Characterizing brain structures and remodeling after TBI based on information content, diffusion entropy.

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...

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Main Authors: Niloufar Fozouni, Michael Chopp, Siamak P Nejad-Davarani, Zheng Gang Zhang, Norman L Lehman, Steven Gu, Yuji Ueno, Mei Lu, Guangliang Ding, Lian Li, Jiani Hu, Hassan Bagher-Ebadian, David Hearshen, Quan Jiang
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2013-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC3797055?pdf=render
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author Niloufar Fozouni
Michael Chopp
Siamak P Nejad-Davarani
Zheng Gang Zhang
Norman L Lehman
Steven Gu
Yuji Ueno
Mei Lu
Guangliang Ding
Lian Li
Jiani Hu
Hassan Bagher-Ebadian
David Hearshen
Quan Jiang
author_facet Niloufar Fozouni
Michael Chopp
Siamak P Nejad-Davarani
Zheng Gang Zhang
Norman L Lehman
Steven Gu
Yuji Ueno
Mei Lu
Guangliang Ding
Lian Li
Jiani Hu
Hassan Bagher-Ebadian
David Hearshen
Quan Jiang
author_sort Niloufar Fozouni
collection DOAJ
description 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.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.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.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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spelling doaj.art-e9e32b05ff5b4fe7993f9f9e1beb99c32022-12-21T19:52:14ZengPublic Library of Science (PLoS)PLoS ONE1932-62032013-01-01810e7634310.1371/journal.pone.0076343Characterizing brain structures and remodeling after TBI based on information content, diffusion entropy.Niloufar FozouniMichael ChoppSiamak P Nejad-DavaraniZheng Gang ZhangNorman L LehmanSteven GuYuji UenoMei LuGuangliang DingLian LiJiani HuHassan Bagher-EbadianDavid HearshenQuan JiangTo 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.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.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.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.http://europepmc.org/articles/PMC3797055?pdf=render
spellingShingle Niloufar Fozouni
Michael Chopp
Siamak P Nejad-Davarani
Zheng Gang Zhang
Norman L Lehman
Steven Gu
Yuji Ueno
Mei Lu
Guangliang Ding
Lian Li
Jiani Hu
Hassan Bagher-Ebadian
David Hearshen
Quan Jiang
Characterizing brain structures and remodeling after TBI based on information content, diffusion entropy.
PLoS ONE
title Characterizing brain structures and remodeling after TBI based on information content, diffusion entropy.
title_full Characterizing brain structures and remodeling after TBI based on information content, diffusion entropy.
title_fullStr Characterizing brain structures and remodeling after TBI based on information content, diffusion entropy.
title_full_unstemmed Characterizing brain structures and remodeling after TBI based on information content, diffusion entropy.
title_short Characterizing brain structures and remodeling after TBI based on information content, diffusion entropy.
title_sort characterizing brain structures and remodeling after tbi based on information content diffusion entropy
url http://europepmc.org/articles/PMC3797055?pdf=render
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