Factors influencing the performance of patient specific quality assurance for pencil beam scanning IMPT fields

Yet anOther Dose Algorithm (YODA) for independent computations of dose and dose changes due to anatomical changes

Objective.To assess the viability of a physics-based, deterministic and adjoint-capable algorithm for performing treatment planning system independent dose calculations and for computing dosimetric differences caused by anatomical changes.Approach.A semi-numerical approach is employed to solve two partial differential equations for the proton phase-space density which determines the deposited dose. Lateral hetereogeneities are accounted for by an optimized (Gaussian) beam splitting scheme. Adjoint theory is applied to approximate the change in the deposited dose caused by a new underlying patient anatomy.Main results.The dose engine's accuracy was benchmarked through three-dimensional gamma index comparisons against Monte Carlo simulations done in TOPAS. For a lung test case, the worst passing rate with (1 mm, 1%, 10% dose cut-off) criteria is 94.55%. The effect of delivering treatment plans on repeat CTs was also tested. For non-robustly optimized plans the adjoint component was accurate to 5.7% while for a robustly optimized plan it was accurate to 4.8%.Significance.Yet anOther Dose Algorithm is capable of accurate dose computations in both single and multi spot irradiations when compared to TOPAS. Moreover, it is able to compute dosimetric differences due to anatomical changes with small to moderate errors thereby facilitating its use for patient-specific quality assurance in online adaptive proton therapy.

Proton 3D dose measurement with a multi-layer strip ionization chamber (MLSIC) device

Objective. In current clinical practice for quality assurance (QA), intensity modulated proton therapy (IMPT) fields are verified by measuring planar dose distributions at one or a few selected depths in a phantom. A QA device that measures full 3D dose distributions at high spatiotemporal resolution would be highly beneficial for existing as well as emerging proton therapy techniques such as FLASH radiotherapy. Our objective is to demonstrate feasibility of 3D dose measurement for IMPT fields using a dedicated multi-layer strip ionization chamber (MLSIC) device.Approach.Our developed MLSIC comprises a total of 66 layers of strip ion chamber (IC) plates arranged, alternatively, in thexandydirection. The first two layers each has 128 channels in 2 mm spacing, and the following 64 layers each has 32/33 IC strips in 8 mm spacing which are interconnected every eight channels. A total of 768-channel IC signals are integrated and sampled at a speed of 6 kfps. The MLSIC has a total of 19.2 cm water equivalent thickness and is capable of measurement over a 25 × 25 cm2field size. A reconstruction algorithm is developed to reconstruct 3D dose distribution for each spot at all depths by considering a double-Gaussian-Cauchy-Lorentz model. The 3D dose distribution of each beam is obtained by summing all spots. The performance of our MLSIC is evaluated for a clinical pencil beam scanning (PBS) plan.Main results.The dose distributions for each proton spot can be successfully reconstructed from the ionization current measurement of the strip ICs at different depths, which can be further summed up to a 3D dose distribution for the beam. 3D Gamma Index analysis indicates acceptable agreement between the measured and expected dose distributions from simulation, Zebra and MatriXX.Significance.The dedicated MLSIC is the first pseudo-3D QA device that can measure 3D dose distribution in PBS proton fields spot-by-spot.

Evaluation of monte carlo to support commissioning of the treatment planning system of new pencil beam scanning proton therapy facilities

Objective. To demonstrate the potential of Monte Carlo (MC) to support the resource-intensive measurements that comprise the commissioning of the treatment planning system (TPS) of new proton therapy facilities.Approach. Beam models of a pencil beam scanning system (Varian ProBeam) were developed in GATE (v8.2), Eclipse proton convolution superposition algorithm (v16.1, Varian Medical Systems) and RayStation MC (v12.0.100.0, RaySearch Laboratories), using the beam commissioning data. All models were first benchmarked against the same commissioning data and validated on seven spread-out Bragg peak (SOBP) plans. Then, we explored the use of MC to optimise dose calculation parameters, fully understand the performance and limitations of TPS in homogeneous fields and support the development of patient-specific quality assurance (PSQA) processes. We compared the dose calculations of the TPSs against measurements (DDTPSvs.Meas.) or GATE (DDTPSvs.GATE) for an extensive set of plans of varying complexity. This included homogeneous plans with varying field-size, range, width, and range-shifters (RSs) (n= 46) and PSQA plans for different anatomical sites (n= 11).Main results. The three beam models showed good agreement against the commissioning data, and dose differences of 3.5% and 5% were found for SOBP plans without and with RSs, respectively. DDTPSvs.Meas.and DDTPSvs.GATEwere correlated in most scenarios. In homogeneous fields the Pearson's correlation coefficient was 0.92 and 0.68 for Eclipse and RayStation, respectively. The standard deviation of the differences between GATE and measurements (±0.5% for homogeneous and ±0.8% for PSQA plans) was applied as tolerance when comparing TPSs with GATE. 72% and 60% of the plans were within the GATE predicted dose difference for both TPSs, for homogeneous and PSQA cases, respectively.Significance. Developing and validating a MC beam model early on into the commissioning of new proton therapy facilities can support the validation of the TPS and facilitate comprehensive investigation of its capabilities and limitations.

