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Wang X, Liang J, Li Y, Zhang Q. Hybrid Monte Carlo methods for Geant4-based nuclear well logging implementation. ANN NUCL ENERGY 2022. [DOI: 10.1016/j.anucene.2021.108824] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Newpower M, Schuemann J, Mohan R, Paganetti H, Titt U. Comparing 2 Monte Carlo Systems in Use for Proton Therapy Research. Int J Part Ther 2019; 6:18-27. [PMID: 31773045 DOI: 10.14338/ijpt-18-00043.1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2018] [Accepted: 03/20/2019] [Indexed: 11/21/2022] Open
Abstract
Purpose Several Monte Carlo transport codes are available for medical physics users. To ensure confidence in the accuracy of the codes, they must be continually cross-validated. This study provides comparisons between MC2 and Tool for Particle Simulation (TOPAS) simulations, that is, between medical physics applications for Monte Carlo N-Particle Transport Code (MCNPX) and Geant4. Materials and Methods Monte Carlo simulations were repeated with 2 wrapper codes: TOPAS (based on Geant4) and MC2 (based on MCNPX). Simulations increased in geometrical complexity from a monoenergetic beam incident on a water phantom, to a monoenergetic beam incident on a water phantom with a bone or tissue slab at various depths, to a spread-out Bragg peak incident on a voxelized computed tomography (CT) geometry. The CT geometry cases consisted of head and neck tissue and lung tissue. The results of the simulations were compared with one another through dose or energy deposition profiles, r 90 calculations, and γ-analyses. Results Both codes gave very similar results with monoenergetic beams incident on a water phantom. Systematic differences were observed between MC2 and TOPAS simulations when using a lung or bone slab in a water phantom, particularly in the r 90 values, where TOPAS consistently calculated r 90 to be deeper by about 0.4%. When comparing the performance of the 2 codes in a CT geometry, the results were still very similar, exemplified by a 3-dimensional γ-analysis pass rate > 95% at the 2%-2-mm criterion for tissues from both head and neck and lung. Conclusion Differences between TOPAS and MC2 were minor and were not considered clinically relevant.
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Affiliation(s)
- Mark Newpower
- Department of Radiation Physics, MD Anderson Cancer Center, Houston, TX 77030, USA.,Medical Physics Program, University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Houston, TX 77030, USA
| | - Jan Schuemann
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Radhe Mohan
- Department of Radiation Physics, MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Harald Paganetti
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Uwe Titt
- Department of Radiation Physics, MD Anderson Cancer Center, Houston, TX 77030, USA
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Chen SK, Chiang BH, Lee CC, Tung CJ, Hong JH, Chao TC. The impact of MCS models and EFAC values on the dose simulation for a proton pencil beam. Radiat Phys Chem Oxf Engl 1993 2017. [DOI: 10.1016/j.radphyschem.2016.02.015] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Anjomrouz M, Bakht MK, Sadeghi M. Feasibility study of FLUKA Monte Carlo simulation for a beta-emitting brachytherapy source: dosimetric parameters of 142Pr glass seed. J Radioanal Nucl Chem 2016. [DOI: 10.1007/s10967-016-4744-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
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Abstract
The physics of proton therapy has advanced considerably since it was proposed in 1946. Today analytical equations and numerical simulation methods are available to predict and characterize many aspects of proton therapy. This article reviews the basic aspects of the physics of proton therapy, including proton interaction mechanisms, proton transport calculations, the determination of dose from therapeutic and stray radiations, and shielding design. The article discusses underlying processes as well as selected practical experimental and theoretical methods. We conclude by briefly speculating on possible future areas of research of relevance to the physics of proton therapy.
