Reference datasets for commissioning of model‐based dose calculation algorithms for electronic brachytherapy
Authors:
Open Access
- 25 May 2025
- journal article
- Published by Wiley in Medical Physics
- Vol. 52 (7)
Abstract
Purpose: This 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 Methods: The 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 Notes: The 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 Applications: This 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.Keywords
Funding Information
- Agencia Estatal de Investigación
- Canadian Institutes of Health Research (FDN‐143257)
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