Abstract

Purpose To describe the development and benchmarking of a library of brachytherapy sources and applicators for use with egs_brachy, a new open-source code for brachytherapy calculations. Methods egs_brachy is a modern EGSnrc application employing the EGSnrc C++ class library (egs++) [1] . The extended egs++ framework (new geometry and shape classes developed with egs_brachy) is used to construct detailed models of sources and applicators. Source models are constructed for 52 photon brachytherapy sources (radionuclides Pd-103, I-125, Cs-131, Cs-137, Ir-192, Yb-169, and Co-60). A generic miniature X-ray tube source is modeled. Eye plaque applicators include 10–24 mm diameter Collaborative Ocular Melanoma Study (COMS) plaques (containing I-125 or Pd-103 seeds) and BEBIG Ru-106 beta-emitting plaques (diameters 11.6–25.4 mm). The generic high-dose rate (HDR) Ir-192 shielded applicator of the AAPM-ESTRO-ABG Working Group on Dose Calculation Algorithms for Brachytherapy (WG-DCAB) is modeled. Dose distributions and TG-43 parameters (photon sources only) computed with egs_brachy are compared with published values. Results For photon (radionuclide) sources, dose-rate constant, radial dose function, and anisotropy function values are generally in excellent agreement with published values [2] . Miniature X-ray tube results for egs_brachy agree with BrachyDose results within statistical uncertainties. Ocular plaque dose distributions show excellent agreement with published values. For COMS plaques, egs_brachy results agree with BrachyDose and MCNP5 published values within uncertainties [3] . For Ru-106 beta-emitting plaques, egs_brachy results agree within sub-2% uncertainties with PENELOPE results [4] , and this agreement is notable due to the historically poor agreement between results from different publications. Dose distributions about the WG-DCAB applicator agree with results from other MC codes. Conclusions egs_brachy can model diverse source and applicator models and dose distributions are in excellent agreement with published values, demonstrating the code’s versatility and accuracy. Source and applicator models will be included in future egs_brachy distributions.

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