A multi-layer strip ionization chamber (MLSIC) device for proton pencil beam scan quality assurance

Objective. Proton pencil beam scanning (PBS) treatment fields needs to be verified before treatment deliveries to ensure patient safety. In current practice, treatment beam quality assurance (QA) is measured at a few selected depths using film or a 2D detector array, which is insensitive and time-consuming. A QA device that can measure all key dosimetric characteristics of treatment beams spot-by-spot within a single beam delivery is highly desired.Approach. We developed a multi-layer strip ionization chamber (MLSIC) prototype device that comprises of two layers of strip ionization chambers (IC) plates for spot position measurement and 64 layers of plate IC for beam energy measurement. The 768-channel strip ion chamber signals are integrated and sampled at a speed of 3.125 kHz. It has a 25.6 cm × 25.6 cm maximum measurement field size and 2 mm spatial resolution for spot position measurement. The depth resolution and maximum depth were 2.91 mm and 18.6 cm for 1.6 mm thick IC plate, respectively. The relative weight of each spot was determined from total charge by all IC detector channels.Main results. The MLSIC is able to measure ionization currents spot-by-spot. The depth dose measurement has a good agreement with the ground truth measured using a water tank and commercial one-dimensional (1D) multi-layer plate chamber. It can verify the spot position, energy, and relative weight of clinical PBS beams and compared with the treatment plans.Significance. The MLSIC is a highly efficient QA device that can measure the key dosimetric characteristics of proton treatment beams spot-by-spot with a single beam delivery. It may improve the quality and efficiency of clinical proton treatments.

The root cause analysis on failed patient-specific measurements of pencil beam scanning protons using a 2D detection array with finite size ionization chambers

The aim of this report is to present the root cause analysis on failed patient‐specific quality assurance (QA) measurements of pencil beam scanning (PBS) protons; referred to as PBS‐QA measurement. A criterion to fail a PBS‐QA measurement is having a <95% passing rate in a 3.0%‐3.0 mm gamma index analysis. Clinically, we use a two‐dimensional (2D) gamma index analysis to obtain the passing rate. The IBA MatriXX PT 2D detection array with finite size ionization chamber was utilized. A total of 2488 measurements performed in our PBS beamline were cataloged. The percentage of measurements for the sites of head/neck, breast, prostate, and other are 53.3%, 22.7%, 10.5%, and 13.5%, respectively. The measurements with a passing rate of 100 to >94%, 94 to >88%, and <88% were 93.6%, 5.6%, and 0.8%, respectively. The percentage of failed measurements with a <95% passing rate was 10.9%. After removed the user errors of either re‐measurement or re‐analysis, 8.1% became acceptable. We observed a feature of >3% per mm dose gradient with respect to depth on the failed measurements. We utilized a 2D/three‐dimensional (3D) gamma index analysis toolkit to investigate the effect of depth dose gradient. By utilizing this 3D toolkit, 43.1% of the failed measurements were improved. A feature among measurements that remained sub‐optimal after re‐analysis was a sharp >3% per mm lateral dose gradient that may not be well handled using the detector size of 5.0 mm in‐diameter. An analysis of the sampling of finite size detectors using one‐dimensional (1D) error function showed a large dose deviation at locations of low‐dose areas between two high‐dose plateaus. User error, large depth dose gradient, and the effect of detector size are identified as root causes. With the mitigation of the root causes, the goals of patient‐specific QA, specifically detecting actual deviation of beam delivery or identifying limitations of the dose calculation algorithm of the treatment planning system, can be directly related to failure of the PBS‐QA measurements.

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.

Evaluation of GATE-RTion (GATE/Geant4) Monte Carlo simulation settings for proton pencil beam scanning quality assurance

PURPOSE

Geant4 is a multi-purpose Monte Carlo simulation tool for modeling particle transport in matter. It provides a wide range of settings, which the user may optimize for their specific application. This study investigates GATE/Geant4 parameter settings for proton pencil beam scanning therapy.

