Unlabelled: (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.

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 (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.

Results: 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).

Conclusion: 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.

Download full-text PDF

Source
http://dx.doi.org/10.2967/jnumed.112.107185DOI Listing

Publication Analysis

Top Keywords

β-amyloid binding
16
binding parameters
12
β-amyloid deposits
8
deposits human
8
pet imaging
8
kinetic model-based
8
quantification β-amyloid
8
pet data
8
18f-florbetaben pet
8
time-activity curves
8

Similar Publications

Efficient and accurate drug-target affinity (DTA) prediction can significantly accelerate the drug development process. Recently, deep learning models have been widely applied to DTA prediction and have achieved notable success. However, existing methods often encounter several common issues: first, the data representations lack sufficient information; second, the extracted features are not comprehensive; and third, most methods lack interpretability when modeling drug-target binding.

View Article and Find Full Text PDF

Objective: Endometrial cancer (EC) is a malignant tumor with various histological subtypes and molecular phenotypes. The evaluation of drug resistance is important for cancer treatment. Progesterone resistance is the major challenge in EC.

View Article and Find Full Text PDF

The P2YR is activated by UDP and UDP glucose and is involved in many human inflammatory diseases. Based on the molecular docking analysis of currently reported P2YR antagonists and the crystallographic overlap study between PPTN and compound , a series of 3-substituted 5-amidobenzoate derivatives were designed, synthesized, and identified as promising P2YR antagonists. The optimal compound (methyl 3-(1-benzo[]imidazol-2-yl)-5-(2-(-tolyl) acetamido)benzoate, IC = 0.

View Article and Find Full Text PDF

Microtubule associated protein 2 (MAP2) interacts with the regulatory protein 14-3-3ζ in a cAMP-dependent protein kinase (PKA) phosphorylation dependent manner. Using selective phosphorylation, calorimetry, nuclear magnetic resonance, chemical crosslinking, and X-ray crystallography, we characterized interactions of 14-3-3ζ with various binding regions of MAP2c. Although PKA phosphorylation increases the affinity of MAP2c for 14-3-3ζ in the proline rich region and C-terminal domain, unphosphorylated MAP2c also binds the dimeric 14-3-3ζ via its microtubule binding domain and variable central domain.

View Article and Find Full Text PDF

This study explores the optoelectronic and photovoltaic potential of acceptor-π-donor (A-π-D) architectures utilizing CSi quantum dots (CSiQDs) through a combination of density functional theory (DFT) and time-dependent DFT (TDDFT). We examined two key structural configurations: C-C and Si-C conformers. In these systems, CSiQDs serve as the acceptor, CHSF as the π-bridge, and 3 × (CHO) as the donor.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!