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
  • [31] Monte Carlo-based treatment planning for a spoiler system with experimental validation using plane-parallel ionization chambers
    Kang, SK
    Cho, BC
    Park, SH
    Park, HC
    Bae, H
    Kim, JO
    Keall, PJ
    Siebers, JV
    PHYSICS IN MEDICINE AND BIOLOGY, 2004, 49 (22): : 5145 - 5155
  • [32] Column generation-based Monte Carlo treatment planning for rotating shield brachytherapy
    Renaud, M. A.
    Famulari, G.
    Seuntjens, J.
    Enger, S. A.
    RADIOTHERAPY AND ONCOLOGY, 2016, 119 : S118 - S118
  • [33] Dual energy CT tissue quantitation for Monte Carlo based treatment planning for brachytherapy
    Devic, S
    Monroe, JI
    Mutic, S
    Whiting, B
    Williamson, JF
    PROCEEDINGS OF THE 22ND ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-4, 2000, 22 : 364 - 367
  • [34] DEVELOPMENT OF A MULTIMODAL MONTE CARLO BASED TREATMENT PLANNING SYSTEM
    Kumada, Hiroaki
    Takada, Kenta
    Sakurai, Yoshinori
    Suzuki, Minoru
    Takata, Takushi
    Sakurai, Hideyuki
    Matsumura, Akira
    Sakae, Takeji
    RADIATION PROTECTION DOSIMETRY, 2018, 180 (1-4) : 286 - 290
  • [35] Chronological Monte Carlo-based assessment of distribution system reliability
    Leite da Silva, Armando M.
    Cassula, Agnelo M.
    Nascimento, Luiz C.
    Freire, Jose C., Jr.
    Sacramento, Cleber E.
    Guimaraes, Ana Carolina R.
    2006 INTERNATIONAL CONFERENCE ON PROBABILISTIC METHODS APPLIED TO POWER SYSTEMS, VOLS 1 AND 2, 2006, : 1165 - 1171
  • [36] Fast online Monte Carlo-based IMRT planning for the MRI linear accelerator
    Bol, G. H.
    Hissoiny, S.
    Lagendijk, J. J. W.
    Raaymakers, B. W.
    PHYSICS IN MEDICINE AND BIOLOGY, 2012, 57 (05): : 1375 - 1385
  • [37] Application of Monte Carlo calculations for validation of a treatment planning system in high dose rate brachytherapy
    Naseri, Alireza
    Mesbahi, Asghar
    REPORTS OF PRACTICAL ONCOLOGY AND RADIOTHERAPY, 2009, 14 (06) : 200 - 204
  • [38] A Monte Carlo Based Treatment Optimization Technique for the Xoft Electronic Brachytherapy System
    Fahimian, B.
    DeMarco, J.
    Iwamoto, K.
    Saxon, S.
    MEDICAL PHYSICS, 2010, 37 (06) : 3193 - +
  • [39] Monte Carlo-based lung cancer treatment planning incorporating PET-defined target volumes
    Chetty, Indrin J.
    Fernando, Shaneli
    Kessler, Marc L.
    Mcshan, Daniel L.
    Brooks, Cassandra
    Haken, Randall K. Ten
    Kong, Feng-Ming Spring
    JOURNAL OF APPLIED CLINICAL MEDICAL PHYSICS, 2005, 6 (04): : 65 - 76
  • [40] FAST MONTE CARLO TREATMENT PLANNING FOR PROSTATE BRACHYTHERAPY: A COMPARISON WITH VARISEED
    Abboud, F.
    Scalliet, P.
    Vynckier, S.
    RADIOTHERAPY AND ONCOLOGY, 2009, 92 : S103 - S103