Commissioning of pencil beam and Monte Carlo dose engines for non-isocentric treatments in scanned proton beam therapy

Commissioning of a commercial treatment planning system for scanned carbon-ion radiotherapy

PURPOSE

To commission the RayStation (RS) TPS (treatment planning system) for scanned CIRT (carbon-ion radiotherapy) utilizing pencil beam algorithms (PBv4.2).

METHODS

The beam model commissioning entailed employing 1D single beams and 2D monoenergetic fields to validate spot profiles with films, assess beam range using Peakfinder measurements, and evaluate fragment spectra through dose-averaged linear energy transfer (LETd) calculations. 3D dose distributions were verified in homogeneous phantoms for both absorbed and relative biological effectiveness (RBE)-weighted doses, and further assessed in double wedge and anthropomorphic phantoms for absorbed dose only. Finally, RBE-weighted dose verification and patient-specific quality assurance were conducted using 58 beams from 20 clinically treated patient plans.

RESULTS

The results demonstrated good agreement in absolute dose distribution between TPS calculations and measurements, with mean dose discrepancies within 3%. However, deviations were slightly higher (> 1%) for the cases involving the range shifter (RaShi) compared to those without the RaShi (< 1%). Beam range, depth dose distribution, and lateral profiles of spread-out Bragg peaks (SOBPs) closely matched between RS TPS calculations and measurements. Some discrepancies (less than 0.5 mm) were observed at field edges and in penumbra regions due to limitations in simulating asymmetrical spots, but within clinical tolerance. After model tuning, RBE-weighted dose calculations in RS TPS were in agreement with those from the clinically used TPS, except for variations exceeding 3% observed at energies exceeding 408.07 MeV/u, primarily attributed to fragment spectra differences.

CONCLUSION

Overall, this study validated the RS TPS for calculating absorbed doses against measurements and RBE-weighted doses against a clinically used TPS. The results suggested that the RS TPS could be utilized for CIRT treatment planning, except for energies exceeding 408.07 MeV/u.

Treatment planning of scanned proton beams in RayStation

The use of scanned proton beams in external beam radiation therapy has seen a rapid development over the past decade. This technique places new demands on treatment planning, as compared to conventional photon-based radiation therapy. In this article, several proton specific functions as implemented in the treatment planning system RayStation are presented. We will cover algorithms for energy layer and spot selection, basic optimization including the handling of spot weight limits, optimization of the linear energy transfer (LET) distribution, robust optimization including the special case of 4D optimization, proton arc planning, and automatic planning using deep learning. We will further present the Monte Carlo (MC) proton dose engine in RayStation to some detail, from the material interpretation of the CT data, through the beam model parameterization, to the actual MC transport mechanism. Useful tools for plan evaluation, including robustness evaluation, and the versatile scripting interface are also described. The overall aim of the paper is to give an overview of some of the key proton planning functions in RayStation, with example usages, and at the same time provide the details about the underlying algorithms that previously have not been fully publicly available.

Small field proton irradiation for in vivo studies: Potential and limitations when adapting clinical infrastructure

PURPOSE

To evaluate the dosimetric accuracy for small field proton irradiation relevant for pre-clinical in vivo studies using clinical infrastructure and technology. In this context additional beam collimation and range reduction was implemented.

METHODS AND MATERIALS

The clinical proton beam line employing pencil beam scanning (PBS) was adapted for the irradiation of small fields at shallow depths. Cylindrical collimators with apertures of 15, 12, 7 and 5mm as well as two different range shifter types, placed at different distances relative to the target, were tested: a bolus range shifter (BRS) attached to the collimator and a clinical nozzle mounted range shifter (CRS) placed at a distance of 72cm from the collimator. The Monte Carlo (MC) based dose calculation engine implemented in the clinical treatment planning system (TPS) was commissioned for these two additional hardware components. The study was conducted with a phantom and cylindrical target sizes between 2 and 25mm in diameter following a dosimetric end-to-end test concept.

RESULTS

The setup with the CRS provided a uniform dose distribution across the target. An agreement of better than5% between the planned dose and the measurements was obtained for a target with 3mm diameter (collimator 5mm). A 2mm difference between the collimator and the target diameter (target being 2 mm smaller than the collimator) sufficed to cover the whole target with the planned dose in the setup with CRS. Using the BRS setup (target 8mm, collimator 12mm) resulted in non-homogeneous dose distributions, with a dose discrepancy of up to 10% between the planned and measured doses.

CONCLUSION

The clinical proton infrastructure with adequate beam line adaptations and a state-of-the-art TPS based on MC dose calculations enables small animal irradiations with a high dosimetric precision and accuracy for target sizes down to 3mm.

