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Mansour, I. R., Valdes-Cortez, C., Ayala Alvarez, D. S., Berumen, F., Côte, J. S., Ndoutoume-Paquet, G., et al. (2025). Reference datasets for commissioning of model-based dose calculation algorithms for electronic brachytherapy. Med. Phys., , 11pp.
Abstract: PurposeThis work provides the first two clinical test cases for commissioning electronic brachytherapy (eBT) model-based dose calculation algorithms (MBDCAs) for skin irradiation using surface applicators.Acquisition and Validation MethodsThe test cases utilize the INTRABEAM 30 mm surface applicator. Test Case I: water phantom is used to evaluate the algorithm's performance in a uniform medium consisting of a voxelized water cube surrounded by air. Test Case II: Surface eBT represents a heterogeneous medium with four distinct layers: skin tissue, adipose tissue, cortical bone, and soft tissue. Treatment plans for both cases were created and exported into the Radiance treatment planning system (TPS). Dose-to-medium calculations were then performed using this Monte Carlo (MC)-based TPS and compared with MC simulations conducted independently by three different groups using two codes: EGSnrc and PENELOPE. The results agreed within expected Type A and B statistical uncertainties.Data Format and Usage NotesThe dataset is available online at https://doi.org/10.52519/00005. A proprietary file designed for use within Radiance containing CT images and the treatment plan for both test cases, the LINAC modeling, and the CT calibration are included, as well as reference MC and TPS dose data in RTdose format and all files required to run the MC simulations.Potential ApplicationsThis dataset serves as a valuable resource for commissioning eBT MBDCAs and lays the groundwork for developing clinical test cases for other eBT systems. It is also a helpful educational tool for exploring various eBT devices and their advantages and drawbacks. Furthermore, brachytherapy researchers seeking a benchmark for dosimetric calculations in the low-energy domain will find this dataset indispensable.
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Peppa, V., Thomson, R. M., Enger, S. A., Fonseca, G. P., Lee, C. N., Lucero, J. N. E., et al. (2023). A MC-based anthropomorphic test case for commissioning model-based dose calculation in interstitial breast 192-Ir HDR brachytherapy. Med. Phys., 50(7), 4675–4687.
Abstract: PurposeTo provide the first clinical test case for commissioning of Ir-192 brachytherapy model-based dose calculation algorithms (MBDCAs) according to the AAPM TG-186 report workflow. Acquisition and Validation MethodsA computational patient phantom model was generated from a clinical multi-catheter Ir-192 HDR breast brachytherapy case. Regions of interest (ROIs) were contoured and digitized on the patient CT images and the model was written to a series of DICOM CT images using MATLAB. The model was imported into two commercial treatment planning systems (TPSs) currently incorporating an MBDCA. Identical treatment plans were prepared using a generic Ir-192 HDR source and the TG-43-based algorithm of each TPS. This was followed by dose to medium in medium calculations using the MBDCA option of each TPS. Monte Carlo (MC) simulation was performed in the model using three different codes and information parsed from the treatment plan exported in DICOM radiation therapy (RT) format. Results were found to agree within statistical uncertainty and the dataset with the lowest uncertainty was assigned as the reference MC dose distribution. Data Format and Usage NotesThe dataset is available online at ,. Files include the treatment plan for each TPS in DICOM RT format, reference MC dose data in RT Dose format, as well as a guide for database users and all files necessary to repeat the MC simulations. Potential ApplicationsThe dataset facilitates the commissioning of brachytherapy MBDCAs using TPS embedded tools and establishes a methodology for the development of future clinical test cases. It is also useful to non-MBDCA adopters for intercomparing MBDCAs and exploring their benefits and limitations, as well as to brachytherapy researchers in need of a dosimetric and/or a DICOM RT information parsing benchmark. Limitations include specificity in terms of radionuclide, source model, clinical scenario, and MBDCA version used for its preparation.
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