Adam H Aitkenhead

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.

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.

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 centres 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.

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

Contouring structures in the head and neck is time-consuming, and automatic segmentation 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 segmentation of the parotid and larynx. PACS number(s): 87.57.nm, 87.55.D, 87.55.Qr.Contouring structures in the head and neck is time‐consuming, and automatic segmentation 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 segmentation of the parotid and larynx. PACS number(s): 87.57.nm, 87.55.D, 87.55.Qr

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.

Parametrized rectal dose and associations with late toxicity in prostate cancer radiotherapy

OBJECTIVE We investigated possible associations between planned dose-volume parameters and rectal late toxicity in 170 patients having radical prostate cancer radiotherapy. METHODS For each patient, the rectum was outlined from anorectal junction to sigmoid colon, and rectal dose was parametrized using dose-volume (DVH), dose-surface (DSH) and dose-line (DLH) histograms. Generation of DLHs differed from previous studies in that the rectal dose was parametrized without first unwrapping onto 2-dimensional dose-surface maps. Patient-reported outcomes were collected using a validated Later Effects in Normal Tissues Subjective, Objective, Management and Analytic questionnaire. Associations between dose and toxicity were assessed using a one-sided Mann-Whitney U test. RESULTS Associations (p < 0.05) were found between equieffective dose (EQD23) and late toxicity as follows: overall toxicity with DVH and DSH at 13-24 Gy; proctitis with DVH and DSH at 25-36 Gy and with DVH, DSH and DLH at 61-67 Gy; bowel urgency with DVH and DSH at 10-20 Gy. None of these associations met statistical significance following the application of a Bonferroni correction. CONCLUSION Independently confirmed associations between rectal dose and late toxicity remain elusive. Future work to increase the accuracy of the knowledge of the rectal dose, either by accounting for interfraction and intrafraction rectal motion or via stabilization of the rectum during treatment, may be necessary to allow for improved dose-toxicity comparisons. ADVANCES IN KNOWLEDGE This study is the first to use parametrized DLHs to study associations with patient-reported toxicity for prostate radiotherapy showing that it is feasible to model rectal dose mapping in three dimensions.

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.

Validating a Monte Carlo approach to absolute dose quality assurance for proton pencil beam scanning.

For radiotherapy, it is crucial to guarantee that the delivered dose matches the planned dose. Therefore, patient specific quality assurance (QA) of absolute dose distributions is necessary. Here, we investigate the potential of replacing patient specific QA for pencil beam scanned proton therapy with Monte Carlo simulations. First, the set-up of the automated Monte Carlo model is presented with an emphasis on the absolute dose validation. Second, the absolute dose results obtained from the Monte Carlo simulation for a comprehensive set of patient fields are compared to patient specific QA measurements. Absolute doses measured with the Farmer chamber are shown to be 1.4% higher than the doses measured with the Semiflex chamber. For single energy layers, Monte Carlo simulated doses are 2.1%  ±  0.4% lower than the ones measured with the ionization chamber and 1.1%  ±  1.0% lower than measurements compared to patient field verification measurements. After rescaling to account for this 1.1% discrepancy, 98 fields (94.2%) agree within 2% to measurements, the maximum difference being 2.3%. In conclusion, an automated, easy-to-use Monte Carlo calculation system has been set up. This system reproduced patient specific QA results over a wide range of cases, showing that the time consuming measurements could be reduced or even replaced using Monte Carlo simulations without jeopardizing treatment quality.

Evaluation of a 3D diamond detector for medical radiation dosimetry

Synthetic diamond has several properties that are particularly suited to applications in medical radiation dosimetry. It is tissue equivalent, not toxic and shows a high resistance to radiation damage, low leakage current and stability of response. It is an electrical insulator, robust and realizable in small size; due to these features there are several examples of diamond devices, mainly planar single-crystalline chemical vapor depositation (sCVD) diamond, used for relative dose measurement in photon beams. Thanks to a new emerging technology, diamond devices with 3-dimensional structures are produced by using laser pulses to create graphitic paths in the diamond bulk. The necessary bias voltage to operate such detector decreases considerably while the signal response and radiation resistance increase. In order to evaluate the suitability of this new technology for measuring the dose delivered by radiotherapy beams in oncology a 3D polycrystalline (pCVD) diamond detector designed for single charged particle detection has been tested and the photon beam profile has been studied. The good linearity and high sensitivity to the dose observed in the 3D diamond, opens the way to the possibility of realizing a finely segmented device with the potential for dose distribution measurement in a single exposure for small field dosimetry that nowadays is still extremely challenging.

EP-1583: An automated Monte Carlo plan verification system for spot-scanning proton therapy

Material and Methods: Realistic clinical beam models were developed by matching simulations (using GATE/GEANT4) to measurements made in a clinical beamline. They consist of a tuned physics list, a lookup table relating each of the 115 nominal beam energies to a tuned spot energy (mean and standard deviation) and phase space parameters which allow spot sizes to be properly modeled for any combination of energy and nozzle extension. For all beam energies simulations accurately reproduce both integral depth dose profiles (>97% of data-points pass a local gamma analysis at 2%/2mm) and lateral profiles measured in air and in solid water (with a 0.2 mm maximum difference). The model was further validated against a series of simple test plans which were optimized in the clinical Treatment Planning System (TPS) to produce uniform dose volumes at various depths in water.The automated MC system can process, simulate and analyse treatment plans without user input once it receives the TPS files.