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Title: SU-C-BRC-03: Development of a Novel Strategy for On-Demand Monte Carlo and Deterministic Dose Calculation Treatment Planning and Optimization for External Beam Photon and Particle Therapy

Abstract

Purpose: Accurate and fast dose calculation is a prerequisite of precision radiation therapy in modern photon and particle therapy. While Monte Carlo (MC) dose calculation provides high dosimetric accuracy, the drastically increased computational time hinders its routine use. Deterministic dose calculation methods are fast, but problematic in the presence of tissue density inhomogeneity. We leverage the useful features of deterministic methods and MC to develop a hybrid dose calculation platform with autonomous utilization of MC and deterministic calculation depending on the local geometry, for optimal accuracy and speed. Methods: Our platform utilizes a Geant4 based “localized Monte Carlo” (LMC) method that isolates MC dose calculations only to volumes that have potential for dosimetric inaccuracy. In our approach, additional structures are created encompassing heterogeneous volumes. Deterministic methods calculate dose and energy fluence up to the volume surfaces, where the energy fluence distribution is sampled into discrete histories and transported using MC. Histories exiting the volume are converted back into energy fluence, and transported deterministically. By matching boundary conditions at both interfaces, deterministic dose calculation account for dose perturbations “downstream” of localized heterogeneities. Hybrid dose calculation was performed for water and anthropomorphic phantoms. Results: We achieved <1% agreement between deterministic and MCmore » calculations in the water benchmark for photon and proton beams, and dose differences of 2%–15% could be observed in heterogeneous phantoms. The saving in computational time (a factor ∼4–7 compared to a full Monte Carlo dose calculation) was found to be approximately proportional to the volume of the heterogeneous region. Conclusion: Our hybrid dose calculation approach takes advantage of the computational efficiency of deterministic method and accuracy of MC, providing a practical tool for high performance dose calculation in modern RT. The approach is generalizable to all modalities where heterogeneities play a large role, notably particle therapy.« less

Authors:
; ; ;  [1]
  1. Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA (United States)
Publication Date:
OSTI Identifier:
22624314
Resource Type:
Journal Article
Resource Relation:
Journal Name: Medical Physics; Journal Volume: 43; Journal Issue: 6; Other Information: (c) 2016 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; 61 RADIATION PROTECTION AND DOSIMETRY; ACCURACY; ANIMAL TISSUES; APPROXIMATIONS; DISTURBANCES; HYBRIDIZATION; MONTE CARLO METHOD; OPTIMIZATION; PHANTOMS; PLANNING; PLANT TISSUES; PROTON BEAMS; RADIATION DOSES; RADIOTHERAPY

