A combined approach of variance-reduction techniques for the efficient Monte Carlo simulation of linacs

Validation of an in vivo transit dosimetry algorithm using Monte Carlo simulations and ionization chamber measurements

PURPOSE

Transit dosimetry is a safety tool based on the transit images acquired during treatment. Forward-projection transit dosimetry software, as PerFRACTION, compares the transit images acquired with an expected image calculated from the DICOM plan, the CT, and the structure set. This work aims to validate PerFRACTION expected transit dose using PRIMO Monte Carlo simulations and ionization chamber measurements, and propose a methodology based on MPPG5a report.

METHODS

The validation process was divided into three groups of tests according to MPPG5a: basic dose validation, IMRT dose validation, and heterogeneity correction validation. For the basic dose validation, the fields used were the nine fields needed to calibrate PerFRACTION and three jaws-defined. For the IMRT dose validation, seven sweeping gaps fields, the MLC transmission and 29 IMRT fields from 10 breast treatment plans were measured. For the heterogeneity validation, the transit dose of these fields was studied using three phantoms: 10 , 30 , and a 3 cm cork slab placed between 10 cm of solid water. The PerFRACTION expected doses were compared with PRIMO Monte Carlo simulation results and ionization chamber measurements.

RESULTS

Using the 10 cm solid water phantom, for the basic validation fields, the root mean square (RMS) of the difference between PerFRACTION and PRIMO simulations was 0.6%. In the IMRT fields, the RMS of the difference was 1.2%. When comparing respect ionization chamber measurements, the RMS of the difference was 1.0% both for the basic and the IMRT validation. The average passing rate with a γ(2%/2 mm, TH = 20%) criterion between PRIMO dose distribution and PerFRACTION expected dose was 96.0% ± 5.8%.

CONCLUSION

We validated PerFRACTION calculated transit dose with PRIMO Monte Carlo and ionization chamber measurements adapting the methodology of the MMPG5a report. The methodology presented can be applied to validate other forward-projection transit dosimetry software.

Monte Carlo simulation of the Varian TrueBeam flattened-filtered beams using a surrogate geometry in PRIMO

BACKGROUND

Monte Carlo simulation of radiation transport for medical linear accelerators (linacs) requires accurate knowledge of the geometrical description of the linac head. Since the geometry of Varian TrueBeam machines has not been disclosed, the manufacturer distributes phase-space files of the linac patient-independent part to allow researchers to compute absorbed dose distributions using the Monte Carlo method. This approach limits the possibility of achieving an arbitrarily small statistical uncertainty. This work investigates the use of the geometry of the Varian Clinac 2100, which is included in the Monte Carlo system PRIMO, as a surrogate.

METHODS

Energy, radial and angular distributions extracted from the TrueBeam phase space files published by the manufacturer and from phase spaces tallied with PRIMO for the Clinac 2100 were compared for the 6, 8, 10 and 15 MV flattened-filtered beams. Dose distributions in water computed for the two sets of PSFs were compared with the Varian Representative Beam Data (RBD) for square fields with sides ranging from 3 to 30 cm. Output factors were calculated for square fields with sides ranging from 2 to 40 cm.

RESULTS

Excellent agreement with the RBD was obtained for the simulations that employed the phase spaces distributed by Varian as well as for those that used the surrogate geometry, reaching in both cases Gamma ([Formula: see text], 2 mm) pass rates larger than [Formula: see text], except for the 15 MV surrogate. This result supports previous investigations that suggest a change in the material composition of the TrueBeam 15 MV flattening filter. In order to get the said agreement, PRIMO simulations were run using enlarged transport parameters to compensate the discrepancies between the actual and surrogate geometries.

CONCLUSIONS

This work sustains the claim that the simulation of the 6, 8 and 10 MV flattening-filtered beams of the TrueBeam linac can be performed using the Clinac 2100 model of PRIMO without significant loss of accuracy.

Complete patient exposure during paediatric brain cancer treatment for photon and proton therapy techniques including imaging procedures

Background

In radiotherapy, especially when treating children, minimising exposure of healthy tissue can prevent the development of adverse outcomes, including second cancers. In this study we propose a validated Monte Carlo framework to evaluate the complete patient exposure during paediatric brain cancer treatment.

Materials and methods

Organ doses were calculated for treatment of a diffuse midline glioma (50.4 Gy with 1.8 Gy per fraction) on a 5-year-old anthropomorphic phantom with 3D-conformal radiotherapy, intensity modulated radiotherapy (IMRT), volumetric modulated arc therapy (VMAT) and intensity modulated pencil beam scanning (PBS) proton therapy. Doses from computed tomography (CT) for planning and on-board imaging for positioning (kV-cone beam CT and X-ray imaging) accounted for the estimate of the exposure of the patient including imaging therapeutic dose. For dose calculations we used validated Monte Carlo-based tools (PRIMO, TOPAS, PENELOPE), while lifetime attributable risk (LAR) was estimated from dose-response relationships for cancer induction, proposed by Schneider et al.

