Quantification of β-Amyloidosis and rCBF with Dedicated PET, 7 T MR Imaging, and High-Resolution Microscopic MR Imaging at 16.4 T in APP23 Mice

Florian C. Maier, Marianne D. Keller, Daniel Bukala, Benjamin Bender, Julia G. Mannheim, Ian M. Brereton, Graham J. Galloway, Bernd J. Pichler

Non-invasive quantification of the amyloid-load is of paramount interest in the field of Alzheimerŕs disease research. We present a combined PET/7 T-MRI and 16.4 T-microscopic-MRI (µMRI) dual-modality imaging approach enabling the quantification of the amyloid-load at high-sensitivity and high-resolution, and of regional cerebral blood flow (rCBF) in the brain of transgenic APP23 mice. Moreover, we demonstrate a novel, voxel-based correlative data analysis method which we used for in-depth evaluation of amyloid-PET and rCBF-data. We injected [(11)C]PIB intravenously in transgenic (tg) and control (co) APP23 mice and performed dynamic PET measurements. rCBF-data were recorded with a flow sensitive alternating inversion recovery (FAIR) approach at 7 T. Subsequently, animals were sacrificed and brains harvested for ex vivo µMRI at 16.4 T with a T2*-weighted gradient-echo sequence at 30 µm spatial resolution. Additionally, correlative amyloid histology was performed. The [(11)C]PIB-PET data were quantified to non-displaceable binding potentials (BPnd) using the Logan graphical analysis; FAIR-data were quantified with a simplified version of the Bloch equation. Amyloid-load assessed by both, [(11)C]PIB-PET and amyloid histology (AβH) was highest in the frontal cortex of tg mice ([(11)C]PIB-BPnd: 0.93±0.08, AβH: 15.1±1.5%), followed by the temporoparietal cortex ([(11)C]PIB-BPnd: 0.75±0.08, AβH: 13.9±0.7%) and the hippocampus ([(11)C]PIB-BPnd: 0.71±0.09, AβH: 9.2±0.9%), and was lowest in the thalamus ([(11)C]PIB-BPnd: 0.40±0.07, AβH: 6.6±0.6%). However, [(11)C]PIB-BPnd and AβH linearly correlated (R(2)=0.82, p<0.05) and were significantly higher in tg animals (p<0.01). Similarly, µMRI allowed quantifying the amyloid-load, in addition the detection of substructures within single amyloid plaques correlating with amyloid deposition density and the measurement of hippocampal atrophy. Finally, we detected an inverse relationship between [(11)C]PIB-BPnd and rCBF-MRI in the voxel-based analysis that was absent in control mice (slopetg: -0.11±0.03; slopeco: 0.004±0.005, P = 0.014). Our dual-modality imaging approach employing [(11)C]PIB-PET/7 T-MRI and 16.4 T-µMRI allowed amyloid-load quantification with high-sensitivity and high-resolution, the identification of substructures within single amyloid plaques, and the quantification of rCBF. Future applications of this multiparametrical imaging and data-analysis approach could simplify the identification of treatment impact on amyloid-load status and brain physiology and aid the development of new treatment strategies, enabling both a morphological and functional classification of underlying mechanisms-of-action.