Total-body [18F]FDG-PET/CT imaging of healthy volunteers with minimal effective dose

Purpose High-sensitivity, total-body (TB) positron emission tomography (PET) and computed tomography (CT) imaging systems enable substantial reduction of injected radioactivity without compromising image quality. Synthetic CT-like attenuation maps can be generated from PET data via deep learning (DL) to further minimise subject radiation exposure. We explored combining TB-PET with DL-derived attenuation maps to minimise effective dose in healthy subjects undergoing TB-PET/CT imaging with [ 18 F]Fluorodeoxyglucose ([ 18 F]FDG). Methods 47 healthy Caucasians (25 F/22 M, BMI: 24 ± 3 kg/m²) underwent TB-PET/CT imaging. After 6-hour fasting, subjects received low-dose CT (1 mSv) and (109 ± 7) MBq [ 18 F]FDG, followed by a 62-minute dynamic PET acquisition (supine, arms down). PET data from 57 to 62 min were down-sampled to simulate reduced activities (50%, 25%, 10%, 5%). Effective doses (ED) were estimated for each activity level. Synthetic CTs (ED = 0 mSv) were generated from PET raw data (at all activity levels) and used to reconstruct attenuation-corrected PETs, which were compared to the original images. Organ-level segmentation enabled quantification of Standardized Uptake Values normalised to body weight (SUVbw) and coefficients of variation (CV). Results Across the cohort, organ-based SUVbw differences remained < 10% versus reference PET for simulated activities down to 10%. At 25% activity (~ 25 MBq, ED~ 0.45 mSv), PET quantification remained robust, though CV increased in skeletal muscle and fat. At 5% activity, SUVbw deviations exceeded 10% in several organs. Conclusion Total-body [ 18 F]FDG-PET/CT enables reliable organ-level quantification (%-differences < 10%) at injected activities as low as ~ 25 MBq. Such low-dose protocols may support the creation of reference datasets of healthy controls while minimising radiation exposure to subjects and staff.