Monte Carlo Dose Calculation Research Articles

Monte Carlo Simulation of Organ Absorbed Dose of Worker's Radiation Exposure in Bone Scintigraphy

Objectives: This study examines individual organ doses and the impact of ionizing radiation sources on effective radiation doses. Methods: In the research, the ICRP-defined adult standing phantom was used as the phantom material in the Visual Monte Carlo Dose Calculation Program (VMC). Subsequently, the incurred doses were calculated by defining different doses, distances, and durations for the 99mTc radioactive source. Results: Exposure times were set at 5 minutes and 20 minutes in comparison. The results indicated that for 5 minutes and 20 minutes at 360 cm, doses remained below the ICRP recommended annual dose limit of 5.7 µSv/h for occupational exposure. Conclusion: Organ absorbed and effective doses varied with exposure time and source-phantom distance. To optimize radiation exposure, people working in radiation fields must make an increased effort to reduce radiation doses following the ALARA principles. Keywords: Effective dose, absorbed dose, VMC software, Monte Carlo

A quantification of the electron return effect using Monte Carlo simulations and experimental measurements for the MRI-linac

The integration of magnetic resonance (MR) imaging and linear accelerators into hybrid treatment systems has made MR-guided radiation therapy a clinical reality. This work aims to evaluate the influence of the Electron Return Effect (ERE) on the dose distributions. This study was conducted using MRIdian (ViewRay, Cleveland, Ohio) system. Monte-Carlo simulations (MCs) and experimental measurements with EBT3 Gafchromic films were performed to investigate the dose distribution in a slab water phantom with and without a 2-cm air gap. Plus, MCs took into account different field sizes and a lung gap. A gamma analysis compared calculated versus measured dose distributions. The MCs have shown an increase of the ERE with the radiation field size both in Percent Depth Dose (PDD) and crossline direction. As concerns to the PDD direction, the smallest field for which there was a significant dose accumulation was 4.15×4.15 cm2both for air-gap (13.5%) and lung-gap (3.3%). The largest field for which there was a significant dose accumulation was 24.07×24.07 cm2both for air-gap (39.7%) and lung-gap (4.9%). Instead for the crossline direction, the smallest field for which there was a significant dose accumulation was 2.49×2.49 cm2both for air-gap (8.6% ) and lung-gap (0.5%). The largest field for which there was a significant dose accumulation was 24.07×24.07 cm2both for air-gap (46.2%) and lung-gap (4.2%). PDD and crossline profiles showed good agreement with a gamma-passing rate higher than 91.15% for 2%/2 mm. The ERE can be adequately calculated by MC dose calculation platform available in the MRIdian Treatment Planning System. The MCs show an increase of the ERE directly proportional with the radiation field size. Good agreement was observed between the experimental measurements and calculated dose distributions.

Monte Carlo dose calculation for photon and electron radiotherapy on dynamically deforming anatomy.

Dose calculation in radiotherapy aims to accurately estimate and assess the dose distribution of a treatment plan. Monte Carlo (MC) dose calculation is considered the gold standard owing to its ability to accurately simulate particle transport in inhomogeneous media. However, uncertainties such as the patient's dynamically deforming anatomy can still lead to differences between the delivered and planned dose distribution. Development and validation of a deformable voxel geometry for MC dose calculations (DefVoxMC) to account for dynamic deformation in the dose calculation process of photon- and electron-based radiotherapy treatment plans for clinically motivated cases. DefVoxMC relies on the subdivision of a regular voxel geometry into dodecahedrons. It allows shifting the dodecahedrons' corner points according to the deformation in the patient's anatomy using deformation vector fields (DVF). DefVoxMC is integrated into the Swiss Monte Carlo Plan (SMCP) to allow the MC dose calculation of photon- and electron-based treatment plans on the deformable voxel geometry. DefVoxMC is validated in two steps. A compression test and a Fano test are performed in silico. Delta4 (for photon beams) and EBT4 film measurements in a cubic PMMA phantom (for electron beams) are performed on a TrueBeam in Developer Mode for clinically motivated treatment plans. During these measurements, table motion is used to mimic rigid dynamic patient motion. The measured and calculated dose distributions are compared using gamma passing rate (GPR) (3% / 2mm (global), 10% threshold). DefVoxMC is used to study the impact of patient-recorded breathing motion on the dose distribution for clinically motivated lung and breast cases, each prescribed 50Gy to 50% of the target volume. A volumetric modulated arc therapy (VMAT) and an arc mixed-beam radiotherapy (Arc-MBRT) plan are created for the lung and breast case, respectively. For the dose calculation, the dynamic deformation of the patient's anatomy is described by DVFs obtained from deformable image registration of the different phases of 4DCTs. The resulting dose distributions are compared to the ones of the static situation using dose-volume histograms and dose differences. DefVoxMC is successfully integrated into the SMCP to enable the MC dose calculation of photon- and electron-based treatments on a dynamically deforming patient anatomy. The compression and the Fano test agree within 1.0% and 0.1% with the expected result, respectively. Delta4 and EBT4 film measurements agree with the calculated dose by a GPR>95%. For the clinically motivated cases, breathing motion resulted in areas with a dose increase of up to 26.9Gy (lung) and up to 7.6Gy (breast) compared to the static situation. The largest dose differences are observed in high-dose-gradient regions perpendicular to the beam plane, consequently decreasing the planning target volume coverage (V95%) by 4.2% for the lung case and 2.0% for the breast case. A novel method for MC dose calculation for photon- and electron-based treatments on dynamically deforming anatomy is successfully developed and validated. Applying DefVoxMC to clinically motivated cases, we found that breathing motion has non-negligible impact on the dosimetric plan quality.

