Room: Exhibit Hall | Forum 3
Purpose: To evaluate the ability of the Swiss cheese error detection (SCED) metric to detect subtle, non-gross VMAT plan delivery errors via real-time monitoring of cine of cine EPID imaging compared with Gamma analysis.
Methods: intrEPID, an in house software developed in C++ and Varian iTools interface, which interrogates the on-board EPID aS1200 imager with cine (~10 Hz) acquisition, was used to measure cine-EPID images of two slightly different VMAT auto plans of the same head and neck case, both planned as 1 full arc, 442 MU and varied only by ten iterations of optimization with the same objectives. The dose-coverage of the plans differed slightly as they were exported from the same plan optimization session, at differing number of iterations. SCED utilizes a dynamic aperture masking algorithm, which uses just-in-time interpolation of intended MLC positions to predict each frameâ€™s beam apertures to ascertain aperture delivery errors. For gamma, a 3%/3 mm, 10% dose threshold and >90% passing rate was used to identify delivery errors.
Results: The two treatment plans are highly similar, yet have distinct modulation. In acquisition, each plan resulted in 688 acquired EPID frames. SCED just-in-time masking detected 11.8% of frames with than a >20 mm2 area mismatch. Gamma analysis indicated that 8.4% of the frames have <90% of points with Î³<1. During-delivery gamma analysis on the composite of the delivered frames had >90% of points with Î³<1 through-out the delivery. Mimicking clinical practice, the composite at the conclusion of the delivery indicated a 99.7% passing rate.
Conclusion: Real-time monitoring, which initially aimed to provided gross error detection, can detect subtle, non-gross errors such as a plan which differs slightly from the intended delivery. Detection requires frame-by-frame analysis, and is trivial when the SCED metric is used.
Funding Support, Disclosures, and Conflict of Interest: This work was funded by Varian Medical Systems.
Not Applicable / None Entered.