scholarly journals Investigating The Functional Consequence Of White Matter Damage: An Automatic Pipeline To Create Longitudinal Disconnection Tractograms

2017 ◽  
Author(s):  
Kesshi Marin Jordan ◽  
Anisha Keshavan ◽  
Eduardo Caverzasi ◽  
Joseph Osorio ◽  
Nico Papinutto ◽  
...  
Keyword(s):  
White Matter ◽  
Human Brain ◽  
Large Scale ◽  
Diffusion Imaging ◽  
White Matter Injury ◽  
High Angular Resolution ◽  
Single Subject ◽  
White Matter Damage ◽  
Time Investment ◽  
Manual Intervention

Neurosurgical resection is one of the few opportunities researchers have to image the human brain both prior to and following focal damage. One of the challenges associated with studying brains undergoing surgical resection is that they often do not fit the brain templates most image-processing methodologies are based on, so manual intervention is required to reconcile the pathology and the most extreme cases must be excluded. Manual intervention requires significant time investment and introduces reproducibility concerns. We propose an automatic longitudinal pipeline based on High Angular Resolution Diffusion Imaging acquisitions to facilitate a Pathway Lesion Symptom Mapping analysis relating focal white matter injury to functional deficits. This two-part approach includes (i) automatic segmentation of focal white matter injury from anisotropic power differences, and (ii) modeling disconnection using tractography on the single-subject level, which specifically identifies the disconnections associated with focal white matter damage. The advantages of this approach stem from (1) objective and automatic lesion segmentation and tractogram generation, (2) objective and precise segmentation of affected tissue likely to be associated with damage to long-range white matter pathways (defined by anisotropic power), (3) good performance even in the cases of anatomical distortions by use of nonlinear tensor-based registration in the patient space, which aligns images using white matter contrast. Mapping a system as variable and complex as the human brain requires sample sizes much larger than the current technology can support. This pipeline can be used to execute large-scale, sufficiently powered analyses by meeting the need for an automatic approach to objectively quantify white matter disconnection.

scholarly journals Q -ball imaging of macaque white matter architecture

2005 ◽  
Vol 360 (1457) ◽  
pp. 869-879 ◽  
Author(s):  
David S Tuch ◽  
Jonathan J Wisco ◽  
Mark H Khachaturian ◽  
Leeland B Ekstrom ◽  
Rolf Kötter ◽  
...  
Keyword(s):  
White Matter ◽  
Magnetic Resonance ◽  
Diffusion Imaging ◽  
Large Body ◽  
Macaque Monkey ◽  
High Angular Resolution ◽  
Imaging Method ◽  
Diffusion Tractography ◽  
Axonal Projections ◽  
Histological Validation

Diffusion-weighted magnetic resonance imaging holds substantial promise as a technique for non-invasive imaging of white matter (WM) axonal projections. For diffusion imaging to be capable of providing new insight into the connectional neuroanatomy of the human brain, it will be necessary to histologically validate the technique against established tracer methods such as horseradish peroxidase and biocytin histochemistry. The macaque monkey provides an ideal model for histological validation of the diffusion imaging method due to the phylogenetic proximity between humans and macaques, the gyrencephalic structure of the macaque cortex, the large body of knowledge on the neuroanatomic connectivity of the macaque brain and the ability to use comparable magnetic resonance acquisition protocols in both species. Recently, it has been shown that high angular resolution diffusion imaging (HARDI) can resolve multiple axon orientations within an individual imaging voxel in human WM. This capability promises to boost the accuracy of tract reconstructions from diffusion imaging. If the macaque is to serve as a model for histological validation of the diffusion tractography method, it will be necessary to show that HARDI can also resolve intravoxel architecture in macaque WM. The present study therefore sought to test whether the technique can resolve intravoxel structure in macaque WM. Using a HARDI method called q -ball imaging (QBI) it was possible to resolve composite intravoxel architecture in a number of anatomic regions. QBI resolved intravoxel structure in, for example, the dorsolateral convexity, the pontine decussation, the pulvinar and temporal subcortical WM. The paper concludes by reviewing remaining challenges for the diffusion tractography project.

