Room: AAPM ePoster Library
Purpose: aim of this study was to develop a delivery quality assurance system which enables verification of both three-dimensional (3D) dose distribution and mechanical motion simultaneously in intensity-modulated radiation therapy (IMRT) using helical tomotherapy.
Methods: developed a prototype detector system which consisted of a cylindrical plastic scintillator (20 cm diameter and 15 cm thickness) and a cooled charged-coupled device (CCD) camera. The scintillation light was recorded by a CCD camera with 512 × 680 pixels, 16-bit gray scale and 8.1 frame per second. First, we measured the relationship between the amount of light recorded by a CCD camera and the leaf opening time of the multi-leaf collimator (MLC). Then, the light distribution was obtained by integrating all frames during IMRT irradiation. The distribution was compared with calculated dose distribution exported from the radiation treatment planning system (RTPS). Finally, regarding the mechanical motion, leaf opening time of the MLC was obtained from the amount of light recorded in each frame. The measured leaf opening time was compared with a sinogram exported from RTPS.
Results: between the leaf opening time and the amount of light was linear. The light distribution showed similar shape as the dose distribution. In an axial plane at the center of planning target volume, they were 1.0±0.3% and 99%, respectively. In accumulated distribution for all axial planes, average dose difference and the pass rate of gamma evaluation with 3%/3 mm were 1.4±0.2% and 99%, respectively. As a result of examination of MLC movements, the sensitivity and specificity of reconstructed sinogram were more than 97%, and average leaf opening error was -3.9±7.8%.
Conclusion: developed delivery quality assurance system which enables to verify both 3D dose distribution and mechanical motion simultaneously and accurately in helical tomotherapy.
Funding Support, Disclosures, and Conflict of Interest: The present study was supported by JSPS KAKENHI Grant Number 18K15561.