RapidBrachyMCTPS: a Monte Carlo-based treatment planning system for brachytherapy applications

被引:32
|
作者
Famulari, Gabriel [1 ]
Renaud, Marc-Andre [1 ]
Poole, Christopher M. [1 ,2 ]
Evans, Michael D. C. [1 ,3 ]
Seuntjens, Jan [1 ,4 ,5 ]
Enger, Shirin A. [1 ,4 ,5 ]
机构
[1] McGill Univ, Med Phys Unit, Montreal, PQ H4A 3J1, Canada
[2] Radiat Analyt Pty Ltd, Mt Creek, Qld 4557, Australia
[3] McGill Univ, Hlth Ctr, Dept Med Phys, Montreal, PQ H4A 3J1, Canada
[4] McGill Univ, Dept Oncol, Montreal, PQ H4A 3J1, Canada
[5] McGill Univ, Hlth Ctr, Res Inst, Montreal, PQ H3H 2L9, Canada
来源
PHYSICS IN MEDICINE AND BIOLOGY | 2018年 / 63卷 / 17期
基金
加拿大自然科学与工程研究理事会;
关键词
brachytherapy; model-based dose calculation algorithms; Monte Carlo; treatment planning; INTERSEED ATTENUATION; DOSE CALCULATIONS; HDR BRACHYTHERAPY; TISSUE COMPOSITION; DOSIMETRY; GEANT4; IR-192; EGSNRC; RECOMMENDATIONS; UNCERTAINTIES;
D O I
10.1088/1361-6560/aad97a
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Despite being considered the gold standard for brachytherapy dosimetry, Monte Carlo (MC) has yet to be implemented into a software for brachytherapy treatment planning. The purpose of this work is to present RapidBrachyMCTPS, a novel treatment planning system (TPS) for brachytherapy applications equipped with a graphical user interface (GUI), optimization tools and a Geant4based MC dose calculation engine, RapidBrachyMC. Brachytherapy sources and applicators were implemented in RapidBrachyMC and made available to the user via a source and applicator library in the GUI. To benchmark RapidBrachyMC, TG-43 parameters were calculated for the microSelectron v2 (Ir-192) and SelectSeed (I-125) source models and were compared against previously validated MC brachytherapy codes. The performance of RapidBrachyMC was evaluated for a prostate high dose rate case. To assess the accuracy of RapidBrachyMC in a heterogeneous setup, dose distributions with a cylindrical shielded/unshielded applicator were validated against film measurements in a Solid Water (TM) phantom. TG-43 parameters calculated using RapidBrachyMC generally agreed within 1%-2% of the results obtained in previously published work. For the prostate case, clinical dosimetric indices showed general agreement with Oncentra TPS within 1%. Simulation times were on the order of minutes on a single core to achieve uncertainties below 2% in voxels within the prostate. The calculation time was decreased further using the multithreading features of Geant4. In the comparison between MC-calculated and film-measured dose distributions, at least 95% of points passed the 3%/3 mm gamma index criteria in all but one case. RapidBrachyMCTPS can be used as a post-implant dosimetry toolkit, as well as for MC-based brachytherapy treatment planning. This software is especially well suited for the development of new source and applicator models.
引用
收藏
页数:13
相关论文
共 50 条
  • [41] Fast Monte Carlo Treatment Planning for Prostate Brachytherapy: A Comparison with VariSeed
    Abboud, F.
    Scalliet, P.
    Vynckier, S.
    MEDICAL PHYSICS, 2011, 38 (06)
  • [42] Experimental validation of a Monte Carlo-based treatment-planning system for electron beams [Experimentelle validierung eines Monte-Carlo-basierten bestrahlungsplanungssystems für elektronenstrahlung]
    Mika S.
    Christ G.
    Strahlentherapie und Onkologie, 2007, 183 (3) : 150 - 156
  • [43] Automation of Monte Carlo-based treatment plan verification for proton therapy
    Kaluarachchi, Maduka
    Moskvin, Vadim
    Pirlepesov, Fakhriddin
    Wilson, Lydia J.
    Xie, Fang
    Faught, Austin M.
    JOURNAL OF APPLIED CLINICAL MEDICAL PHYSICS, 2020, 21 (08): : 131 - 138
  • [44] Monte Carlo-based tail exponent estimator
    Barunik, Jozef
    Vacha, Lukas
    PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2010, 389 (21) : 4863 - 4874
  • [45] Verification of Accuracy of the Monte Carlo Based Electron Treatment Planning System
    Lee, J.
    Chan, R.
    MEDICAL PHYSICS, 2008, 35 (06) : 2841 - +
  • [46] Acceptance and Commissioning of a Treatment Planning System Based on Monte Carlo Calculations
    Lopez-Tarjuelo, J.
    Garcia-Molla, R.
    Juan-Senabre, X. J.
    Quiros-Higueras, J. D.
    Santos-Serra, A.
    de Marco-Blancas, N.
    Calzada-Feliu, S.
    TECHNOLOGY IN CANCER RESEARCH & TREATMENT, 2014, 13 (02) : 129 - 138
  • [47] Introduction of scoregrids into a Monte-Carlo based treatment planning system
    Reynaert, N
    De Smedt, B
    Thierens, H
    Coghe, M
    De Wagter, C
    De Neve, W
    RADIOTHERAPY AND ONCOLOGY, 2003, 68 : S91 - S91
  • [48] Monte Carlo-based food irradiation simulator
    Kim, J
    Moreira, RG
    Rivadeneira, R
    Castell-Perez, ME
    JOURNAL OF FOOD PROCESS ENGINEERING, 2006, 29 (01) : 72 - 88
  • [49] A radiosurgery Monte Carlo based treatment planning
    Chave, A
    Lopes, MC
    Oliveira, C
    Peralta, L
    RADIOTHERAPY AND ONCOLOGY, 2004, 73 : S374 - S374
  • [50] A new Monte Carlo-based fitting method
    Pedroni, P.
    Sconfietti, S.
    JOURNAL OF PHYSICS G-NUCLEAR AND PARTICLE PHYSICS, 2020, 47 (05)