Sedation-free pediatric [F]FDG imaging on totalbody PET/CT with the assistance of artificial intelligence.

PURPOSE

While sedation is routinely used in pediatric PET examinations to preserve diagnostic quality, it may result in side effects and may affect the radiotracer's biodistribution. This study aims to investigate the feasibility of sedation-free pediatric PET imaging using ultra-fast total-body (TB) PET scanners and deep learning (DL)-based attenuation and scatter correction (ASC).

METHODS

This retrospective study included TB PET (uExplorer) imaging of 35 sedated pediatric patients under four years old to determine the minimum effective scanning time. A DL-based ASC method was applied to enhance PET quantification. Both quantitative and qualitative assessments were conducted to evaluate the image quality of ultra-fast DL-ASC PET. Five non-sedated pediatric patients were subsequently used to validate the proposed approach.

RESULTS

Comparisons between standard 300-second and ultra-fast 15-second imaging, CT-ASC and DL-ASC ultra-fast 15-second images, as well as DL-ASC ultra-fast 15-second images in non-sedated and sedated patients, showed no significant differences in qualitative scoring, lesion detectability, and quantitative Standard Uptake Value (SUV) (P = ns).

CONCLUSIONS

This study demonstrates that pediatric PET imaging can be effectively performed without sedation by combining ultra-fast imaging techniques with a DL-based ASC. This advancement in sedation-free ultra-fast PET imaging holds potential for broader clinical adoption.