Evaluating the sensitivity of Halcyon’s automatic transit image acquisition for treatment error detection: A phantom study using static IMRT

PURPOSE: The Varian Halcyon™ electronic portal imaging detector is always in‐line with the beam and automatically acquires transit images for every patient with full‐field coverage. These images could be used for “every patient, every monitor unit” quality assurance (QA) and eventually adaptive radiotherapy. This study evaluated the imager’s sensitivity to potential clinical errors and day‐to‐day variations from clinical exit images. METHODS: Open and modulated fields were delivered for each potential error. To evaluate output changes, monitor units were scaled by 2%–10% and delivered to solid water slabs and a homogeneous CIRS phantom. To mimic weight changes, 0.5–5.0 cm of buildup was added to the solid water. To evaluate positioning changes, a homogeneous and heterogeneous CIRS phantom were shifted 2–10 cm and 0.2–1.5 cm, respectively. For each test, mean relative differences (MRDs) and standard deviations in the pixel‐difference histograms (σ(RD)) between test and baseline images were calculated. Lateral shift magnitudes were calculated using cross‐correlation and edge‐detection filtration. To assess patient variations, MRD and σ(RD) were calculated from six prostate patients’ daily exit images and compared between fractions with and without gas present. RESULTS: MRDs responded linearly to output and buildup changes with a standard deviation of 0.3%, implying a 1% output change and 0.2 cm changes in buildup could be detected with 2.5σ confidence. Shifting the homogenous phantom laterally resulted in detectable MRD and σ(RD) changes, and the cross‐correlation function calculated the shift to within 0.5 mm for the heterogeneous phantom. MRD and σ(RD) values were significantly associated with the presence of gas for five of the six patients. CONCLUSIONS: Rapid analyses of automatically acquired Halcyon™ exit images could detect mid‐treatment changes with high sensitivity, though appropriate thresholds will need to be set. This study presents the first steps toward developing effortless image evaluation for all aspects of every patient’s treatment.