Monte Carlo dose verification of VMAT treatment plans using Elekta Agility 160-leaf MLC

Monte Carlo modeling of the Elekta Versa HD and patient dose calculation with EGSnrc/BEAMnrc

Introduction

Numerous studies have proven the Monte Carlo method to be an accurate means of dose calculation. Although there are several commercial Monte Carlo treatment planning systems (TPSs), some clinics may not have access to these resources. We present a method for routine, independent patient dose calculations from treatment plans generated in a commercial TPS with our own Monte Carlo model using free, open‐source software.

Materials and methods

A model of the Elekta Versa HD linear accelerator was developed using the EGSnrc codes. A MATLAB script was created to take clinical patient plans and convert the DICOM RTP files into a format usable by EGSnrc. Ten patients’ treatment plans were exported from the Monaco TPS to be recalculated using EGSnrc. Treatment simulations were done in BEAMnrc, and doses were calculated using Source 21 in DOSXYZnrc. Results were compared to patient plans calculated in the Monaco TPS and evaluated in Verisoft with a gamma criterion of 3%/2 mm.

Results

Our Monte Carlo model was validated within 1%/1‐mm accuracy of measured percent depth doses and profiles. Gamma passing rates ranged from 82.1% to 99.8%, with 7 out of 10 plans having a gamma pass rate over 95%. Lung and prostate patients showed the best agreement with doses calculated in Monaco. All statistical uncertainties in DOSXYZnrc were less than 3.0%.

Conclusion

A Monte Carlo model for routine patient dose calculation was successfully developed and tested. This model allows users to directly recalculate DICOM RP files containing patients’ plans that have been exported from a commercial TPS.

Determination and validation of the initial beam parameters of Elekta Agility collimator head by Monte Carlo simulations

The availability of geometrical, physical, and initial beam parameters for Monte Carlo (MC) simulations of the Elekta Agility collimator head has become very difficult due to the proprietary nature of this data. This study presents strategies to independently determine the geometrical and physical properties of the components and initial beam parameters of the Agility collimator head for full beam simulations and postulates a benchmarking process using the EGSnrc MC toolkit. Target material of W (90%) and Re (10%) of 0.09 cm thickness, flattening filter of 1.77 cm thick stainless steel placed on 0.5 cm Al disc, and primary and secondary collimators of Tungsten alloy have been found to best fit the Agility head. The initial beam energy of 6.0 MeV with a radial distribution given as full-width half maxima (FWHM) of 0.301 cm (crossline) × 0.201 cm (inline) for 6 MV beam with a mean angular spread of 1.34° has been found best fitting the model. Variations of 0.29% and 0.59% have been noted in the measured and calculated values of TPR_20,10 and D₁₀ respectively. More than 90% dose points for all simulations passed the 2D gamma criteria of 3% DD, 3 mm DTA. This MC model of the Agility head can be used for dose calculation and validation of advanced treatment techniques.

Determination of the Small-Field Output Factor for 6 MV Photon Beam Using EGSnrc Monte Carlo

Accuracy of ionization chamber (IC) to measure the scatter output factor (Scp) of a linear accelerator (linac) is crucial, especially in small field (<4 cm × 4 cm). The common IC volume of 0.6 cc is not adequate for small-field measurement and not all radiotherapy centers can afford to purchase additional IC due to the additional cost. This study aimed to determine the efficiency of the EGSnrc Monte Carlo (MC) to calculate the Scp for various field sizes including small field in Elekta Synergy (Agility multileaf collimator) linac. The BEAMnrc and DOSXYZnrc user codes were used to simulate a 6 MV linac model for various field sizes and calculate the radiation dose output in water phantom. The modeled linac treatment head was validated by comparing the percentage depth dose (PDD), beam profile, and beam quality (Tissue Phantom Ratio (TPR)20,10) with the IC measurement. The validated linac model was simulated to calculate the Scp consisting of collimator scatter factor (Sc) and phantom scatter factor (Sp). The PDD and beam profile of the simulated field sizes were within a good agreement of ±2% compared with the measured data. The TPR20,10 value was 0.675 for field size 10 cm × 10 cm. The Scp, Sc, and Sp simulated values were close to the IC measurement within ±2% difference. The simulation for Sc and Sp in 3 cm × 3 cm field size was calculated to be 0.955 and 0.884, respectively. In conclusion, this study validated the efficiency of the MC simulation as a promising tool for the Scp calculation including small-field size for linac.

A multivariate approach to determine electron beam parameters for a Monte Carlo 6 MV Linac model: Statistical and machine learning methods

PURPOSE

This study aimed to determine the optimal initial electron beam parameters of a Linac for radiotherapy with a multivariate approach using statistical and machine-learning tools.

METHODS

For MC beam commissioning, a 6 MV Varian Clinac was simulated using the Geant4 toolkit. The authors investigated the relations between simulated dose distribution and initial electron beam parameters, namely, mean energy (E), energy spread (ES), and radial beam size (RS). The goodness of simulation was evaluated by the slope of differences between the simulated and the golden beam data. The best-fit combination of the electron beam parameters that minimized the slope of dose difference was searched through multivariate methods using conventional statistical methods and machine-learning tools of the scikit-learn library.

