Author: Dong Wook Kim, Jin Sung Kim, Dongho Lee, Sangmin Lee 👨🔬
Affiliation: Department of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine, Department of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine, Seoul, Korea, Republic of (South) 🌍
Purpose:
This study aims to analyze the characteristics of a novel detector based on a dielectric layer (Vieworks Co., Korea), which demonstrates high tolerance to high radiation doses and light transmittance, and to evaluate its feasibility as a tool for LINAC quality assurance (QA).
Methods:
We use a medical linear accelerator (LINAC, Harmony Pro, Elekta, Sweden) that delivering therapeutic high-energy photons beams to evaluate detectors that convert radiation into signals using dielectric layers different from conventional detectors that consist of semiconductor layers. The detector’s characteristics are assessed based on reproducibility, repeatability, and energy dependency. Additionally, its applicability for QA purposes was evaluated through measurements of linearity, flatness, symmetry, and wedge transmission factors. The standard setup include a source-to-surface distance (SSD) of 100 cm, a field size of 20 × 20 cm², a beam energy of 6 MV, and 100 monitor units (MU). For energy dependency evaluation, beam energies of 6 MV, 10 MV, and 15 MV are utilized. For linearity assessment, measurements were performed at 20, 50, 100, and 300 MU.
Results:
The reproducibility test shows a mean pixel value of 6972.5 with a relative standard deviation (RSD) of 1.0 %. Repeatability demonstrates an RSD of 0.24 %. Energy dependency measurements indicate linearity across beam energies (6 MV to 15 MV), with an R² value of 0.99. Flatness and symmetry are within acceptable limits, measured at 1.04 % and 0.91 %, respectively. The results for 45° wedge transmission factor are within clinically acceptable limits.
Conclusion:
The dielectric layer-based detector demonstrates excellent characteristics and shows the possibility of the reliable tool for LINAC QA. Future studies will focus on validating its clinical applicability and assessing its long-term performance.