Citation Formats

Yang, Y M, Bush, K, Han, B, and Xing, L. SU-C-BRC-03: Development of a Novel Strategy for On-Demand Monte Carlo and Deterministic Dose Calculation Treatment Planning and Optimization for External Beam Photon and Particle Therapy. United States: N. p., 2016. Web. doi:10.1118/1.4955550.
Yang, Y M, Bush, K, Han, B, & Xing, L. SU-C-BRC-03: Development of a Novel Strategy for On-Demand Monte Carlo and Deterministic Dose Calculation Treatment Planning and Optimization for External Beam Photon and Particle Therapy. United States. doi:10.1118/1.4955550.
Yang, Y M, Bush, K, Han, B, and Xing, L. 2016. "SU-C-BRC-03: Development of a Novel Strategy for On-Demand Monte Carlo and Deterministic Dose Calculation Treatment Planning and Optimization for External Beam Photon and Particle Therapy". United States. doi:10.1118/1.4955550.
@article{osti_22624314,
title = {SU-C-BRC-03: Development of a Novel Strategy for On-Demand Monte Carlo and Deterministic Dose Calculation Treatment Planning and Optimization for External Beam Photon and Particle Therapy},
author = {Yang, Y M and Bush, K and Han, B and Xing, L},
abstractNote = {Purpose: Accurate and fast dose calculation is a prerequisite of precision radiation therapy in modern photon and particle therapy. While Monte Carlo (MC) dose calculation provides high dosimetric accuracy, the drastically increased computational time hinders its routine use. Deterministic dose calculation methods are fast, but problematic in the presence of tissue density inhomogeneity. We leverage the useful features of deterministic methods and MC to develop a hybrid dose calculation platform with autonomous utilization of MC and deterministic calculation depending on the local geometry, for optimal accuracy and speed. Methods: Our platform utilizes a Geant4 based “localized Monte Carlo” (LMC) method that isolates MC dose calculations only to volumes that have potential for dosimetric inaccuracy. In our approach, additional structures are created encompassing heterogeneous volumes. Deterministic methods calculate dose and energy fluence up to the volume surfaces, where the energy fluence distribution is sampled into discrete histories and transported using MC. Histories exiting the volume are converted back into energy fluence, and transported deterministically. By matching boundary conditions at both interfaces, deterministic dose calculation account for dose perturbations “downstream” of localized heterogeneities. Hybrid dose calculation was performed for water and anthropomorphic phantoms. Results: We achieved <1% agreement between deterministic and MC calculations in the water benchmark for photon and proton beams, and dose differences of 2%–15% could be observed in heterogeneous phantoms. The saving in computational time (a factor ∼4–7 compared to a full Monte Carlo dose calculation) was found to be approximately proportional to the volume of the heterogeneous region. Conclusion: Our hybrid dose calculation approach takes advantage of the computational efficiency of deterministic method and accuracy of MC, providing a practical tool for high performance dose calculation in modern RT. The approach is generalizable to all modalities where heterogeneities play a large role, notably particle therapy.},
doi = {10.1118/1.4955550},
journal = {Medical Physics},
number = 6,
volume = 43,
place = {United States},
year = 2016,
month = 6
}
  • The Monte Carlo (MC) method has been shown through many research studies to calculate accurate dose distributions for clinical radiotherapy, particularly in heterogeneous patient tissues where the effects of electron transport cannot be accurately handled with conventional, deterministic dose algorithms. Despite its proven accuracy and the potential for improved dose distributions to influence treatment outcomes, the long calculation times previously associated with MC simulation rendered this method impractical for routine clinical treatment planning. However, the development of faster codes optimized for radiotherapy calculations and improvements in computer processor technology have substantially reduced calculation times to, in some instances, within minutesmore » on a single processor. These advances have motivated several major treatment planning system vendors to embark upon the path of MC techniques. Several commercial vendors have already released or are currently in the process of releasing MC algorithms for photon and/or electron beam treatment planning. Consequently, the accessibility and use of MC treatment planning algorithms may well become widespread in the radiotherapy community. With MC simulation, dose is computed stochastically using first principles; this method is therefore quite different from conventional dose algorithms. Issues such as statistical uncertainties, the use of variance reduction techniques, the ability to account for geometric details in the accelerator treatment head simulation, and other features, are all unique components of a MC treatment planning algorithm. Successful implementation by the clinical physicist of such a system will require an understanding of the basic principles of MC techniques. The purpose of this report, while providing education and review on the use of MC simulation in radiotherapy planning, is to set out, for both users and developers, the salient issues associated with clinical implementation and experimental verification of MC dose algorithms. As the MC method is an emerging technology, this report is not meant to be prescriptive. Rather, it is intended as a preliminary report to review the tenets of the MC method and to provide the framework upon which to build a comprehensive program for commissioning and routine quality assurance of MC-based treatment planning systems.« less
