Proton linear energy transfer and variable relative biological effectiveness for adolescent patients with Hodgkin lymphoma.

Objectives: Proton therapy has a theoretical dosimetric advantage due to the Bragg peak, but the linear energy transfer (LET), and therefore the relative biological effectiveness (RBE), increase at the end of range. For patients with Hodgkin lymphoma, the distal edge of beam is often located within or close to the heart, where elevated RBE would be of potential concern. The purpose of this study was to investigate the impact of RBE and the choice of beam arrangement for adolescent patients with mediastinal Hodgkin lymphoma. Methods: For three previously treated adolescent patients, proton plans with 1-3 fields were created to a prescribed dose of 19.8 Gy (RBE) in 11 fractions (Varian Eclipse v13.7), assuming an RBE of 1.1. Plans were recalculated using Monte-Carlo (Geant4 v10.3.3/Gate v8.1) to calculate dose-averaged LET. Variable RBE-weighted dose was calculated using the McNamara model, assuming an α/ß ratio of 2 Gy for organs-at-risk. Results: Although the LET decreased as the number of fields increased, the difference in RBE-weighted dose (Δdose) to organs-at-risk did not consistently decrease. Δdose values varied by patient and organ and were mostly of the order of 0-3 Gy (RBE), with a worst-case of 4.75 Gy (RBE) in near-maximum dose to the left atrium for one plan. Conclusions: RBE-weighted doses to organs-at-risk are sensitive to the choice of RBE model, which is of particular concern for the heart. Advances in knowledge: There is a need to remain cautious when evaluating proton plans for Hodgkin lymphoma, especially when near-maximum doses to organs-at-risk are considered.

Proposing a Clinical Model for RBE Based on Proton Track-End Counts.

PURPOSE: In proton therapy, the clinical application of linear energy transfer (LET) optimization remains contentious, in part because of challenges associated with the definition and calculation of LET and its exact relationship with relative biological effectiveness (RBE) because of large variation in experimental in vitro data. This has raised interest in other metrics with favorable properties for biological optimization, such as the number of proton track ends in a voxel. In this work, we propose a novel model for clinical calculations of RBE, based on proton track end counts. METHODS AND MATERIALS: We developed an effective dose concept to translate between the total proton track-end count per unit mass in a voxel and a proton RBE value. Dose, track end, and dose-averaged LET (LETd) distributions were simulated using Monte Carlo models for a series of water phantoms, in vitro radiobiological studies, and patient treatment plans. We evaluated the correlation between track ends and regions of elevated biological effectiveness in comparison to LETd-based models of RBE. RESULTS: Track ends were found to correlate with biological effects in in vitro experiments with an accuracy comparable to LETd. In patient simulations, our track end model identified the same biological hotspots as predicted by LETd-based radiobiological models of proton RBE. CONCLUSIONS: These results suggest that, for clinical optimization and evaluation, an RBE model based on proton track end counts may match LETd-based models in terms of information provided while also offering superior statistical properties.

A computational approach to quantifying miscounting of radiation-induced double-strand break immunofluorescent foci.

Immunofluorescent tagging of DNA double-strand break (DSB) markers, such as γ-H2AX and other DSB repair proteins, are powerful tools in understanding biological consequences following irradiation. However, whilst the technique is widespread, there are many uncertainties related to its ability to resolve and reliably deduce the number of foci when counting using microscopy. We present a new tool for simulating radiation-induced foci in order to evaluate microscope performance within in silico immunofluorescent images. Simulations of the DSB distributions were generated using Monte Carlo track-structure simulation. For each DSB distribution, a corresponding DNA repair process was modelled and the un-repaired DSBs were recorded at several time points. Corresponding microscopy images for both a DSB and (γ-H2AX) fluorescent marker were generated and compared for different microscopes, radiation types and doses. Statistically significant differences in miscounting were found across most of the tested scenarios. These inconsistencies were propagated through to repair kinetics where there was a perceived change between radiation-types. These changes did not reflect the underlying repair rate and were caused by inconsistencies in foci counting. We conclude that these underlying uncertainties must be considered when analysing images of DNA damage markers to ensure differences observed are real and are not caused by non-systematic miscounting.

