An automated daily QA strategy for dosimetry and imaging guidance check of a novel PET/CT ring gantry linac

一种新型PET/CT环形机架直线加速器剂量测定和成像引导检查的自动化日常质量保证策略

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Abstract

BACKGROUND: The RefleXion X1 is a novel PET/CT-guided ring gantry linac that introduces unique geometry and workflow compared to conventional systems. Existing QA guidelines (AAPM TG-142, 148, 306) cover standard linacs and tomotherapy but do not address this platform's needs. Therefore, an automated daily QA solution is required to ensure accurate output, imaging guidance, and couch positioning, which motivated the development and evaluation of the workflow presented in this study. PURPOSE: To develop and evaluate an automated, efficient, and comprehensive daily quality assurance (QA) workflow for a novel PET/CT-guided ring gantry linear accelerator (RefleXion X1), incorporating tests for dosimetry, imaging guidance, and couch positioning accuracy. METHODS: An IMRT QA plan was designed following the CT scan of the TomoDose 2D diode detector array (Sun Nuclear, Melbourne, FL) within the RefleXion treatment planning system (TPS). Several spherical targets of varying sizes were contoured to conform the dose distribution to these targets and evaluate beam output, laser localization, profile constancy, and CT-MV isocenter coincidence. Linear models correlating spatial location of dose peak with intentional shifts in different directions were developed and integrated into an in-house analysis software, iQA, written in C#. The software was validated for robustness and successfully implemented in clinical practice. RESULTS: Validation with 42 intentional shifts showed submillimeter accuracy, with mean deviations of 0.2 mm (X), 0.1 mm (Y), and 0.79 mm (Z), and R(2) values ≥ 0.98. Over 1 year, daily QA data showed stable output constancy (1.006 ± 0.016), left/right target dose constancy (1.007 ± 0.005 and 0.996 ± 0.004), and consistent CT-MV isocenter offsets (-0.335 ± 0.23 mm in X, 0.19 ± 0.19 mm in Y, and -0.544 ± 0.36 mm in Z). The software also detected a gradual output drift in between, prompting a timely linac adjustment. CONCLUSION: This fully automated, single-delivery QA workflow enables efficient and robust evaluation of multiple IGRT performance parameters. It improves standardization, reduces human error, and reliably monitors long-term machine stability. The tools and methodology may be adopted by other clinics seeking a practical and automated daily QA solution. Future developments will focus on incorporating PET QA and rotational couch validations to further enhance the system's comprehensiveness and adaptability.

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