Proton dose calculation with LSTM networks in presence of a magnetic field

Objective.To present a long short-term memory (LSTM) network-based dose calculation method for magnetic resonance (MR)-guided proton therapy.Approach.35 planning computed tomography (CT) images of prostate cancer patients were collected for Monte Carlo (MC) dose calculation under a perpendicular 1.5 T magnetic field. Proton pencil beams (PB) at three energies (150, 175, and 200 MeV) were simulated (7560 PBs at each energy). A 3D relative stopping power cuboid covering the extent of the PB dose was extracted and given as input to the LSTM model, yielding a 3D predicted PB dose. Three single-energy (SE) LSTM models were trained separately on the corresponding 150/175/200 MeV datasets and a multi-energy (ME) LSTM model with an energy embedding layer was trained on either the combined dataset with three energies or a continuous energy (CE) dataset with 1 MeV steps ranging from 125 to 200 MeV. For each model, training and validation involved 25 patients and 10 patients were for testing. Two single field uniform dose prostate treatment plans were optimized and recalculated with MC and the CE model.Results.Test results of all PBs from the three SE models showed a mean gamma passing rate (2%/2 mm, 10% dose cutoff) above 99.9% with an average center-of-mass (COM) discrepancy below 0.4 mm between predicted and simulated trajectories. The ME model showed a mean gamma passing rate exceeding 99.8% and a COM discrepancy of less than 0.5 mm at the three energies. Treatment plan recalculation by the CE model yielded gamma passing rates of 99.6% and 97.9%. The inference time of the models was 9-10 ms per PB.Significance.LSTM models for proton dose calculation in a magnetic field were developed and showed promising accuracy and efficiency for prostate cancer patients.

Towards accurate dose assessment for emergency industrial radiography source retrieval operations: A preliminary study of 4D Monte Carlo dose calculations

The exposure devices utilizing high-activity gamma radiation sources for industrial radiography frequently encounter issues such as stuck or disconnected sources, posing a substantial risk of radiation exposure to the workers executing emergency source retrieval operations, emphasizing the importance of accurate dose assessment. In the present study, the radiation dose to the main worker during the process of source retrieval was calculated and compared for five emergency source retrieval procedures to retrieve stuck or disconnected sources, using 4D Monte Carlo dose calculation and a mesh-type reference computational phantom. For a stuck source, the dose values of the two source retrieval procedures (i.e., repair and cut methods) were found to be relatively small, which indicates that the worker might select either method based on personal preference or situational convenience. Conversely, for a disconnected source, the dose values of the three source retrieval procedures (i.e., fishing, connect/push, and hot stick methods) were much larger and show significant differences. Notably, the fishing method was associated with the lowest dose, whereas the hot stick method resulted in significantly higher doses, differences being as large as ∼5 times. These results underscore the fishing method as a preferable option, particularly over the hot stick method.

