Journal of Medical Physics (Jun 2024)
Validation and Efficiency Evaluation of Automated Quality Assurance Software SunCHECK™ Machine for Mechanical and Dosimetric Quality Assurance
Abstract
Recent decades have witnessed transformative advances in radiation physics and computer technology, revolutionizing the precision of radiation therapy. The adoption of intricate treatment techniques such as three-dimensional conformal radiotherapy, intensity-modulated radiotherapy, volumetric-modulated arc therapy, and image-guided radiotherapy necessitates robust quality assurance (QA) programs. This study introduces the SunCHECK™ Machine (SCM), a web-based QA platform, presenting early results from its integration into a comprehensive QA program. linear accelerators (LINAC) demand QA programs to uphold machine characteristics within accepted tolerances. The increasing treatment complexity underscores the need for streamlined procedures. The selection of QA tools is vital, requiring efficiency, accuracy, and alignment with clinic needs, as per recommendations such as the AAPM task group 142 report. The materials and methods section details SCM implementation in various QA aspects, encompassing daily QA (DQA), imaging QA with Catphan, conventional output assessment with a water phantom, and LINAC isocenter verification through the Winston–Lutz test. Challenges in QA processes, such as manual data transcription and limited device integration, are highlighted. Early results demonstrate SCM’s significant reduction in QA time, ensuring accuracy and efficiency. Its automation eliminates interobserver variation and human errors, contributing to time savings and near-immediate result publication. SCM’s role in consolidating and storing DQA data within a single platform is emphasized, offering potential in resource optimization, especially in resource-limited settings. In conclusion, SCM shows promise for efficient and accurate mechanical and dosimetric QA in radiation therapy. The study underscores SCM’s potential to address contemporary QA challenges, contributing to improved resource utilization without compromising quality and safety standards.
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