Planning Strategy to Optimize the Dose-Averaged LET Distribution in Large Pelvic Sarcomas/Chordomas Treated with Carbon-Ion Radiotherapy

To improve outcomes in large sarcomas/chordomas treated with CIRT, there has been recent interest in LET optimization. We evaluated 22 pelvic sarcoma/chordoma patients treated with CIRT [large: HD-CTV ≥ 250 cm3 (n = 9), small: HD-CTV < 250 cm3 (n = 13)], DRBE|LEM-I = 73.6 (70.4-73.6) Gy (RBE)/16 fractions, using the local effect model-I (LEM-I) optimization and modified-microdosimetric kinetic model (mMKM) recomputation. We observed that to improve high-LETd distribution in large tumors, at least 27 cm3 (low-LETd region) of HD-CTV should receive LETd of ≥33 keV/µm (p < 0.05). Hence, LETd optimization using 'distal patching' was explored in a treatment planning setting (not implemented clinically yet). Distal-patching structures were created to stop beams 1-2 cm beyond the HD-PTV-midplane. These plans were reoptimized and DRBE|LEM-I, DRBE|mMKM, and LETd were recomputed. Distal patching increased (a) LETd50% in HD-CTV (from 38 ± 3.4 keV/µm to 47 ± 8.1 keV/µm), (b) LETdmin in low-LETd regions of the HD-CTV (from 32 ± 2.3 keV/µm to 36.2 ± 3.6 keV/µm), (c) the GTV fraction receiving LETd of ≥50 keV/µm, (from <10% to >50%) and (d) the high-LETd component in the central region of the GTV, without significant compromise in DRBE distribution. However, distal patching is sensitive to setup/range uncertainties, and efforts to ascertain robustness are underway, before routine clinical implementation.

Requirements for dose calculation on an active scanned proton beamline for small, shallow fields

INTRODUCTION

A growing interest in using proton pencil beam scanning in combination with collimators for the treatment of small, shallow targets, such as ocular melanoma or pre-clinical research emerged recently. This study aims at demonstrating that the dose of a synchrotron-based PBS system with a dedicated small, shallow field nozzle can be accurately predicted by a commercial treatment planning system (TPS) following appropriate tuning of both, nozzle and TPS.

MATERIALS

A removable extension to the clinical nozzle was developed to modify the beam shape passively. Five circular apertures with diameters between 5 to 34mm, mounted 72cm downstream of a range shifter were used. For each collimator treatment plans with spread-out Bragg peaks (SOBP) with a modulation of 3 to 30mm were measured and calculated with GATE/Geant4 and the research TPS RayStation (RS11B-R). The dose grid, multiple coulomb scattering and block discretization resolution were varied to find the optimal balance between accuracy and performance.

RESULTS

For SOBPs deeper than 10mm, the dose in the target agreed within 1% between RS11B-R, GATE/Geant4 and measurements for aperture diameters between 8 to 34mm, but deviated up to 5% for smaller apertures. A plastic taper was introduced reducing scatter contributions to the patient (from the pipe) and improving the dose calculation accuracy of the TPS to a 5% level in the entrance region for large apertures.

CONCLUSION

The commercial TPS and GATE/Geant4 can accurately calculate the dose for shallow, small proton fields using a collimator and pencil beam scanning.

Commissioning dose computation model for proton source in pencil beam scanning therapy by convolution neural networks

Objective. Proton source model commissioning (PSMC) is critical for ensuring accurate dose calculation in pencil beam scanning (PBS) proton therapy using Monte Carlo (MC) simulations. PSMC aims to match the calculated dose to the delivered dose. However, commissioning the 'nominal energy' and 'energy spread' parameters in PSMC can be challenging, as these parameters cannot be directly obtained from solving equations. To efficiently and accurately commission the nominal energy and energy spread in a proton source model, we developed a convolution neural network (CNN) named 'PSMC-Net.'Methods. The PSMC-Net was trained separately for 33 energies (E, 70-225 MeV with a step of 5 MeV plus 226.09 MeV). For eachE, a dataset was generated consisting of 150 source model parameters (15 nominal energies ∈ [E,E+ 1.5 MeV], ten spreads ∈ [0, 1]) and the corresponding 150 MC integrated depth doses (IDDs). Of these 150 data pairs, 130 were used for training the network, 10 for validation, and 10 for testing.Results. The source model, built by 33 measured IDDs and 33 PSMC-Nets (cost 0.01 s), was used to compute the MC IDDs. The gamma passing rate (GPRs, 1 mm/1%) between MC and measured IDDs was 99.91 ± 0.12%. However, when no commissioning was made, the corresponding GPR was reduced to 54.11 ± 22.36%, highlighting the tremendous significance of our CNN commissioning method. Furthermore, the MC doses of a spread-out Bragg peak and 20 patient PBS plans were also calculated, and average 3D GPRs (2 mm/2% with a 10% threshold) were 99.89% and 99.96 ± 0.06%, respectively.Significance. We proposed a nova commissioning method of the proton source model using CNNs, which made the PSMC process easy, efficient, and accurate.