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Affiliation(s)
- Wayne D Newhauser
- Medical Physics Program, Department of Physics and Astronomy, Louisiana State University, 202 Nicholson Hall, Baton Rouge, LA, 70803, USA
- Mary Bird Perkins Cancer Center, 4950 Essen Lane, Baton Rouge, LA, 70809, USA
| | - Rui Zhang
- Medical Physics Program, Department of Physics and Astronomy, Louisiana State University, 202 Nicholson Hall, Baton Rouge, LA, 70803, USA
- Mary Bird Perkins Cancer Center, 4950 Essen Lane, Baton Rouge, LA, 70809, USA
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Jabbari K, Seuntjens J. A fast Monte Carlo code for proton transport in radiation therapy based on MCNPX. J Med Phys 2014; 39:156-63. [PMID: 25190994 PMCID: PMC4154183 DOI: 10.4103/0971-6203.139004] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2013] [Revised: 04/10/2014] [Accepted: 04/23/2014] [Indexed: 11/04/2022] Open
Abstract
An important requirement for proton therapy is a software for dose calculation. Monte Carlo is the most accurate method for dose calculation, but it is very slow. In this work, a method is developed to improve the speed of dose calculation. The method is based on pre-generated tracks for particle transport. The MCNPX code has been used for generation of tracks. A set of data including the track of the particle was produced in each particular material (water, air, lung tissue, bone, and soft tissue). This code can transport protons in wide range of energies (up to 200 MeV for proton). The validity of the fast Monte Carlo (MC) code is evaluated with data MCNPX as a reference code. While analytical pencil beam algorithm transport shows great errors (up to 10%) near small high density heterogeneities, there was less than 2% deviation of MCNPX results in our dose calculation and isodose distribution. In terms of speed, the code runs 200 times faster than MCNPX. In the Fast MC code which is developed in this work, it takes the system less than 2 minutes to calculate dose for 10(6) particles in an Intel Core 2 Duo 2.66 GHZ desktop computer.
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Affiliation(s)
- Keyvan Jabbari
- Department of Medical Physics and Engineering, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Jan Seuntjens
- Medical Physics Unit, McGill University Health Center, Montréal, Québec, Canada
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Zhang M, Flynn RT, Mo X, Mackie TR. The energy margin strategy for reducing dose variation due to setup uncertainty in intensity modulated proton therapy (IMPT) delivered with distal edge tracking (DET). J Appl Clin Med Phys 2012; 13:3863. [PMID: 22955652 PMCID: PMC4439946 DOI: 10.1120/jacmp.v13i5.3863] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2011] [Revised: 05/06/2012] [Accepted: 05/05/2012] [Indexed: 12/14/2022] Open
Abstract
Intensity-modulated proton therapy (IMPT) can produce plans with similar target dose conformity but lower normal tissue dose than intensity-modulated X-ray therapy (IMXT). However, due to the finite range of proton beams in tissue, proton therapy treatment plans are usually more sensitive to setup uncertainties than X-ray therapy plans. In this work, the energy margin (EM) concept, which was initially developed for passive scattering proton therapy, was generalized to apply to IMPT treatment planning. The effectiveness of the EM method was evaluated on five head-and-neck cancer patients with distal edge tracking (DET) treatment plans by comparing the original plans (ORG) without an EM to those with an EM. Three beam arrangements were considered: 24 beams delivered over a 360° arc, 12 beams delivered over a 180° arc, and 12 beams delivered over two 90° fan angles. Setup uncertainty was modeled by sampling rigid translational shifts from a Gaussian distribution with a mean of 0 mm and standard deviation of 2 mm in all directions. Delivered dose distributions for all 30 fractions were recalculated using the Geant4 Monte Carlo code. Normalized total dose (NTD) for both the CTV and a ring structure surrounding the PTV were recorded. The plan quality comparison revealed that EM plans had the same CTV coverage but higher dose to the normal tissue than ORG plans. After the simulated delivery, ORG plans resulted in more than 3% underdosage to 5% of the CTV volume in all three beam arrangements, whereas the EM plans did not. Both ORG and EM plans did not produce more than 5% overdose to D2% of the ring structure. The use of an EM for IMPT treatment planning can substantially reduce sensitivity of the resulting dose distributions to setup uncertainty.
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Affiliation(s)
- Miao Zhang
- Department of Radiation Oncology,1 The Cancer Institute of New Jersey, UMDNJ-Robert Wood Johnson Medical School, New Brunswick, NJ 08901,USA.
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Abstract
The main advantages of proton therapy are the reduced total energy deposited in the patient as compared to photon techniques and the finite range of the proton beam. The latter adds an additional degree of freedom to treatment planning. The range in tissue is associated with considerable uncertainties caused by imaging, patient setup, beam delivery and dose calculation. Reducing the uncertainties would allow a reduction of the treatment volume and thus allow a better utilization of the advantages of protons. This paper summarizes the role of Monte Carlo simulations when aiming at a reduction of range uncertainties in proton therapy. Differences in dose calculation when comparing Monte Carlo with analytical algorithms are analyzed as well as range uncertainties due to material constants and CT conversion. Range uncertainties due to biological effects and the role of Monte Carlo for in vivo range verification are discussed. Furthermore, the current range uncertainty recipes used at several proton therapy facilities are revisited. We conclude that a significant impact of Monte Carlo dose calculation can be expected in complex geometries where local range uncertainties due to multiple Coulomb scattering will reduce the accuracy of analytical algorithms. In these cases Monte Carlo techniques might reduce the range uncertainty by several mm.
