Validation of a virtual source model of medical linac for Monte Carlo dose calculation using multi-threaded Geant4

A discrete ordinates Boltzmann solver for application to inverse planning of photons and protons

The aim of this work is to develop a discrete ordinates Boltzmann solver that can be used for calculation of absorbed dose from both photons and protons within an inverse planning optimiser, so as to perform accurate dose calculation throughout the whole of the inverse planning process. With photons, five transport sweeps were performed to obtain scattered photon fluence, and unscattered electron fluence was then obtained and used as a fixed source for solution of the electron transport equations. With protons, continuous slowing down was treated as a fixed source, and five transport sweeps were used to calculate scattered fluence. The total electron or proton fluence was multiplied by the stopping power ratio for the transport medium to obtain absorbed dose. The method was evaluated in homogeneous media and in a lung case where the planning target volume was surrounded by low-density lung material. Photon arc, proton passive scattering and proton arc treatments were considered. The results were compared to a clinically validated convolution dose calculation for photons, and with an analytical method for protons. In water-equivalent media, the discrete ordinates method agrees with the alternative algorithms to within 2%. Convergence is found to be sufficiently complete for water-, lung- and bone-equivalent materials after five iterations. The dose calculated by the relatively simple angular quadrature is seen to be very close to that calculated by a more comprehensive quadrature. For inhomogeneous lung plans, the method shows more heterogeneity of dose to the planning target volume than the comparative methods. The discrete ordinates Boltzmann solver provides a general framework for dose calculation with both photons and protons. The method is suitable for incorporation into an inverse planning optimiser, so that accurate dose calculation in a heterogeneous medium can be obtained throughout inverse planning, with the result that the final dose distribution is as predicted by the optimiser.

A phase space model of a Versa HD linear accelerator for application to Monte Carlo dose calculation in a real-time adaptive workflow

PURPOSE

This study aims to develop and validate a simple geometric model of the accelerator head, from which a particle phase space can be calculated for application to fast Monte Carlo dose calculation in real-time adaptive photon radiotherapy. With this objective in view, the study investigates whether the phase space model can facilitate dose calculations which are compatible with those of a commercial treatment planning system, for convenient interoperability.

MATERIALS AND METHODS

A dual-source model of the head of a Versa HD accelerator (Elekta AB, Stockholm, Sweden) was created. The model used parameters chosen to be compatible with those of 6-MV flattened and 6-MV flattening filter-free photon beams in the RayStation treatment planning system (RaySearch Laboratories, Stockholm, Sweden). The phase space model was used to calculate a photon phase space for several treatment plans, and the resulting phase space was applied to the Dose Planning Method (DPM) Monte Carlo dose calculation algorithm. Simple fields and intensity-modulated radiation therapy (IMRT) treatment plans for prostate and lung were calculated for benchmarking purposes and compared with the convolution-superposition dose calculation within RayStation.

RESULTS

For simple square fields in a water phantom, the calculated dose distribution agrees to within ±2% with that from the commercial treatment planning system, except in the buildup region, where the DPM code does not model the electron contamination. For IMRT plans of prostate and lung, agreements of ±2% and ±6%, respectively, are found, with slightly larger differences in the high dose gradients.

CONCLUSIONS

The phase space model presented allows convenient calculation of a phase space for application to Monte Carlo dose calculation, with straightforward translation of beam parameters from the RayStation beam model. This provides a basis on which to develop dose calculation in a real-time adaptive setting.

Development of a virtual source model for Monte Carlo-based independent dose calculation for varian linac

Monte Carlo (MC) independent dose calculations are often based on phase-space files (PSF), as they can accurately represent particle characteristics. PSF generally are large and create a bottleneck in computation time. In addition, the number of independent particles is limited by the PSF, preventing further reduction of statistical uncertainty. The purpose of this study is to develop and validate a virtual source model (VSM) to address these limitations. Particles from existing PSF for the Varian TrueBeam medical linear accelerator 6X, 6XFFF, 10X, and 10XFFF beam configurations were tallied, analyzed, and used to generate a dual-source photon VSM that includes electron contamination. The particle density distribution, kinetic energy spectrum, particle direction, and the correlations between characteristics were computed. The VSM models for each beam configuration were validated with water phantom measurements as well as clinical test cases against the original PSF. The new VSM requires 67 MB of disk space for each beam configuration, compared to 50 GB for the PSF from which they are based and effectively remove the bottleneck set by the PSF. At 3% MC uncertainty, the VSM approach reduces the calculation time by a factor of 14 on our server. MC doses obtained using the VSM approach were compared against PSF-generated doses in clinical test cases and measurements in a water phantom using a gamma index analysis. For all tests, the VSMs were in excellent agreement with PSF doses and measurements (>90% passing voxels between doses and measurements). Results of this study indicate the successful derivation and implementation of a VSM model for Varian Linac that significantly saves computation time without sacrificing accuracy for independent dose calculation.

