J Perl

Geant4 developments and applications

Geant4 is a software toolkit for the simulation of the passage of particles through matter. It is used by a large number of experiments and projects in a variety of application domains, including high energy physics, astrophysics and space science, medical physics and radiation protection. Its functionality and modeling capabilities continue to be extended, while its performance is enhanced. An overview of recent developments in diverse areas of the toolkit is presented. These include performance optimization for complex setups; improvements for the propagation in fields; new options for event biasing; and additions and improvements in geometry, physics processes and interactive capabilities

TOPAS: An innovative proton Monte Carlo platform for research and clinical applications

PURPOSE While Monte Carlo particle transport has proven useful in many areas (treatment head design, dose calculation, shielding design, and imaging studies) and has been particularly important for proton therapy (due to the conformal dose distributions and a finite beam range in the patient), the available general purpose Monte Carlo codes in proton therapy have been overly complex for most clinical medical physicists. The learning process has large costs not only in time but also in reliability. To address this issue, we developed an innovative proton Monte Carlo platform and tested the tool in a variety of proton therapy applications. METHODS Our approach was to take one of the already-established general purpose Monte Carlo codes and wrap and extend it to create a specialized user-friendly tool for proton therapy. The resulting tool, TOol for PArticle Simulation (TOPAS), should make Monte Carlo simulation more readily available for research and clinical physicists. TOPAS can model a passive scattering or scanning beam treatment head, model a patient geometry based on computed tomography (CT) images, score dose, fluence, etc., save and restart a phase space, provides advanced graphics, and is fully four-dimensional (4D) to handle variations in beam delivery and patient geometry during treatment. A custom-designed TOPAS parameter control system was placed at the heart of the code to meet requirements for ease of use, reliability, and repeatability without sacrificing flexibility. RESULTS We built and tested the TOPAS code. We have shown that the TOPAS parameter system provides easy yet flexible control over all key simulation areas such as geometry setup, particle source setup, scoring setup, etc. Through design consistency, we have insured that user experience gained in configuring one component, scorer or filter applies equally well to configuring any other component, scorer or filter. We have incorporated key lessons from safety management, proactively removing possible sources of user error such as line-ordering mistakes. We have modeled proton therapy treatment examples including the UCSF eye treatment head, the MGH stereotactic alignment in radiosurgery treatment head and the MGH gantry treatment heads in passive scattering and scanning modes, and we have demonstrated dose calculation based on patient-specific CT data. Initial validation results show agreement with measured data and demonstrate the capabilities of TOPAS in simulating beam delivery in 3D and 4D. CONCLUSIONS We have demonstrated TOPAS accuracy and usability in a variety of proton therapy setups. As we are preparing to make this tool freely available for researchers in medical physics, we anticipate widespread use of this tool in the growing proton therapy community.

Modeling the TrueBeam linac using a CAD to Geant4 geometry implementation: Dose and IAEA-compliant phase space calculations