1492: 4D proton MC dose calculation before treatment: An independent free-breathing QA frame

1492: 4D proton MC dose calculation before treatment: An independent free-breathing QA frame

Machine Learning for Predicting Neutron Effective Dose

The calculation of effective doses is crucial in many medical and radiation fields in order to ensure safety and compliance with regulatory limits. Traditionally, Monte Carlo codes using detailed human body computational phantoms have been used for such calculations. Monte Carlo dose calculations can be time-consuming and require expertise in different processes when building the computational phantom and dose calculations. This study employs various machine learning (ML) algorithms to predict the organ doses and effective dose conversion coefficients (DCCs) from different anthropomorphic phantoms. A comprehensive data set comprising neutron energy bins, organ labels, masses, and densities is compiled from Monte Carlo studies, and it is used to train and evaluate the supervised ML models. This study includes a broad range of phantoms, including those from the International Commission on Radiation Protection (ICRP-110, ICRP-116 phantom), the Visible-Human Project (VIP-man phantom), and the Medical Internal Radiation Dose Committee (MIRD-Phantom), with row data prepared using numerical data and organ categorical labeled data. Extreme gradient boosting (XGB), gradient boosting (GB), and the random forest-based Extra Trees regressor are employed to assess the performance of the ML models against published ICRP neutron DCC values using the mean square error, mean absolute error, and R2 metrics. The results demonstrate that the ML predictions significantly vary in lower energy ranges and vary less in higher neutron energy ranges while showing good agreement with ICRP values at mid-range energies. Moreover, the categorical data models align closely with the reference doses, suggesting the potential of ML in predicting effective doses for custom phantoms based on regional populations, such as the Saudi voxel-based model. This study paves the way for efficient dose prediction using ML, particularly in scenarios requiring rapid results without extensive computational resources or expertise. The findings also indicate potential improvements in data representation and the inclusion of larger data sets to refine model accuracy and prevent overfitting. Thus, ML methods can serve as valuable techniques for the continued development of personalized dosimetry.

Development and verification of an electron Monte Carlo engine for applications in intraoperative radiation therapy.

In preparation of future clinical trials employing the Mobetron electron linear accelerator to deliver FLASH Intraoperative Radiation Therapy (IORT), the development of a Monte Carlo (MC)-based framework for dose calculation was required. To extend and validate the in-house developed fast MC dose engine MonteRay (MR) for future clinical applications in IORT. MR is a CPU MC dose calculation engine written in C++ that is capable of simulating therapeutic proton, helium, and carbon ion beams. In this work, development steps are taken to include electrons and photons in MR are presented. To assess MRs accuracy, MR generated simulation results were compared against FLUKA predictions in water, in presence of heterogeneities as well as in an anthropomorphic phantom. Additionally, dosimetric data has been acquired to evaluate MRs accuracy in predicting dose-distributions generated by the Mobetron accelerator. Runtimes of MR were evaluated against those of the general-purpose MC code FLUKA on standard benchmark problems. MR generated dose distributions for electron beams incident on a water phantom match corresponding FLUKA calculated distributions within 2.3% with range values matching within 0.01mm. In terms of dosimetric validation, differences between MR calculated and measured dose values were below 3% for almost all investigated positions within the water phantom. Gamma passing rate (1%/1mm) for the scenarios with inhomogeneities and gamma passing rate (3%/2mm) with the anthropomorphic phantom, were>99.8% and 99.4%, respectively. The average dose differences between MR (FLUKA) and the measurements was 1.26% (1.09%). Deviations between MR and FLUKA were well within 1.5% for all investigated depths and 0.6% on average. In terms of runtime, MR achieved a speedup against reference FLUKA simulations of about 13 for 10 MeV electrons. Validations against general purpose MC code FLUKA predictions and experimental dosimetric data have proven the validity of the physical models implemented in MR for IORT applications. Extending the work presented here, MR will be interfaced with external biophysical models to allow accurate FLASH biological dose predictions in IORT.

Dose, dose, dose, but where is the patient dose?

The article reviews the historical developments in radiation dose metrices in medical imaging. It identifies the good, the bad, and the ugly aspects of current-day metrices. The actions on shifting focus from International Commission on Radiological Protection (ICRP) Reference-Man-based population-average phantoms to patient-specific computational phantoms have been proposed and discussed. Technological developments in recent years involving AI-based automatic organ segmentation and 'near real-time' Monte Carlo dose calculations suggest the feasibility and advantage of obtaining patient-specific organ doses. It appears that the time for ICRP and other international organizations to embrace 'patient-specific' dose quantity representing risk may have finally come. While the existing dose metrices meet specific demands, emphasis needs to be also placed on making radiation units understandable to the medical community.