Results

Out-of-field organ dose equivalent data of proton therapy are lower, with doses between 0.6 mSv (testes) and 120 mSv (thyroid), when compared to photon therapy revealing the highest out-of-field doses for IMRT ranging between 43 mSv (testes) and 575 mSv (thyroid). Dose delivered by CT ranged between 0.01 mSv (testes) and 72 mSv (scapula) while a single imaging positioning ranged between 2 μSv (testes) and 1.3 mSv (thyroid) for CBCT and 0.03 μSv (testes) and 48 μSv (scapula) for X-ray. Adding imaging dose from CT and daily CBCT to the therapeutic demonstrated an important contribution of imaging to the overall radiation burden in the course of treatment, which is subsequently used to predict the LAR, for selected organs.

Conclusion

The complete patient exposure during paediatric brain cancer treatment was estimated by combining the results from different Monte Carlo-based dosimetry tools, showing that proton therapy allows significant reduction of the out-of-field doses and secondary cancer risk in selected organs.

Dosimetric Evaluation of Radiation Treatment Planning for Simultaneous Integrated Boost Technique Using Monte Carlo Simulation

Monte Carlo (MC) techniques have been recognized as the gold standard for the simulation of radiation transport in radiotherapy. The aim of the study is to perform dosimetric evaluation of Simultaneous Integrated Boost (SIB) radiation treatment planning using MC simulation approach. The geometrical source modeling and simulation of 6 MV Flattening Filter Free (FFF)beam from TrueBeam linear accelerator have been carried out to simulate Volumetric Modulated Arc Therapy (VMAT) plans using MC simulation software PRIMO. All the SIB plans have been generated using VMAT techniques for patients with locally advanced postoperative head-and-neck squamous cell carcinoma in Eclipse Treatment Planning System (TPS) retrospectively. TPS plans have been compared against their respective MC-simulated plans in PRIMO. The quality assessments of plans have been performed using several dose volume parameters, plan quality indices, and methods of gamma analysis. Dmean, D50%, and D2% received by planning target volume (PTV), PTV60, and PTV52 have been found significantly lower in TPS-generated plans compared to MC-simulated plans. D100%, D98%, and D95% received by PTV60 exhibit good agreement. However, PTV52 shows a significant deviation between TPS and MC plans. The mean organ-at-risk doses have been found significantly lower in TPS plans compared to MC plans. TPS and MC plans have been found in close agreement within gamma acceptance criteria of 3% Dose Difference (DD) and 3 mm Distance to Agreement (DTA). Dose distributions computed using MC simulation techniques are reliable, accurate, and consistent with analytical anisotropic algorithm. Plan quality indices have been found slightly compromised in MC-simulated plans compared with TPS-generated plans appeared to be a true representation of real dose distribution obtained from MC simulation technique. Validation using MC simulation approach provides an independent secondary check for ensuring accuracy of TPS-generated plan.

A correlated sampling-based Monte Carlo simulation for fast CBCT iterative scatter correction

BACKGROUND

In recent years, cone-beam computed tomography (CBCT) has played an important role in medical imaging. However, the applications of CBCT are limited due to the severe scatter contamination. Conventional Monte Carlo (MC) simulation can provide accurate scatter estimation for scatter correction, but the expensive computational cost has always been the bottleneck of MC method in clinical application.

PURPOSE

In this work, an MC simulation method combined with a variance reduction technique called correlated sampling is proposed for fast iterative scatter correction.

METHODS

Correlated sampling exploits correlation between similar simulation systems to reduce the variance of interest quantities. Specifically, conventional MC simulation is first performed on the scatter-contaminated CBCT to generate the initial scatter signal. In the subsequent correction iterations, scatter estimation is then updated by applying correlated MC sampling to the latest corrected CBCT images by reusing the random number sequences of the task-related photons in conventional MC. Afterward, the corrected projections obtained by subtracting the scatter estimation from raw projections are utilized for FDK reconstruction. These steps are repeated until an adequate scatter correction is obtained. The performance of the proposed framework is evaluated by the accuracy of the scatter estimation, the quality of corrected CBCT images and efficiency.