PURPOSE To create an accurate 6 MV Monte Carlo simulation phase space for the Varian TrueBeam treatment head geometry imported from CAD (computer aided design) without adjusting the input electron phase space parameters. METHODS GEANT4 v4.9.2.p01 was employed to simulate the 6 MV beam treatment head geometry of the Varian TrueBeam linac. The electron tracks in the linear accelerator were simulated with Parmela, and the obtained electron phase space was used as an input to the Monte Carlo beam transport and dose calculations. The geometry components are tessellated solids included in GEANT4 as GDML (generalized dynamic markup language) files obtained via STEP (standard for the exchange of product) export from Pro/Engineering, followed by STEP import in Fastrad, a STEP-GDML converter. The linac has a compact treatment head and the small space between the shielding collimator and the divergent are of the upper jaws forbids the implementation of a plane for storing the phase space. Instead, an IAEA (International Atomic Energy Agency) compliant phase space writer was implemented on a cylindrical surface. The simulation was run in parallel on a 1200 node Linux cluster. The 6 MV dose calculations were performed for field sizes varying from 4 x 4 to 40 x 40 cm2. The voxel size for the 60 x 60 x 40 cm3 water phantom was 4 x 4 x 4 mm3. For the 10 x 10 cm2 field, surface buildup calculations were performed using 4 x 4 x 2 mm3 voxels within 20 mm of the surface. RESULTS For the depth dose curves, 98% of the calculated data points agree within 2% with the experimental measurements for depths between 2 and 40 cm. For depths between 5 and 30 cm, agreement within 1% is obtained for 99% (4 x 4), 95% (10 x 10), 94% (20 x 20 and 30 x 30), and 89% (40 x 40) of the data points, respectively. In the buildup region, the agreement is within 2%, except at 1 mm depth where the deviation is 5% for the 10 x 10 cm2 open field. For the lateral dose profiles, within the field size for fields up to 30 x 30 cm2, the agreement is within 2% for depths up to 10 cm. At 20 cm depth, the in-field maximum dose difference for the 30 x 30 cm2 open field is within 4%, while the smaller field sizes agree within 2%. Outside the field size, agreement within 1% of the maximum dose difference is obtained for all fields. The calculated output factors varied from 0.938 +/- 0.015 for the 4 x 4 cm2 field to 1.088 +/- 0.024 for the 40 x 40 cm2 field. Their agreement with the experimental output factors is within 1%. CONCLUSIONS The authors have validated a GEANT4 simulated IAEA-compliant phase space of the TrueBeam linac for the 6 MV beam obtained using a high accuracy geometry implementation from CAD. These files are publicly available and can be used for further research.

The accuracy of EGSnrc, Geant4 and PENELOPE Monte Carlo systems for the simulation of electron scatter in external beam radiotherapy

Three widely used Monte Carlo systems were benchmarked against recently published measurements of the angular distribution of 13 MeV and 20 MeV electrons scattered from foils of different atomic numbers and thicknesses. Source and geometry were simulated in detail to calculate electron fluence profiles 118.2 cm from the exit window. Results were compared to the measured fluence profiles and the characteristic angle where the fluence drops to 1/e of its maximum value. EGSnrc and PENELOPE results, on average, agreed with measurement within 1 standard deviation experimental uncertainty, with EGSnrc estimating slightly lower scatter than measurement and PENELOPE slightly higher scatter. Geant4.9.2 overestimated the characteristic angle for the lower atomic number foils by as much as 10%. Retuning of the scatter distributions in Geant4 led to a much better agreement with measurement, close to that achieved with the other codes. The 3% differences from measurement seen with all codes for at least some of the foils would result in clinically significant errors in the fluence profiles (2%/4 mm), given accurate knowledge of the electron source and treatment head geometry used in radiotherapy. Further improvement in simulation accuracy is needed to achieve 1%/1 mm agreement with measurement for the full range of beam energies, foil atomic number and thickness used in radiotherapy. EGSnrc would achieve this accuracy with an increase in thickness of the mylar sheets in the monitor chamber, PENELOPE with a decrease in thickness.

Extension of TOPAS for the simulation of proton radiation effects considering molecular and cellular endpoints

The aim of this work is to extend a widely used proton Monte Carlo tool, TOPAS, towards the modeling of relative biological effect (RBE) distributions in experimental arrangements as well as patients. TOPAS provides a software core which users configure by writing parameter files to, for instance, define application specific geometries and scoring conditions. Expert users may further extend TOPAS scoring capabilities by plugging in their own additional C++ code. This structure was utilized for the implementation of eight biophysical models suited to calculate proton RBE. As far as physics parameters are concerned, four of these models are based on the proton linear energy transfer, while the others are based on DNA double strand break induction and the frequency-mean specific energy, lineal energy, or delta electron generated track structure. The biological input parameters for all models are typically inferred from fits of the models to radiobiological experiments. The model structures have been implemented in a coherent way within the TOPAS architecture. Their performance was validated against measured experimental data on proton RBE in a spread-out Bragg peak using V79 Chinese Hamster cells. This work is an important step in bringing biologically optimized treatment planning for proton therapy closer to the clinical practice as it will allow researchers to refine and compare pre-defined as well as user-defined models.