Korean-specific dose coefficients for external environmental exposures: Soil contamination

In this study, we first produced the Korean-specific dose coefficients (DCs) for soil contamination using the Mesh-type Reference Korean Phantoms (MRKPs). The Korean DCs were compared with the values in ICRP Publication 144 produced using the Caucasian-based ICRP reference phantoms to investigate dosimetric impact due to the racial difference (Korean/Asian vs Caucasian). Monte Carlo dose calculations using the Geant4 code were conducted where the photon and electron sources in the phase-space data used for the ICRP-144 DC calculations were irradiated to the MRKPs. For photons, the organ DCs of the MRKPs showed a good agreement with the ICRP-144 DCs (deviations <20 %) for most energies, while significant differences at energies below 0.05 MeV were observed by up to a factor of 55.6 (thymus at 0.015 MeV). For electrons, notable differences in the organ DCs were observed the overall energy region (deviations >20 % for most cases). The effective DCs of the MRKPs showed an excellent agreement with the ICRP-144 DCs for photons (deviations <16 %), whereas notable differences by up to 1.7 times (0.05 MeV) were observed for electrons. The Korean DCs for soil contamination will be beneficially used in dose estimates for Koreans especially in risk assessments.

MR compatible detectors assessment for a 0.35 T MR-linac commissioning

PurposeTo assess a large panel of MR compatible detectors on the full range of measurements required for a 0.35 T MR-linac commissioning by using a specific statistical method represented as a continuum of comparison with the Monte Carlo (MC) TPS calculations. This study also describes the commissioning tests and the secondary MC dose calculation validation.Material and methodsPlans were created on the Viewray TPS to generate MC reference data. Absolute dose points, PDD, profiles and output factors were extracted and compared to measurements performed with ten different detectors: PTW 31010, 31021, 31022, Markus 34045 and Exradin A28 MR ionization chambers, SN Edge shielded diode, PTW 60019 microdiamond, PTW 60023 unshielded diode, EBT3 radiochromic films and LiF µcubes. Three commissioning steps consisted in comparison between calculated and measured dose: the beam model validation, the output calibration verification in four different phantoms and the commissioning tests recommended by the IAEA-TECDOC-1583.Main resultsThe symmetry for the high resolution detectors was higher than the TPS data of about 1%. The angular responses of the PTW 60023 and the SN Edge were − 6.6 and − 11.9% compared to the PTW 31010 at 60°. The X/Y-left and the Y-right penumbras measured by the high resolution detectors were in good agreement with the TPS values except for the PTW 60023 for large field sizes. For the 0.84 × 0.83 cm2 field size, the mean deviation to the TPS of the uncorrected OF was − 1.7 ± 1.6% against − 4.0 ± 0.6% for the corrected OF whereas we found − 4.8 ± 0.8% for passive dosimeters. The mean absolute dose deviations to the TPS in different phantoms were 0 ± 0.4%, − 1.2 ± 0.6% and 0.5 ± 1.1% for the PTW 31010, PTW 31021 and Exradin A28 MR respectively.ConclusionsThe magnetic field effects on the measurements are considerably reduced at low magnetic field. The PTW 31010 ionization chamber can be used with confidence in different phantoms for commissioning and QA tests requiring absolute dose verifications. For relative measurements, the PTW 60019 presented the best agreement for the full range of field size. For the profile assessment, shielded diodes had a behaviour similar to the PTW 60019 and 60023 while the ionization chambers were the most suitable detectors for the symmetry. The output correction factors published by the IAEA TRS 483 seem to be applicable at low magnetic field pending the publication of new MR specific values.

Independent Monte Carlo dose calculation identifies single isocenter multi-target radiosurgery targets most likely to fail pre-treatment measurement.

For individual targets of single isocenter multi-target (SIMT) Stereotactic radiosurgery (SRS), we assess dose difference between the treatment planning system (TPS) and independent Monte Carlo (MC), and demonstrate persistence into the pre-treatment Quality Assurance (QA) measurement. Treatment plans from 31 SIMT SRS patients were recalculated in a series of scenarios designed to investigate sources of discrepancy between TPS and independent MC. Targets with>5% discrepancy in DMean[Gy] after progressing through all scenarios were measured with SRS MapCHECK. A matched pair analysis was performed comparing SRS MapCHECK results for these targets with matched targets having similar characteristics (volume & distance from isocenter) but no such MC dose discrepancy. Of 217 targets analyzed, individual target mean dose (DMean[Gy]) fell outside a 5% threshold for 28 and 24 targets before and after removing tissue heterogeneity effects, respectively, while only 5 exceeded the threshold after removing effect of patient geometry (via calculation on StereoPHAN geometry). Significant factors affecting agreement between the TPS and MC included target distance from isocenter (0.83% decrease in DMean[Gy] per 2cm), volume (0.15% increase per cc), and degree of plan modulation (0.37% increase per 0.01 increase in modulation complexity score). SRS MapCHECK measurement had better agreement with MC than with TPS (2%/1mm / 10% threshold gamma pass rate (GPR)=99.4±1.9%vs. 93.1±13.9%, respectively). In the matched pair analysis, targets exceeding 5% for MC versus TPS also had larger discrepancies between TPS and measurement with no GPR (2%/1mm / 10% threshold) exceeding 90% (71.5%±16.1%); whereas GPR was high for matched targets with no such MC versus TPS difference (96.5%±3.3%, p=0.01). Independent MC complements pre-treatment QA measurement for SIMT SRS by identifying problematic individual targets prior to pre-treatment measurement, thus enabling plan modifications earlier in the planning process and guiding selection of targets for pre-treatment QA measurement.