RESULTS

Overall, the difference in mean absolute percentage error between scatter estimation with and without correlated sampling is 0.25% for full-fan case and 0.34% for half-fan case, respectively. In simulation studies, scatter artifacts are substantially eliminated, where the mean absolute error value is reduced from 15 to 2 HU in full-fan case and from 53 to 13 HU in half-fan case. Scatter-to-primary ratio is reduced to 0.02 for full-fan and 0.04 for half-fan, respectively. In phantom study, the contrast-to-noise ratio (CNR) is increased by a factor of 1.63, and the contrast is increased by a factor of 1.77. As for clinical studies, the CNR is improved by 11% and 14% for half-fan and full-fan, respectively. The contrast after correction is increased by 19% for half-fan and 44% for full-fan. Furthermore, root mean square error is also effectively reduced, especially from 78 to 4 HU for full-fan. Experimental results demonstrate that the figure of merit is improved between 23 and 43 folds when using correlated sampling. The proposed method takes less than 25 s for the whole iterative scatter correction process.

CONCLUSIONS

The proposed correlated sampling-based MC simulation method can achieve fast and accurate scatter correction for CBCT, making it suitable for real-time clinical use.

Assessment of Surface and Build-up Doses for a 6 MV Photon Beam using Parallel Plate Chamber, EBT3 Gafchromic Films, and PRIMO Monte Carlo Simulation Code

Background:

Accurate assessment of surface and build-up doses has a key role in radiotherapy, especially for the superficial lesions with uncertainties involved while performing measurements in the build-up region.

Objective:

This study aimed to assess surface and build-up doses for 6 MV photon beam from linear accelerator using parallel plate ionization chamber, EBT3 Gafchromic films, and PRIMO Monte Carlo (MC) simulation code.

Material and Methods:

In this experimental study, parallel plate chamber (PPC05) and EBT3 Gafchromic films were used to measure doses in a build-up region for 6 MV beam from the linear accelerator for different field sizes at various depths ranging from 0 to 2 cm from the surface with 100 cm source to surface distance (SSD) in a solid water phantom. Measured results were compared with Monte Carlo simulated results using PENELOPE-based PRIMO simulation code for the same setup conditions. Effect of gantry angle incidence and SSD were also analyzed for depth doses at the surface and build-up regions using PPC05 ion chamber and EBT3 Gafchromic films.

Results:

Doses measured at the surface were 14.78%, 19.87%, 25.83%, and 31.54% for field sizes of 5×5, 10×10, 15×15, and 20×20 cm², respectively for a 6 MV photon beam with a parallel plate chamber and 14.20%, 19.14%, 25.149%, and 30.90%, respectively for EBT3 Gafchromic films. Both measurement sets were in good agreement with corresponding simulated results from the PRIMO MC simulation code; doses increase with the increase in field sizes.

Conclusion:

Good agreement was observed between the measured depth doses using parallel plate ionization chamber, EBT3 Gafchromic films, and the simulated depth doses using PRIMO Monte Carlo simulation code.

Experimental Validation of an Analytical Program and a Monte Carlo Simulation for the Computation of the Far Out-of-Field Dose in External Beam Photon Therapy Applied to Pediatric Patients

Background

The out-of-the-field absorbed dose affects the probability of primary second radiation-induced cancers. This is particularly relevant in the case of pediatric treatments. There are currently no methods employed in the clinical routine for the computation of dose distributions from stray radiation in radiotherapy. To overcome this limitation in the framework of conventional teletherapy with photon beams, two computational tools have been developed—one based on an analytical approach and another depending on a fast Monte Carlo algorithm. The purpose of this work is to evaluate the accuracy of these approaches by comparison with experimental data obtained from anthropomorphic phantom irradiations.

Materials and Methods

An anthropomorphic phantom representing a 5-year-old child (ATOM, CIRS) was irradiated considering a brain tumor using a Varian TrueBeam linac. Two treatments for the same planned target volume (PTV) were considered, namely, intensity-modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT). In all cases, the irradiation was conducted with a 6-MV energy beam using the flattening filter for a prescribed dose of 3.6 Gy to the PTV. The phantom had natLiF : Mg, Cu, P (MCP-N) thermoluminescent dosimeters (TLDs) in its 180 holes. The uncertainty of the experimental data was around 20%, which was mostly attributed to the MCP-N energy dependence. To calculate the out-of-field dose, an analytical algorithm was implemented to be run from a Varian Eclipse TPS. This algorithm considers that all anatomical structures are filled with water, with the exception of the lungs which are made of air. The fast Monte Carlo code dose planning method was also used for computing the out-of-field dose. It was executed from the dose verification system PRIMO using a phase-space file containing 3x109 histories, reaching an average standard statistical uncertainty of less than 0.2% (coverage factor k = 1 ) on all voxels scoring more than 50% of the maximum dose. The standard statistical uncertainty of out-of-field voxels in the Monte Carlo simulation did not exceed 5%. For the Monte Carlo simulation the actual chemical composition of the materials used in ATOM, as provided by the manufacturer, was employed.