RESULTS

Simulation results with 87 combinations of the electron beam parameters were analyzed. Regardless of being univariate or multivariate, traditional statistical models did not recommend a single parameter set simultaneously minimizing slope of dose differences for percent depth dose (PDD) and lateral dose profile (LDP). Two machine learning classification modules, RandomForestClassifier and BaggingClassifier, agreed in recommending (E = 6.3 MeV, ES = ±5.0%, RS = 1.0 mm) for predicting simultaneous acceptance of PDD and LDP.

CONCLUSIONS

The machine learning with random-forest and bagging classifier modules recommended a consistent result. It was possible to draw an optimal electron beam parameter set using multivariate methods for MC simulation of a radiotherapy 6 MV Linac.

Characterizing a Geant4 Monte Carlo model of a multileaf collimator for a TrueBeam™ linear accelerator

PURPOSE

The purpose of this work was to develop and validate a multileaf collimator (MLC) model for a TrueBeam™ linac using Geant4 Monte Carlo (MC) simulation kit.

METHODS

A Geant4 application was developed to accurately represent TrueBeam™ linac. Pre-computed phase-space file in a plane just above the jaws was used for radiation transport. A Varian 120 leaf Millennium™ MLC was modeled using geometry and material specifications provided by the manufacturer using Geant4 constructs. Leaf characteristics e.g. tongue-groove design, variable thickness, interleaf gap were simulated. The linac model was validated by comparing simulated dose profiles and depth-doses with experimental data using an ionization chamber in water. Dosimetric characteristics of the MLC such as inter- and intra-leaf leakage, penumbra effect, MLC leaf positioning, and dynamic characteristics were also investigated.

RESULTS

For the depth dose curves, 99% of the calculated data points agree within 1% of the experimental values for the 4 × 4 cm² and 10 × 10 cm² and within 2% of the experimental values for 20 × 20, 30 × 30 and 40 × 40 cm² jaw defined fields. The cross-plane dose profiles show agreement <2% for depths up to 10 cm and to within 4% beyond 10 cm. MLC dosimetric characterization with MC agree well with film measurements. The rounded leaf penumbra remained constant throughout the range of leaf motion.

CONCLUSIONS

The TrueBeam™ linac equipped with 120-leaf MLC was successfully modeled using Geant4. The accuracy of the model was verified by comparing the simulations with experiments. The model may be utilized for independent dose verification and QA of IMRT.

Optimizing beam models for dosimetric accuracy over a wide range of treatments

This work presents a systematic approach for testing a dose calculation algorithm over a variety of conditions designed to span the possible range of clinical treatment plans. Using this method, a TrueBeam STx machine with high definition multi-leaf collimators (MLCs) was commissioned in the RayStation treatment planning system (TPS). The initial model parameters values were determined by comparing TPS calculations with standard measured depth dose and profile curves. The MLC leaf offset calibration was determined by comparing measured and calculated field edges utilizing a wide range of MLC retracted and over-travel positions. The radial fluence was adjusted using profiles through both the center and corners of the largest field size, and through measurements of small fields that were located at highly off-axis positions. The flattening filter source was adjusted to improve the TPS agreement for the output of MLC-defined fields with much larger jaw openings. The MLC leaf transmission and leaf end parameters were adjusted to optimize the TPS agreement for highly modulated intensity-modulated radiotherapy (IMRT) plans. The final model was validated for simple open fields, multiple field configurations, the TG 119 C-shape target test, and a battery of clinical IMRT and volumetric-modulated arc therapy (VMAT) plans. The commissioning process detected potential dosimetric errors of over 10% and resulted in a final model that provided in general 3% dosimetric accuracy. This study demonstrates the importance of using a variety of conditions to adjust a beam model and provides an effective framework for achieving high dosimetric accuracy.

Dosimetric and localization accuracy of Elekta high definition dynamic radiosurgery

BACKGROUND AND PURPOSE

With the increasingly prominent role of stereotactic radiosurgery in radiation therapy, there is a clinical need for robust, efficient, and accurate solutions for targeting multiple sites with one patient setup. The end-to-end accuracy of high definition dynamic radiosurgery with Elekta treatment planning and delivery systems was investigated in this study.

MATERIALS AND METHODS

A patient-derived CT scan was used to create a radiosurgery plan to seven targets in the brain. Monaco was used for treatment planning using 5 VMAT non-coplanar arcs. Prior to delivery, 3D-printed phantoms from RTsafe were ordered including a gel phantom for 3D dosimetry, phantom with 2D film insert, and an ion chamber phantom for point dose measurement. Delivery was performed using the Elekta VersaHD, XVI cone-beam CT, and HexaPOD six degree of freedom tabletop.

RESULTS

Absolute dose accuracy was verified within 2%. 3D global gamma analysis in the film measurement revealed 3%/2 mm passing rates >95%. Gel dosimetry 3D global gamma analysis (3%/2 mm) were above 90% for all targets with the exception of one. Results were indicative of typical end-to-end accuracies (<1 mm spatial uncertainty, 2% dose accuracy) within 4 cm of isocenter. Beyond 4 cm, 2 mm accuracy was found.

CONCLUSIONS

High definition dynamic radiosurgery expands clinically acceptable stereotactic accuracy to a sphere around isocenter allowing for radiosurgery of several targets with one setup with a high degree of dosimetric precision. Gel dosimetry proved to be an essential tool for the validation of the 3D dose distributions in this technique.