Patient-Specific Quality Control (PSQA) of stereotactic treatments in radiotherapy: a study of the sensitivity of a commercial in-vivo dosimetry system

Abstract

This study evaluates a commercial automated in-vivo dosimetry software for stereotactic radiotherapy, focusing on its sensitivity to variations and accuracy in dose prediction. Development: The system’s sensitivity was assessed through linear accelerator performance tests, detecting both natural and intentionally introduced errors. Methods: The research was divided into two parts. In Part A, the system’s sensitivity was tested by assessing output constancy and linearity for different field sizes. A homogeneous phantom simulated static fields, allowing the introduction of controlled discrepancies, including geometric shifts, multileaf collimator (MLC) deviations, and energy variations. Part B used a heterogeneous phantom replicating human head and neck anatomy to simulate realistic stereotactic radiotherapy plans with varying targets and doses. These plans were intentionally modified before irradiation and delivered to an electronic portal imaging device. Planned and delivered dose distributions were compared using gamma index criteria. Results: Output linearity tests showed improved gamma passing rates with higher dose deliveries, while larger fields exhibited degraded rates due to steep dose falloff at field borders. The 3%/3mm criterion was ineffective for low-dose segments. For output constancy, gamma passing rates improved with stricter 2%/2mm and 1%/1mm criteria as dose decreased, whereas the 3%/3mm criterion remained insensitive. The system effectively detected intentional output variations, though sensitivity dropped for dose differences below 5%. It identified field size variations up to 1 mm and collimator rotations up to 5°, with MLC discrepancies detectable up to 1 mm. Among the tested criteria, 3%/3mm proved least robust. Energy variations were accurately detected. Tests with the heterogeneous phantom confirmed the platform’s ability to verify planned treatment parameters and dose metrics accurately. Conclusion: The study provided a comprehensive assessment of stereotactic treatment plan quality. The evaluated platform demonstrated strong capability to detect performance variations, geometric and MLC errors, and energy discrepancies, ensuring confidence in the quality assurance process. The findings support avoiding the use of permissive gamma criteria such as 3%/3mm in stereotactic treatments, as they provide limited insight into plan quality.