Results

In the out-of-the-field region, the absorbed dose was on average four orders of magnitude lower than the dose at the PTV. For the two modalities employed, the discrepancy between the central values of the TLDs located in the out-of-the-field region and the corresponding positions in the analytic model were in general less than 40%. The discrepancy in the lung doses was more pronounced for IMRT. The same comparison between the experimental and the Monte Carlo data yielded differences which are, in general, smaller than 20%. It was observed that the VMAT irradiation produces the smallest out-of-the-field dose when compared to IMRT.

Conclusions

The proposed computational methods for the routine calculation of the out-of-the-field dose produce results that are similar, in most cases, with the experimental data. It has been experimentally found that the VMAT irradiation produces the smallest out-of-the-field dose when compared to IMRT for a given PTV.

Monte Carlo simulation of conical collimators for stereotactic radiosurgery with a 6 MV flattening-filter-free photon beam

PURPOSE

Conical collimators, or cones, are tertiary collimators that attach to a radiotherapy linac and are suited for the stereotactic radiosurgery treatment of small brain lesions. The small diameter of the most used cones makes difficult the acquisition of the dosimetry data needed for the commissioning of treatment planning systems. Although many publications report dosimetric data of conical collimators for stereotactic radiosurgery, most of the works use different setups, which complicates comparisons. In other cases, the cone output factors reported do not take into account the effect of the small cone diameter on the detector response. Finally, few data exist on the dosimetry of cones with flattening-filter-free (FFF) beams from modern linac models. This work aims at obtaining a dosimetric characterization of the conical collimators manufactured by Brainlab AG (Munich, Germany) in a 6 MV FFF beam from a TrueBeam STx linac (Varian Medical Systems).

METHODS

Percentage depth dose curves, lateral dose profiles and cone output factors were obtained using Monte Carlo simulations for the cones with diameters of 4, 5, 6, 7.5, 8, 10, 12.5, 15, 17.5, 20, 25, and 30 mm. The simulation of the linac head was carried out with the PRIMO Monte Carlo software, and the simulations of the cones and the water phantom were run with the general-purpose Monte Carlo code PENELOPE. The Monte Carlo model was validated by comparing the simulation results with measurements performed for the cones of 4, 5, and 7.5 mm of diameter using a stereotactic field diode, a microDiamond detector and EBT3 radiochromic film. In addition, for those cones, simulations and measurements were done for comparison purposes, by reproducing the experimental setups from the available publications.

RESULTS

The experimental data acquired for the cones of 4, 5, and 7.5 mm validated the developed Monte Carlo model. The simulations accurately reproduced the experimental depths of maximum dose and the dose ratio at 20- and 10-cm depth (PDD_20/10 ). A good agreement was obtained between simulated and experimental lateral dose profiles: The differences in the full-width at half-maximum were smaller than 0.2 mm, and the differences in the penumbra 80%-20% were smaller than 0.25 mm. The difference between the simulated and the average of the experimental output factors for the cones of 4, 5, and 7.5 mm of diameter was 0.0%, 0.0%, and 3.0%, respectively, well within the statistical uncertainty of the simulations (4.4% with coverage factor k = 2). It was also found that the simulated cone output factors agreed within 2% with the average of output factors reported in the literature for a variety of setup conditions, detectors, beam qualities, and cone manufacturers.

CONCLUSION

A Monte Carlo model of cones for stereotactic radiosurgery has been developed and validated. The cone dosimetry dataset obtained in this work, consisting of percentage depth doses, lateral dose profiles and output factors, is useful to benchmark data acquired for the commissioning of cone-based radiosurgery treatment planning systems.

DeepMC: a deep learning method for efficient Monte Carlo beamlet dose calculation by predictive denoising in magnetic resonance-guided radiotherapy

Emerging magnetic resonance (MR) guided radiotherapy affords significantly improved anatomy visualization and, subsequently, more effective personalized treatment. The new therapy paradigm imposes significant demands on radiation dose calculation quality and speed, creating an unmet need for the acceleration of Monte Carlo (MC) dose calculation. Existing deep learning approaches to denoise the final plan MC dose fail to achieve the accuracy and speed requirements of large-scale beamlet dose calculation in the presence of a strong magnetic field for online adaptive radiotherapy planning. Our deep learning dose calculation method, DeepMC, addresses these needs by predicting low-noise dose from extremely noisy (but fast) MC-simulated dose and anatomical inputs, thus enabling significant acceleration. DeepMC simultaneously reduces MC sampling noise and predicts corrupted dose buildup at tissue-air material interfaces resulting from MR-field induced electron return effects. Here we demonstrate our model's ability to accelerate dose calculation for daily treatment planning by a factor of 38 over traditional low-noise MC simulation with clinically meaningful accuracy in deliverable dose and treatment delivery parameters. As a post-processing approach, DeepMC provides compounded acceleration of large-scale dose calculation when used alongside established MC acceleration techniques in variance reduction and graphics processing unit-based MC simulation.