Commissioning a beam line for MR-guided particle therapy assisted by in silico methods

BACKGROUND

Radiation therapy is continuously moving towards more precise dose delivery. The combination of online MR imaging and particle therapy, for example, radiation therapy using protons or carbon ions, could enable the next level of precision in radiotherapy. In particle therapy, research towards a combination of MR and particle therapy is well underway, but still far from clinical systems. The combination of high magnetic fields with particle therapy delivery poses several challenges for treatment planning, treatment workflow, dose delivery, and dosimetry.

PURPOSE

To present a workflow for commissioning of a light ion beam line with an integrated dipole magnet to perform MR-guided particle therapy (MRgPT) research, producing not only basic beam data but also magnetic field maps for accurate dose calculation. Accurate dose calculation in magnetic field environments requires high-quality magnetic field maps to compensate for magnetic-field-dependent trajectory changes and dose perturbations.

METHODS

The research beam line at MedAustron was coupled with a resistive dipole magnet positioned at the isocenter. Beam data were measured for proton and carbon ions with and without an applied magnetic field of 1 T. Laterally integrated depth-dose curves (IDC) as well as beam profiles were measured in water while beam trajectories were measured in air. Based on manufacturer data, an in silico model of the magnet was created, allowing to extract high-quality 3D magnetic field data. An existing GATE/Geant4 Monte Carlo (MC) model of the beam line was extended with the generated magnetic field data and benchmarked against experimental data.

RESULTS

A 3D magnetic field volume covering fringe fields until 50 mT was found to be sufficient for an accurate beam trajectory modeling. The effect on particle range retraction was found to be 2.3 and 0.3 mm for protons and carbon ions, respectively. Measured lateral beam offsets in water agreed within 0.4 and -0.5 mm with MC simulations for protons and carbon ions, respectively. Experimentally determined in-air beam trajectories agreed within 0.4 mm in the homogeneous magnetic field area.

CONCLUSION

The presented approach based on in silico modeling and measurements allows to commission a beam line for MRgPT while providing benchmarking data for the magnetic field modeling, required for state-of-the art dose calculation methods.

Dose calculation accuracy in particle therapy: Comparing carbon ions with protons

PURPOSE

This work presents the validation of an analytical pencil beam dose calculation algorithm in a commercial treatment planning system (TPS) for carbon ions by measurements of dose distributions in heterogeneous phantom geometries. Additionally, a comparison study of carbon ions versus protons is performed considering current best solutions in commercial TPS.

METHODS

All treatment plans were optimized and calculated using the RayStation TPS (RaySearch, Sweden). The dose distributions calculated with the TPS were compared with measurements using a 24-pinpoint ionization chamber array (T31015, PTW, Germany). Tissue-like inhomogeneities (bone, lung, and soft tissue) were embedded in water, while a target volume of 4 x 4 x 4 cm3 was defined at two different depths behind the heterogeneities. In total, 10 different test cases, with and without range shifter as well as different air gaps, were investigated. Dose distributions inside as well as behind the target volume were evaluated.

RESULTS

Inside the target volume, the mean dose difference between calculations and measurements, averaged over all test cases, was 1.6% for carbon ions. This compares well to the final agreement of 1.5% obtained in water at the commissioning stage of the TPS for carbon ions and is also within the clinically acceptable interval of 3%. The mean dose difference and maximal dose difference obtained outside the target area were 1.8% and 13.4%, respectively. The agreement of dose distributions for carbon ions in the target volumes was comparable or better to that between Monte Carlo (MC) dose calculations and measurements for protons. Percentage dose differences of more than 10% were present outside the target area behind bone-lung structures, where the carbon ion calculations systematically over predicted the dose. MC dose calculations for protons were superior to carbon ion beams outside the target volumes.

CONCLUSION

The pencil beam dose calculations for carbon ions in RayStation were found to be in good agreement with dosimetric measurements in heterogeneous geometries for points of interest located within the target. Large local discrepancies behind the target may contribute to incorrect dose predictions for organs at risk.

Clinical validation of a GPU-based Monte Carlo dose engine of a commercial treatment planning system for pencil beam scanning proton therapy

PURPOSE

To perform the validation of the GPU-based (Graphical Processing Unit based) proton Monte Carlo (MC) dose engine implemented in a commercial TPS (RayStation 10B) and to report final dose calculation times for clinical cases.

