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SU‐E‐T‐482: Development and Systematic Testing of Dose Analysis Engine for Research and Clinical Applications Using API Interface of Varian Eclipse Treatment Planning System
Author(s) -
Fatyga M,
Gao F,
Wu T,
Liu W
Publication year - 2014
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 - 10.1118/1.4888815
Subject(s) - computer science , histogram , dose volume histogram , voxel , eclipse , software , interface (matter) , dicom , standard deviation , volume (thermodynamics) , bitmap , radiation treatment planning , nuclear medicine , data mining , mathematics , computer graphics (images) , statistics , artificial intelligence , medicine , radiation therapy , image (mathematics) , physics , bubble , quantum mechanics , astronomy , maximum bubble pressure method , parallel computing , programming language
Purpose: To validate standalone software that provides dose analysis capabilities of a treatment planning system. The intended use of this software is in research and in clinical applications where commercial solutions are not yet available. Methods: We used Application Programmer Interface (API) of the Eclipse Treatment Planning System (Varian,Inc), to extract dosimetric information from treatment plans. We used dose volume histogram (DVH) object to extract standard dose volume histogram data. We used two API functions to construct 3D representation of anatomy (a bitmap) and compute dose values at all voxels that belong to a structure. We wrote a C++ package which achieves the same reconstruction based on stored contour data and a dose volume. For this work we compared structure volumes and simple dose statistics on dose buffers (minimum, mean, maximum and standard deviation). We used data from 6 Head and Neck patients and examined a total of 102 structures. Results: The API based reconstruction of 3D anatomy systematically overestimates structure volumes when compared to volumes reported by the API DVH module. The discrepancy is largest for small structures, and can exceed 20%. Volume estimates obtained by the C++ package show better agreement with the DVH module if partial volume corrections are applied to surface voxels. Among four dosimetric variables, largest discrepancies are observed for the minimum dose. While we observe better than 2% agreement in most cases, we find outliers with discrepancies reaching over 20%, even when we compare the two API based methods. Conclusion: We find that good validation of a standalone dose analysis package requires testing on a large series of structures obtained from multiple patients. Disagreements between two API based methods show that vendor algorithms have hidden features which may affect dosimetric analysis.