PET Quantification of 18F-Florbetaben Binding to β-Amyloid Deposits in Human Brains

F-18-florbetaben is a novel F-18-labeled tracer for PET imaging of beta-amyloid deposits in the human brain. We evaluated the kinetic model-based approaches to the quantification of beta-amyloid binding in the brain from dynamic PET data. The validity of the practically useful tissue ratio was also evaluated against the model-based parameters. Methods: F-18-florbetaben PET imaging was performed with concurrent multiple arterial sampling after tracer injection (300 MBq) in 10 Alzheimer disease (AD) patients and 10 age-matched healthy controls. Regional brain-tissue time-activity curves for 90 min were analyzed by a 1-tissue-compartment model and a 2-tissue-compartment model (2TCM) with metabolite-corrected plasma data estimating the specific distribution volume (V-S) and distribution volume ratio (DVR [2TCM]) and a multilinear reference tissue model estimating DVR (DVR [MRTM]) using the cerebellar cortex as the reference tissue. Target-to-reference tissue standardized uptake value ratios (SUVRs) at 70-90 min were also calculated. Results: All brain regions required 2TCM to describe the time-activity curves. All beta-amyloid binding parameters in the cerebral cortex (V-S, DVR [2TCM], DVR [MRTM], and SUVR) were significantly increased in AD patients (P < 0.05), and there were significant linear correlations among these parameters (r(2) > 0.83). Effect sizes in group discrimination between 8 beta-amyloid-positive AD scans and 9 beta-amyloid-negative healthy control scans for all binding parameters were excellent, being largest for DVR (2TCM) (4.22) and smallest for V-S (3.25) and intermediate and the same for DVR (MRTM) and SUVR (4.03). Conclusion: These results suggest that compartment kinetic model-based quantification of beta-amyloid binding from F-18-florbetaben PET data is feasible and that all beta-amyloid binding parameters including SUVR are excellent in discriminating between beta-amyloid-positive and -negative scans.