Performing radiation therapy research using the open-source SlicerRT toolkit

Radiation therapy (RT) is a common treatment option for a wide variety of cancer types. Despite significant improvements in this technique over the past years, software tools for research in RT are limited to either expensive, closed, proprietary applications or heterogeneous sets of open-source software packages with limited scope, reliability, and user support. Our SlicerRT toolkit aspires to overcome these limitations by providing an extensive set of RT research tools leveraging the advanced visualization and image analysis features of its base platform 3D Slicer. The SlicerRT toolkit comprises of a set of 3D Slicer extensions: SlicerRT core, Matlab Bridge, Multi-dimensional Data, and Gel Dosimetry. The SlicerRT core extension contains 26 modules, many of which provide common RT tools used in most RT research scenarios. Matlab Bridge provides a convenient way for connecting the researchers’ existing MATLAB algorithms to the SlicerRT ecosystem. Multi-dimensional Data offers a feature set for handling multi-dimensional datasets, such as longitudinal studies or 4D data. Finally, Gel Dosimetry facilitates gel dosimetry analysis workflows through a streamlined, workflow-based end-user application. It serves as an example and proof of concept for such applications implementing advanced clinical or research workflows. Using these open-source software tools makes it possible to conduct cutting edge RT research without parallel development efforts. It acts as a medium into which researchers can integrate their methods into, and which they can use to perform comparative validation, develop novel RT techniques, or transition advanced methods into routine clinical practice. Keywords— Radiation therapy, 3D Slicer, DICOM-RT, dosimetry, adaptive radiation therapy