Amyloid tracer shows diagnostic promise for Alzheimer’s disease
The amyloid imaging agent F-18 florbetaben has been moving forward in clinical trials for the diagnosis of Alzheimer’s disease. F-18 florbetaben is from the same stilbene derivative with strong binding potential like that of Amyvid, also known as F-18 florbetapir, which was approved by the FDA in April 2012. The up and coming F-18 florbetaben is showing signs of similar effectiveness, according to research published in the May issue of The Journal of Nuclear Medicine that presented a dynamic model of amyloid imaging using the tracer.
Georg A. Becker, PhD, from the department of nuclear medicine at the University of Leipzig, in Germany, and colleagues reviewed the quantitative value of F-18 florbetaben using a kinetic compartment theory of analysis. Previous studies have focused on visual evaluation and scoring of amyloid burden in the brain, but this study investigated dynamic parameters of amyloid deposition using F-18 florbetaben, which binds reversibly in neural tissues.
This technique allows a quantification of binding site density, tracer-tissue clearance and blood flow and calls for more dynamic PET data. A total of 20 subjects, 10 with Alzheimer’s disease and 10 healthy controls at the same age were imaged using PET and F-18 florbetaben. The study also utilized serial arterial blood sampling and all PET studies were motion-corrected and coregistered using MRI.
Time-activity curves for brain regions were documented for 90 minutes and distribution volume and ratio were estimated using metabolite-corrected plasma data. Standardized uptake value ratios (SUVR) were determined using the cerebral cortex as a tissue reference model. Results of the study showed that amyloid binding parameters were significantly increased in the cerebral cortex for Alzheimer’s patients compared with healthy controls.
“Compartment kinetic model–based quantification of [beta -amyloid] binding from 18 F-florbetaben PET data is feasible, and all [beta-amyloid] binding parameters, including those by the reference tissue model and the practically useful SUVR, are excellent in discriminating between beta-amyloid–positive–and–negative scans,” concluded the authors.