Kinetic modeling of BAY 94-9172 binding to β-amyloid in human brains using PET data

Objectives BAY 94-9172 is a ¹⁸F-labeled stilbene derivativewhich in early phase clinical development has demonstratedconvincing diagnostic accuracy in the differentiation betweensubjects with Alzheimer's disease (AD) and healthy volunteers (HV) [Rowe et al., Lancet Neurol 2008, Barthel et al., J Nucl Med 2008].The value of kinetic modeling of this PET tracer for absolutequantification of brain β-amyloid load and differentiation betweensubjects with AD and HVs was investigated.

Methods After i.v. administration of 300MBq BAY 94-9172, 7 ADsubjects and 10 age-matched HVs underwent 90min 3D-PET scanning.VOI-based tissue-activity curves from 25 brain regions were analyzedusing a two compartment model with metabolite-corrected arterial input-function,and by a reference tissue approach. Total distribution volume (DV) andbinding potential (BP) = k3/k4 and k3 were used to characterize specific binding.SUV- and DV-ratios were computed using the cerebellar cortex as a reference region.

Results All investigated parameters were significantly higher in ADs compared toHVs e.g. in frontal cortex(DV: 11.3±3.5 vs 7.2±1.3, p=0.004; BP: 3.2±1.3 vs 1.6±0.3, p= 0.002; k3= 0.059±0.029 vs 0.028±0.005, p=0.004). When the cerebellar cortex was used as a referenc region (DV- and SUV-ratios) results were highly significant (p<0.0001), too .

Conclusions Kinetic modeling of BAY 94-9172 brain PET images provides absolute quantification of brain ß-amyloid load which may be valuable for early disease detection and for monitoring the effect of amyloid modifying therapy.

Research Support The trial is sponsored and supported by the Bayer-Schering Pharma AG