PyTRiP - a toolbox and GUI for the proton/ion therapy planning system TRiP

17th International Conference on the Use of Computers in Radiation Therapy

物理学;计算机科学

Toftegaard, J.^1 ; Petersen, J.B.^2 ; Bassler, N.^1,3

Department of Physics and Astronomy, Aarhus University, Aarhus, Denmark^1

Department of Medical Physics, Aarhus University Hospital, Aarhus, Denmark^2

Department of Experimental Clinical Oncology, Aarhus University Hospital, Aarhus, Denmark^3

关键词: Computer skill;    Graphical user interfaces (GUI);    Linear energy transfer;    Object oriented;    Platform independent;    Therapy planning systems;    Treatment planning systems;    Treatment plans;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/489/1/012045/pdf
DOI  :  10.1088/1742-6596/489/1/012045

学科分类：计算机科学（综合）

来源: IOP

【 摘 要 】

Purpose: Only very few treatment planning systems (TPS) are capable of handling heavy ions. Commercial heavy ion TPS are costly and normally restrict the possibility to implement new functionalities. PyTRiP provides Python bindings and a platform-independent graphical user interface (GUI) for the heavy ion treatment program TRiP, and adds seamless support of DICOM files. We aim to provide a front-end for TRiP which does not require any special computer skills. Methods: PyTRiP is written in Python combined with C for fast computing. Routines for DICOM file import/export to TRiPs native file format are implemented. The GUI comes as an executable with all its dependencies including PyTRiP making it easy to install on Windows, Mac and Linux. Results: PyTRiP is a comprehensive toolbox for handling TRiP. Treatment plans are handled using an object oriented structure. Bindings to TRiP (which only runs on Linux, either locally or on a remote server) are performed through a single function call. GUI users can intuitively create treatment plans without much knowledge about the TRiP user interface. Advanced users still have full access to all TRiP functionality. The user interface comes with a comprehensive plotting tool, which can visualize 2D contours, volume histograms, as well as dose- and linear energy transfer (LET) distributions. Conclusion: We developed a powerful toolbox for ion therapy research using TRiP as backend. The corresponding GUI allows to easily and intuitively create, calculate and visualize treatment plans. TRiP is thereby more accessible and simpler to use.