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SlicerRT: Radiation therapy research toolkit for 3D Slicer
Author(s) -
Pinter Csaba,
Lasso Andras,
Wang An,
Jaffray David,
Fichtinger Gabor
Publication year - 2012
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.4754659
Subject(s) - computer science , visualization , workflow , software , dicom , software engineering , documentation , medical imaging , medical physics , data mining , artificial intelligence , programming language , database , medicine
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, and 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, and 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. Conclusions: A new open‐source software toolkit has been developed for radiation therapy research. SlicerRT can import treatment plans from various sources into 3D Slicer for visualization, analysis, comparison, and processing. The provided algorithms are extensively tested and they are accessible through a convenient graphical user interface as well as a flexible application programming interface.