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SU‐E‐T‐594: Software Application for Comparison and Verification of Radiotherapy Treatment Plans
Author(s) -
Bacchus I,
Gopalakrishnan M,
Kang Z
Publication year - 2013
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 - 10.1118/1.4815022
Subject(s) - dicom , collimator , computer science , software , medical physics , radiation treatment planning , plan (archaeology) , matlab , test plan , simulation , nuclear medicine , radiation therapy , operating system , medicine , physics , mathematics , statistics , optics , radiology , archaeology , weibull distribution , history
Purpose: The physics check of a patient treatment plan is one of many that guard against treatment errors in radiation oncology departments. The process would be improved by adding a comparison of treatment plan and prescription parameters, but this would be inordinately time consuming, if not impossible, to do by eye, and would raise the potential for human error. The goal of this project was to develop a software application that would automatically compare treatment parameters from the treatment planning system (Pinnacle3) and the electronic record and verifying system (Mosaiq), supplementing the physics check without sacrificing speed or accuracy. Methods: Both Mosaiq and Pinnacle3 can generate .RTP files. These files contain relevant plan information, are delimited, and have comparable structures. MATLAB code was used to create a GUI‐based application that can run outside of the MATLAB environment. Using .RTP files as inputs, the application compares linac name, beam energy and modality, patient position, DICOM position, field names, gantry angles (checking that the field names contain the gantry angles), MU/fraction, SSD to reference point, beam weights, collimator angles, field sizes, and leaf positions. Program alerts user to any discrepancies and results are written to .txt files and an Excel spreadsheet (for leaf positions) that highlight any discrepancies. Results: The application is currently being rolled out in the Oncology Department for beta testing. During preliminary testing, the application flagged errors in cases with known discrepancies between treatment plan and prescription, indicating the applications effectiveness. Conclusion: The application adds another layer of safety for patients by providing a check for human error immediately before treatment. It focuses the user on patient care by ensuring he or she is cognizant of the current treatment plan. Finally, it produces digitally compact, easy‐to‐read records of the parameters of a given patients treatment.