Tungsten carbide and LMPA electron cutouts: comparison and validation using Monte Carlo modelling and measurement of dose

Electron applicator cutouts for radiation therapy electron beam shaping are typically cast from Low Melting Point Alloys (LMPA), such as cerrobend. In this work, we describe the Monte Carlo modelling of novel 3D printed cutouts based on tungsten carbide powder and the resulting dose profiles subject to Elekta Agility electron beams. Cerrobend cutouts were also modelled using the Monte Carlo code EGSnrc. Cerrobend and tungsten carbide cutouts were found to have the same dose profiles within model variance. Computed profiles and percentage depth dose (PDDs) curves of the Elekta Agility accelerator model using standard cutouts in water were found to agree with water tank measurements using gamma criteria of 2%/2mm. The Monte Carlo computed dose profiles of the tungsten carbide cutouts in a polystyrene phantom were also found to agree with liquid-filled ionization chamber array measurements using gamma criteria of 2%/2mm. We conclude that the tungsten carbide cutouts are clinically equivalent to LMPA cutouts.

Validation of PRIMO Monte Carlo Model of Clinac®iX 6MV Photon Beam

Purpose

This study aims to model 6MV photon of Clinac^®iX linear accelerator using PRIMO Monte Carlo (MC) code and to assess PRIMO as an independent MC-based dose verification and quality assurance tool.

Materials and Methods

The modeling of Clinac^®iX linear accelerator has been carried out by using PRIMO simulation software (Version 0.3.1.1681). The simulated beam parameters were compared against the measured beam data of the Clinac^®iX machine. The PRIMO simulation model of Clinac^®iX was also validated against Eclipse^® Acuros XB dose calculations in the case of both homogenous and inhomogeneous mediums. The gamma analysis method with the acceptance criteria of 2%, 2 mm was used for the comparison of dose distributions.

Results

Gamma analysis shows a minimum pass percentage of 99% for depth dose curves and 95.4% for beam profiles. The beam quality index and output factors and absolute point dose show good agreement with measurements. The validation of PRIMO dose calculations, in both homogeneous and inhomogeneous medium, against Acuros^® XB shows a minimum gamma analysis pass rate of 99%.

Conclusions

This study shows that the research software PRIMO can be used as a treatment planning system-independent quality assurance and dose verification tool in daily clinical practice. Further validation will be performed with different energies, complex multileaf collimators fields, and with dynamic treatment fields.

Validation of irtGPUMCD, a GPU-based Monte Carlo internal dosimetry framework for radionuclide therapy

PURPOSE

Monte Carlo (MC) simulations are highly desirable for dose treatment planning and evaluation in radiation oncology. This is true also in emerging nuclear medicine applications such as internal radiotherapy with radionuclides. The purpose of this study is the validation of irtGPUMCD, a GPU-based MC code for dose calculations in internal radiotherapy.

METHODS

The female and male phantoms of the International Commission on Radiological Protection (ICRP 110) were used as benchmarking geometries for this study focused on ¹⁷⁷Lu and including ^99mTc and ¹³¹I. Dose calculations were also conducted for a real patient. For phantoms, twelve anatomical structures were considered as target/source organs. The S-values were evaluated with irtGPUMCD simulations (10⁸ photons), with gamma branching ratios of ICRP 107 publication. The ¹⁷⁷Lu electrons S-values were calculated for source organs only, based on local deposition of dose in irtGPUMCD. The S-value relative difference between irtGPUMCD and IDAC-DOSE were evaluated for all targets/sources considered. A DVHs comparison with GATE was conducted. An exponential track length estimator was introduced in irtGPUMCD to increase computational efficiency.

RESULTS

The relative S-value differences between irtGPUMCD and IDAC-DOSE were <5% while this comparison with GATE was <1%. The DVHs dosimetric indices comparison between GATE and irtGPUMCD for the patient led to an excellent agreement (<2%). The time required for the simulation of 10⁸ photons was 1.5 min for the female phantom, and one minute for the real patient (<1% uncertainty). These results are promising and let envision the use of irtGPUMCD for internal dosimetry in clinical applications.

MLC parameters from static fields to VMAT plans: an evaluation in a RT-dedicated MC environment (PRIMO)

Background

PRIMO is a graphical environment based on PENELOPE Monte Carlo (MC) simulation of radiotherapy beams able to compute dose distribution in patients, from plans with different techniques. The dosimetric characteristics of an HD-120 MLC (Varian), simulated using PRIMO, were here compared with measurements, and also with Acuros calculations (in the Eclipse treatment planning system, Varian).

