Abstract

Background: The quality of positron emission tomography/computed tomography (PET/CT) images plays an important role in tumor detection. This imaging method often yields poor-quality images of overweight patients due to the high level of noise, originating from scattering and photon attenuation. Objectives: The point spread function (PSF) is mostly used to enhance the spatial resolution and signal-to-noise ratio (SNR); however, it is known to increase the edge artifacts. The time-of-flight (TOF) principle can reduce edge artifacts in PSF modeling and improve lesion detection, especially in the thorax. The present study aimed to assess these two new techniques by applying different reconstruction parameters. Materials and Methods: An in-house phantom with an inner diameter of 35 cm was used for the simulation of overweight patients. Lesion-to-background ratios (LBRs) of 2: 1 and 8: 1, as well as background activity concentrations of 3 and 5 kBq/cc, were considered in this study. The list-mode data were reconstructed with various reconstruction protocols, numbers of subsets, and filter sizes. Quantitative analyses, including the coefficient of variation (COV), SNR, and recovery coefficient (RC), were also carried out. Moreover, box-and-whisker plots were performed. Results: At LBR of 2: 1, by changing the protocol from ordered subset expectation maximization (OSEM) to OSEM + PSF + TOF, the median value of SNR for 13-mm lesions (37 mm) increased by 39.25% and 53.45% (42.22% and 56.21%), at background activity concentrations of 3 and 5 kBq/cc respectively. However, at LBR of 8: 1, the corresponding values were 33.22% and 48.94% (40.22% and 52.15%) at background activity concentrations of 3 and 5 kBq/cc respectively. Conclusion: The TOF protocols were strongly recommended for both background activity concentrations at LBR of 2: 1 and for the low background activity concentration at LBR of 8: 1, especially when using smaller filter sizes. Moreover, subset numbers of 18 and 24 were appropriate for all protocols. However, a smaller subset number was suitable when a low background activity concentration and a smaller filter size were applied, especially at a lower LBR.

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