Automated Spatial Brain Normalization and Hindbrain White Matter Reference Tissue Give Improved [18F]-Florbetaben PET Quantitation in Alzheimer's Model Mice

Preclinical PET studies of 13-amyloid (A beta) accumulation are of growing importance, but comparisons between research sites require standardized and optimized methods for quantitation. Therefore, we aimed to evaluate systematically the (1) impact of an automated algorithm for spatial brain normalization, and (2) intensity scaling methods of different reference regions for A beta-PET in a large dataset of transgenic mice. PS2APP mice in a 6 week longitudinal setting (N = 37) and another set of PS2APP mice at a histologically assessed narrow range of A beta burden (N = 40) were investigated by florbetaben PET Manual spatial normalization by three readers at different training levels was performed prior to application of an automated brain spatial normalization and inter -reader agreement was assessed by Fleiss Kappa (kappa). For this method the impact of templates at different pathology stages was investigated. Four different reference regions on brain uptake normalization were used to calculate frontal cortical standardized uptake value ratios (SUVRc-rx/REF) relative to raw SUVCTX. Results were compared on the basis of longitudinal stability (Cohen's d), and in reference to gold standard histopathological quantitation (Pearson's R). Application of an automated brain spatial normalization resulted in nearly perfect agreement (all If kappa >= 0.99) between different readers, with constant or improved correlation with histology. Templates based on inappropriate pathology stage resulted in up to 2.9% systematic bias for SUVRc-Fx, /REF " All SUVRG-Fx, /REF methods performed better than SUVGTx both with regard to longitudinal stability (d >= 1.21 vs. d = 0.23) and histological gold standard agreement (R >= 0.66 vs. R >= 0.31). Voxel-wise analysis suggested a physiologically implausible longitudinal decrease by global mean scaling. The hindbrain white matter reference (R-mean = 0.75)