Longitudinal Quality Assurance of Elekta Versa HD XVI CBCT: A Phantom-Based Analysis of Image Quality and Noise Performance

Abstract

Background: Given the critical role of the Elekta Versa HD XVI cone-beam computed tomography (CBCT) system in image-guided radiotherapy, rigorous quality assurance is essential to ensure diagnostic accuracy. Objectives: This study establishes a physics-driven quality assurance (QA) protocol for the Elekta Versa HD XVI CBCT system to quantify image quality and identify technical deviations that may affect clinical positioning accuracy in radiotherapy. Methods: Monthly CatPhan 503 QA assessments, including uniformity, noise, low- and high-contrast resolution, and Hounsfield unit (HU) stability, were performed in accordance with the American Association of Physicists in Medicine Task Group-142 and TG-179 guidelines. Linear regression analyses were used to evaluate temporal trends in the five CBCT image QA parameters over the 6-month observation period. Results: Data acquisition included six measurements obtained from a single Elekta Versa HD linear accelerator over six months. Quality assurance demonstrated excellent spatial resolution (14 lp/cm) and HU stability, with a maximum deviation of 18 HU. However, a critical noise failure was identified in the phantom's central region of interest, with a standard deviation (SD) of 22.21 HU and a mean pixel value of 1017 HU. This yielded a noise performance descriptor (NPD) of 2.18%, exceeding the acceptance threshold of ≤ 2.0%. Following detection, the system was removed from clinical use for recalibration and was subsequently returned to operation after meeting standard institutional QA criteria. Conclusions: The Elekta Versa HD XVI CBCT system demonstrates robust performance in spatial resolution, uniformity, and HU stability. However, the NPD exceedance (2.18%), which was subsequently resolved through recalibration, underscores the need to incorporate advanced metrics, such as the noise power spectrum, into routine longitudinal QA. Proactive monitoring is essential to mitigate potential risks to adaptive radiotherapy workflows.