Layered mass geometry: a novel technique to overlay seeds and applicators onto patient geometry in Geant4 brachytherapy simulations

A problem faced by all Monte Carlo (MC) particle transport codes is how to handle overlapping geometries. The Geant4 MC toolkit allows the user to create parallel geometries within a single application. In Geant4 the standard mass-containing geometry is defined in a simulation volume called the World Volume. Separate parallel geometries can be defined in parallel worlds, that is, alternate three dimensional simulation volumes that share the same coordinate system with the World Volume for geometrical event biasing, scoring of radiation interactions, and/or the creation of hits in detailed readout structures. Until recently, only one of those worlds could contain mass so these parallel worlds provided no solution to simplify a complex geometric overlay issue in brachytherapy, namely the overlap of radiation sources and applicators with a CT based patient geometry. The standard method to handle seed and applicator overlay in MC requires removing CT voxels whose boundaries would intersect sources, placing the sources into the resulting void and then backfilling the remaining space of the void with a relevant material. The backfilling process may degrade the accuracy of patient representation, and the geometrical complexity of the technique precludes using fast and memory-efficient coding techniques that have been developed for regular voxel geometries. The patient must be represented by the less memory and CPU-efficient Geant4 voxel placement technique, G4PVPlacement, rather than the more efficient G4NestedParameterization (G4NestedParam). We introduce for the first time a Geant4 feature developed to solve this issue: Layered Mass Geometry (LMG) whereby both the standard (CT based patient geometry) and the parallel world (seeds and applicators) may now have mass. For any area where mass is present in the parallel world, the parallel mass is used. Elsewhere, the mass of the standard world is used. With LMG the user no longer needs to remove patient CT voxels that would include for example seeds. The patient representation can be a regular voxel grid, conducive to G4NestedParam, and the patient CT derived materials remain exact, avoiding the inaccuracy of the backfilling technique. Post-implant dosimetry for one patient with (125)I permanent seed implant was performed using Geant4 version 9.5.p01 using three different geometrical techniques. The first technique was the standard described above (G4PVPlacement). The second technique placed patient voxels as before, but placed seeds with LMG (G4PVPlacement+LMG). The third technique placed patient voxels through G4NestedParam and seeds through LMG (G4NestedParam+LMG). All the scenarios were calculated with 3 different image compression factors to manipulate the number of voxels. Additionally, the dosimetric impact of the backfilling technique was investigated for the case of calcifications in close proximity of sources. LMG eliminated the need for backfilling and simplified geometry description. Of the two LMG techniques, G4PVPlacement+LMG had no benefit to calculation time or memory use, actually increasing calculation time, but G4NestedParam+LMG reduced both calculation time and memory. The benefits of G4NestedParam+LMG over standard G4PVPlacement increased with increasing voxel numbers. For the case of calcifications in close proximity to sources, LMG not only increased efficiency but also yielded more accurate dose calculation than G4PVPlacement. G4NestedParam in combination with LMG present a new, efficient approach to simulate radiation sources that overlap patient geometry. Cases with brachytherapy applicators would constitute a direct extension of the method.

Geometrical splitting technique to improve the computational efficiency in Monte Carlo calculations for proton therapy

