Examining brain microstructure using structure tensor analysis of histological sections
ABSTRACT The mammalian central nervous system has a tremendous structural complexity, and diffusion tensor imaging (DTI) is unique in its ability to extract microstructural tissue properties at a macroscopic scale. However, despite its widespread use and applications in clinical and research settings, accurate validation of DTI has notoriously lagged the advances in image acquisition and analysis. In this report, we demonstrate an approach to visualize and quantify the microscopic features of histological sections on multiple length scales using techniques derived from image texture analysis. Structure tensor (ST) analysis was applied to fluorescence microscopy images of rat brain sections to visualize and quantify tissue microstructure. Images were digitally color-coded based on the local orientation in the pixelwise ST implementation, which allowed direct visualization of white matter complexity at the microscopic level. A piecewise ST algorithm was also employed to quantify anisotropy and orientation at a resolution comparable to that typically acquired with DTI. Anisotropy measured with ST analysis of stained histological sections was highly correlated with anisotropy measured by ex vivo DTI of the same brains (R(2)=0.92). Furthermore, angular histograms, or Fiber Orientation Distributions (FODs), were computed to mimic similar measures derived from high angular resolution diffusion imaging methods. The FODs for each pixel were fit to a mixture of von Mises distributions to identify putative regions of multiple fiber populations (i.e. crossing fibers). Despite its current application to two-dimensional microscopy, the ST analysis is a novel approach to visualize and quantify microstructure in the central nervous system in both health and disease, and advances the available set of tools for validating DTI and other diffusion MRI techniques.
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ABSTRACT: The hippocampus is a very important structure in memory formation and retrieval, as well as in various neurological disorders such as Alzheimer's disease, epilepsy and depression. It is composed of many intricate subregions making it difficult to study the anatomical changes that take place during disease. The hippocampal hilus may have unique neuroanatomy in humans compared to monkeys and rodents, with field CA3h greatly enlarged in humans compared to rodents, and a white-matter pathway, called the endfolial pathway, possibly only present in humans. In this study we have used newly developed 7.0T whole brain imaging, balanced steady-state free precession (bSSFP) that can achieve 0.4mm isotropic images to study, in vivo, the anatomy of the hippocampal hilus. A detailed hippocampal subregional segmentation was performed according to anatomic atlases segmenting the following regions: CA4, CA3, CA2, CA1, SRLM (stratum radiatum lacunosum moleculare), alveus, fornix, and subiculum along with its molecular layer. We also segmented a hypointense structure centrally within the hilus that resembled the endfolial pathway. To validate that this hypointense signal represented the endfolial pathway, we acquired 0.1mm isotropic 8-phase cycle bSSFP on an excised specimen, and then sectioned and stained the specimen for myelin using an anti-myelin basic protein antibody (SMI 94). A structure tensor analysis was calculated on the myelin-stained section to show directionality of the underlying fibers. The endfolial pathway was consistently visualized within the hippocampal body in vivo in all subjects. It is a central pathway in the hippocampus, with unknown relevance in neurodegenerative disorders, but now that it can be visualized noninvasively, we can study its function and alterations in neurodegeneration. Copyright © 2015. Published by Elsevier Inc.NeuroImage 02/2015; 112. DOI:10.1016/j.neuroimage.2015.02.029 · 6.13 Impact Factor
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ABSTRACT: In patients with Alzheimer's disease (AD) the severity of white matter degeneration correlates with the clinical symptoms of the disease. In this study, we performed diffusion-tensor magnetic resonance imaging at ultra-high field in a mouse model for AD (APP(swe)/PS1(dE9)) in combination with a voxel-based approach and tractography to detect changes in water diffusivity in white and gray matter, because these reflect structural alterations in neural tissue. We found substantial changes in water diffusion parallel and perpendicular to axonal tracts in several white matter regions like corpus callosum and fimbria of the hippocampus, that match with previous findings of axonal disconnection and myelin degradation in AD patients. Moreover, we found a significant increase in diffusivity in specific hippocampal subregions, which is supported by neuronal loss as visualized with Klüver-Barrera staining. This work demonstrates the potential of ultra-high field diffusion-tensor magnetic resonance imaging as a noninvasive modality to describe white and gray matter structural changes in mouse models for neurodegenerative disorders, and provides valuable knowledge to assess future AD prevention strategies in translational research.Neurobiology of aging 12/2012; 34(5). DOI:10.1016/j.neurobiolaging.2012.11.017 · 4.85 Impact Factor
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ABSTRACT: There is a need for effective computational methods for quantifying the three-dimensional (3-D) spatial distribution, cellular arbor morphologies, and the morphological diversity of brain astrocytes to support quantitative studies of astrocytes in health, injury, and disease. Confocal fluorescence microscopy of multiplex-labeled (GFAP, DAPI) brain tissue is used to perform imaging of astrocytes in their tissue context. The proposed computational method identifies the astrocyte cell nuclei, and reconstructs their arbors using a local priority based parallel (LPP) tracing algorithm. Quantitative arbor measurements are extracted using Scorcioni's L-measure, and profiled by unsupervised harmonic co-clustering to reveal the morphological diversity. The proposed method identifies astrocyte nuclei, generates 3-D reconstructions of their arbors, and extracts quantitative arbor measurements, enabling a morphological grouping of the cell population. Our method enables comprehensive spatial and morphological profiling of astrocyte populations in brain tissue for the first time, and overcomes limitations of prior methods. Visual proofreading of the results indicate a >95% accuracy in identifying astrocyte nuclei. The arbor reconstructions exhibited 3.2% fewer erroneous jumps in tracing, and 17.7% fewer false segments compared to the widely used fast-marching method that resulted in 9% jumps and 20.8% false segments. The proposed method can be used for large-scale quantitative studies of brain astrocyte distribution and morphology. Includes the software with detailed instructions (A), sample image (B), Sample output (C), and additional figures and movies (D). Copyright © 2015. Published by Elsevier B.V.Journal of Neuroscience Methods 03/2015; 246. DOI:10.1016/j.jneumeth.2015.02.014 · 1.96 Impact Factor