RapidBrachyTG43: A Geant4-based TG-43 parameter and dose calculation module for brachytherapy dosimetry.

The AAPM TG-43U1 formalism remains the clinical standard for dosimetry of low- and high-energy -emitting brachytherapy sources. TG-43U1 and related reports provide consensus datasets of TG-43 parameters derived from various published measured data and Monte Carlo simulations. These data are used to perform standardized and fast dose calculations for brachytherapy treatmentplanning. Monte Carlo TG-43 dosimetry parameters are commonly derived to characterize novel brachytherapy sources. RapidBrachyTG43 is a module of RapidBrachyMCTPS, a Monte Carlo-based treatment planning system, designed to automate this process, requiring minimal user input to prepare Geant4-based Monte Carlo simulations for a source. RapidBrachyTG43 may also perform a TG-43 dose to water-in-water calculation for a plan, substantially accelerating the same calculation performed using RapidBrachyMCTPS's Monte Carlo dose calculationengine. TG-43 parameters , , , and were calculated using three commercial source models, one each of I, Ir, and Co, and were benchmarked to published data. TG-43 dose to water was calculated for a clinical breast brachytherapy plan and was compared to a Monte Carlo dose calculation with all patient tissues, air, and catheters set towater. TG-43 parameters for the three simulated sources agreed with benchmark datasets within tolerances specified by the High Energy Brachytherapy Dosimetry working group. A gamma index comparison between the TG-43 and Monte Carlo dose-to-water calculations with a dose difference and difference to agreement criterion of 1%/1 mm yielded a 98.9% pass rate, with all relevant dose volume histogram metrics for the plan agreeing within 1%. Performing a TG-43-based dose calculation provided an acceleration of dose-to-water calculation by a factor of165. Determination of TG-43 parameter data for novel brachytherapy sources may now be facilitated by RapidBrachyMCTPS. These parameter datasets and existing consensus or published datasets may also be used to determine the TG-43 dose for a plan inRapidBrachyMCTPS.

Technical note: Beamlet-free optimization for Monte-Carlo-based treatment planning in proton therapy.

Dose calculation and optimization algorithms in proton therapy treatment planning often have high computational requirements regarding time and memory. This can hinder the implementation of efficient workflows in clinics and prevent the use of new, elaborate treatment techniques aiming to improve clinical outcomes like robust optimization, arc, and adaptive protontherapy. A new method, namely, the beamlet-free algorithm, is presented to address the aforementioned issue by combining Monte Carlo dose calculation and optimization into a single algorithm and omitting the calculation of the time-consuming and costly dose influencematrix. The beamlet-free algorithm simulates the dose in proton batches of randomly chosen spots and evaluates their relative impact on the objective function at each iteration. Based on the approximated gradient, the spot weights are then updated and used to generate a new spot probability distribution. The beamlet-free method is compared against a conventional, beamlet-based treatment planning algorithm on a brain case and a prostatecase. The beamlet-free algorithm maintained a comparable plan quality while largely reducing the dependence of computation time and memory usage on the number ofspots. The implementation of a beamlet-free treatment planning algorithm for proton therapy is feasible and capable of achieving treatment plans of comparable quality to conventional methods. Its efficient usage of computational resources and low spot dependence makes it a promising method for large plans, robust optimization, and arc protontherapy.