Estimating the percentage of patients who might benefit from proton beam therapy instead of X-ray radiotherapy.

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.

A Monte Carlo study of different LET definitions and calculation parameters for proton beam therapy.

The strongin vitroevidence 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 (LETdto water, to medium and to mass density); (iii) particle inclusion (LETdto 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 LETdfor all particles and maximum LETdfor all protons within the brainstem in the high isodose region (4 keVµm-1and 8 keVµm-1respectively). An RBE model using LETdincluding 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.

Hi-C implementation of genome structure for in silico models of radiation-induced DNA damage.

Developments in the genome organisation field has resulted in the recent methodology to infer spatial conformations of the genome directly from experimentally measured genome contacts (Hi-C data). This provides a detailed description of both intra- and inter-chromosomal arrangements. Chromosomal intermingling is an important driver for radiation-induced DNA mis-repair. Which is a key biological endpoint of relevance to the fields of cancer therapy (radiotherapy), public health (biodosimetry) and space travel. For the first time, we leverage these methods of inferring genome organisation and couple them to nano-dosimetric radiation track structure modelling to predict quantities and distribution of DNA damage within cell-type specific geometries. These nano-dosimetric simulations are highly dependent on geometry and are benefited from the inclusion of experimentally driven chromosome conformations. We show how the changes in Hi-C contract maps impact the inferred geometries resulting in significant differences in chromosomal intermingling. We demonstrate how these differences propagate through to significant changes in the distribution of DNA damage throughout the cell nucleus, suggesting implications for DNA repair fidelity and subsequent cell fate. We suggest that differences in the geometric clustering for the chromosomes between the cell-types are a plausible factor leading to changes in cellular radiosensitivity. Furthermore, we investigate changes in cell shape, such as flattening, and show that this greatly impacts the distribution of DNA damage. This should be considered when comparing in vitro results to in vivo systems. The effect may be especially important when attempting to translate radiosensitivity measurements at the experimental in vitro level to the patient or human level.

Full 3D position reconstruction of a radioactive source based on a novel hyperbolic geometrical algorithm.

A new method to locate, with millimetre uncertainty, in 3D, a γ -ray source emitting multiple γ -rays in a cascade, employing conventional LaBr3(Ce) scintillation detectors, has been developed. Using 16 detectors in a symmetrical configuration the detector energy and time signals, resulting from the γ -ray interactions, are fed into a new source position reconstruction algorithm. The Monte-Carlo based Geant4 framework has been used to simulate the detector array and a 60Co source located at two positions within the spectrometer central volume. For a source located at (0,0,0) the algorithm reports X, Y, Z values of -0.3 ± 2.5, -0.4 ± 2.4, and -0.6 ± 2.5 mm, respectively. For a source located at (20,20,20) mm, with respect to the array centre, the algorithm reports X, Y, Z values of 20.2 ± 1.0, 20.2 ± 0.9, and 20.1 ± 1.2 mm. The resulting precision of the reconstruction means that this technique could find application in a number of areas including nuclear medicine, national security, radioactive waste assay and proton beam therapy.

Automated Monte-Carlo re-calculation of proton therapy plans using Geant4/Gate: implementation and comparison to plan-specific quality assurance measurements.