Materials and methods

A 10 MV FFF beam from a Varian EDGE linac equipped with the HD-120 MLC was used for this work. Initially, the linac head was simulated inside PRIMO, and validated against measurements in a water phantom. Then, a series of different MLC patterns were established to assess the MLC dosimetric characteristics. Those tests included: i) static fields: output factors from MLC shaped fields (2 × 2 to 10 × 10 cm²), alternate open and closed leaf pattern, MLC transmitted dose; ii) dynamic fields: dosimetric leaf gap (DLG) evaluated with sweeping gaps, tongue and groove (TG) effect assessed with profiles across alternate open and closed leaves moving across the field. The doses in the different tests were simulated in PRIMO and then compared with EBT3 film measurements in solid water phantom, as well as with Acuros calculations. Finally, MC in PRIMO and Acuros were compared in some clinical cases, summarizing the clinical complexity in view of a possible use of PRIMO as an independent dose calculation check.

Results

Static output factor MLC tests showed an agreement between MC calculated and measured OF of 0.5%. The dynamic tests presented DLG values of 0.033 ± 0.003 cm and 0.032 ± 0.006 cm for MC and measurements, respectively. Regarding the TG tests, a general agreement between the dose distributions of 1–2% was achieved, except for the extreme patterns (very small gaps/field sizes and high TG effect) were the agreement was about 4–5%. The analysis of the clinical cases, the Gamma agreement between MC in PRIMO and Acuros dose calculation in Eclipse was of 99.5 ± 0.2% for 3%/2 mm criteria of dose difference/distance to agreement.

Conclusions

MC simulations in the PRIMO environment were in agreement with measurements for the HD-120 MLC in a 10 MV FFF beam from a Varian EDGE linac. This result allowed to consistently compare clinical cases, showing the possible use of PRIMO as an independent dose calculation check tool.

Treatment verification using Varian's dynalog files in the Monte Carlo system PRIMO

Background

The PRIMO system is a computer software that allows the Monte Carlo simulation of linear accelerators and the estimation of the subsequent absorbed dose distributions in phantoms and computed tomographies. The aim of this work is to validate the methods incorporated in PRIMO to evaluate the deviations introduced in the dose distributions by errors in the positioning of the leaves of the multileaf collimator recorded in the dynalog files during patient treatment.

Methods

The reconstruction of treatment plans from Varian’s dynalog files was implemented in the PRIMO system. Dose distributions were estimated for volumetric-modulated arc therapy clinical cases of prostate and head&neck using the PRIMO fast Monte Carlo engine DPM. Accuracy of the implemented reconstruction methods was evaluated by comparing dose distributions obtained from the simulations of the plans imported from the treatment planning system with those obtained from the simulations of the plans reconstructed from the expected leaves positions recorded in the dynalog files. The impact on the dose of errors in the positions of the leaves was evaluated by comparing dose distributions estimated for plans reconstructed from expected leaves positions with dose distributions estimated from actual leaves positions. Gamma pass rate (GPR), a hereby introduced quantity named percentage of agreement (PA) and the percentage of voxels with a given systematic difference (α/Δ) were the quantities used for the comparisons. Errors were introduced in leaves positions in order to study the sensitivity of these quantities.

Results

A good agreement of the dose distributions obtained from the plan imported from the TPS and from the plan reconstructed from expected leaves positions was obtained. Not a significantly better agreement was obtained for an imported plan with an increased number of control points such as to approximately match the number of records in the dynalogs. When introduced errors were predominantly in one direction, the methods employed in this work were sensitive to dynalogs with root-mean-square errors (RMS) ≥0.2 mm. Nevertheless, when errors were in both directions, only RMS >1.2 mm produced detectable deviations in the dose. The PA and the α/Δ showed more sensitive to errors in the leaves positions than the GPR.

Conclusions

Methods to verify the accuracy of the radiotherapy treatment from the information recorded in the Varian’s dynalog files were implemented and verified in this work for the PRIMO system. Tolerance limits could be established based on the values of PA and α/Δ. GPR _3,3 is not recommended as a solely evaluator of deviations introduced in the dose by errors captured in the dynalog files.

PENELOPE/PRIMO-calculated photon and electron spectra from clinical accelerators

BACKGROUND

The availability of photon and electron spectra in digital form from current accelerators and Monte Carlo (MC) systems is scarce, and one of the packages widely used refers to linacs with a reduced clinical use nowadays. Such spectra are mainly intended for the MC calculation of detector-related quantities in conventional broad beams, where the use of detailed phase-space files (PSFs) is less critical than for MC-based treatment planning applications, but unlike PSFs, spectra can easily be transferred to other computer systems and users.

