Quality assurance of a gimbaled head swing verification using feature point tracking

To perform dynamic tumor tracking ( DTT ) for clinical applications safely and accurately, gimbaled head swing verification is important. We propose a quantitative gimbaled head swing verification method for daily quality assurance ( QA ), which uses feature point tracking and a web camera. The web camera was placed on a couch at the same position for every gimbaled head swing verification, and could move based on a determined input function (sinusoidal patterns; amplitude: ± 20 mm; cycle: 3 s) in the pan and tilt directions at isocenter plane. Two continuous images were then analyzed for each feature point using the pyramidal Lucas–Kanade ( LK ) method, which is an optical flow estimation algorithm. We used a tapped hole as a feature point of the gimbaled head. The period and amplitude were analyzed to acquire a quantitative gimbaled head swing value for daily QA . The mean ±  SD of the period were 3.00 ± 0.03 (range: 3.00–3.07) s and 3.00 ± 0.02 (range: 3.00–3.07) s in the pan and tilt directions, respectively. The mean ±  SD of the relative displacement were 19.7 ± 0.08 (range: 19.6–19.8) mm and 18.9 ± 0.2 (range: 18.4–19.5) mm in the pan and tilt directions, respectively. The gimbaled head swing was reliable for DTT . We propose a quantitative gimbaled head swing verification method for daily QA using the feature point tracking method and a web camera. Our method can quantitatively assess the gimbaled head swing for daily QA from baseline values, measured at the time of acceptance and commissioning.