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Background: Clinical data suggest that the relative biological effectiveness (RBE) in proton therapy (PT) varies with linear energy transfer (LET). However, LET calculations are neither standardized nor available in clinical routine. Here, the status of LET calculations among European PT institutions and their comparability are assessed. Materials and methods: Eight European PT institutions used suitable treatment planning systems with their center-specific beam model to create treatment plans in a water phantom covering different field arrangements and fulfilling commonly agreed dose objectives. They employed their locally established LET simulation environments and procedures to determine the corresponding LET distributions. Dose distributions D 1.1 and D RBE assuming constant and variable RBE, respectively, and LET were compared among the institutions. Inter-center variability was assessed based on dose- and LET-volume-histogram parameters. Results: Treatment plans from six institutions fulfilled all clinical goals and were eligible for common analysis. D 1.1 distributions in the target volume were comparable among PT institutions. However, corresponding LET values varied substantially between institutions for all field arrangements, primarily due to differences in LET averaging technique and considered secondary particle spectra. Consequently, D RBE using non-harmonized LET calculations increased inter-center dose variations substantially compared to D 1.1 and significantly in mean dose to the target volume of perpendicular and opposing field arrangements (p < 0.05). Harmonizing LET reporting (dose-averaging, all protons, LET to water or to unit density tissue) reduced the inter-center variability in LET to the order of 10–15% within and outside the target volume for all beam arrangements. Consequentially, inter-institutional variability in D RBE decreased to that observed for D 1.1. Conclusion: Harmonizing the reported LET among PT centers is feasible and allows for consistent multi-centric analysis and reporting of tumor control and toxicity in view of a variable RBE. It may serve as basis for harmonized variable RBE dose prescription in PT.

The strong in vitro evidence that proton Relative Biological Effectiveness (RBE) varies with Linear Energy Transfer (LET) has led to an interest in applying LET within treatment planning. However, there is a lack of consensus on LET definition, Monte Carlo (MC) parameters or clinical methodology. This work aims to investigate how common variations of LET definition may affect potential clinical applications. MC simulations (GATE/GEANT4) were used to calculate absorbed dose and different types of LET for a simple Spread Out Bragg Peak (SOBP) and for four clinical PBT plans covering a range of tumour sites. Variations in the following LET calculation methods were considered: (i) averaging (dose-averaged LET (LETd) & track-averaged LET); (ii) scoring (LETd to water, to medium and to mass density); (iii) particle inclusion (LETd to all protons, to primary protons and to particles); (iv) MC settings (hit type and Maximum Step Size (MSS)). LET distributions were compared using: qualitative comparison, LET Volume Histograms (LVHs), single value criteria (maximum and mean values) and optimised LET-weighted dose models. Substantial differences were found between LET values in averaging, scoring and particle type. These differences depended on the methodology, but for one patient a difference of ∼100% was observed between the maximum LETd for all particles and maximum LETd for all protons within the brainstem in the high isodose region (4 keV μm−1 and 8 keV μm−1 respectively). An RBE model using LETd including heavier ions was found to predict substantially different LET-weighted dose compared to those using other LET definitions. In conclusion, the selection of LET definition may affect the results of clinical metrics considered in treatment planning and the results of an RBE model. The authors’ advocate for the scoring of dose-averaged LET to water for primary and secondary protons using a random hit type and automated MSS.

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.

Gold nanoparticles have been proven as potential radiosensitizer when combined with protons. Initially the radiosensitization effect was attributed to the physical interactions of radiation with the gold and the production of secondary electrons that induce DNA damage. However, emerging data challenge this hypothesis, supporting the existence of alternative or supplementary radiosensitization mechanisms. In this work we incorporate a realistic cell model with detailed DNA geometry and a realistic gold nanoparticle biodistribution based on experimental data. The DNA single and double strand breaks, and damage complexity are counted under various scenarios of different gold nanoparticle size, biodistribution and concentration, and proton energy. The locality of the effect, i.e. the existence of higher damage at a location close to the gold distribution, is also addressed by investigating the DNA damage at a chromosomal territory. In all the cases we do not observe any significant increase in the single/double strand break yield or damage complexity in the presence of gold nanoparticles under proton irradiation; nor there is a locality to the effect. Our results show for the first time that the physical interactions of protons with the gold nanoparticles should not be considered directly responsible for the observed radiosensitization effect. The model used only accounts for DNA damage from direct interactions, whilst considering the indirect effect, and it is possible the radiosensitization effect to be due to other physical effects, although we consider that possibility unlikely. Our conclusion suggests that other mechanisms might have greater contribution to the radiosensitization effect and further investigation should be conducted.

