In this paper, we suggest a new method for verifying the motion of a binary multileaf collimator (MLC) in helical tomotherapy. For this we used a combination of a cylindrical scintillator and a general-purpose camcorder. The camcorder records the light from the scintillator following photon irradiation, which we use to track the motion of the binary MLC. The purpose of this study is to demonstrate the feasibility of this method as a binary MLC quality assurance (QA) tool. First, the verification was performed using a simple binary MLC pattern with a constant leaf open time; secondly, verification using the binary MLC pattern used in a clinical setting was also performed. Sinograms of simple binary MLC patterns, in which leaves that were open were detected as "open" from the measured light, define the sensitivity which, in this case, was 1.000. On the other hand, the specificity, which gives the fraction of closed leaves detected as "closed", was 0.919. The leaf open error identified by our method was -1.3 ± 7.5%. The 68.6% of observed leaves were performed within ± 3% relative error. The leaf open error was expressed by the relative errors calculated on the sinogram. In the clinical binary MLC pattern, the sensitivity and specificity were 0.994 and 0.997, respectively. The measurement could be performed with -3.4 ± 8.0% leaf open error. The 77.5% of observed leaves were performed within ± 3% relative error. With this method, we can easily verify the motion of the binary MLC, and the measurement unit developed was found to be an effective QA tool.
[Show abstract][Hide abstract] ABSTRACT: Background
TomoTherapy (Accuray, USA) has an image-guided radiotherapy system with a megavoltage (MV) X-ray source and an on-board imaging device. This system allows one to acquire the delivery sinogram during the actual treatment, which partly includes information from the irradiated object. In this study, we try to develop image reconstruction during treatment with helical tomotherapy.FindingsSinogram data were acquired during helical tomotherapy delivery using an arc-shaped detector array that consists of 576 xenon-gas filled detector cells. In preprocessing, these were normalized with full air-scan data. A software program was developed that reconstructs 3D images during treatment with corrections as; (1) the regions outside the field were masked not to be added in the backprojection (a masking correction), and (2) each voxel of the reconstructed image was divided by the number of the beamlets passing through its voxel (a ray-passing correction).The masking correction produced a reconstructed image, however, it contained streak artifacts. The ray-passing correction reduced this artifact. Although the SNR (the ratio of mean to standard deviation in a homogeneous region) and the contrast of the reconstructed image were slightly improved with the ray-passing correction, use of only the masking correction was sufficient for the visualization purpose.Conclusions
The visualization of the treatment area was feasible by using the sinogram in helical tomotherapy. This proposed method would be useful in the treatment verification.
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