18 F-florbetaben is a novel 18 F-labeled tracer for PET imaging of b-amyloid deposits in the human brain. We evaluated the kinetic model-based approaches to the quantification of b-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: 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 (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 timeactivity curves. All b-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 b-amyloidpositive AD scans and 9 b-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 b-amyloid binding from 18 Fflorbetaben PET data is feasible and that all b-amyloid binding parameters including SUVR are excellent in discriminating between b-amyloid-positive and -negative scans.

2-[(18)F]FA-85380 PET appears to be a sensitive and feasible tool for the detection of a reduction in α4β2* nAChRs which seems to be an early event in AD. In addition, 2-[(18)F]FA-85380 PET might give prognostic information about a conversion from MCI to AD.

These results indicate florbetaben to be a safe and efficacious β-amyloid-targeted tracer with favourable brain kinetics. Subjects with AD could be easily differentiated from HCs by both visual and quantitative assessment of the PET data. The operator-independent, voxel-based analysis yielded whole brain β-amyloid load which appeared valuable as a surrogate marker of disease severity.

Whether α4β2 nicotinic acetylcholine receptor (α4β2-nAChR) expression is reduced in early Alzheimer’s disease is controversial. Using (-)-[18F]Flubatine PET, Sabri, Meyer et al. report α4β2-nAChR deficiency in mild Alzheimer’s dementia, especially within the basal forebrain-cortical and septohippocampal cholinergic projections. Reduced α4β2-nAChR availability correlates with impaired episodic memory and executive function/working memory.

Purpose The brain noradrenaline (NA) system plays an important role in the central nervous control of energy balance and is thus implicated in the pathogenesis of obesity. The specific processes modulated by this neurotransmitter which lead to obesity and overeating are still a matter of debate. Methods We tested the hypothesis that in vivo NA transporter (NAT) availability is changed in obesity by using positron emission tomography (PET) and S, S-[11C]O-methylreboxetine (MRB) in twenty subjects comprising ten highly obese (body mass index BMI > 35 kg/m2), metabolically healthy, non-depressed individuals and ten non-obese (BMI < 30 kg/m2) healthy controls. Results Overall, we found no significant differences in binding potential (BPND) values between obese and non-obese individuals in the investigated brain regions, including the NAT-rich thalamus (0.40 ± 0.14 vs. 0.41 ± 0.18; p = 0.84) though additional discriminant analysis correctly identified individual group affiliation based on regional BPND in all but one (control) case. Furthermore, inter-regional correlation analyses indicated different BPND patterns between both groups but this did not survive testing for multiple comparions. Conclusions Our data do not find an overall involvement of NAT changes in human obesity. However, preliminary secondary findings of distinct regional and associative patterns warrant further investigation.