Beam modeling and commissioning for Monte Carlo photon beam on an Elekta Versa HD LINAC

PURPOSE

This study aims at analyzing beam data commissioning along with verifying Monte Carlo-based treatment planning system on the basis of the manufacturer guidelines for Elekta Versa HD Linear Accelerator. Moreover, evaluating the beam match process in terms of quality index, photon profile and multi leaf collimator (MLC) offset is aimed as well.

MATERIALS AND METHODS

The process of collecting beam data for Monaco 5.51 Treatment Planning System commissioning was done based on the instructions provided by the manufacturer as well as AAPM TG-106. Monte Carlo analysis was done for output factors in water, percent depth dose and beam profiles. A set of eight static and intensity modulated radiation therapy fields were used to verify the MLC parameters.

RESULTS

The difference between the measured and modeled penetrative quality (D₁₀) was achieved to be 0.54%. The output factors for 6 MV photon energy were measured and the difference between the measured and Monte Carlo output results was smaller than 1% for all the fields. The average percentage of passing the gamma criteria for commissioning test fields was (95+-4)%, however, the minimum agreement was 87.5% belonging to "7SEGA". Additionally, the agreement between both LINAC is 96%, however, the second LINAC reveals a positive offset in the point of approximately -4 cm on the x-axis at the crossplane.

CONCLUSION

Test commissioning was successfully verified using a homogeneous phantom for point dose measurements, post modelling MLC parameters and patient QA plans. All plan parameters pass the gamma criteria. 6 MV photon beam was successfully commissioned for Elekta VersaHD LINAC and is ready for clinical implementation.

Implementation of a new virtual source model in Gate 9.0 package to simulate Elekta Synergy MLCi2 6 MV accelerator

Monte Carlo simulation is appreciated as an extraordinary technique to investigate particle physic processes in Radiation Therapy. This task offers a new Virtual Source Model (VSM) based on an innovative reconstruction method to extract energy and angular distribution from the Python phase space output data. Extensive comparisons of dose distributions are performed to evaluate VSM simulation precision. Four squared field configurations extending from 3 × 3 to 20 × 20 cm²are chosen for dose calculation to test field size and symmetry influences. To evaluate simulation accuracy, the beam quality parameters (such asD₁₀(%),d_max(cm),d₈₀(cm), andTPR(20/10)) also validation tests (gamma index formalism for 2%/2 mm criteria, Distance To Agreement DTA, and the estimator standard error (ϵ,ϵ_max)) are determined. Good agreement is achieved in terms of beam quality parameters and validation tests for each evaluated beam size, within a computation time of 58 hours and 17 hours on 20 nodes (presents 160 CPUs) of the full simulation and the VSM, respectively. This advanced VSM generated for the Elekta Synergy MLCi2 platform displays an uncomplicated approach. It is a great example of reconstructing different x-ray beams of various linac accelerators to facilitate its integration in cancer treatment.

An automated optimization strategy to design collimator geometry for small field radiation therapy systems

PURPOSE

To develop an automated optimization strategy to facilitate collimator design for small-field radiotherapy systems.

METHODS

We developed an objective function that links the dose profile characteristics (FWHM, penumbra, and central dose rate) and the treatment head geometric parameters (collimator thickness/radii, source-to-distal-collimator distance[SDC]) for small-field radiotherapy systems. We performed optimization using a downhill simplex algorithm. We applied this optimization strategy to a linac-based radiosurgery system to determine the optimal geometry of four pencil-beam collimators to produce 5, 10, 15, and 20mm diameter photon beams (from a 6.7MeV, 2.1mmFWHM electron beam). Two different optimizations were performed to prioritize minimum penumbra or maximum central dose rate for each beam size. We compared the optimized geometric parameters and dose distributions to an existing clinical system (CyberKnife).

RESULTS

When minimum penumbra was prioritized, using the same collimator thickness and SDC (40cm) as a CyberKnife system, the optimized collimator upstream and downstream radii agreed with the CyberKnife system within 3-14%, the optimized output factors agreed within 0-8%, and the optimized transverse and percentage depth dose profiles matched those of the CyberKnife with the penumbras agreeing within 2%. However, when maximum dose rate was prioritized, allowing both the collimator thickness and SDC to change, the central dose rate for larger collimator sizes (10, 15, 20mm) could be increased by about 1.5-2 times at the cost of 1.5-2 times larger penumbras. No further improvement in central dose rate for the 5mm beam size could be achieved.

CONCLUSIONS

We developed an automated optimization strategy to design the collimator geometry for small-field radiation therapy systems. Using this strategy, the penumbra-prioritized dose distribution and geometric parameters agree well with the CyberKnife system as an example, suggesting that this system was designed to prioritize sharp penumbra. This represents proof-of-principle that an automated optimization strategy may apply to more complex collimator designs with multiple optimization parameters.