Delivery time reduction for mixed photon-electron radiotherapy by using photon MLC collimated electron arcs

Objective. Electron arcs in mixed-beam radiotherapy (Arc-MBRT) consisting of intensity-modulated electron arcs with dynamic gantry rotation potentially reduce the delivery time compared to mixed-beam radiotherapy containing electron beams with static gantry angle (Static-MBRT). This study aims to develop and investigate a treatment planning process (TPP) for photon multileaf collimator (pMLC) based Arc-MBRT. Approach. An existing TPP for Static-MBRT plans is extended to integrate electron arcs with a dynamic gantry rotation and intensity modulation using a sliding window technique. The TPP consists of a manual setup of electron arcs, and either static photon beams or photon arcs, shortening of the source-to-surface distance for the electron arcs, initial intensity modulation optimization, selection of a user-defined number of electron beam energies based on dose contribution to the target volume and finally, simultaneous photon and electron intensity modulation optimization followed by full Monte Carlo dose calculation. Arc-MBRT plans, Static-MBRT plans, and photon-only plans were created and compared for four breast cases. Dosimetric validation of two Arc-MBRT plans was performed using film measurements. Main results. The generated Arc-MBRT plans are dosimetrically similar to the Static-MBRT plans while outperforming the photon-only plans. The mean heart dose is reduced by 32% on average in the MBRT plans compared to the photon-only plans. The estimated delivery times of the Arc-MBRT plans are similar to the photon-only plans but less than half the time of the Static-MBRT plans. Measured and calculated dose distributions agree with a gamma passing rate of over 98% (3% global, 2 mm) for both delivered Arc-MBRT plans. Significance. A TPP for Arc-MBRT is successfully developed and Arc-MBRT plans showed the potential to improve the dosimetric plan quality similar as Static-MBRT while maintaining short delivery times of photon-only treatments. This further facilitates integration of pMLC-based MBRT into clinical practice.

The Anatomy and Evolution of a Quality Proton Therapy Plan Check Process: An Institutional Review.

There exists limited standard guidance from the physics community on the optimal way to ensure high-reliability proton therapy treatments. Following the guidance of AAPM MPPG 4a/4b and Task Groups 100/275, our institution has developed, implemented, and maintained strategies over the last five years to streamline workflows, enable more complex treatments, standardize procedures, and manage risk from slip or omission type errors in proton therapy. The evolution and success of that is observed from an institutional analysis of past operations data. From the outset, standard care paths were used to sequence our workflows. These chains of tasks were well-defined and timestamped upon completion for every patient. Over five years, additional multiple interventions were implemented including clinical site standardization, checklists, root cause analysis, and failure mode identification. These were used to counter environmental variables with potential to disrupt timelines like growing patient volume, staffing demands, and new technique adoptions. These interventions went through extensive design, validation, and continuous improvement phases by the entire clinical team. Using ARIA v15.5, task timestamp data from the past 5 years were mined for physics proton-specific planning tasks and used to compute how early/late each task was in comparison to the expected due time. Average and standard deviation data were computed and used to create control charts. This coupled with the average time per year was cross-referenced with interventions to determine the impact on plan preparation timelines. Over 5 years, the standard care path length reduced from 16 to 13 business days. The greatest impact on timelines was observed from standardizing clinical site guidelines. This minimized variability in task times and allowed the creation of checklists. By standardizing, we identified slack as well the need for new tasks. Overall, the average days late or early went from on-average late to on-average early (Table 1). The control charts indicate that many tasks stabilized in recent years. Furthermore, these interventions allowed us to safely increase the complexity of our proton plans using Monte Carlo dose calculations, 4D-optimization, robustness standards, repainting, and increased beams with no slippage in overall timelines. Clinical site standardization, checklists, consistent process re-evaluation, and a team attitude of continuous improvement allowed us to improve control of our processes while simultaneously expanding treatment complexity and meeting the goals of our quality management plan.

End-to-End Verification and Dosimetric Comparative Study of Brainlab Monte Carlo and Eclipse Acuros XB Photon Dose Calculation Algorithm for VMAT SRS Planning

