egs_brachy: a versatile and fast Monte Carlo code for brachytherapy

egs_brachy is a versatile and fast Monte Carlo (MC) code for brachytherapy applications. It is based on the EGSnrc code system, enabling simulation of photons and electrons. Complex geometries are modelled using the EGSnrc C++ class library and egs_brachy includes a library of geometry models for many brachytherapy sources, in addition to eye plaques and applicators. Several simulation efficiency enhancing features are implemented in the code. egs_brachy is benchmarked by comparing TG-43 source parameters of three source models to previously published values. 3D dose distributions calculated with egs_brachy are also compared to ones obtained with the BrachyDose code. Well-defined simulations are used to characterize the effectiveness of many efficiency improving techniques, both as an indication of the usefulness of each technique and to find optimal strategies. Efficiencies and calculation times are characterized through single source simulations and simulations of idealized and typical treatments using various efficiency improving techniques. In general, egs_brachy shows agreement within uncertainties with previously published TG-43 source parameter values. 3D dose distributions from egs_brachy and BrachyDose agree at the sub-percent level. Efficiencies vary with radionuclide and source type, number of sources, phantom media, and voxel size. The combined effects of efficiency-improving techniques in egs_brachy lead to short calculation times: simulations approximating prostate and breast permanent implant (both with (2 mm)3 voxels) and eye plaque (with (1 mm)3 voxels) treatments take between 13 and 39 s, on a single 2.5 GHz Intel Xeon E5-2680 v3 processor core, to achieve 2% average statistical uncertainty on doses within the PTV. egs_brachy will be released as free and open source software to the research community.

[1]  D. W. O. Rogersb,et al.  EGSnrc Monte Carlo calculated dosimetry parameters for 192 Ir and 169 Yb brachytherapy sources , 2008 .

[2]  F Verhaegen,et al.  ALGEBRA: ALgorithm for the heterogeneous dosimetry based on GEANT4 for BRAchytherapy , 2012, Physics in medicine and biology.

[3]  J. H. Hubbell,et al.  Tables and graphs of atomic subshell and relaxation data derived from the LLNL Evaluated Atomic Data Library (EADL), Z=1-100 , 1991 .

[4]  Mark J Rivard,et al.  Anniversary paper: past and current issues, and trends in brachytherapy physics. , 2008, Medical physics.

[5]  Luc Beaulieu,et al.  Large-scale Retrospective Monte Carlo Dosimetric Study for Permanent Implant Prostate Brachytherapy. , 2017, International journal of radiation oncology, biology, physics.

[6]  R Nath,et al.  Measurement of dose-rate constant for 103Pd seeds with air kerma strength calibration based upon a primary national standard. , 2000, Medical physics.

[7]  R. Taylor,et al.  Benchmarking brachydose: Voxel based EGSnrc Monte Carlo calculations of TG-43 dosimetry parameters. , 2007, Medical physics.

[8]  R M Thomson,et al.  Model-based dose calculations for COMS eye plaque brachytherapy using an anatomically realistic eye phantom. , 2014, Medical physics.

[9]  J. H. Hubbell,et al.  XCOM: Photon cross sections on a personal computer , 1987 .

[10]  N Miksys,et al.  Patient-specific Monte Carlo dose calculations for 103Pd breast brachytherapy , 2016, Physics in medicine and biology.

[11]  Annette Haworth,et al.  A generic high-dose rate (192)Ir brachytherapy source for evaluation of model-based dose calculations beyond the TG-43 formalism. , 2015, Medical physics.

[12]  R. Taylor,et al.  EGSnrc Monte Carlo calculated dosimetry parameters for Ir192 and Yb169 brachytherapy sources. , 2008, Medical physics.

[13]  Constantinos Loukas,et al.  A user-oriented procedure for the commissioning and quality assurance testing of treatment planning system dosimetry in high-dose-rate brachytherapy. , 2016, Brachytherapy.

[14]  G. Yegin,et al.  11 Fast Monte Carlo dose calculations for brachytherapy , 2005 .

[15]  L A DeWerd,et al.  Experimental and Monte Carlo determination of the TG-43 dosimetric parameters for the model 9011 THINSeed brachytherapy source. , 2010, Medical physics.