  • Purpose: To present a comparison of the accuracy of two commercial electron beam treatment planning systems: one uses a Monte Carlo algorithm and the other uses a pencil beam model for dose calculations. Methods and Materials: For the same inhomogeneous phantoms and incident beams, measured dose distributions are compared with those predicted by the commercial treatment planning systems at different source-to-surface distances (SSDs). The accuracy of the pencil beam system for monitor unit calculations is also tested at various SSDs. Beam energies of 6-20 MeV are used. Results: The pencil beam model shows some serious limitations in predicting hot andmore » cold spots in inhomogeneous phantoms for small low- or high-density inhomogeneities, especially for low-energy electron beams, such as 9 MeV. Errors (>10%) are seen in predicting high- and low-dose variations for three-dimensional inhomogeneous phantoms. The Monte Carlo calculated results generally agree much better with measurements. Conclusions: The accuracy of the pencil beam calculations is difficult to predict because it depends on both the inhomogeneity geometry and location. The pencil beam calculations using CADPLAN result in large errors in phantoms containing three-dimensional type inhomogeneities. The Monte Carlo method in Theraplan Plus dose calculation module is shown to be more robust in accurately predicting dose distributions and monitor units under the tested conditions.« less
  • Purpose: Eclipse proton Monte Carlo AcurosPT 13.7 was commissioned and experimentally validated for an IBA dedicated PBS nozzle in water. Topas 1.3 was used to isolate the cause of differences in output and penumbra between simulation and experiment. Methods: The spot profiles were measured in air at five locations using Lynx. PTW-34070 Bragg peak chamber (Freiburg, Germany) was used to collect the relative integral Bragg peak for 15 proton energies from 100 MeV to 225 MeV. The phase space parameters (σx, σθ, ρxθ) number of protons per MU, energy spread and calculated mean energy provided by AcurosPT were identically implementedmore » into Topas. The absolute dose, profiles and field size factors measured using ionization chamber arrays were compared with both AcurosPT and Topas. Results: The beam spot size, σx, and the angular spread, σθ, in air were both energy-dependent: in particular, the spot size in air at isocentre ranged from 2.8 to 5.3 mm, and the angular spread ranged from 2.7 mrad to 6 mrad. The number of protons per MU increased from ∼9E7 at 100 MeV to ∼1.5E8 at 225 MeV. Both AcurosPT and TOPAS agree with experiment within 2 mm penumbra difference or 3% dose difference for scenarios including central axis depth dose and profiles at two depths in multi-spot square fields, from 40 to 200 mm, for all the investigated single-energy and multi-energy beams, indicating clinically acceptable source model and radiation transport algorithm in water. Conclusion: By comparing measured data and TOPAS simulation using the same source model, the AcurosPT 13.7 was validated in water within 2 mm penumbra difference or 3% dose difference. Benchmarks versus an independent Monte Carlo code are recommended to study the agreement in output, filed size factors and penumbra differences. This project is partially supported by the Varian grant under the master agreement between University of Pennsylvania and Varian.« less
  • Prism is a non-commercial Radiotherapy Treatment Planning System (RTPS) develop by Ira J. Kalet from Washington University. Inhomogeneity factor is included in Prism TPS dose calculation. The aim of this study is to investigate the sensitivity of dose calculation on Prism using Monte Carlo simulation. Phase space source from head linear accelerator (LINAC) for Monte Carlo simulation is implemented. To achieve this aim, Prism dose calculation is compared with EGSnrc Monte Carlo simulation. Percentage depth dose (PDD) and R50 from both calculations are observed. BEAMnrc is simulated electron transport in LINAC head and produced phase space file. This file ismore » used as DOSXYZnrc input to simulated electron transport in phantom. This study is started with commissioning process in water phantom. Commissioning process is adjusted Monte Carlo simulation with Prism RTPS. Commissioning result is used for study of inhomogeneity phantom. Physical parameters of inhomogeneity phantom that varied in this study are: density, location and thickness of tissue. Commissioning result is shown that optimum energy of Monte Carlo simulation for 6 MeV electron beam is 6.8 MeV. This commissioning is used R50 and PDD with Practical length (R{sub p}) as references. From inhomogeneity study, the average deviation for all case on interest region is below 5 %. Based on ICRU recommendations, Prism has good ability to calculate the radiation dose in inhomogeneity tissue.« less
  • Purpose: This study evaluated the performance of the electron Monte Carlo dose calculation algorithm in RayStation v4.0 for an Elekta machine with Agility™ treatment head. Methods: The machine has five electron energies (6–8 MeV) and five applicators (6×6 to 25×25 cm {sup 2}). The dose (cGy/MU at d{sub max}), depth dose and profiles were measured in water using an electron diode at 100 cm SSD for nine square fields ≥2×2 cm{sup 2} and four complex fields at normal incidence, and a 14×14 cm{sup 2} field at 15° and 30° incidence. The dose was also measured for three square fields ≥4×4more » cm{sup 2} at 98, 105 and 110 cm SSD. Using selected energies, the EBT3 radiochromic film was used for dose measurements in slab-shaped inhomogeneous phantoms and a breast phantom with surface curvature. The measured and calculated doses were analyzed using a gamma criterion of 3%/3 mm. Results: The calculated and measured doses varied by <3% for 116 of the 120 points, and <5% for the 4×4 cm{sup 2} field at 110 cm SSD at 9–18 MeV. The gamma analysis comparing the 105 pairs of in-water isodoses passed by >98.1%. The planar doses measured from films placed at 0.5 cm below a lung/tissue layer (12 MeV) and 1.0 cm below a bone/air layer (15 MeV) showed excellent agreement with calculations, with gamma passing by 99.9% and 98.5%, respectively. At the breast-tissue interface, the gamma passing rate is >98.8% at 12–18 MeV. The film results directly validated the accuracy of MU calculation and spatial dose distribution in presence of tissue inhomogeneity and surface curvature - situations challenging for simpler pencil-beam algorithms. Conclusion: The electron Monte Carlo algorithm in RayStation v4.0 is fully validated for clinical use for the Elekta Agility™ machine. The comprehensive validation included small fields, complex fields, oblique beams, extended distance, tissue inhomogeneity and surface curvature.« less