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Proceedings Paper

Axonal diameter and density estimated with 7-Tesla hybrid diffusion imaging in transgenic Alzheimer rats
Author(s): Madelaine Daianu; Russell E. Jacobs; Terrence Town; Paul M. Thompson
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Paper Abstract

Diffusion-weighted MR imaging (DWI) is a powerful tool to study brain tissue microstructure. DWI is sensitive to subtle changes in the white matter (WM), and can provide insight into abnormal brain changes in diseases such as Alzheimer’s disease (AD). In this study, we used 7-Tesla hybrid diffusion imaging (HYDI) to scan 3 transgenic rats (line TgF344-AD; that model the full clinico-pathological spectrum of the human disease) ex vivo at 10, 15 and 24 months. We acquired 300 DWI volumes across 5 q-sampling shells (b=1000, 3000, 4000, 8000, 12000 s/mm2). From the top three b-value shells with highest signal-to-noise ratios, we reconstructed markers of WM disease, including indices of axon density and diameter in the corpus callosum (CC) – directly quantifying processes that occur in AD. As expected, apparent anisotropy progressively decreased with age; there were also decreases in the intra- and extra-axonal MR signal along axons. Axonal diameters were larger in segments of the CC (splenium and body, but not genu), possibly indicating neuritic dystrophy – characterized by enlarged axons and dendrites as previously observed at the ultrastructural level (see Cohen et al., J. Neurosci. 2013). This was further supported by increases in MR signals trapped in glial cells, CSF and possibly other small compartments in WM structures. Finally, tractography detected fewer fibers in the CC at 10 versus 24 months of age. These novel findings offer great potential to provide technical and scientific insight into the biology of brain disease.

Paper Details

Date Published: 21 March 2016
PDF: 6 pages
Proc. SPIE 9784, Medical Imaging 2016: Image Processing, 97843G (21 March 2016); doi: 10.1117/12.2216912
Show Author Affiliations
Madelaine Daianu, The Univ. of Southern California (United States)
UCLA School of Medicine (United States)
Russell E. Jacobs, California Institute of Technology (United States)
Terrence Town, The Univ. of Southern California (United States)
Paul M. Thompson, The Univ. of Southern California (United States)
UCLA School of Medicine (United States)

Published in SPIE Proceedings Vol. 9784:
Medical Imaging 2016: Image Processing
Martin A. Styner; Elsa D. Angelini, Editor(s)

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