OBJECTIVES: Software re-calculation of proton pencil beam scanning plans provides a method of verifying treatment planning system (TPS) dose calculations prior to patient treatment. This study describes the implementation of AutoMC, a Geant4 v10.3.3/Gate v8.1 (Gate-RTion v1.0)-based Monte-Carlo (MC) system for automated plan re-calculation, and presents verification results for 153 patients (730 fields) planned within year one of the proton service at The Christie NHS Foundation Trust. METHODS: A MC beam model for a Varian ProBeam delivery system with four range-shifter options (none, 2 cm, 3 cm, 5 cm) was derived from beam commissioning data and implemented in AutoMC. MC and TPS (Varian Eclipse v13.7) calculations of 730 fields in solid-water were compared to physical plan-specific quality assurance (PSQA) measurements acquired using a PTW Octavius 1500XDR array and PTW 31021 Semiflex 3D ion chamber. RESULTS: TPS and MC showed good agreement with array measurements, evaluated using γ analyses at 3%, 3 mm with a 10% lower dose threshold:>94% of fields calculated by the TPS and >99% of fields calculated by MC had γ ≤ 1 for>95% of measurement points within the plane. TPS and MC also showed good agreement with chamber measurements of absolute dose, with systematic differences of <1.5% for all range-shifter options. CONCLUSIONS: Reliable independent verification of the TPS dose calculation is a valuable complement to physical PSQA and may facilitate reduction of the physical PSQA workload alongside a thorough delivery system quality assurance programme. ADVANCES IN KNOWLEDGE: A Gate/Geant4-based MC system is thoroughly validated against an extensive physical PSQA dataset for 730 clinical fields, showing that clinical implementation of MC for PSQA is feasible.

Pitfalls in the beam modelling process of Monte Carlo calculations for proton pencil beam scanning.

OBJECTIVE: Monte Carlo (MC) simulations substantially improve the accuracy of predicted doses. This study aims to determine and quantify the uncertainties of setting up such a MC system. METHODS: Doses simulated with two Geant4-based MC calculation codes, but independently tuned to the same beam data, have been compared. Different methods of MC modelling of a pre-absorber have been employed, either modifying the beam source parameters (descriptive) or adding the pre-absorber as a physical component (physical). RESULTS: After the independent beam modelling of both systems in water (resulting in excellent range agreement) range differences of up to 3.6/4.8 mm (1.5% of total range) in bone/brain-like tissues were found, which resulted from the use of different mean water ionisation potentials during the energy tuning process. When repeating using a common definition of water, ranges in bone/brain agreed within 0.1 mm and gamma-analysis (global 1%,1mm) showed excellent agreement (>93%) for all patient fields. However, due to a lack of modelling of proton fluence loss in the descriptive pre-absorber, differences of 7% in absolute dose between the pre-absorber definitions were found. CONCLUSION: This study quantifies the influence of using different water ionisation potentials during the MC beam modelling process. Furthermore, when using a descriptive pre-absorber model, additional Faraday cup or ionisation chamber measurements with pre-absorber are necessary. ADVANCES IN KNOWLEDGE: This is the first study quantifying the uncertainties caused by the MC beam modelling process for proton pencil beam scanning, and a more detailed beam modelling process for MC simulations is proposed to minimise the influence of critical parameters.

Proton beam therapy: perspectives on the National Health Service England clinical service and research programme.

The UK has an important role in the evaluation of proton beam therapy (PBT) and takes its place on the world stage with the opening of the first National Health Service (NHS) PBT centre in Manchester in 2018, and the second in London coming in 2020. Systematic evaluation of the role of PBT is a key objective. By September 2019, 108 patients had started treatment, 60 paediatric, 19 teenagers and young adults and 29 adults. Obtaining robust outcome data is vital, if we are to understand the strengths and weaknesses of current treatment approaches. This is important in demonstrating when PBT will provide an advantage and when it will not, and in quantifying the magnitude of benefit.The UK also has an important part to play in translational PBT research, and building a research capability has always been the vision. We are perfectly placed to perform translational pre-clinical biological and physical experiments in the dedicated research room in Manchester. The nature of DNA damage from proton irradiation is considerably different from X-rays and this needs to be more fully explored. A better understanding is needed of the relative biological effectiveness (RBE) of protons, especially at the end of the Bragg peak, and of the effects on tumour and normal tissue of PBT combined with conventional chemotherapy, targeted drugs and immunomodulatory agents. These experiments can be enhanced by deterministic mathematical models of the molecular and cellular processes of DNA damage response. The fashion of ultra-high dose rate FLASH irradiation also needs to be explored.

