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BackgroundKinetic modeling of 18F-florbetaben provides important quantification of brain amyloid deposition in research and clinical settings but its use is limited by the requirement of arterial blood data for quantitative PET. The total-body EXPLORER PET scanner supports the dynamic acquisition of a full human body simultaneously and permits noninvasive image-derived input functions (IDIFs) as an alternative to arterial blood sampling. This study quantified brain amyloid burden with kinetic modeling, leveraging dynamic 18F-florbetaben PET in aorta IDIFs and the brain in an elderly cohort.Methods18F-florbetaben dynamic PET imaging was performed on the EXPLORER system with tracer injection (300 MBq) in 3 individuals with Alzheimer's disease (AD), 3 with mild cognitive impairment, and 9 healthy controls. Image-derived input functions were extracted from the descending aorta with manual regions of interest based on the first 30 s after injection. Dynamic time-activity curves (TACs) for 110 min were fitted to the two-tissue compartment model (2TCM) using population-based metabolite corrected IDIFs to calculate total and specific distribution volumes (VT, Vs) in key brain regions with early amyloid accumulation. Non-displaceable binding potential ([Formula: see text] was also calculated from the multi-reference tissue model (MRTM).ResultsAmyloid-positive (AD) patients showed the highest VT and VS in anterior cingulate, posterior cingulate, and precuneus, consistent with [Formula: see text] analysis. [Formula: see text]and VT from kinetic models were correlated (r² = 0.46, P

The emergence of PET probes for amyloid plaques and neurofibrillary tangles, hallmarks of Alzheimer disease (AD), enables monitoring of pathology in AD mouse models. However, small-animal PET imaging is limited by coarse spatial resolution. We have installed a custom-fabricated PET insert into our small-animal MRI instrument and used PET/MRI hybrid imaging to define regions of amyloid vulnerability in 5xFAD mice. We compared fluorine-18 [18F]-Florbetapir uptake in the 5xFAD brain by dedicated small-animal PET/MRI and PET/CT to validate the quantitative measurement of PET/MRI. Next, we used PET/MRI to define uptake in six brain regions. As expected, uptake was comparable to wild-type in the cerebellum and elevated in the cortex and hippocampus, regions implicated in AD. Interestingly, uptake was highest in the thalamus, a region often overlooked in AD studies. Development of small-animal PET/MRI enables tracking of brain region-specific pathology in mouse models, which may prove invaluable to understanding AD progression and therapeutic development.

Background: Kinetic modeling of 18F-florbetaben provides important quantification of brain amyloid deposition in research and clinical settings but its use is limited by the requirement of arterial blood data for quantitative PET. The total-body EXPLORER PET scanner supports the dynamic acquisition of a full human body simultaneously and permits noninvasive image-derived input functions (IDIFs) as an alternative to arterial blood sampling. This study quantified brain amyloid burden with kinetic modeling, leveraging dynamic 18F-florbetaben PET in aorta IDIFs and the brain in an elderly cohort. Methods: 18F-florbetaben dynamic PET imaging was performed on the EXPLORER system with tracer injection (300 MBq) in 3 individuals with Alzheimer's disease (AD), 3 with mild cognitive impairment, and 9 healthy controls. Image-derived input functions were extracted from the descending aorta with manual regions of interest based on the first 30 s after injection. Dynamic time-activity curves (TACs) for 110 min were fitted to the two-tissue compartment model (2TCM) using population-based metabolite corrected IDIFs to calculate total and specific distribution volumes (VT, Vs) in key brain regions with early amyloid accumulation. Non-displaceable binding potential ( was also calculated from the multi-reference tissue model (MRTM). Results: Amyloid-positive (AD) patients showed the highest VT and VS in anterior cingulate, posterior cingulate, and precuneus, consistent with analysis. and VT from kinetic models were correlated (r² = 0.46, P < 2 with a stronger positive correlation observed in amyloid-positive participants, indicating reliable model fits with the IDIFs. VT from 2TCM was highly correlated ( = 0.65, P < 2 ) with Logan graphical VT estimation. Conclusion: Non-invasive quantification of amyloid binding from total-body 18F-florbetaben PET data is feasible using aorta IDIFs with high agreement between kinetic distribution volume parameters compared to in amyloid-positive and amyloid-negative older individuals. [ABSTRACT FROM AUTHOR]