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Proceedings Paper

7T multi-shell hybrid diffusion imaging (HYDI) for mapping brain connectivity in mice
Author(s): Madelaine Daianu; Neda Jahanshad; Julio E. Villalon-Reina; Gautam Prasad; Russell E. Jacobs; Samuel Barnes; Berislav V. Zlokovic; Axel Montagne; Paul M. Thompson
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Paper Abstract

Diffusion weighted imaging (DWI) is widely used to study microstructural characteristics of the brain. High angular resolution diffusion imaging (HARDI) samples diffusivity at a large number of spherical angles, to better resolve neural fibers that mix or cross. Here, we implemented a framework for advanced mathematical analysis of mouse 5-shell HARDI (b=1000, 3000, 4000, 8000, 12000 s/mm2), also known as hybrid diffusion imaging (HYDI). Using q-ball imaging (QBI) at ultra-high field strength (7 Tesla), we computed diffusion and fiber orientation distribution functions (dODF, fODF) to better detect crossing fibers. We also computed a quantitative anisotropy (QA) index, and deterministic tractography, from the peak orientation of the fODFs. We found that the signal to noise ratio (SNR) of the QA was significantly higher in single and multi-shell reconstructed data at the lower b-values (b=1000, 3000, 4000 s/mm2) than at higher b-values (b=8000, 12000 s/mm2); the b=1000 s/mm2 shell increased the SNR of the QA in all multi-shell reconstructions, but when used alone or in <5-shell reconstruction, it led to higher angular error for the major fibers, compared to 5-shell HYDI. Multi-shell data reconstructed major fibers with less error than single-shell data, and was most successful at reducing the angular error when the lowest shell was excluded (b=1000 s/mm2). Overall, high-resolution connectivity mapping with 7T HYDI offers great potential for understanding unresolved changes in mouse models of brain disease.

Paper Details

Date Published: 20 March 2015
PDF: 8 pages
Proc. SPIE 9413, Medical Imaging 2015: Image Processing, 941309 (20 March 2015); doi: 10.1117/12.2081491
Show Author Affiliations
Madelaine Daianu, The Univ. of Southern California (United States)
Neda Jahanshad, The Univ. of Southern California (United States)
Julio E. Villalon-Reina, The Univ. of Southern California (United States)
Gautam Prasad, The Univ. of Southern California (United States)
Russell E. Jacobs, California Institute of Technology (United States)
Samuel Barnes, California Institute of Technology (United States)
Berislav V. Zlokovic, The Univ. of Southern California (United States)
Axel Montagne, The Univ. of Southern California (United States)
Paul M. Thompson, The Univ. of Southern California (United States)


Published in SPIE Proceedings Vol. 9413:
Medical Imaging 2015: Image Processing
Sébastien Ourselin; Martin A. Styner, Editor(s)

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