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SlicerRT - Radiation Therapy Research Toolkit for 3D Slicer

1Laboratory for Percutaneous Surgery, School of Computing, Queen’s University, Kingston, ON, Canada.
2Radiation Medicine Program, Princess Margaret Hospital, University Health Network, Toronto, Ontario, Canada.
Publication Date:
Medical Physics
Volume Number:
Issue Number:
Medical Physics. 2012 Oct;39(10):6332-7.
3D Slicer, DICOM-RT, dose comparison, dose volume histogram, Radiation therapy
Appears in Collections:
SLICER, NA-MIC, Prostate Group
Ontario Research Fund Research Excellence Program, Ontario Consortium for Adaptive Interventions in Radiation Oncology (OCAIRO)
Generated Citation:
Pinter C., Lasso A., Wang A., Jaffray D., Fichtinger G. SlicerRT - Radiation Therapy Research Toolkit for 3D Slicer. Medical Physics. 2012 Oct;39(10):6332-7.
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Purpose: Interest in adaptive radiation therapy research is constantly growing, but software tools available for researchers are mostly either expensive, closed proprietary applications or free open-source packages with limited scope, extensibility, reliability, or user support. To address these limitations, we propose SlicerRT, a customizable, free, open-source radiation therapy research toolkit. SlicerRT aspires to be an open-source toolkit for RT research, providing fast computations, convenient workflows for researchers, and a general image-guided therapy infrastructure to assist clinical translation of experimental therapeutic approaches. It is a medium into which RT researchers can integrate their methods and algorithms, and conduct comparative testing. Methods: SlicerRT was implemented as an extension for the widely used 3D Slicer medical image visualization and analysis application platform. SlicerRT provides functionality specifically designed for radiation therapy research, in addition to the powerful tools that 3D Slicer offers for visualization, registration, segmentation, and data management. The feature set of SlicerRT was defined through consensus discussions with a large pool of RT researchers, including both radiation oncologists and medical physicists. The development processes used were similar to those of 3D Slicer to ensure software quality. Standardized mechanisms of 3D Slicer were applied for documentation, distribution, and user support. The testing and validation environment was configured to automatically launch a regression test upon each software change and to perform comparison with ground truth results provided by other RT applications. Results: Modules have been created for importing and loading DICOM-RT data, computing and displaying dose volume histograms, creating accumulated dose volumes, comparing dose volumes, visualizing isodose lines and surfaces. The effectiveness of using 3D Slicer with the proposed SlicerRT extension for radiation therapy research was demonstrated on multiple use cases.

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