WE‐E‐141‐07: Automating Linac QA for Delivery and Analysis

Abstract

Purpose: To assess the quantitative performance and reproducibility of a new generation linear accelerator using images and trajectory log files across institutions. Methods: A test suite was created to include tests recommended by TG142 (e.g, picket fence at cardinal static gantry angles and during VMAT) and TG179 (e.g. image quality). The test suite, distributed to a consortium of 7 institutions, consisted of DICOM‐RT files and a phantom with BBs at known locations. During each delivery, EPID images were acquired along with trajectory log files. Baseline for each irradiation was set with a flood field without the table or phantom. The phantom was then placed in position and the remaining tests were performed. An analysis program, created in Matlab, assessed the accuracy of leaf, jaw, and collimator positions utilizing the EPID images. Trajectory log files were analyzed as well to assess dynamic parameters such as the reproducibility of gantry motion during arc delivery. Results: Fifteen irradiations were performed on 5 accelerators. Leaf position reproducibility was 0.095 mm for a standard MLC and 0.110 mm for an HDMLC, with maximum standard deviations of 0.019, 0.053, and 0.002 mm for static, IMRT, and arc fields over all linacs. Trajectory logs were consistent with measurements. The maximum gantry deviation was 0.247 ± 0.0160 degrees. Using two different materials, the contrast‐to‐noise ratio was 1.43 ±0.740 and 7.41 ±0.24 for kV and MV images with kV CNR varying by more than a factor of 2 between different machines. Conclusion: EPID and trajectory logs demonstrated thresholds for detection of leaf position errors that were an order of magnitude less than TG142 requirements for different delivery types across institutions. Trajectory log files provided more detailed information regarding stability of gantry position. When tracked over time, these data can be used to reassess the frequency of different test types. This work is supported by Varian Medical Systems.