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Affiliation(s)
- Harald Paganetti
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA.
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Paganetti H. Range uncertainties in proton therapy and the role of Monte Carlo simulations. Phys Med Biol 2012. [PMID: 22571913 DOI: 10.1088/0031‐9155/57/11/r99] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
The main advantages of proton therapy are the reduced total energy deposited in the patient as compared to photon techniques and the finite range of the proton beam. The latter adds an additional degree of freedom to treatment planning. The range in tissue is associated with considerable uncertainties caused by imaging, patient setup, beam delivery and dose calculation. Reducing the uncertainties would allow a reduction of the treatment volume and thus allow a better utilization of the advantages of protons. This paper summarizes the role of Monte Carlo simulations when aiming at a reduction of range uncertainties in proton therapy. Differences in dose calculation when comparing Monte Carlo with analytical algorithms are analyzed as well as range uncertainties due to material constants and CT conversion. Range uncertainties due to biological effects and the role of Monte Carlo for in vivo range verification are discussed. Furthermore, the current range uncertainty recipes used at several proton therapy facilities are revisited. We conclude that a significant impact of Monte Carlo dose calculation can be expected in complex geometries where local range uncertainties due to multiple Coulomb scattering will reduce the accuracy of analytical algorithms. In these cases Monte Carlo techniques might reduce the range uncertainty by several mm.
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Affiliation(s)
- Harald Paganetti
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA.
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Seravalli E, Robert C, Bauer J, Stichelbaut F, Kurz C, Smeets J, Van Ngoc Ty C, Schaart DR, Buvat I, Parodi K, Verhaegen F. Monte Carlo calculations of positron emitter yields in proton radiotherapy. Phys Med Biol 2012; 57:1659-73. [PMID: 22398196 DOI: 10.1088/0031-9155/57/6/1659] [Citation(s) in RCA: 57] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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Kimstrand P, Traneus E, Ahnesjö A, Tilly N. Parametrization and application of scatter kernels for modelling scanned proton beam collimator scatter dose. Phys Med Biol 2008; 53:3405-29. [PMID: 18547915 DOI: 10.1088/0031-9155/53/13/001] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Collimators are routinely used in proton radiotherapy to laterally confine the field and improve the penumbra. Collimator scatter contributes up to 15% of the local dose and is therefore important to include in treatment planning dose calculation. We present a method for reconstruction of the collimator scatter phase space based on the parametrization of pre-calculated scatter kernels. Collimator scatter distributions, generated by the Monte Carlo (MC) package GEANT4.8.2, were scored differential in direction and energy. The distributions were then parametrized so as to enable a fast reconstruction by sampling. MC calculated dose distributions in water based on the parametrized phase space were compared to full MC simulations that included the collimator in the simulation geometry, as well as to experimental data. The experiments were performed at the scanned proton beam line at the The Svedberg Laboratory (TSL) in Uppsala, Sweden. Dose calculations using the parametrization of this work and the full MC for isolated typical cases of collimator scatter were compared by means of the gamma index. The result showed that in total 96.7% (99.3%) of the voxels fulfilled the gamma 2.0%/2.0 mm (3.0%/3.0 mm) criterion. The dose distribution for a collimated field was calculated based on the phase space created by the collimator scatter model incorporated into the generation of the phase space of a scanned proton beam. Comparing these dose distributions to full MC simulations, including particle transport in the MLC, yielded that in total for 18 different collimated fields, 99.1% of the voxels satisfied the gamma 1.0%/1.0 mm criterion and no voxel exceeded the gamma 2.6%/2.6 mm criterion. The dose contribution of collimator scatter along the central axis as predicted by the model showed good agreement with experimental data.
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Affiliation(s)
- Peter Kimstrand
- Section of Oncology, Department of Oncology, Radiology and Clinical Immunology, Uppsala University, Akademiska Sjukhuset, S-751 85 Uppsala, Sweden.
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