METHODS

A set of spectra for a range of Varian linacs has been calculated using the PENELOPE/PRIMO MC system. They have been extracted from PSFs tallied for field sizes of 10 cm × 10 cm and 15 cm × 15 cm for photon and electron beams, respectively. The influence of the spectral bin width and of the beam central axis region used to extract the spectra have been analyzed.

RESULTS

Spectra have been compared to those by other authors showing good agreement with those obtained using the, now superseded, EGS4/BEAM MC code, but significant differences with the most widely used photon data set. Other spectra, particularly for electron beams, have not been published previously for the machines simulated in this work. The influence of the bin width on the spectrum mean energy for 6 and 10 MV beams has been found to be negligible. The size of the region used to extract the spectra yields differences of up to 40% for the mean energies in 10 MV beams, but the maximum difference for TPR _20,10 values derived from depth-dose distributions does not exceed 2% relative to those obtained using the PSFs. This corresponds to k_Q differences below 0.2% for a typical Farmer-type chamber, considered to be negligible for reference dosimetry. Different configurations for using electron spectra have been compared for 6 MeV beams, concluding that the geometry used for tallying the PSFs used to extract the spectra must be accounted for in subsequent calculations using the spectra as a source.

CONCLUSIONS

An up-to-date set of consistent spectra for Varian accelerators suitable for the calculation of detector-related quantities in conventional broad beams has been developed and made available in digital form.

PRIMO Monte Carlo software benchmarked against a reference dosimetry dataset for 6 MV photon beams from Varian linacs

BACKGROUND

The software PRIMO for the Monte Carlo simulation of radiotherapy linacs could potentially act as a independent calculation system to verify the calculations of treatment planning systems. We investigated the suitability of the PRIMO default beam parameters to produce accurate dosimetric results for 6 MV photon beams from Varian Clinac 2100 linacs and 6 MV flattening-filter-free photon beams from Varian TrueBeam linacs.

METHODS

Simulation results with the DPM algorithm were benchmarked against a published reference dosimetry dataset based on point measurements of 25 dosimetric parameters on a large series of linacs. Studied parameters (for several field sizes and depths) were: PDD, off-axis ratios, and output factors for open fields and IMRT/SBRT-style fields. For the latter, the output factors were also determined with radiochromic film and with a small-sized ionization chamber. Benchmark data, PRIMO simulation results and our experimental results were compared.

RESULTS

PDD, off-axis ratios, and open-field output factors obtained from the simulations with the PRIMO default beam parameters agreed with the benchmark data within 2.4% for Clinac 2100, and within 1.3% for TrueBeam. Higher differences were found for IMRT/SBRT-style output factors: up to 2.8% for Clinac 2100, and up to 3.3% for TrueBeam. Experimental output factors agreed with benchmark data within 1.0% (ionization chamber) and within 1.9% (radiochromic film).

CONCLUSIONS

PRIMO default initial beam parameters for 6 MV photon beams from Varian Clinac 2100 linacs and 6 MV FFF photon beams from Varian TrueBeam linacs allowed agreement within 3.3% with a dosimetry database based on measurements of a high number of linacs. This finding represents a first step in the validation of PRIMO for the independent verification of radiotherapy plans.

Optimization of Variance Reduction Techniques used in EGSnrc Monte Carlo Codes

Monte Carlo (MC) simulations are often used in calculations of radiation transport to enable accurate prediction of radiation-dose, even though the computation is relatively time-consuming. In a typical MC simulation, significant computation time is allocated to following non-important events. To address this issue, variance reduction techniques (VRTs) have been suggested for reducing the statistical variance for the same computation time. Among the available MC simulation codes, electron gamma shower (National Research Council of Canada) (EGSnrc) is a general-purpose coupled electron-photon transport code that also features an even-handed, rich set of VRTs. The most well-known VRTs are the photon splitting, Russian roulette (RR), and photon cross-section enhancement (XCSE) techniques. The objective of this work was to determine the optimal combination of VRTs that increases the simulation speed and the efficiency of simulation, without compromising its accuracy. Selection of VRTs was performed using EGSnrc MC User codes, such as cavity and egs_chamber, for simulating various ion chamber geometries using 6 MV photon beams and 1.25 MeV 60Co photon beams. The results show that the combination of XCSE and RR yields the highest efficiency for ion-chamber dose calculations inside a 30 cm × 30 cm × 30 cm water phantom. Hence, properly selecting a different VRT without altering the underlying physics increases the efficiency of MC simulations for ion-chamber dose calculation.

