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SU‐E‐T‐100: Designing a QA Tool for Enhance Dynamic Wedges Based On Dynalog Files
Author(s) -
Yousuf A,
Hussain A
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 - 10.1118/1.4888430
Subject(s) - quality assurance , computer science , wedge (geometry) , orientation (vector space) , imaging phantom , simulation , algorithm , nuclear medicine , mathematics , geometry , medicine , external quality assessment , pathology
Purpose: A robust quality assurance (QA) program for computer controlled enhanced dynamic wedge (EDW) has been designed and tested. Calculations to perform such QA test is based upon the EDW dynamic log files generated during dose delivery. Methods: Varian record & verify system generates dynamic log (dynalog) files during dynamic dose delivery. The system generated dynalog files contain information such as date and time of treatment, energy, monitor units, wedge orientation, and type of treatment. It also contains the expected calculated segmented treatment tables (STT) and the actual delivered STT for the treatment delivery as a verification record. These files can be used to assess the integrity and precision of the treatment plan delivery. The plans were delivered with a 6 MV beam from a Varian linear accelerator. For available EDW angles (10°, 15°, 20°, 25°, 30°, 45°, and 60°) Varian STT values were used to manually calculate monitor units for each segment. It can also be used to calculate the EDW factors. Independent verification of fractional MUs per segment was performed against those generated from dynalog files. The EDW factors used to calculate MUs in TPS were dosimetrically verified in solid water phantom with semiflex chamber on central axis. Results: EDW factors were generated from the STT provided by Varian and verified against practical measurements. The measurements were in agreement of the order of 1 % to the calculated EDW data. Variation between the MUs per segment obtained from dynalog files and those manually calculated was found to be less than 2%. Conclusion: An efficient and easy tool to perform routine QA procedure of EDW is suggested. The method can be easily implemented in any institution without a need for expensive QA equipment. An error of the order of ≥2% can be easily detected.