METHODS

GATE8.1/Geant4.10.3.p03 (matching the versions used in GATE-RTion1.0) simulations were performed with a set of prebuilt Geant4 physics lists (QGSP_BIC, QGSP_BIC_EMY, QGSP_BIC_EMZ, QGSP_BIC_HP_EMZ), using 0.1mm-10mm as production cuts on secondary particles (electrons, photons, positrons) and varying the maximum step size of protons (0.1mm, 1mm, none). The results of the simulations were compared to measurement data taken during clinical patient specific quality assurance at The Christie NHS Foundation Trust pencil beam scanning proton therapy facility. Additionally, the influence of simulation settings was quantified in a realistic patient anatomy based on computer tomography (CT) scans.

RESULTS

When comparing the different physics lists, only the results (ranges in water) obtained with QGSP_BIC (G4EMStandardPhysics_Option0) depend on the maximum step size. There is clinically negligible difference in the target region when using High Precision neutron models (HP) for dose calculations. The EMZ electromagnetic constructor provides a closer agreement (within 0.35 mm) to measured beam sizes in air, but yields up to 20% longer execution times compared to the EMY electromagnetic constructor (maximum beam size difference 0.79 mm). The impact of this on patient-specific quality assurance simulations is clinically negligible, with a 97% average 2%/2 mm gamma pass rate for both physics lists. However, when considering the CT-based patient model, dose deviations up to 2.4% are observed. Production cuts do not substantially influence dosimetric results in solid water, but lead to dose differences of up to 4.1% in the patient CT. Small (compared to voxel size) production cuts increase execution times by factors of 5 (solid water) and 2 (patient CT).

CONCLUSIONS

Taking both efficiency and dose accuracy into account and considering voxel sizes with 2 mm linear size, the authors recommend the following Geant4 settings to simulate patient specific quality assurance measurements: No step limiter on proton tracks; production cuts of 1 mm for electrons, photons and positrons (in the phantom and range-shifter) and 10 mm (world); best agreement to measurement data was found for QGSP_BIC_EMZ reference physics list at the cost of 20% increased execution times compared to QGSP_BIC_EMY. For simulations considering the patient CT model, the following settings are recommended: No step limiter on proton tracks; production cuts of 1 mm for electrons, photons and positrons (phantom/range-shifter) and 10 mm (world) if the goal is to achieve sufficient dosimetric accuracy to ensure that a plan is clinically safe; or 0.1 mm (phantom/range-shifter) and 1 mm (world) if higher dosimetric accuracy is needed (increasing execution times by a factor of 2); most accurate results expected for QGSP_BIC_EMZ reference physics list, at the cost of 10-20% increased execution times compared to QGSP_BIC_EMY.

Shortening delivery times for intensity-modulated proton therapy by reducing the number of proton spots: an experimental verification

Delivery times of intensity-modulated proton therapy (IMPT) can be shortened by reducing the number of spots in the treatment plan, but this may affect clinical plan delivery. Here, we assess the experimental deliverability, accuracy and time reduction of spot-reduced treatment planning for a clinical case, as well as its robustness. For a single head-and-neck cancer patient, a spot-reduced plan was generated and compared with the conventional clinical plan. The number of proton spots was reduced using the iterative 'pencil beam resampling' technique. This involves repeated inverse optimization, while adding in each iteration a small sample of randomly selected spots and subsequently excluding low-weighted spots until plan quality deteriorates. Field setup was identical for both plans and comparable dosimetric quality was a prerequisite. Both IMPT plans were delivered on PSI Gantry 2 and measured in water, while delivery log-files were used to extract delivery times and reconstruct the delivered dose via Monte-Carlo dose calculations. In addition, robustness simulations were performed to assess sensitivity to machine inaccuracies and errors in patient setup and proton range. The number of spots was reduced by 96% (from 33 855 to 1510 in total) without compromising plan quality. The spot-reduced plan was deliverable on our gantry in standard clinical mode and resulted in average delivery times per field being shortened by 46% (from 51.2 to 27.6 s). For both plans, differences between measured and calculated dose were within clinical tolerance for patient-specific verifications and Monte-Carlo dose reconstructions were in accordance with clinical experience. The spot-reduced plan was slightly more sensitive to machine inaccuracies, but more robust against setup and range errors. In conclusion, for an example head-and-neck case, spot-reduced IMPT planning provided a deliverable treatment plan and enabled considerable shortening of the delivery time (∼50%) without compromising plan quality or delivery accuracy, and without substantially affecting robustness.

