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RapidBrachyMCTPS: Addition of Contouring Tools to the Monte Carlo-Based Treatment Planning System for Brachytherapy Applications

Harry Glickman*1, Majd Antaki1, Shirin A. Enger1,2,3, (1) Medical Physics Unit, McGill University, Montreal, Quebec, H4A 3J1, Canada (2) Department of Oncology, McGill University, Montreal, Quebec, H4A 3J1, Canada (3) Research Institute of the McGill University Health Centre, Montreal, Quebec, H3H 2L9, Canada


(Sunday, 7/14/2019)  

Room: ePoster Forums

Purpose: We have previously described RapidBrachyMCTPS, a brachytherapy treatment planning toolkit consisting of a graphical user interface (GUI), optimizers, and a Geant-4 based Monte Carlo (MC) dose calculation engine. This work will describe the contouring tools that have been added to RapidBrachyMCTPS, such that it now serves as the first standalone application for MC-based brachytherapy treatment planning.

Methods: All GUI elements are built using Qt, a cross-platform UI software development kit. The contouring tools have been added primarily using the Visualization Toolkit, a C++ library designed to manipulate and display scientific data. Concepts essential for implementation of contouring tools include patient image data representation, contour polygon representation, binary mask generation, polygon and mask logical operations, and contour interpolation.

Results: Users are able to contour structures entirely within the application, using freehand draw, polygon draw, or brush tools. Boolean operations can be performed using any of the draw styles, and contours can be morphed or translated once drawn. Contours can be created on any of the three orthogonal axes, with the other two axes updating accordingly. Instead of drawing on every slice, interpolation can be performed to fill in the missing slices. Contours can also be loaded from, or exported as, DICOM-RT files.

Conclusion: RapidBrachyMCTPS is now a standalone application for brachytherapy treatment planning, and offers a user-friendly interface to access powerful MC calculations. It can be used to validate dose distributions from clinical treatment planning systems or model-based dose calculation algorithms, and is also well suited to testing novel combinations of sources and applicators, especially those shielded with high-Z materials.

Funding Support, Disclosures, and Conflict of Interest: This work was supported by the Collaborative Health Research Projects (grant 523394-18) and Natural Sciences and Engineering Research Council (grant 241018).


Brachytherapy, Treatment Planning, Computer Software


TH- Brachytherapy: Dose optimization and planning

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