Gold nanoparticles (GNPs) have been shown to sensitize cancer cells to x-ray radiation, particularly at kV energies where photoelectric interactions dominate and the high atomic number of gold makes a large difference to x-ray absorption. Protons have a high cross-section for gold at a large range of relevant clinical energies, and so potentially could be used with GNPs for increased therapeutic effect.Here, we investigate the contribution of secondary electron emission to cancer cell radiosensitization and investigate how this parameter is affected by proton energy and a free radical scavenger. We simulate the emission from a realistic cell phantom containing GNPs after traversal by protons and x-rays with different energies. We find that with a range of proton energies (1-250 MeV) there is a small increase in secondaries compared to a much larger increase with x-rays. Secondary electrons are known to produce toxic free radicals. Using a cancer cell line in vitro we find that a free radical scavenger has no protective effect on cells containing GNPs irradiated with 3 MeV protons, while it does protect against cells irradiated with x-rays. We conclude that GNP generated free radicals are a major cause of radiosensitization and that there is likely to be much less dose enhancement effect with clinical proton beams compared to x-rays.

Purpose In proton therapy precise knowledge of the beam range is essential to guarantee the treatment’s efficacy and to avoid unnecessary toxicities. Over a fractionated course of treatment anatomical changes can severely impact the delivered dose distribution from that planned; evaluation of these changes on a fraction-by-fraction basis is essential. We report the first results of a new method to determine proton beam range in three dimensions, for pencil-beam scanning systems, with an uncertainty below 3 mm. Methods The range is determined through the reconstruction of the origin of prompt gamma (PG) rays emitted from nuclear de-excitations following proton bombardment. PG emission is almost instantaneous and is characterised by a high-production rate. The prototype system is comprised of 16 symmetrically-spaced LaBr3(Ce) detectors, in a spherical design. Initially the position reconstruction capability of the detector system was examined using Geant4 simulations. To determine the PG-rays emission positions in 3D, the information recorded by each detector is fed into a reconstruction algorithm, developed in the MATLAB environment. The development, testing and laboratory validation of the algorithm has been conducted using a sealed 60 Co source. Furthermore the algorithm has been employed to investigate, by means of Geant4 simulations, how the system performs with a proton pencil beam at different clinical energies. In the simulations a water phantom with 2-cm thick body materials slabs embedded inside has been modelled. Results Preliminary simulation results show that for an ideal detector system the reconstruction algorithm is capable of determining the source position to within 1 mm in the 3D space. The algorithm is also able of discriminating between multiple sources with a relative separation of 0.15 mm. A good agreement has been observed between the dose and the prompt-gamma distribution from a proton pencil beam impinging the different phantoms at all the employed clinical energies. Conclusions Proof-of-principle for the reconstruction algorithm with a sealed 60 Co source has been obtained. The response of the system with a clinical proton beam has been evaluated, by means on Monte Carlo simulations. The next stage is to test the system with a proton beam experimentally.

The potential that laser based particle accelerators offer to solve sizing and cost issues arising with conventional proton therapy has generated great interest in the understanding and development of laser ion acceleration, and in investigating the radiobiological effects induced by laser accelerated ions. Laser-driven ions are produced in bursts of ultra-short duration resulting in ultra-high dose rates, and an investigation at Queen's University Belfast was carried out to investigate this virtually unexplored regime of cell rdaiobiology. This employed the TARANIS terawatt laser producing protons in the MeV range for proton irradiation, with dose rates exceeding 109 Gys-1 on a single exposure. A clonogenic assay was implemented to analyse the biological effect of proton irradiation on V79 cells, which, when compared to data obtained with the same cell line irradiated with conventionally accelerated protons, was found to show no significant difference. A Relative Biological effectiveness of 1.4±0.2 at 10 % Survival Fraction was estimated from a comparison with a 225 kVp X-ray source. © 2013 SPIE.

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.

Objectives: High-energy Proton Beam Therapy (PBT) commenced in England in 2018 and NHS England commissions PBT for 1.5% of patients receiving radical radiotherapy. We sought expert opinion on the level of provision. Methods: Invitations were sent to 41 colleagues working in PBT, most at one UK centre, to contribute by completing a spreadsheet. 39 responded: 23 (59%) completed the spreadsheet; 16 (41%) declined, arguing that clinical outcome data are lacking, but joined six additional site-specialist oncologists for two consensus meetings. The spreadsheet was pre-populated with incidence data from Cancer Research UK and radiotherapy use data from the National Cancer Registration and Analysis Service. ‘Mechanisms of Benefit’ of reduced growth impairment, reduced toxicity, dose escalation and reduced second cancer risk were examined. Results: The most reliable figure for percentage of radical radiotherapy patients likely to benefit from PBT was that agreed by 95% of the 23 respondents at 4.3%, slightly larger than current provision. The median was 15% (range 4–92%) and consensus median 13%. The biggest estimated potential benefit was from reducing toxicity, median benefit to 15% (range 4–92%), followed by dose escalation median 3% (range 0 to 47%); consensus values were 12 and 3%. Reduced growth impairment and reduced second cancer risk were calculated to benefit 0.5% and 0.1%. Conclusions: The most secure estimate of percentage benefit was 4.3% but insufficient clinical outcome data exist for confident estimates. The study supports the NHS approach of using the evidence base and developing it through randomised trials, non-randomised studies and outcomes tracking. Advances in knowledge: Less is known about the percentage of patients who may benefit from PBT than is generally acknowledged. Expert opinion varies widely. Insufficient clinical outcome data exist to provide robust estimates. Considerable further work is needed to address this, including international collaboration; much is already underway but will take time to provide mature data.