Author: Alejandro Bertolet, Jorge Naoki Dominguez Kondo, Bruce A. Faddegon, Thongchai Masilela, Isaac Meyer, Victor V. Onecha, Harald Paganetti, Jose A. Ramos-Mendez, Jan PO Schuemann, Wook-Geun Shin 👨🔬
Affiliation: University of California San Francisco, Massachusetts General Hospital and Harvard Medical School, Massachusetts General Hospital 🌍
Purpose: To present the results of 15 years of developments of the TOPAS TOol for PArticle Simulation framework, and to highlight recent and new developments.
Methods: Fundamental understanding of radiotherapy and radiology is greatly facilitated through accurate and detailed simulation of the interaction of ionizing radiation with a patient using the Monte Carlo (MC) method. TOPAS extends Geant4 providing a reliable, and experimentally validated MC tool for medical physicists, radiobiologists, and clinicians. Simulations are defined and controlled by an intuitive, text-based parameter file system, giving access to a multitude of specialized functions designed to facilitate radiation-applied simulations. The latest TOPAS version, OpenTOPAS 4.0, is open source and accompanied by extensive documentation and an active user forum on GitHub.
Results: The initial TOPAS release provided a flexible 4D-MC system focused on proton therapy, incorporating treatment head geometries, patient setup, and advanced tallies, including dose and linear energy transfer (LET). Subsequently added capabilities include radiotherapy outcome and relative biological effectiveness (RBE) modeling, extensive variance reduction methods and settings optimized for proton, X-ray/photon, and electron therapies, a specialized setting for efficient simulation of photoneutrons, brachytherapy seed designs using mass layered geometries, and simulations of optical photons. In addition, TOPAS provides a graphical user interface for simulation setup and visualization. Our latest developments include a multi-scale framework for the simulation of the biological radiation response, the first extensions to model medical imaging systems and radiopharmaceutical therapy dosimetry features. Each release of TOPAS is extensively validated through automated regression testing based on experimental data. A significant focus of our Collaboration has been user support, which is reflected in the success of TOPAS, with over 2500 users and over 1100 citations of the reference paper.
Conclusion: TOPAS is a widely used MC toolkit providing access to simulations of most radiotherapies without the need to write code.