Insights into the non-homologous end joining pathway and double strand break end mobility provided by mechanistic in silico modelling.

After radiation exposure, one of the critical processes for cellular survival is the repair of DNA double strand breaks. The pathways involved in this response are complex in nature and involve many individual steps that act across different time scales, all of which combine to produce an overall behaviour. It is therefore experimentally challenging to unambiguously determine the mechanisms involved and how they interact whilst maintaining strict control of all confounding variables. In silico methods can provide further insight into results produced by focused experimental investigations through testing of the hypotheses generated. Such computational testing can asses competing hypotheses by investigating their effects across all time scales concurrently, highlighting areas where further experimental work can have the most significance. We describe the construction of a mechanistic model by combination of several hypothesised mechanisms reported in the literature and supported by experiment. Compatibility of these mechanisms was tested by fitting simulation to results reported in the literature. To avoid over-fitting, we used an approach of sequentially testing individual mechanisms within this pathway. We demonstrate that using this approach the model is capable of reproducing published protein kinetics and overall repair trends. This provides evidence supporting the feasibility of the proposed mechanisms and revealed how they interact to produce an overall behaviour. Furthermore, we show that the assumed motion of individual double strand break ends plays a crucial role in determining overall system behaviour.

A New Method to Reconstruct in 3D the Emission Position of the Prompt Gamma Rays following Proton Beam Irradiation.

A new technique for range verification in proton beam therapy has been developed. It is based on the detection of the prompt γ rays that are emitted naturally during the delivery of the treatment. A spectrometer comprising 16 LaBr3(Ce) detectors in a symmetrical configuration is employed to record the prompt γ rays emitted along the proton path. An algorithm has been developed that takes as inputs the LaBr3(Ce) detector signals and reconstructs the maximum γ-ray intensity peak position, in full 3 dimensions. For a spectrometer radius of 8 cm, which could accommodate a paediatric head and neck case, the prompt γ-ray origin can be determined from the width of the detected peak with a σ of 4.17 mm for a 180 MeV proton beam impinging a water phantom. For spectrometer radii of 15 and 25 cm to accommodate larger volumes this value increases to 5.65 and 6.36 mm. For a 8 cm radius, with a 5 and 10 mm undershoot, the σ is 4.31 and 5.47 mm. These uncertainties are comparable to the range uncertainties incorporated in treatment planning. This work represents the first step towards a new accurate, real-time, 3D range verification device for spot-scanning proton beam therapy.

Assessing MR-linac radiotherapy robustness for anatomical changes in head and neck cancer.

The MR-Linac will provide excellent soft tissue contrast for on-treatment imaging. It is well known that the electron return effect (ERE) results in areas of increased and decreased dose at air/tissue boundaries, which can be compensated for in plan optimisation. However, anatomical changes may affect the quality of this compensation. In this paper we aim to quantify the interaction of anatomical changes with ERE in head and neck (H&N) cancer patients. Twenty patients treated with either 66 Gy or 60 Gy in 30 fractions were selected. Ten had significant weight-loss during treatment requiring repeat CT (rCT) and ten had PTVs close to the sinus cavity. Plans were optimised using Monaco to meet the departmental dose constraints and copied to the rCT and re-calculated. For the sinus patients, we optimised plans with full and empty sinus at both 0 T and 1.5 T. The effect of the opposite filling state was next evaluated. No clinically relevant difference between the doses in the PTV and OARs were observed related to weight-loss in 0 T or 1.5 T fields. Variable sinus filling caused greater dosimetric differences near the walls of the sinus for plans optimised with a full cavity in 1.5 T, indicating that optimising with an empty sinus makes the plan more robust to changes in filling. These findings indicate that current off-line strategies for adaptive planning for H&N patients are also valid on an MR-linac, if care is taken with sinus filling.

Modelling direct DNA damage for gold nanoparticle enhanced proton therapy.

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.

A robust optimisation approach accounting for the effect of fractionation on setup uncertainties.

