Impact of point spread function on image quality and SUV in FDG PET imaging

Objective: To discuss the impact of an iterative reconstruction algorithm (True X) implemented with point spread function (PSF) on image quality and SUV in ¹⁸F-FDG PET, and compare with other reconstruction algorithms. Methods: A total of 79 hypermetabolic lesions from 37 cancer patients (23 males, 14 females, age (63.38 ± 15.25) years) were retrospectively studied. The PET images were reconstructed using the follow-ing six reconstruction algorithms, including FBP, FBP + TOF, iteration, iteration + TOF, True X, True X + TOF. Paired t test was used for statistical analysis. Results: All six reconstruction algorithms showed significant difference in lesion SUV_max. The adoption of PSF increased SUV_max by 15%-16%, and decreased the dispersion of SUV in the liver parenchyma remarkably. Conclusions: Lesion SUV_max calculated from different reconstruction algorithms has significant differences. Caution should be taken in using PSF, as it can improve image quality but may also increase lesion SUV_max. (authors)