MATERIALS AND METHODS

440 patients treated at the Proton Therapy Center of Trento, Italy, between 2018 and 2019 were selected for this study. 636 approved plans with 3361 beams computed with the clinically implemented CPU-MC dose engine (version 4.2 and 4.5), were used for the validation of the new algorithm. For each beam, the dose was recalculated using the new GPU-MC dose engine with the initial CPU computation settings and compared to the original CPU-MC dose. Beam dose difference distributions were studied to ensure that the two dose distributions were equal within the expected fluctuations of the MC statistical uncertainty (s) of each computation. Plan dose distributions were compared with respect to the dosimetric indices D₉₈, D₅₀ and D₁ of all ROIs defined as targets. A complete assessment of the computation time as a function of s and dose grid voxel size was done.

RESULTS

The median over all mean beam dose differences between CPU- and GPU-MC was -0.01% and the median of the corresponding standard deviations was close to (√2s) both for simulations with an s of 0.5% and 1.0% per beam. This shows that the two dose distributions can be considered equal. All the DVH indices showed an average difference below 0.04%. About half of the plans were computed with 1.0% statistical uncertainty on a 2 mm dose calculation grid, for which the median computation time was 5.2 s. The median computational speed for all plans in the study was 8.4 million protons/second.

CONCLUSION

A validation of a clinical MC algorithm running on GPU was performed on a large pool of patients treated with pencil beam scanning proton therapy. We demonstrated that the differences with the previous CPU-based MC were only due to the intrinsic statistical fluctuations of the MC method, which translated to insignificant differences on plan dose level. The significant increase in dose calculation speed is expected to facilitate new clinical workflows.

Time-resolved dosimetry for validation of 4D dose calculation in PBS proton therapy

Four-dimensional dose calculation (4D-DC) is crucial for predicting the dosimetric outcome in the presence of intra-fractional organ motion. Time-resolved dosimetry can provide significant insights into 4D pencil beam scanning dose accumulation and is therefore irreplaceable for benchmarking 4D-DC. In this study a novel approach of time-resolved dosimetry using five PinPoint ionization chambers (ICs) embedded in an anthropomorphic dynamic phantom was employed and validated against beam delivery details. Beam intensity variations as well as the beam delivery time structure were well reflected with an accuracy comparable to the temporal resolution of the IC measurements. The 4D dosimetry approach was further applied for benchmarking the 4D-DC implemented in the RayStation 6.99 treatment planning system. Agreement between computed values and measurements was investigated for (i) partial doses based on individual breathing phases, and (ii) temporally distributed cumulative doses. For varied beam delivery and patient-related parameters the average unsigned dose difference for (i) was 0.04 ± 0.03 Gy over all considered IC measurement values, while the prescribed physical dose was 2 Gy. By implementing (ii), a strong effect of the dose gradient on measurement accuracy was observed. The gradient originated from scanned beam energy modulation and target motion transversal to the beam. Excluding measurements in the high gradient the relative dose difference between measurements and 4D-DCs for a given treatment plan at the end of delivery was 3.5% on average and 6.6% at maximum over measurement points inside the target. Overall, the agreement between 4D dose measurements in the moving phantom and retrospective 4D-DC was found to be comparable to the static dose differences for all delivery scenarios. The presented 4D-DC has been proven to be suitable for simulating treatment deliveries with various beam- as well as patient-specific parameters and can therefore be employed for dosimetric validation of different motion mitigation techniques.

Dynamic lung phantom commissioning for 4D dose assessment in proton therapy

Anthropomorphic phantoms mimicking organ and tumor motion of patients are essential for end-to-end testing of motion mitigation techniques in ion beam therapy. In this work a commissioning procedure developed with the in-house designed respiratory phantom ARDOS (Advanced Radiation DOSimetry system) is presented. The phantom was tested and benchmarked for 4D dose verification in proton therapy, which included: characterization of the tissue equivalent materials from computed tomography (CT) imaging, assessment of dose calculation accuracy in critical structures of the phantom, and testing various detectors for proton dosimetry in the ARDOS phantom. To prove the validity of the CT calibration curve, measured relative stopping powers (RSP) of the ARDOS materials were compared with values from CTs: original and overwritten with known material parameters. Override of rib- and soft-tissue phantom components improved RSP accuracy while inhomogeneous lung tissue, represented by the balsa wood, was better modelled by the CT Hounsfield units. Monte Carlo (MC) dose calculations were benchmarked against measurements with a reference Farmer chamber embedded in ARDOS material samples showing less than 3% relative dose difference. Differences between MC calculated dose distributions and those calculated by analytical algorithms for the ARDOS geometry were higher than 20% of the prescribed dose, depending on the position in the phantom. Pinpoint ionization chambers and thermoluminescence dosimeters showed differences of up to 5.5% compared to MC dose calculations for all lung setups in the static phantom. They were also able to detect dose distortions due to motion. EBT3 film dosimetry was shown to be suitable for 2D relative dose characterization, which could provide extended information on dose distributions in the penumbra area. The presented methodology and results can be used for drafting general recommendations for dynamic phantom commissioning, which is an essential step towards end-to-end evaluation of motion mitigation techniques in ion beam therapy.