Proton plans are subject to a number of uncertainties which must be accounted for to ensure that they are delivered safely. Misalignment resulting from residual errors in daily patient positioning can result in both a displacement and distortion of dose distributions. This can be particularly important for intensity modulated proton therapy treatments where the accurate alignment of highly modulated fields may be required to deliver the intended treatment. A number of methods to generate plans that are robust to these uncertainties exist. These include robust optimisation approaches which account for the effect of uncertainties on the dose distribution within the optimisation process. However, robustness to uncertainty comes at the cost of plan quality. For this reason, it is important that the uncertainties considered are realistic. Existing approaches to robust optimisation have neglected the role of fractionated treatment deliveries in reducing the uncertainties that result from random setup errors. Here, a method of robust optimisation which accounts for this effect is presented and is evaluated using a 2D planning environment. The optimisation algorithm considers the dose in the estimated upper and lower bounds of the dose distribution under the effect of setup and range errors. A comparison with plans robustly optimised without consideration of the effect of fractionation and conventionally optimised plans is presented. Fractionation incorporated robust optimisation demonstrates a reduced sensitivity to uncertainty compared to conventionally optimised plans and a reduced integral dose compared to robustly optimised plans.

An automated workflow for patient-specific quality control of contour propagation.

Contour propagation is an essential component of adaptive radiotherapy, but current contour propagation algorithms are not yet sufficiently accurate to be used without manual supervision. Manual review of propagated contours is time-consuming, making routine implementation of real-time adaptive radiotherapy unrealistic. Automated methods of monitoring the performance of contour propagation algorithms are therefore required. We have developed an automated workflow for patient-specific quality control of contour propagation and validated it on a cohort of head and neck patients, on which parotids were outlined by two observers. Two types of error were simulated-mislabelling of contours and introducing noise in the scans before propagation. The ability of the workflow to correctly predict the occurrence of errors was tested, taking both sets of observer contours as ground truth, using receiver operator characteristic analysis. The area under the curve was 0.90 and 0.85 for the observers, indicating good ability to predict the occurrence of errors. This tool could potentially be used to identify propagated contours that are likely to be incorrect, acting as a flag for manual review of these contours. This would make contour propagation more efficient, facilitating the routine implementation of adaptive radiotherapy.

The suitability of common metrics for assessing parotid and larynx autosegmentation accuracy.

Contouring structures in the head and neck is time-consuming, and automatic seg-mentation is an important part of an adaptive radiotherapy workflow. Geometric accuracy of automatic segmentation algorithms has been widely reported, but there is no consensus as to which metrics provide clinically meaningful results. This study investigated whether geometric accuracy (as quantified by several commonly used metrics) was associated with dosimetric differences for the parotid and larynx, comparing automatically generated contours against manually drawn ground truth contours. This enabled the suitability of different commonly used metrics to be assessed for measuring automatic segmentation accuracy of the parotid and larynx. Parotid and larynx structures for 10 head and neck patients were outlined by five clinicians to create ground truth structures. An automatic segmentation algorithm was used to create automatically generated normal structures, which were then used to create volumetric-modulated arc therapy plans. The mean doses to the automatically generated structures were compared with those of the corresponding ground truth structures, and the relative difference in mean dose was calculated for each structure. It was found that this difference did not correlate with the geometric accuracy provided by several metrics, notably the Dice similarity coefficient, which is a commonly used measure of spatial overlap. Surface-based metrics provided stronger correlation and are, therefore, more suitable for assessing automatic seg-mentation of the parotid and larynx.

A Monte Carlo study on the collimation of pencil beam scanning proton therapy beams.