[16]  R. Taylor,et al.  An EGSnrc Monte Carlo-calculated database of TG-43 parameters. , 2008, Medical physics.

[17]  I. Kawrakow,et al.  The EGSnrc Code System: Monte Carlo Simulation of Electron and Photon Transport , 2016 .

[18]  D. Rogers,et al.  On determining dose rate constants spectroscopically. , 2012, Medical physics.

[19]  Ravinder Nath,et al.  Comparison of dose calculation methods for brachytherapy of intraocular tumors. , 2010, Medical physics.

[20]  I. Kawrakow,et al.  History by history statistical estimators in the BEAM code system. , 2002, Medical physics.

[21]  J. Williamson,et al.  Accelerated Monte Carlo-based dose calculations for brachytherapy planning using correlated sampling , 2000, Proceedings of the 22nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (Cat. No.00CH37143).

[22]  D. R. White,et al.  The composition of body tissues. , 1986, The British journal of radiology.

[23]  Omar Chibani,et al.  MCPI: a sub-minute Monte Carlo dose calculation engine for prostate implants. , 2005, Medical physics.

[24]  E Pantelis,et al.  Current state of the art brachytherapy treatment planning dosimetry algorithms. , 2014, The British journal of radiology.

[25]  R M Thomson,et al.  Monte Carlo dosimetry for I125 and Pd103 eye plaque brachytherapy. , 2008, Medical physics.

[26]  D. Rogers,et al.  Effect of improved TLD dosimetry on the determination of dose rate constants for (125)I and (103)Pd brachytherapy seeds. , 2014, Medical physics.

[27]  R. Taylor,et al.  An EGSnrc Monte Carlo-calculated database of TG-43 parameters. , 2008, Medical physics.

[28]  D W O Rogers,et al.  Efficiency improvements of x-ray simulations in EGSnrc user-codes using bremsstrahlung cross-section enhancement (BCSE). , 2007, Medical physics.

[29]  W. Butler,et al.  Erratum: Update of AAPM Task Group No. 43 Report: A revised AAPM protocol for brachytherapy dose calculations (Medical Physics (2004) 31 (633-674)) , 2004 .

[30]  J F Williamson,et al.  Volume-based geometric modeling for radiation transport calculations. , 1992, Medical physics.

[31]  Vincent Magnoux,et al.  Fast GPU-based Monte Carlo simulations for LDR prostate brachytherapy , 2015, Physics in medicine and biology.

[32]  G. Yegin,et al.  TU‐EE‐A1‐04: Monte Carlo Modelling of the Xoft AXXENT X‐Ray Source , 2006 .

[33]  J F Williamson,et al.  Monte Carlo evaluation of kerma at a point for photon transport problems. , 1987, Medical physics.

[34]  Omar Chibani,et al.  HDRMC, an accelerated Monte Carlo dose calculator for high dose rate brachytherapy with CT-compatible applicators. , 2014, Medical physics.

[35]  J. Williamson,et al.  Report of the Task Group 186 on model-based dose calculation methods in brachytherapy beyond the TG-43 formalism: current status and recommendations for clinical implementation. , 2012, Medical physics.

[36]  G. Yegin.  A new approach to geometry modeling for Monte Carlo particle transport: An application to the EGS code system , 2003 .

[37]  J. Williamson,et al.  Update of AAPM Task Group No. 43 Report: A revised AAPM protocol for brachytherapy dose calculations. , 2004 .

[38]  I. Kawrakow,et al.  Investigation of variance reduction techniques for Monte Carlo photon dose calculation using XVMC , 2000, Physics in medicine and biology.

[39]  J G H Sutherland,et al.  Changes in dose with segmentation of breast tissues in Monte Carlo calculations for low-energy brachytherapy. , 2011, Medical physics.

[40]  Anders Ahnesjö,et al.  Brachytherapy source characterization for improved dose calculations using primary and scatter dose separation. , 2005, Medical physics.

[41]  Jeffrey F. Williamson,et al.  Accelerated Monte Carlo based dose calculations for brachytherapy planning using correlated sampling. , 2002 .