Validation of the Oncentra Brachy Advanced Collapsed cone Engine for a commercial (192)Ir source using heterogeneous geometries.

PURPOSE To validate the Advanced Collapsed cone Engine (ACE) dose calculation engine of Oncentra Brachy (OcB) treatment planning system using an (192)Ir source. METHODS AND MATERIALS Two levels of validation were performed, conformant to the model-based dose calculation algorithm commissioning guidelines of American Association of Physicists in Medicine TG-186 report. Level 1 uses all-water phantoms, and the validation is against TG-43 methodology. Level 2 uses real-patient cases, and the validation is against Monte Carlo (MC) simulations. For each case, the ACE and TG-43 calculations were performed in the OcB treatment planning system. ALGEBRA MC system was used to perform MC simulations. RESULTS In Level 1, the ray effect depends on both accuracy mode and the number of dwell positions. The volume fraction with dose error ≥2% quickly reduces from 23% (13%) for a single dwell to 3% (2%) for eight dwell positions in the standard (high) accuracy mode. In Level 2, the 10% and higher isodose lines were observed overlapping between ACE (both standard and high-resolution modes) and MC. Major clinical indices (V100, V150, V200, D90, D50, and D2cc) were investigated and validated by MC. For example, among the Level 2 cases, the maximum deviation in V100 of ACE from MC is 2.75% but up to ~10% for TG-43. Similarly, the maximum deviation in D90 is 0.14 Gy between ACE and MC but up to 0.24 Gy for TG-43. CONCLUSION ACE demonstrated good agreement with MC in most clinically relevant regions in the cases tested. Departure from MC is significant for specific situations but limited to low-dose (<10% isodose) regions.

[1]  Firas Mourtada,et al.  Comparison of a finite-element multigroup discrete-ordinates code with Monte Carlo for radiotherapy calculations , 2006, Physics in medicine and biology.

[2]  A Ahnesjö,et al.  The collapsed cone superposition algorithm applied to scatter dose calculations in brachytherapy. , 2000, Medical physics.

[3]  Anders Ahnesjö,et al.  Optimization of the computational efficiency of a 3D, collapsed cone dose calculation algorithm for brachytherapy. , 2008, Medical physics.

[4]  Xun Jia,et al.  GPU-based fast Monte Carlo simulation for radiotherapy dose calculation. , 2011, Physics in medicine and biology.

[5]  A. Ahnesjö.  Collapsed cone convolution of radiant energy for photon dose calculation in heterogeneous media. , 1989, Medical physics.

[6]  Luc Beaulieu,et al.  The evolution of brachytherapy treatment planning. , 2009, Medical physics.

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

[8]  Frank Verhaegen,et al.  A CT-based analytical dose calculation method for HDR 192Ir brachytherapy. , 2009, Medical physics.

[9]  D. Rogers.  Fifty years of Monte Carlo simulations for medical physics , 2006, Physics in medicine and biology.

[10]  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.

[11]  Luc Beaulieu,et al.  The collapsed cone algorithm for 192Ir dosimetry using phantom-size adaptive multiple-scatter point kernels , 2015, Physics in medicine and biology.

[12]  Anders Ahnesjö,et al.  Accounting for high Z shields in brachytherapy using collapsed cone superposition for scatter dose calculation. , 2003, Medical physics.

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

[14]  Jeffrey F Williamson,et al.  Brachytherapy technology and physics practice since 1950: a half-century of progress , 2006, Physics in medicine and biology.

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

[16]  E Pantelis,et al.  Dosimetric accuracy of a deterministic radiation transport based (192)Ir brachytherapy treatment planning system. Part III. Comparison to Monte Carlo simulation in voxelized anatomical computational models. , 2012, Medical physics.

[17]  M. Rivard,et al.  Enhancements to commissioning techniques and quality assurance of brachytherapy treatment planning systems that use model-based dose calculation algorithms. , 2010, Medical physics.

[18]  C E Floyd,et al.  Segmentation of suspicious clustered microcalcifications in mammograms. , 2000, Medical physics.

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

[20]  Frank Verhaegen,et al.  Patient-specific Monte Carlo dose calculations for high-dose-rate endorectal brachytherapy with shielded intracavitary applicator. , 2008, International journal of radiation oncology, biology, physics.

[21]  R. Kuske,et al.  Dosimetric performance of Strut-Adjusted Volume Implant: a new single-entry multicatheter breast brachytherapy applicator. , 2011, Brachytherapy.

[22]  J. Williamson,et al.  Update of AAPM Task Group No. 43 Report: A revised AAPM protocol for brachytherapy dose calculations. , 2003, Medical physics.

[23]  J. Williamson,et al.  Monte Carlo-aided dosimetry of a new high dose-rate brachytherapy source. , 1998, Medical physics.

[24]  D Granero,et al.  A dosimetric study on the Ir-192 high dose rate flexisource. , 2006, Medical physics.

[25]  B. Ozell,et al.  Sub-second high dose rate brachytherapy Monte Carlo dose calculations with bGPUMCD. , 2012, Medical physics.

[26]  J. Pouliot,et al.  Patient-specific Monte Carlo-based dose-kernel approach for inverse planning in afterloading brachytherapy. , 2011, International journal of radiation oncology, biology, physics.

[27]  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.

[28]  Benoît Ozell,et al.  Validation of GPUMCD for low-energy brachytherapy seed dosimetry. , 2011, Medical physics.

[29]  K. Zourari,et al.  Dosimetric accuracy of a deterministic radiation transport based 192Ir brachytherapy treatment planning system. Part I: single sources and bounded homogeneous geometries. , 2010, Medical physics.

[30]  E. Poon,et al.  Comparison of dose calculation algorithms for colorectal cancer brachytherapy treatment with a shielded applicator. , 2008, Medical physics.

[31]  L. Anderson,et al.  Dosimetry of interstitial brachytherapy sources: Recommendations of the AAPM Radiation Therapy Committee Task Group No. 43 , 1995 .

[32]  J. Sempau,et al.  PENELOPE-2006: A Code System for Monte Carlo Simulation of Electron and Photon Transport , 2009 .

[33]  E Pantelis,et al.  Dosimetric accuracy of a deterministic radiation transport based 192Ir brachytherapy treatment planning system. Part II: Monte Carlo and experimental verification of a multiple source dwell position plan employing a shielded applicator. , 2011, Medical physics.

[34]  Firas Mourtada,et al.  Validation of a new grid-based Boltzmann equation solver for dose calculation in radiotherapy with photon beams , 2010, Physics in medicine and biology.