PURPOSE: The lateral edge of a proton therapy beam is commonly used to achieve conformality to the treatment volume where critical structures reside close to the target. However, when treating shallow depths, the lateral edge of a pencil beam scanning (PBS) system may be broader than that of a double scattered (DS) system. Use of a range-shifter to degrade the beam and allow treatment of very shallow depths further blurs the lateral edge. The authors investigate the potential use of a collimator with a PBS system for delivery of 3D uniform dose-volumes to a water-tank phantom, identifying the key factors controlling the width of the lateral edge. METHODS: The geant4 application for tomographic emission (gate) Monte Carlo (MC) environment was used, following validation against previously published data. Key parameters for PBS beams were investigated to assess their impact on the lateral edge of both monoenergetic beams and uniform dose-volumes. These parameters included nozzle-to-surface distance (NSD), vacuum window-to-surface distance (VSD), use of a range-shifter, and spot optimization parameters. RESULTS: The lateral edge of an uncollimated PBS beam is particularly sensitive to VSD and NSD. While use of a range-shifter blurs the lateral edge, collimation allows the edge to be sharpened to between 2 and 4 mm depending on the depth of the target. Optimization of the spot weightings alone can provide a penumbral width close to that of a single spot, but also leads to poorer uniformity near the edge of the target volume. CONCLUSIONS: Collimation of PBS beams should be considered for superficial targets particularly for beams delivered through a range-shifter, since the resultant sharpening of the lateral edge will allow improved sparing of adjacent normal tissues. Further work is needed to develop collimators which are integrated into both nozzle designs and planning system optimization algorithms.

Incorporating the effect of fractionation in the evaluation of proton plan robustness to setup errors.

To ensure the safe delivery of proton therapy treatments it is important to evaluate the effect of potential uncertainties, such as patient mispositioning, on the intended dose distribution. However, it can be expected that the uncertainty resulting from patient positioning is reduced in a fractionated treatment due to the convergence of random variables with the delivery of repeated treatments. This is neglected by current approaches to robustness analysis resulting in an overly conservative assessment of the robustness which can lead to sub-optimal plans. Here, a fast method of accounting for this reduced uncertainty is presented. An estimated bound to the error in the dose distribution resulting from setup uncertainty over a specified number of fractions is calculated by considering the distribution of values for each voxel across 14 initial error scenarios. The bound on the error in a given voxel is estimated using a 99.9% confidence limit assuming a convergence towards a normal distribution in line with the central limit theorem, and a correction of [Formula: see text] accounting for the reduction in the standard deviation over n fractions. The proposed method was validated in 5 patients by comparison to Monte Carlo simulations of 300 treatment courses. A voxelwise and volumetric analysis of the estimated and simulated bounds to the uncertainty in the dose distribution demonstrate that the proposed technique can be used to assess proton plan robustness more accurately allowing for less conservative treatment plans.

Simulation of realistic linac motion improves the accuracy of a Monte Carlo based VMAT plan QA system.

PURPOSE: To investigate the use of a software-based pre-treatment QA system for VMAT, which incorporates realistic linac motion during delivery. METHODS: A beam model was produced using the GATE platform for GEANT4 Monte Carlo dose calculations. Initially validated against static measurements, the model was then integrated with a VMAT delivery emulator, which reads plan files and generates a set of dynamic delivery instructions analogous to the linac control system. Monte Carlo simulations were compared to measurements on dosimetric phantoms for prostate and head and neck VMAT plans. Comparisons were made between calculations using fixed control points, and simulations of continuous motion utilising the emulator. For routine use, the model was incorporated into an automated pre-treatment QA system. RESULTS: The model showed better agreement with measurements when incorporating linac motion: mean gamma pass (Γ<1) over 5 prostate plans was 100.0% at 3%/3mm and 97.4% at 2%/2mm when compared to measurement. For the head and neck plans, delivered to the anatomical phantom, gamma passes were 99.4% at 4%/4mm and 94.94% at 3%/3mm. For example simulations within patient CT data, gamma passes were observed which are within our centre's tolerance for pre-treatment QA. CONCLUSIONS: Through comparison to phantom measurements, it was found that the incorporation of a realistic linac motion improves the accuracy of the model compared to the simulation of fixed control points. The ability to accurately calculate dose as a second check of the planning system, and determine realistic delivery characteristics, may allow for the reduction of machine-based pre-treatment plan QA for VMAT.