Platform for automatic patient quality assurance via Monte Carlo simulations in proton therapy

For radiation therapy, it is crucial to ensure that the delivered dose matches the planned dose. Errors in the dose calculations done in the treatment planning system (TPS), treatment delivery errors, other software bugs or data corruption during transfer might lead to significant differences between predicted and delivered doses. As such, patient specific quality assurance (QA) of dose distributions, through experimental validation of individual fields, is necessary. These measurement based approaches, however, are performed with 2D detectors, with limited resolution and in a water phantom. Moreover, they are work intensive and often impose a bottleneck to treatment efficiency. In this work, we investigated the potential to replace measurement-based approach with a simulation-based patient specific QA using a Monte Carlo (MC) code as independent dose calculation engine in combination with treatment log files. Our developed QA platform is composed of a web interface, servers and computation scripts, and is capable to autonomously launch simulations, identify and report dosimetric inconsistencies. To validate the beam model of independent MC engine, in-water simulations of mono-energetic layers and 30 SOBP-type dose distributions were performed. Average Gamma passing ratio 99 ± 0.5% for criteria 2%/2 mm was observed. To demonstrate feasibility of the proposed approach, 10 clinical cases such as head and neck, intracranial indications and craniospinal axis, were retrospectively evaluated via the QA platform. The results obtained via QA platform were compared to QA results obtained by measurement-based approach. This comparison demonstrated consistency between the methods, while the proposed approach significantly reduced in-room time required for QA procedures.

Transitioning from measurement-based to combined patient-specific quality assurance for intensity-modulated proton therapy

OBJECTIVE

This study is part of ongoing efforts aiming to transit from measurement-based to combined patient-specific quality assurance (PSQA) in intensity-modulated proton therapy (IMPT). A Monte Carlo (MC) dose-calculation algorithm is used to improve the independent dose calculation and to reveal the beam modeling deficiency of the analytical pencil beam (PB) algorithm.

METHODS

A set of representative clinical IMPT plans with suboptimal PSQA results were reviewed. Verification plans were recalculated using an MC algorithm developed in-house. Agreements of PB and MC calculations with measurements that quantified by the γ passing rate were compared.

RESULTS

The percentage of dose planes that met the clinical criteria for PSQA (>90% γ passing rate using 3%/3 mm criteria) increased from 71.40% in the original PB calculation to 95.14% in the MC recalculation. For fields without beam modifiers, nearly 100% of the dose planes exceeded the 95% γ passing rate threshold using the MC algorithm. The model deficiencies of the PB algorithm were found in the proximal and distal regions of the SOBP, where MC recalculation improved the γ passing rate by 11.27% (p < 0.001) and 16.80% (p < 0.001), respectively.

CONCLUSIONS

The MC algorithm substantially improved the γ passing rate for IMPT PSQA. Improved modeling of beam modifiers would enable the use of the MC algorithm for independent dose calculation, completely replacing additional depth measurements in IMPT PSQA program. For current users of the PB algorithm, further improving the long-tail modeling or using MC simulation to generate the dose correction factor is necessary.

ADVANCES IN KNOWLEDGE

We justified a change in clinical practice to achieve efficient combined PSQA in IMPT by using the MC algorithm that was experimentally validated in almost all the clinical scenarios in our center. Deficiencies in beam modeling of the current PB algorithm were identified and solutions to improve its dose-calculation accuracy were provided.

RIDOS: A new system for online computation of the delivered dose distributions in scanning ion beam therapy

PURPOSE

To describe a new system for scanned ion beam therapy, named RIDOS (Real-time Ion DOse planning and delivery System), which performs real time delivered dose verification integrating the information from a clinical beam monitoring system with a Graphic Processing Unit (GPU) based dose calculation in patient Computed Tomography.

METHODS

A benchmarked dose computation algorithm for scanned ion beams has been parallelized and adapted to run on a GPU architecture. A workstation equipped with a NVIDIA GPU has been interfaced through a National Instruments PXI-crate with the dose delivery system of the Italian National Center of Oncological Hadrontherapy (CNAO) to receive in real-time the measured beam parameters. Data from a patient monitoring system are also collected to associate the respiratory phases with each spot during the delivery of the dose. Using both measured and planned spot properties, RIDOS evaluates during the few seconds of inter-spill time the cumulative delivered and prescribed dose distributions and compares them through a fast γ-index algorithm.

RESULTS

The accuracy of the GPU-based algorithms was assessed against the CPU-based ones and the differences were found below 1‰. The cumulative planned and delivered doses are computed at the end of each spill in about 300 ms, while the dose comparison takes approximatively 400 ms. The whole operation provides the results before the next spill starts.