We commissioned the Brainlab Monte Carlo Dose Calculation Algorithm for VMAT SRS planning and verified it by measurements and comparisons with two other algorithms: Pencil beam and Eclipse Acuros. The end-to-end verification and dosimetric comparative study results are reported in this abstract. Brainlab Elements Cranial SRS (v3.0) provides single lesion planning using VMAT optimization, thus allowing dose modulation with MLC leaf positioning, dose rate, and gantry speed. We commissioned and performed quality assurance for the available dose calculation algorithms, including Pencil Beam (PB) algorithm with only reference beam data (RBM PB) and PB with full beam data (Elements PB), and Monte Carlo (MC) algorithm XVMC. Calculation between the two were compared to each other and to Acuros XB dose calculation algorithm by Varian. Open field MLC, static cone, dynamic MLC, and conical cone plans were calculated with each algorithm. IBA CC01 ionization chamber was used for each measurement, and small field correction factors as determined in TRT-483 were applied. End-to-end tests were performed using an anthropomorphic stereotactic end-to-end verification (STEEV) phantom from CIRS and a phantom/diode array, StereoPHAN/SRSMapCHECK from SunNuclear. Each phantom was CT scanned with 0.5 mm slice thickness. Four clinical plans were optimized in Brainlab Elements Treatment Planning System (TPS). Each plan was calculated with the following algorithms: Elements PB, RBM PB, MC, and Acuros XB with 1 mm dose grid size. The delivered dose was measured with a SunNuclear SRSMapCHECK diode array detector. The calculated dose was compared with the measured dose by Gamma analysis with DTA 1%/1mm, 2%/1mm, and 3%/1mm. The results of point dose measurements for field size larger than 1 × 1 cm2 among measured dose, dose calculated by pencil beam algorithms, and dose calculated by Monte Carlo algorithm were in excellent agreement (1.45% ± 0.7%). For the small rectangular field sizes (0.4 × 1, 0.2 × 1 cm2), Monte Carlo calculation showed superior accuracy and robustness to pencil beam algorithm when compared with measured dose, with percent dose difference 13% and -2.2%, respectively. Monte Carlo calculation have higher gamma results compared with pencil beam algorithm due more accurate calculations with heterogenous materials. Acuros XB showed comparable accuracy with MC in terms of gamma passing rate. The SRS MapCHECK measurement agrees dosimetrically with the plans calculated by Pencil Beam algorithm and the Monte Carlo algorithm XVMC by Brainlab, as well as the Acuros XB dose calculation algorithm by Varian. Point dose calculation for small field dosimetry and gamma analysis using SRS MapCHECK both showed that Monte Carlo algorithm is more robust and is superior in regions of heterogenous materials. Therefore, we recommend that Monte Carlo algorithm for dose calculation be used in clinical SRS and SRT cases.

Comprehensive Beam Modeling, Secondary Dose Computations and Treatment Planning for a 1.5 T MRgRT System

Magnetic resonance imaging guided radiotherapy (MRgRT) combines soft tissue visualization with online adaptive radiotherapy. The MRgRT workflow is characterized by many steps which needs to be performed swiftly and therefore greatly benefits from automation. The purpose of this study was to model a MRgRT system for dose computation and intensity modulated radiotherapy (IMRT) planning within a 1.5 T magnetic field in an independent treatment planning system (iTPS) with automation functionalities. A beam model for a 1.5 T MRgRT system was commissioned in an iTPS using beam profiles and output factor measurements. The cryostat of the MRgRT system was modeled using a cylindrical multi-layer combination of epoxy and aluminum and matched to source-to-surface dependent cryostat scatter measurement in air, and corrected for angular dependent cryostat transmission readings. The beam model was used with a fast Monte Carlo dose engine to account for the electron return and electron streaming effects within an external magnetic field. The multi-leaf collimator (MLC) was characterized with a novel synchronous and asynchronous sweeping gap (aSG) test. The aSGs have a shift (between 0 - 40 mm) between adjacent leaves which remains constant over the sweep. Measured doses map the shadowing due to the tongue-and-groove (TG) exposure and TG and leaf tip (LT) parameters are derived to match this within the iTPS. Clinical IMRT plans of 10 prostate, 5 lymph node and 5 rectal plans created in the default clinical TPS were recomputed in the iTPS and evaluated with the corresponding plan-specific quality assurance measurements. In addition, three IMRT plans were optimized within the iTPS, delivered with the MRgRT system and evaluated using PSQA using a 3%/3mm gamma criterium with a 10% threshold. Monte Carlo dose computation in the iTPS closely resembled the measured profiles in the presence of the 1.5 T magnetic field. The cryostat scatter simulations were <0.7% compared to the measurements and literature. The aSG/SGs test demonstrated that the TG width gradually increased up to 1 mm for a distance of 15 mm away from the leaf tip end. These effects were closely replicated in the iTPS with a difference of <1.5% for 95% of the aSGs. The difference between the clinical dose and the dose calculation in the iTPS was, on average, <0.5% within the volume receiving 50% of the maximum dose. The gamma pass rate was 100% for 98% of the PSQA results. The plans optimized within the iTPS were successfully delivered at the MRgRT system. We successfully modeled and commissioned a 1.5 T MRgRT system in an independent TPS. The beam model can be used for a second opinion dose computation in a magnetic field and for direct treatment planning. Next, the beam model will be incorporated in a semi-automated and adaptive workflow using the iTPS.