PURPOSE To present the implementation and validation of a geometrical based variance reduction technique for the calculation of phase space data for proton therapy dose calculation. METHODS The treatment heads at the Francis H Burr Proton Therapy Center were modeled with a new Monte Carlo tool (TOPAS based on Geant4). For variance reduction purposes, two particle-splitting planes were implemented. First, the particles were split upstream of the second scatterer or at the second ionization chamber. Then, particles reaching another plane immediately upstream of the field specific aperture were split again. In each case, particles were split by a factor of 8. At the second ionization chamber and at the latter plane, the cylindrical symmetry of the proton beam was exploited to position the split particles at randomly spaced locations rotated around the beam axis. Phase space data in IAEA format were recorded at the treatment head exit and the computational efficiency was calculated. Depth-dose curves and beam profiles were analyzed. Dose distributions were compared for a voxelized water phantom for different treatment fields for both the reference and optimized simulations. In addition, dose in two patients was simulated with and without particle splitting to compare the efficiency and accuracy of the technique. RESULTS A normalized computational efficiency gain of a factor of 10-20.3 was reached for phase space calculations for the different treatment head options simulated. Depth-dose curves and beam profiles were in reasonable agreement with the simulation done without splitting: within 1% for depth-dose with an average difference of (0.2 ± 0.4)%, 1 standard deviation, and a 0.3% statistical uncertainty of the simulations in the high dose region; 1.6% for planar fluence with an average difference of (0.4 ± 0.5)% and a statistical uncertainty of 0.3% in the high fluence region. The percentage differences between dose distributions in water for simulations done with and without particle splitting were within the accepted clinical tolerance of 2%, with a 0.4% statistical uncertainty. For the two patient geometries considered, head and prostate, the efficiency gain was 20.9 and 14.7, respectively, with the percentages of voxels with gamma indices lower than unity 98.9% and 99.7%, respectively, using 2% and 2 mm criteria. CONCLUSIONS The authors have implemented an efficient variance reduction technique with significant speed improvements for proton Monte Carlo simulations. The method can be transferred to other codes and other treatment heads.

The Geant4 Visualisation System

The Geant4 Visualization System is a multi-driver graphics system designed to serve the Geant4 Simulation Toolkit. It is aimed at the visualization of Geant4 data, primarily detector descriptions and simulated particle trajectories and hits. It can handle a variety of graphical technologies simultaneously and interchangeably, allowing the user to choose the visual representation most appropriate to requirements. It conforms to the low-level Geant4 abstract graphical user interfaces and introduces new abstract classes from which the various drivers are derived and that can be straightforwardly extended, for example, by the addition of a new driver. It makes use of an extendable class library of models and filters for data representation and selection. The Geant4 Visualization System supports a rich set of interactive commands based on the Geant4 command system. It is included in the Geant4 code distribution and maintained and documented like other components of Geant4.

Linking computer-aided design (CAD) to Geant4-based Monte Carlo simulations for precise implementation of complex treatment head geometries

Most of the treatment head components of medical linear accelerators used in radiation therapy have complex geometrical shapes. They are typically designed using computer-aided design (CAD) applications. In Monte Carlo simulations of radiotherapy beam transport through the treatment head components, the relevant beam-generating and beam-modifying devices are inserted in the simulation toolkit using geometrical approximations of these components. Depending on their complexity, such approximations may introduce errors that can be propagated throughout the simulation. This drawback can be minimized by exporting a more precise geometry of the linac components from CAD and importing it into the Monte Carlo simulation environment. We present a technique that links three-dimensional CAD drawings of the treatment head components to Geant4 Monte Carlo simulations of dose deposition.

Validation of the radiobiology toolkit TOPAS-nBio in simple DNA geometries

Computational simulations offer a powerful tool for quantitatively investigating radiation interactions with biological tissue and can help bridge the gap between physics, chemistry and biology. The TOPAS collaboration is tackling this challenge by extending the current Monte Carlo tool to allow for sub-cellular in silico simulations in a new extension, TOPAS-nBio. TOPAS wraps and extends the Geant4 Monte Carlo simulation toolkit and the new extension allows the modeling of particles down to vibrational energies (∼2eV) within realistic biological geometries. Here we present a validation of biological geometries available in TOPAS-nBio, by comparing our results to two previously published studies. We compare the prediction of strand breaks in a simple linear DNA strand from TOPAS-nBio to a published Monte Carlo track structure simulation study. While TOPAS-nBio confirms the trend in strand break generation, it predicts a higher frequency of events below an energy of 17.5eV compared to the alternative Monte Carlo track structure study. This is due to differences in the physics models used by each code. We also compare the experimental measurement of strand breaks from incident protons in DNA plasmids to TOPAS-nBio simulations. Our results show good agreement of single and double strand breaks predicting a similar increase in the strand break yield with increasing LET.