The multiorgan kinetic profile of 18F-flurpiridaz targeting mitochondrial complex I remains inadequately characterized. We aim to characterize preliminary total-body pharmacokinetics of 18F-flurpiridaz in healthy volunteers and evaluate shortened acquisition protocols for clinical translation. Methods: Twelve healthy volunteers were imaged with 18F-flurpiridaz during a 60-min dynamic total-body PET/CT scan on the uEXPLORER scanner at rest. Time–activity curves were derived from volumes of interest generated by an automated CT-based segmentation method applied to motion-corrected dynamic PET images, with manual delineation of the descending aorta, kidney, and breasts. The descending aorta served as the input function for most organs, whereas the pulmonary artery was used for the lungs. The 2-tissue irreversible (2T3K) and 2-tissue reversible (2T4K) compartment models incorporating blood volume and time-delay correction were compared using the Akaike information criterion (AIC). Simplified metrics of distribution volume (VT) from a Logan plot and SUVmean from truncated scans (10, 30, and 60 min) were correlated with the reference 60-min 2T4K VT. Results: Four distinct kinetic patterns were observed across different organs. At 60 min, the 2T4K model demonstrated superior fitting performance (lower AIC) in 15 of 18 targeted regions. The 2T3K model exhibited lower AIC in the heart, brain, and kidneys at 10 min. In the thyroid and spinal cord, the optimal model shifted from the 2T3K model at 60 min to the 2T4K model at 10 min. Logan VT from 30-min (r = 0.974) and 60-min (r = 0.979) scans strongly correlated with reference VT. Notably, SUVmean around 10-min postinjection also showed strong correlation with reference VT (r = 0.834–0.909), only slightly lower than that observed in the optimal 25–30-min window (r = 0.922; all P Conclusion: This total-body kinetic atlas of 18F-flurpiridaz supports the use of the 2T4K model for multiorgan quantification, time-dependent model preference, and the feasibility of ultrashort imaging strategies for clinical mitochondrial complex I assessment, establishing a foundation for future applications in oncology (e.g., metabolism evaluation), neurology (e.g., mitochondrial mapping), and integrated cardio-oncology diagnostics.
Song et al. (Thu,) studied this question.