CONCLUSIONS

RIDOS system is able to provide a fast computation of the delivered dose in the inter-spill time of the CNAO facility and allows to monitor online the dose deposition accuracy all along the treatment.

Evaluation of the ray-casting analytical algorithm for pencil beam scanning proton therapy

For pencil beam scanned (PBS) proton therapy, analytical dose calculation engines are still typically used for the optimisation process, and often for the final evaluation of the plan. Recently however, the suitability of analytical calculations for planning PBS treatments has been questioned. Conceptually, the two main approaches for these analytical dose calculations are the ray-casting (RC) and the pencil-beam (PB) method. In this study, we compare dose distributions and dosimetric indices, calculated on both the clinical dose calculation grid and as a function of dose grid resolution, to Monte Carlo (MC) calculations. The analysis is done using a comprehensive set of clinical plans which represent a wide choice of treatment sites. When analysing dose difference histograms for relative treatment plans, pencil beam calculations with double grid resolution perform best, with on average 97.7%/91.9% (RC), 97.9%/92.7% (RC, double grid resolution), 97.6%/91.0% (PB) and 98.6%/94.0% (PB, double grid resolution) of voxels agreeing within  ±5%/±  3% between the analytical and the MC calculations. Even though these point-to-point dose comparison shows differences between analytical and MC calculations, for all algorithms, clinically relevant dosimetric indices agree within  ±4% for the PTV and within  ±5% for critical organs. While the clinical agreement depends on the treatment site, there is no substantial difference of indices between the different algorithms. The pencil-beam approach however comes at a higher computational cost than the ray-casting calculation. In conclusion, we would recommend using the ray-casting algorithm for fast dose optimization and subsequently combine it with one MC calculation to scale the absolute dose and assure the quality of the treatment plan.

Log file based Monte Carlo calculations for proton pencil beam scanning therapy

Patient specific quality assurance is crucial to guarantee safety in proton pencil beam scanning. In current clinical practice, this requires extensive, time consuming measurements. Additionally, these measurements do not consider the influence of density heterogeneities in the patient and are insensitive to delivery errors. In this work, we investigate the use of log file based Monte Carlo calculations for dose reconstructions in the patient CT, which takes the combined influence of calculational and delivery errors into account. For one example field, 87%/90% of the voxels agree within  ±3% when taking either calculational or delivery uncertainties into account (analytical versus Monte Carlo calculation/Monte Carlo from planned versus Monte Carlo from log file). 78% agree when considering both uncertainties simultaneously (nominal field versus Monte Carlo from log files). We then show the application of the log file based Monte Carlo calculations as a patient specific quality assurance tool for a set of five patients (16 fields) treated for different indications. For all fields, absolute dose scaling factors based on the log file Monte Carlo agree within  ±3% to the measurement based absolute dose scaling. Relative comparison shows that more than 90% of the voxels agree within  ±  5% between the analytical calculated plan and the Monte Carlo based on log files. The log file based Monte Carlo approach is an end-to-end test incorporating all requirements of patient specific quality assurance. It has the potential to reduce the workload and therefore to increase the patient throughput, while simultaneously enabling more accurate dose verification directly in the patient geometry.

Comprehensive clinical commissioning and validation of the RayStation treatment planning system for proton therapy with active scanning and passive treatment techniques

PURPOSE

To commission the treatment planning system (TPS) RayStation for proton therapy including beam models for spot scanning and for uniform scanning.

METHODS

Tests consist of procedures from ESTRO booklet number 7, the German DIN for constancy checks of TPSs, and extra tests checking the dose perturbation function. The dose distributions within patients were verified in silico by a comparison of 65 clinical treatment plans with the TPS XiO. Dose-volume parameters, dose differences, and three-dimensional gamma-indices serve as measures of similarity. The monthly constancy checks of Raystation have been automatized with a script.

RESULTS

The basic functionality of the software complies with ESTRO booklet number 7. For a few features minor enhancements are suggested. The dose distribution in RayStation agrees with the calculation in XiO. This is supported by a gamma-index (3mm/3%) pass rate of >98.9% (median over 59 plans) for the volume within the 20% isodose line and a difference of <0.3% of V₉₅ of the PTV (median over 59 plans). If spot scanning is used together with a range shifter, the dose level calculated by RayStation can be off by a few percent.

CONCLUSIONS

RayStation can be used for the creation of clinical proton treatment plans. Compared to XiO RayStation has an improved modelling of the lateral dose fall-off in passively delivered fields. For spot scanning fields with range shifter blocks an empirical adjustment of monitor units is required. The computation of perturbed doses also allows the evaluation of the robustness of a treatment plan.