Proton Based Stereotactic Radiotherapy for Skull Base Patients: Dosimetric Comparison to 4 Modern Radiation Treatment Modalities

Re-irradiation with ablative doses to a smaller target volume and strict critical structure constraint is a challenge for modern radiation planning and delivery systems. Several advanced radiation treatment techniques can be used for fractionated stereotactic ablative radiosurgery (FSRS) in select patients with unresectable recurrent head and neck tumors. In this study, in order to better understand the dosimetry advantage of each technique, we compare the stereotactic treatment plans of our new small spot size Hitachi proton treatment unit to those of CyberKnife stereotactic radiosurgery (CK), Gamma Knife radiosurgery (GK), volumetric modulated arc therapy (VMAT), and MR Linac radiotherapy (MRL). Ten FSRS skull base patients treated at our institution using VMAT (n = 5) or GK (n = 5) techniques. Intensity-modulated proton therapy (IMPT) plans were created in Raystation using Monte Carlo dose calculation algorithm. VMAT, CK, GK and MRL plans were generated in RayStation, Accuray Precision, Leksell Gamma Plan, and Monaco treatment planning systems, separately. Planning goals were to achieve the best target coverage of prescribed dose without compromising the critical organs at risk dose volume constraints of the clinical treatment plans. Plans were compared based on percent CTV coverage, Paddick conformity index (PCI), gradient index (GI, V50/V100), dose homogeneity index (HI, (D2-D98)/D50), low dose bath volume (LDBV, ratio of total volume irradiated between 20% and 50% prescription dose and the target volume), beam-on-time (BOT), and mean/maximum doses to brainstems. The median target volume was 15.5 cm3 (range 1.0 - 36.23 cm3). The prescription was 45 Gy in 5 fractions for VMAT patients, and 21 - 27 Gy in 3 fractions for GK patients. The comparison of the treatment plans of these 5 delivery modalities was shown in table. All techniques achieved comparable CTV coverage. GI was superior for GK plans and outstanding in CK and IMPT plans. IMPT plans were also outstanding in regard to BOT and PCI. Significantly improved HI, LDBV and brainstem mean doses were achieved in IMPT plans. For adjacent brainstem and other OARs, maximum doses were comparable among all techniques. In these five advanced radiation therapy modalities, proton therapy SBRT showed dosimetric advantage over other modalities to spare nearby OARs without sacrifice of target coverage. Further studies are needed to utilize this clinical benefit and investigate plan robustness.

Development and validation of MonteRay, a fast Monte Carlo dose engine for carbon ion beam radiotherapy.

Monte Carlo (MC) simulations are considered the gold-standard for accuracy in radiotherapy dose calculation; so far however, no commercial treatment planning system (TPS) provides a fast MC for supporting clinical practice in carbon ion therapy. To extend and validate the in-house developed fast MC dose engine MonteRay for carbon ion therapy, including physical and biological dose calculation. MonteRay is a CPU MC dose calculation engine written in C++ that is capable of simulating therapeutic proton, helium and carbon ion beams. In this work, development steps taken to include carbon ions in MonteRay are presented. Dose distributions computed with MonteRay are evaluated using a comprehensive validation dataset, including various measurements (pristine Bragg peaks, spread out Bragg peaks in water and behind an anthropomorphic phantom) and simulations of a patient plan. The latter includes both physical and biological dose comparisons. Runtimes of MonteRay were evaluated against those of FLUKA MC on a standard benchmark problem. Dosimetric comparisons between MonteRay and measurements demonstrated good agreement. In terms of pristine Bragg peaks, mean errors between simulated and measured integral depth dose distributions were between -2.3% and +2.7%. Comparing SOBPs at 5, 12.5 and 20cm depth, mean absolute relative dose differences were 0.9%, 0.7% and 1.6% respectively. Comparison against measurements behind an anthropomorphic head phantom revealed mean absolute dose differences of with global 3%/3mm 3D-γ passing rates of 99.3%, comparable to those previously reached with FLUKA (98.9%). Comparisons against dose predictions computed with the clinical treatment planning tool RayStation 11B for a meningioma patient plan revealed excellent local 1%/1mm 3D-γ passing rates of 98% for physical and 94% for biological dose. In terms of runtime, MonteRay achieved speedups against reference FLUKA simulations ranging from 14× to 72×, depending on the beam's energy and the step size chosen. Validations against clinical dosimetric measurements in homogeneous and heterogeneous scenarios and clinical TPS calculations have proven the validity of the physical models implemented in MonteRay. To conclude, MonteRay is viable as a fast secondary MC engine for supporting clinical practice in proton, helium and carbon ion radiotherapy.