Evaluación prospectiva de software de corrección de movimiento para PET con 18F-FDG del cerebro

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 (SUV_max and SUV_mean) 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.