Validation of the TOPAS Monte Carlo toolkit for LDR brachytherapy simulations

Poher, Audran; Murillo, Francisco Berumen; Ma, Y.; Beaulieu, Luc

doi:10.1016/j.ejmp.2022.102516

Cited by 9 publications

(10 citation statements)

References 38 publications

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“…Additionally, since the stretching tail of the %ΔD global distribution is not seen in the %ΔD local distribution, it can be inferred that these high absolute dose differences are, in a relative perspective, small. Thus, the %ΔD global differences reaching more than 1% can be associated with the differences in the high dose region close to the seed, being a known source of divergences from the TG43 1D or 2D approximations (Poher et al 2023). This can also be seen from the agreement of the isodose lines shown in figure 4.…”

Section: Discussionmentioning

confidence: 86%

“…From the standard deviations, being respectively 1.3% and 1.5% for TOPAS and egs_brachy, it is possible to notice that the distribution shape depends on the MC code. This can be explained by the differences observed in the TG43 parameters (anisotropy, geometry radial dose functions) coming from the consensus data and those derived independently from each MC codes (Chamberland et al 2016, Safigholi et al 2020, Poher et al 2023.…”

Section: Discussionmentioning

confidence: 99%

“…Based on the classes previously mentioned, two simulation input file generators have been developed to create the text-based input files required by either egs_brachy (Chamberland et al 2016, Safigholi et al 2020 or TOPAS (Perl et al 2012, Faddegon et al 2020, Berumen et al 2021, Poher et al 2023. Each generator is designed to produce either MC simulations following the TG186 guidelines or reproducing TG43-equivalent conditions (MCTG43).…”

Section: Simulation Input File Generatormentioning

confidence: 99%

“…Depending on the source model found in the DICOMs, the brachytherapy source geometry is taken from the previously published works for both MC codes (Chamberland et al 2016, Safigholi et al 2020, Poher et al 2023. One difference between each code is the removal of inter-seed effects for MCTG43 simulations.…”

Section: Simulation Input File Generatormentioning

confidence: 99%

“…On the other hand, both codes seem in agreement in the medium and lowdose regions (100%, 75%, 30% and 15%), which is also seen in the PTV D90 and V100 differences: being of 0.5% and 0.1%. The dose rate constant difference between both MC codes is not taken into account because its impact is negligible: being a difference of 0.34% (Poher et al 2023).…”

Section: Tg186 Validationmentioning

confidence: 99%

See 4 more Smart Citations

A Monte Carlo dose recalculation pipeline for durable datasets: an I-125 LDR prostate brachytherapy use case

Ouellet,

Lemaréchal,

Berumen-Murillo

et al. 2023

Phys. Med. Biol.

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Monte Carlo (MC) dose datasets are valuable for large-scale dosimetric studies. This work aims to build and validate a DICOM-compliant automated Monte Carlo dose recalculation pipeline with an application to the production of I-125 LDR prostate brachytherapy MC datasets. Built as a self-contained application, the recalculation pipeline ingested clinical DICOM-RT studies, reproduced the treatment into the Monte Carlo simulation, and outputted a traceable and durable dose distribution in the DICOM dose format. MC simulations with TG43-equivalent conditions using both TOPAS and egs brachy MC codes were compared to TG43 calculations to validate the pipeline. The consistency of the pipeline when generating TG186 simulations was measured by comparing simulations made with both MC codes. Finally, egs brachy simulations were run on a 240-patient cohort to simulate a large-scale application of the pipeline. Compared to line source TG43 calculations, simulations with both MC codes had more than 90% of voxels with a local difference under ±1%. Differences of 2.1% and less were seen in dosimetric indices when comparing TG186 simulations from both MC codes. The large-scale comparison of egs brachy simulations with TPS dose calculation seen the same dose overestimation of TG43 calculations showed in previous studies. The MC dose recalculation pipeline built and validated against TG43 calculations in this work efficiently produced durable MC dose datasets. Since the dataset could reproduce previous dosimetric studies within 15h hours at a rate of 20 cases per 25 minutes, the pipeline is a promising tool for future large-scale dosimetric studies.

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Section: Discussionmentioning

confidence: 86%

Section: Discussionmentioning

confidence: 99%

Section: Simulation Input File Generatormentioning

confidence: 99%

Section: Simulation Input File Generatormentioning

confidence: 99%

Section: Tg186 Validationmentioning

confidence: 99%

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A Monte Carlo dose recalculation pipeline for durable datasets: an I-125 LDR prostate brachytherapy use case

Ouellet,

Lemaréchal,

Berumen-Murillo

et al. 2023

Phys. Med. Biol.

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Generation and comparison of 3D dosimetric reference datasets for COMS eye plaque brachytherapy using model‐based dose calculations

Fletcher,

Ballester,

Beaulieu

et al. 2023

Medical Physics

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PurposeA joint Working Group of the American Association of Physicists in Medicine (AAPM), the European Society for Radiotherapy and Oncology (ESTRO), and the Australasian Brachytherapy Group (ABG) was created to aid in the transition from the AAPM TG‐43 dose calculation formalism, the current standard, to model‐based dose calculations. This work establishes the first test cases for low‐energy photon‐emitting brachytherapy using model‐based dose calculation algorithms (MBDCAs).Acquisition and Validation MethodsFive test cases are developed: (1) a single model 6711 125I brachytherapy seed in water, 13 seeds (2) individually and (3) in combination in water, (4) the full Collaborative Ocular Melanoma Study (COMS) 16 mm eye plaque in water, and (5) the full plaque in a realistic eye phantom. Calculations are done with four Monte Carlo (MC) codes and a research version of a commercial treatment planning system (TPS). For all test cases, local agreement of MC codes was within ∼2.5% and global agreement was ∼2% (4% for test case 5). MC agreement was within expected uncertainties. Local agreement of TPS with MC was within 5% for test case 1 and ∼20% for test cases 4 and 5, and global agreement was within 0.4% for test case 1 and 10% for test cases 4 and 5.Data Format and Usage NotesDose distributions for each set of MC and TPS calculations are available online (https://doi.org/10.52519/00005) along with input files and all other information necessary to repeat the calculations.Potential ApplicationsThese data can be used to support commissioning of MBDCAs for low‐energy brachytherapy as recommended by TGs 186 and 221 and AAPM Report 372. This work additionally lays out a sample framework for the development of test cases that can be extended to other applications beyond eye plaque brachytherapy.

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

Kalinowski,

Enger

2024

Medical Physics

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BackgroundThe AAPM TG‐43U1 formalism remains the clinical standard for dosimetry of low‐ and high‐energy γ‐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 treatment planning.PurposeMonte 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 calculation engine.MethodsTG‐43 parameters , Λ, , and were calculated using three commercial source models, one each of 125I, 192Ir, and 60Co, 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 to water.ResultsTG‐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 of 165.ConclusionsDetermination 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 in RapidBrachyMCTPS.

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Validation of the TOPAS Monte Carlo toolkit for LDR brachytherapy simulations

Cited by 9 publications

References 38 publications

A Monte Carlo dose recalculation pipeline for durable datasets: an I-125 LDR prostate brachytherapy use case

A Monte Carlo dose recalculation pipeline for durable datasets: an I-125 LDR prostate brachytherapy use case

Generation and comparison of 3D dosimetric reference datasets for COMS eye plaque brachytherapy using model‐based dose calculations

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

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