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J Nucl Med. 2015 Oct;56(10):1593-9. doi: 10.2967/jnumed.115.159350. Epub 2015 Aug 6.

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.

Author information

1
Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, Eberhard Karls University Tübingen, Tübingen, Germany.
2
University of Queensland, Centre for Advanced Imaging, Brisbane, Australia South Australian Health and Medical Research Institute, Adelaide, Australia; and.
3
Department for Neuroradiology, University Hospital Tübingen, Tübingen, Germany.
4
University of Queensland, Centre for Advanced Imaging, Brisbane, Australia.
5
Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, Eberhard Karls University Tübingen, Tübingen, Germany bernd.pichler@med.uni-tuebingen.de.

Abstract

We present a combined PET/7 T MR imaging and 16.4 T microscopic MR imaging dual-modality imaging approach enabling 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 for in-depth evaluation of amyloid PET and rCBF data.

METHODS:

We injected 11C-Pittsburgh compound B (PIB) intravenously in transgenic and control APP23 mice and performed dynamic PET measurements. rCBF data were recorded with a flow-sensitive alternating inversion recovery approach at 7 T. Subsequently, the animals were sacrificed and their brains harvested for ex vivo microscopic MR imaging at 16.4 T with a T2*-weighted gradient-echo sequence at 30-μm spatial resolution. Additionally, correlative amyloid histology was performed. The 11C-PIB PET data were quantified to nondisplaceable binding potentials (BPND) using the Logan graphical analysis; flow-sensitive alternating inversion recovery data were quantified with a simplified version of the Bloch equation.

RESULTS:

Amyloid load assessed by both 11C-PIB PET and amyloid histology was highest in the frontal cortex of transgenic mice (11C-PIB BPND: 0.93±0.08; amyloid histology: 15.1%±1.5%), followed by the temporoparietal cortex (11C-PIB BPND: 0.75±0.08; amyloid histology: 13.9%±0.7%) and the hippocampus (11C-PIB BPND: 0.71±0.09; amyloid histology: 9.2%±0.9%), and was lowest in the thalamus (11C-PIB BPND: 0.40±0.07; amyloid histology: 6.6%±0.6%). However, 11C-PIB BPND and amyloid histology linearly correlated (R2=0.82, P<0.05) and were significantly higher in transgenic animals (P<0.01). Similarly, microscopic MR imaging allowed quantifying the amyloid load, in addition to the detection of substructures within single amyloid plaques correlating with amyloid deposition density and the measurement of hippocampal atrophy. Finally, we found an inverse relationship between 11C-PIB BPND and rCBF MR imaging in the voxel-based analysis that was absent in control mice (slopetg: -0.11±0.03; slopeco: 0.004±0.005; P=0.014).

CONCLUSION:

Our dual-modality imaging approach using 11C-PIB PET/7 T MR imaging and 16.4 T microscopic MR imaging allowed amyloid-load quantification with high sensitivity and high resolution, the identification of substructures within single amyloid plaques, and the quantification of rCBF.

KEYWORDS:

Alzheimer disease; PET and MR imaging; amyloid; microscopic MR imaging; rCBF

PMID:
26251417
DOI:
10.2967/jnumed.115.159350
[Indexed for MEDLINE]
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