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Three Year Experience of Electronic Portal Image Device Based DailyQA for Photon Radiation Beams

B Cai , Y He , D Bollinger , R Morris , S Goddu , S Mutic , B Sun*, Washington University School of Medicine, St. Louis, MO

Presentations

(Saturday, 4/7/2018)  

Room: Foyer

Purpose: To review and analyze three years’ EPID based daily QA results of photon beams on a Varian TrueBeam linac.

Methods: An in-house designed EPID based QA strategy was deployed clinically to test machine daily performance before treatment. Beam dosimetic parameters, such as output, flatness, symmetry, uniformity, TPR20/10, MLC field delivery repeatability, as well as image quality metrics, e.g. high or low contrast resolutions, were accessed based on MV and kV EPID image analysis. Three years data were collected and analyzed. Trend analysis with data visualization, comparisons to ionization chamber (IC) results and QA failure studies were performed to evaluate the reliability and robustness of the EPID based daily QA system.

Results: The EPID output tests over the three-year period agreed with the monthly QA IC system within 1.3% and TG51 results within 1%. A consistent positive output drifting was detected for all energies over the time. A faster drifting speed was observed after the installation of a new dose monitoring chamber but slowed down over the time. Symmetry, flatness, and uniformity were stable and the changes were directly related to beam steering and the imager calibration. TPR20/10 is not sensitive to dosimetry fluctuations and a good delivery repeatability of MLC fields were observed. The image quality metrics were also stable and a failure rate around 2% were observed. Based on QA failure analysis, efforts were made to improve the robustness of the process, such as staff training, algorithm modification and tolerance adjustment.

Conclusion: The three years data indicates the EPID based process is an efficient and reliable QA solution for daily linac performance check. The long term trend analysis and data visualization helps physicists understand the behavior of linac, optimize daily QA procedure and has the potential to predict machine failures ahead of incidents.

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