Monte Carlo systems used for treatment planning and dose verification

General-purpose radiation transport Monte Carlo codes have been used for estimation of the absorbed dose distribution in external photon and electron beam radiotherapy patients since several decades. Results obtained with these codes are usually more accurate than those provided by treatment planning systems based on non-stochastic methods. Traditionally, absorbed dose computations based on general-purpose Monte Carlo codes have been used only for research, owing to the difficulties associated with setting up a simulation and the long computation time required. To take advantage of radiation transport Monte Carlo codes applied to routine clinical practice, researchers and private companies have developed treatment planning and dose verification systems that are partly or fully based on fast Monte Carlo algorithms. This review presents a comprehensive list of the currently existing Monte Carlo systems that can be used to calculate or verify an external photon and electron beam radiotherapy treatment plan. Particular attention is given to those systems that are distributed, either freely or commercially, and that do not require programming tasks from the end user. These systems are compared in terms of features and the simulation time required to compute a set of benchmark calculations.

A geometrical model for the Monte Carlo simulation of the TrueBeam linac

Monte Carlo simulation of linear accelerators (linacs) depends on the accurate geometrical description of the linac head. The geometry of the Varian TrueBeam linac is not available to researchers. Instead, the company distributes phase-space files of the flattening-filter-free (FFF) beams tallied at a plane located just upstream of the jaws. Yet, Monte Carlo simulations based on third-party tallied phase spaces are subject to limitations. In this work, an experimentally based geometry developed for the simulation of the FFF beams of the Varian TrueBeam linac is presented. The Monte Carlo geometrical model of the TrueBeam linac uses information provided by Varian that reveals large similarities between the TrueBeam machine and the Clinac 2100 downstream of the jaws. Thus, the upper part of the TrueBeam linac was modeled by introducing modifications to the Varian Clinac 2100 linac geometry. The most important of these modifications is the replacement of the standard flattening filters by ad hoc thin filters. These filters were modeled by comparing dose measurements and simulations. The experimental dose profiles for the 6 MV and 10 MV FFF beams were obtained from the Varian Golden Data Set and from in-house measurements performed with a diode detector for radiation fields ranging from 3  ×  3 to 40  ×  40 cm(2) at depths of maximum dose of 5 and 10 cm. Indicators of agreement between the experimental data and the simulation results obtained with the proposed geometrical model were the dose differences, the root-mean-square error and the gamma index. The same comparisons were performed for dose profiles obtained from Monte Carlo simulations using the phase-space files distributed by Varian for the TrueBeam linac as the sources of particles. Results of comparisons show a good agreement of the dose for the ansatz geometry similar to that obtained for the simulations with the TrueBeam phase-space files for all fields and depths considered, except for the 40  ×  40 cm(2) field where the ansatz geometry was able to reproduce the measured dose more accurately. Our approach overcomes some of the limitations of using the Varian phase-space files. It makes it possible to: (i) adapt the initial beam parameters to match measured dose profiles; (ii) reduce the statistical uncertainty to arbitrarily low values; and (iii) assess systematic uncertainties (type B) by using different Monte Carlo codes. One limitation of using phase-space files that is retained in our model is the impossibility of performing accurate absolute dosimetry simulations because the geometrical description of the TrueBeam ionization chamber remains unknown.

PRIMO: a graphical environment for the Monte Carlo simulation of Varian and Elekta linacs

BACKGROUND

The accurate Monte Carlo simulation of a linac requires a detailed description of its geometry and the application of elaborate variance-reduction techniques for radiation transport. Both tasks entail a substantial coding effort and demand advanced knowledge of the intricacies of the Monte Carlo system being used.

METHODS

PRIMO, a new Monte Carlo system that allows the effortless simulation of most Varian and Elekta linacs, including their multileaf collimators and electron applicators, is introduced. PRIMO combines (1) accurate physics from the PENELOPE code, (2) dedicated variance-reduction techniques that significantly reduce the computation time, and (3) a user-friendly graphical interface with tools for the analysis of the generated data. PRIMO can tally dose distributions in phantoms and computerized tomographies, handle phase-space files in IAEA format, and import structures (planning target volumes, organs at risk) in the DICOM RT-STRUCT standard.

RESULTS

A prostate treatment, conformed with a high definition Millenium multileaf collimator (MLC 120HD) from a Varian Clinac 2100 C/D, is presented as an example. The computation of the dose distribution in 1.86×3.00×1.86 mm3 voxels with an average 2% standard statistical uncertainty, performed on an eight-core Intel Xeon at 2.67 GHz, took 1.8 h-excluding the patient-independent part of the linac, which required 3.8 h but it is simulated only once.

CONCLUSION

PRIMO is a self-contained user-friendly system that facilitates the Monte Carlo simulation of dose distributions produced by most currently available linacs. This opens the door for routine use of Monte Carlo in clinical research and quality assurance purposes. It is free software that can be downloaded from http://www.primoproject.net.