Prospective Evaluation of Motion Correction Software for 18 F-FDG PET of the Brain

In this study, we aimed to quantify the impact of data-driven motion-correction reconstruction for PET imaging on still and motion-corrupted 18F-FDG PET brain scans of children and adolescents. Methods: In this prospective study, participants underwent a 9-min PET brain scan after clinically indicated whole-body 18F-FDG PET/CT between December 2022 and March 2023. Participants remained still during minutes 1–6 and performed scripted head movements during minutes 7–9. PET images were reconstructed from list-mode data into still (minutes 1–6) and mixed still/motion-corrupted (minutes 4–9) datasets, with and without motion correction. Three radiologists independently assessed image quality, gray and white matter differentiation, basal ganglia definition, and cortical uniformity. Quantitative parameters of the brain (SUVmax and SUVmean) were obtained by a separate observer. Wilcoxon rank-sum and Kruskal–Wallis tests assessed differences between reconstructions and motion groups. Results: Sixteen participants (mean age, 13 ± 3 y; 8 males and 8 females) were included. Still images with motion correction scored higher than still images without motion correction for overall image quality (P = 0.013). Motion-corrupted images with motion correction outperformed still images without motion correction in gray and white matter contrast, basal ganglia delineation, and cortical uniformity (P < 0.018). Quantitatively, motion-corrected images did not significantly differ from still images without motion correction. Conclusion: Motion correction software improved the image quality of motion-corrupted 18F-FDG PET/CT brain scans. Corrected scans were qualitatively superior or did not differ from non–motion-corrected images, with no impact on quantitative measurements. Motion correction has the potential to allow awake, nonsedated pediatric patients to undergo PET scans.