Author: Ana Maria Barragan Montero, Damien Dasnoy, Sylvain Deffet, Valentine Dormal, Colin Gaban, Melanie Ghislaine, Valentin Hamaide, Guillaume Janssens, John A. Lee, Eliot Peeters, Danah Pross, Luciano Rivetti, Benjamin Roberfroid, Romain Schyns, Kevin Souris, Edmond S. Sterpin, Sophie Wuyckens 👨🔬
Affiliation: Ion Beam Applications SA, Hospital Riviera-Chablais, UCLouvain, Multitel, Université Catholique de Louvain, IBA, Faculty of Mathematics and Physics, University of Ljubljana, Universite Catholique de Louvain 🌍
Purpose: Treatment planning systems (TPSs) are essential for simulating and optimizing radiotherapy treatments. However, clinical TPSs are expensive software commercialized by private companies and often considered black-boxes with limited access to most of their features (i.e., image registration, dose calculation and optimization). This hampers their use for educational purposes, and holds up researchers trying to implement and test new ideas. We have developed an open-source software platform (opentps.org) to create customized treatment plans for educational and research purposes, particularly for emerging delivery and optimization techniques like FLASH or arc proton therapy, among others.
Methods: OpenTPS is written in python and designed to be easily extended and customized. The software is organized into two packages: the Core, which defines libraries for data classes, data processing, and IO methods, and the GUI, a graphical user interface for viewing and interacting with the data (based on PyQt, VTK, and PyQtGraph libraries, widely recognised in research and educational environments). The choice to separate core from GUI aims at having enhanced flexibility to support both students and researchers using basic GUI-based operations, and basic to advanced scripting operations in high-performance computers and servers.
Results: The main building blocks of the Core package are: image processing tools (DICOM reading/writing, rigid/non-rigid deformation, etc.), dose calculation algorithms (Monte Carlo with MCsquare for protons and Collapsed Cone Convolution for photons), and a set of optimization algorithms (including robust optimization). The entire GUI is extensible and modifiable by the user. To date, OpenTPS has been used in more than 15 research publications, 5 master thesis, and we are currently investigating its use in master courses for biomedical engineering students.
Conclusion: OpenTPS offers a flexible and dynamic platform for exploring new educational and research possibilities and pushing the boundaries of what is possible in radiation therapy treatment planning.