Characterizing Brain Structures and Remodeling after TBI Based on Information Content, Diffusion Entropy

Niloufar Fozouni,Michael Chopp,Siamak P Nejad-Davarani,Quan Jiang,Steven Gu,Jiani Hu,Mei Lu,Lian Li,Zheng Gang Zhang,Yuji Ueno,Norman L Lehman,Guangliang Ding,David Hearshen,Hassan Bagher-Ebadian,Stefano L Sensi

doi:10.1371/journal.pone.0076343

Niloufar Fozouni, Michael Chopp + Show 13 more

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https://doi.org/10.1371/journal.pone.0076343

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Abstract

BackgroundTo 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.MethodsThirteen 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.ResultsUnlike 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.ConclusionsEntropy 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.

Highlights

Diffusion Tensor Imaging (DTI), developed more than a decade ago [1], has been successfully used for the study of brain anatomy and in clinical neurodiagnostics, the latter especially for disease processes involving the white matter, such as multiple sclerosis (MS) [2,3], amyotrophic lateral sclerosis (ALS) [4], cerebral ischemia [5,6], brain tumors [7,8], and head trauma [9,10,11].The diffusivity from traditional DTI is derived from a symmetric rank-2, positive tensor[12]
The signal intensities in the entropy and Fractional Anisotropy (FA) maps showed similar patterns of intensity changes, from the highest in corpus callosum (CC), intermediate in gray matter, and the lowest in cerebrospinal fluid (CSF)
The anatomic details of brain structure in gray matter can be much more identified in the entropy map compared with the more uniform unidentified dark regions seen in the FA map

Summary

Introduction

Diffusion Tensor Imaging (DTI), developed more than a decade ago [1], has been successfully used for the study of brain anatomy and in clinical neurodiagnostics, the latter especially for disease processes involving the white matter, such as multiple sclerosis (MS) [2,3], amyotrophic lateral sclerosis (ALS) [4], cerebral ischemia [5,6], brain tumors [7,8], and head trauma [9,10,11].The diffusivity from traditional DTI is derived from a symmetric rank-2, positive tensor[12]. Examples of DTI model failure in analyzing areas of fiber crossing in white matter have been documented [18,19]. The second shortcoming of the DTI model results from its assumption that water diffusion in white matter follows a Gaussian distribution [20]. The foregoing observations indicate the unreliability of the conventional DTI model in addressing the non-Gaussian diffusion in the brain. 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

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Conclusion