Investigate the quantification accuracy of small lesions in oncological 18F-FDG PET/CT using a deep progressive learning reconstruction method

Background To investigate the impact of deep progressive learning reconstruction (DPR) on small lesion detection and image quality compared to ordered subset expectation maximum (OSEM) and regularized OSEM (ROSEM) in ¹⁸ F-FDG PET/CT imaging. Methods The NEMA phantom was filled with ¹⁸ F-FDG solution, with a hot sphere-to-background ratio of 4:1. Twenty-six patients with ¹⁸ F-FDG-avid lung lesions (diameter < 2.0 cm) were enrolled in the study. The PET images were reconstructed by seven groups: routine OSEM, ROSEM with a penalization factor of 0.8 (ROSEM), and DPR reconstructions with five different filter strength factors ranging from smooth to sharp:1–5 (DPR1, DPR2, DPR3, DPR4, and DPR5). The contrast recovery (CR), background variability (BV), contrast-to-noise ratio (CNR), and radioactivity concentration ratio (RCR) were measured in the phantom study. The maximum standardized uptake values (SUV _max ), target-to-background ratio (TBR), CNR, the volume of the lesions, and the coefficient of variation (COV) of the liver were calculated and compared between these methods in the patient study. Two radiologists evaluated the image quality using a five-point Likert scale. Results In the phantom study, the DPR2 to DPR5 and ROSEM groups achieved higher CR, CNR, RCR, and lower BV than the OSEM group. For the smallest 10-mm hot sphere, the DPR3 achieved a CNR of 24.46, while the ROSEM and OSEM groups achieved the corresponding values of 22.25 and 10.39, respectively. In the patient study, the DPR1 to DPR4 groups exhibited significantly lower liver COVs than the OSEM group (all p < 0.05). Nevertheless, no significant difference was observed between the DPR3 and ROSEM groups (p = 0.65). The lesion SUVs, TBRs, and CNRs of the DPR2 to DPR4 groups were found to be significantly higher than those of the OSEM group (all p < 0.05). However, the lesion SUVs and TBRs of the DPR4 and DPR5 groups were found to be equivalent to those of the ROSEM group (SUVs: p = 0.19–0.61, and TBRs: p = 0.26–0.70). Moreover, the CNRs of the DPR3 and ROSEM groups were found to be comparable (p = 0.75). The volume of the lesion obtained from the ROSEM group was statistically equivalent to that measured on CT images (p = 0.48), but those were overestimated by all DPR groups (all p < 0.05). The overall image quality scores for DPR2, DPR3, and DPR4 were found to be superior to those obtained with OSEM (p < 0.01), while those for DPR2 and DPR3 groups were not statistically different from the ROSEM group (p = 0.56, and p = 0.85). Conclusions The DPR method demonstrated a significant improvement in lesion contrast, TBR, and volumetric quantification accuracy for small lesions compared to the OSEM method in the ¹⁸ F-FDG PET/CT imaging. The DPR method, with a filter strength factor of 3, demonstrated comparable enhancement of PET image quality to the ROSEM method.