Implementation and evaluation of the AAPM TG 111 for radiation dosimetry in a state-of-the-art C-arm cone beam CT system.

Journal of radiological protection : official journal of the Society for Radiological Protection(2023)

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摘要
The aim of this study was to assess the dosimetric characteristics of a state-of-the-art C-arm cone beam computed tomography (CBCT) system using the methodology proposed by the American Association of Physicists in Medicine (AAPM) Task Group (TG) 111. The dose measurement methodology described in AAPM TG 111 for wide cone beam acquisitions without table translation was employed to estimate equilibrium beam length and equilibrium dose in various interventional task-specific protocols with different tube arc projection geometries. Dose profiles were derived from point dose measurements in the center and peripheral locations of the ICRU/AAPM and standard polymethyl methacrylate (PMMA) body phantom. Dose measurements were performed in phantom and free-in-air using a solid-state point detector. Monte Carlo (MC) based simulation dosimetry was performed to quantify the inhomogeneous dose patterns imparted in the phantoms. Estimated equilibrium beam length and equilibrium dose on the ICRU/AAPM phantom was up to 49.4 cm and 6.17 mGy/100 mAs, respectively. Corresponding values determined on the PMMA phantom were 139 cm and 8.8 mGy/100 mAs, respectively. Free-in-air dose measurement ranged from 1.43 mGy/100 mAs to 5.93 mGy/100 mAs. Percent difference in equilibrium beam length and equilibrium dose between MC simulation and solid-state point detector measurement methods in the ICRU/AAPM phantom were within 16% and 18%, respectively. Manufacturers can use the presented methodology to characterize the dosimetric properties of C-arm CBCT systems. Clinical medical physicists may follow this methodology to verify corresponding data provided by the manufacturer and check for C-arm CBCT system performance dosimetric consistency. .
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关键词
C-arm CBCT, quality control, equilibrium beam length, equilibrium dose, Monte Carlo simulation
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