GAMMORA: a tool to automatically prepare radiotherapy simulations

The radiation dose delivered to the patient in radiotherapy is usually calculated using commercial software (“TPS”) which allows a very accurate calculation in the vast majority of clinical cases. However, it is sometimes necessary to have access to a reference calculation under certain complex conditions or for research purposes: very small treatment fields, presence of very dense heterogeneity, complex target motion, determination of reference data, etc. The Monte-Carlo method is considered as the reference calculation in medical physics and the GATE platform () is one of the most used tools in this field. It is based on the Geant4 computational library (geant4.web.cern.ch) developed by the CERN physics teams. This article presents GAMMORA, a project developed at the CRCT that allows to easily generate Monte-Carlo GATE simulations for radiotherapy, for the VARIAN TrueBeam accelerator (one of the most common in the world). This tool has many applications in the field, some of which are presented here.  This is a technical note, i.e. a reference article that presents the project.

The clinical impact of this work will be for example, modulated stereotaxy (SBRT VMAT) of bronchial cancers has started in the Department of Radiotherapy after evaluating the importance of the interplay effect using measurements and simulations with the GAMMORA tool. The evaluation of a new commercial TPS algorithm is also underway by comparing it with GAMMORA measurements and simulations.

The tool is open-source under the LGPL license.

This work is freely available:  https://github.com/uhqd/GAMMORA (this link points to a github repository which contains all the documentation and publications related to the project)

This work benefited from access to the CALMIP supercomputer (project 2016-P19001) and received a “Physicancer” grant from the INCA (STEREPID) in 2016

One picture

Example of radiotherapy modelling with GAMMORA. All elements of the machine head are modelled. A CT scan of a patient with bronchial cancer is used here.

Collaborations and acknowledgements