHODS

A Monte Carlo approach was used to compute various statistics about the modelled centre, including the throughput capacity, fraction times for different groups of patients and beam waiting times. A method of quantifying the saturation level is also demonstrated.

RESULTS

Benchmarking against the MD Anderson Cancer Center showed good agreement between the modelled (140 ± 4 fractions per day) and reported (133 ± 35 fractions per day) throughputs. A sensitivity analysis of that system studied the impact of beam switch time, the number of treatment rooms, patient set-up times and the potential benefit of having a second accelerator. Finally, scenarios relevant to a potential UK facility were studied, finding that a centre with the same four-room, single-accelerator configuration as the MD Anderson Cancer Center but handling a more complex UK-type caseload would have a throughput reduced by approximately 19%, but still be capable of treating in excess of 100 fractions per 16-h treatment day.

CONCLUSIONS

The model provides a useful tool to aid in understanding the operating dynamics of a proton therapy facility, and for investigating potential scenarios for prospective centres.

ADVANCES IN KNOWLEDGE

The model helps to identify which technical specifications should be targeted for future improvements.