PET quantification of 18F-florbetaben binding to β-amyloid deposits in human brains

(18)F-florbetaben is a novel (18)F-labeled tracer for PET imaging of β-amyloid deposits in the human brain. We evaluated the kinetic model-based approaches to the quantification of β-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.

(18)F-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 (VS) 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.

All brain regions required 2TCM to describe the time-activity curves. All β-amyloid binding parameters in the cerebral cortex (VS, 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 β-amyloid-positive AD scans and 9 β-amyloid-negative healthy control scans for all binding parameters were excellent, being largest for DVR (2TCM) (4.22) and smallest for VS (3.25) and intermediate and the same for DVR (MRTM) and SUVR (4.03).

These results suggest that compartment kinetic model-based quantification of β-amyloid binding from (18)F-florbetaben PET data is feasible and that all β-amyloid binding parameters including SUVR are excellent in discriminating between β-amyloid-positive and -negative scans.