Clinical implementation of an open-source Monte Carlo system across multiple centers for permanent implant
Narjes Moghadam1, Fatemeh Akbari1, Claire Zhang2
1Department of Physics, Carleton Laboratory for Radiotherapy Physics, Carleton University, Ottawa, Ontario, Canada.
Purpose:
This study aims to clinically implement eb_gui, a user-friendly toolkit for Monte Carlo simulations utilizing egs_brachy, in the context of low-dose-rate (LDR) brachytherapy for prostate and breast cancers.
Methods:
A set of test cases, ranging from simple to complex scenarios including single- and multi-seed patient models, was developed for LDR brachytherapy of both breast (103Pd) and prostate (125I). Utilizing Digital Imaging and Communications in Medicine (DICOM) files, the open-source interface eb_gui was employed to compute doses. The commissioning process involved comparing eb_gui results against clinical TG-43 treatment planning system (TG43-TPS) calculations, encompassing point-by-point differences across 3D dose distributions, dose volume histograms, and dose metrics. Additionally, patient-specific dose distributions were computed using eb_gui's full-tissue models (TG186-MC) and compared against TG-43 Monte Carlo calculations (TG43-MC) across multiple cancer centers.
Results:
Excellent agreement was observed between TG43-TPS and TG43-MC calculated doses, with point-to-point differences of less than 1 Gy (∼1% of prescription dose) for breast and prostate cases. Comparisons between multicenter TG186-MC and TG43-MC doses highlighted discrepancies that underscore the limitations of the TG-43 formalism and affirming the necessity for a model-based dose calculation algorithm (MBDCA).
Conclusion:
This study successfully developed a series of test cases and a commissioning workflow for implementing eb_gui in LDR brachytherapy across multiple centers. The findings underscore the potential of TG-186 MBDCA to enhance the precision of patient dosimetry and improve the accuracy of treatment outcome predictions in LDR brachytherapy. This work represents a significant step toward broader adoption of advanced dose calculation methodologies in clinical practice.
