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Constrained spherical deconvolution on diffusion-weighted images of dolphin brains.
- Source :
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Magnetic resonance imaging [Magn Reson Imaging] 2024 May; Vol. 108, pp. 104-110. Date of Electronic Publication: 2024 Feb 08. - Publication Year :
- 2024
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Abstract
- Invasive neuronal tract-tracing is not permitted in very large or endangered animals. This is especially the case in marine mammals like dolphins. Diffusion-weighted imaging of fiber tracts could be an alternative if feasible even in brains that have been fixed in formalin for a long time. This currently is a problem, especially for detecting crossing fibers. We applied a state-of-the-art algorithm of Diffusion-weighted imaging called Constrained Spherical Deconvolution on diffusion data of three fixed brains of bottlenose dolphins using clinical human MRI parameters and were able to identify complex fiber patterns within a voxel. Our findings indicate that in order to maintain the structural integrity of the tissue, short-term post-mortem fixation is necessary. Furthermore, pre-processing steps are essential to remove the classical Diffusion-weighted imaging artifacts from images: however, the algorithm is still able to resolve fiber tracking in regions with various signal intensities. The described imaging technique reveals complex fiber patterns in cetacean brains that have been preserved in formalin for extended periods of time and thus opens a new window into our understanding of cetacean neuroanatomy.<br />Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.<br /> (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)
Details
- Language :
- English
- ISSN :
- 1873-5894
- Volume :
- 108
- Database :
- MEDLINE
- Journal :
- Magnetic resonance imaging
- Publication Type :
- Academic Journal
- Accession number :
- 38336113
- Full Text :
- https://doi.org/10.1016/j.mri.2024.02.002