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Characterizing Brain Structures and Remodeling after TBI Based on Information Content, Diffusion Entropy
Author(s) -
Niloufar Fozouni,
Michael Chopp,
Siamak P. NejadDavarani,
Zheng Gang Zhang,
Norman L. Lehman,
Steven Gu,
Yuji Ueno,
Mei Lü,
Guangliang Ding,
Lian Li,
Jiani Hu,
Hassan BagherEbadian,
David Hearshen,
Quan Jiang
Publication year - 2013
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0076343
Subject(s) - white matter , traumatic brain injury , luxol fast blue stain , pathology , diffusion mri , diffuse axonal injury , corpus callosum , magnetic resonance imaging , cerebrospinal fluid , voxel , human brain , chemistry , nuclear magnetic resonance , neuroscience , medicine , anatomy , biology , central nervous system , physics , myelin , radiology , psychiatry
Background To overcome the limitations of conventional diffusion tensor magnetic resonance imaging resulting from the assumption of a Gaussian diffusion model for characterizing voxels containing multiple axonal orientations, Shannon's entropy was employed to evaluate white matter structure in human brain and in brain remodeling after traumatic brain injury (TBI) in a rat. Methods Thirteen healthy subjects were investigated using a Q-ball based DTI data sampling scheme. FA and entropy values were measured in white matter bundles, white matter fiber crossing areas, different gray matter (GM) regions and cerebrospinal fluid (CSF). Axonal densities' from the same regions of interest (ROIs) were evaluated in Bielschowsky and Luxol fast blue stained autopsy (n = 30) brain sections by light microscopy. As a case demonstration, a Wistar rat subjected to TBI and treated with bone marrow stromal cells (MSC) 1 week after TBI was employed to illustrate the superior ability of entropy over FA in detecting reorganized crossing axonal bundles as confirmed by histological analysis with Bielschowsky and Luxol fast blue staining. Results Unlike FA, entropy was less affected by axonal orientation and more affected by axonal density. A significant agreement (r = 0.91) was detected between entropy values from in vivo human brain and histologically measured axonal density from post mortum from the same brain structures. The MSC treated TBI rat demonstrated that the entropy approach is superior to FA in detecting axonal remodeling after injury. Compared with FA, entropy detected new axonal remodeling regions with crossing axons, confirmed with immunohistological staining. Conclusions Entropy measurement is more effective in distinguishing axonal remodeling after injury, when compared with FA. Entropy is also more sensitive to axonal density than axonal orientation, and thus may provide a more accurate reflection of axonal changes that occur in neurological injury and disease.

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