scholarly journals Computational Representation of White Matter Fiber Orientations

2013 ◽  
Vol 2013 ◽  
pp. 1-12
Author(s):  
Adelino R. Ferreira da Silva
Keyword(s):  
White Matter ◽  
Angular Resolution ◽  
Diffusion Imaging ◽  
Real Data ◽  
Orientation Distribution ◽  
Directional Data ◽  
High Angular Resolution ◽  
Clustering Data ◽  
Von Mises ◽  
Computational Representation

We present a new methodology based on directional data clustering to represent white matter fiber orientations in magnetic resonance analyses for high angular resolution diffusion imaging. A probabilistic methodology is proposed for estimating intravoxel principal fiber directions, based on clustering directional data arising from orientation distribution function (ODF) profiles. ODF reconstructions are used to estimate intravoxel fiber directions using mixtures of von Mises-Fisher distributions. The method focuses on clustering data on the unit sphere, where complexity arises from representing ODF profiles as directional data. The proposed method is validated on synthetic simulations, as well as on a real data experiment. Based on experiments, we show that by clustering profile data using mixtures of von Mises-Fisher distributions it is possible to estimate multiple fiber configurations in a more robust manner than currently used approaches, without recourse to regularization or sharpening procedures. The method holds promise to support robust tractographic methodologies and to build realistic models of white matter tracts in the human brain.

scholarly journals Euclidean distance as a measure to distinguish ventral and dorsal white matter connectivity in the human brain

2016 ◽  
Author(s):  
Philipp Kellmeyer ◽  
Magnus-Sebastian Vry
Keyword(s):  
White Matter ◽  
Human Brain ◽  
Cognitive Processing ◽  
Euclidean Distance ◽  
Large Scale ◽  
Diffusion Tensor ◽  
Large Body ◽  
Coordinate Space ◽  
Fiber Tractography

AbstractFiber tractography based on diffusion tensor imaging (DTI) has become an important research tool for investigating the anatomical connectivity between brain regions in vivo. Combining DTI with functional magnetic resonance imaging (fMRI) allows for the mapping of structural and functional architecture of large-scale networks for cognitive processing. This line of research has shown that ventral and dorsal fiber pathways subserve different aspects of bottom-up- and top-down processing in the human brain.Here, we investigate the feasibility and applicability of Euclidean distance as a simple geometric measure to differentiate ventral and dorsal long-range white matter fiber pathways tween parietal and inferior frontal cortical regions, employing a body of studies that used probabilistic tractography.We show that ventral pathways between parietal and inferior frontal cortex have on average a significantly longer Euclidean distance in 3D-coordinate space than dorsal pathways. We argue that Euclidean distance could provide a simple measure and potentially a boundary value to assess patterns of connectivity in fMRI studies. This would allow for a much broader assessment of general patterns of ventral and dorsal large-scale fiber connectivity for different cognitive operations in the large body of existing fMRI studies lacking additional DTI data.

scholarly journals Development of a high angular resolution diffusion imaging human brain template

NeuroImage ◽  
2014 ◽  
Vol 91 ◽  
pp. 177-186 ◽  
Author(s):  
Anna Varentsova ◽  
Shengwei Zhang ◽  
Konstantinos Arfanakis
Keyword(s):  
Human Brain ◽  
Angular Resolution ◽  
Diffusion Imaging ◽  
High Angular Resolution ◽  
Brain Template

scholarly journals Diffusion Maps Clustering for Magnetic Resonance Q-Ball Imaging Segmentation

2008 ◽  
Vol 2008 ◽  
pp. 1-12 ◽  
Author(s):  
Demian Wassermann ◽  
Maxime Descoteaux ◽  
Rachid Deriche
Keyword(s):  
White Matter ◽  
Diffusion Tensor ◽  
Diffusion Imaging ◽  
Orientation Distribution ◽  
Fiber Bundles ◽  
High Angular Resolution ◽  
Complex Data ◽  
Diffusion Maps ◽  
Clustering Method ◽  
Number Of Clusters

White matter fiber clustering aims to get insight about anatomical structures in order to generate atlases, perform clear visualizations, and compute statistics across subjects, all important and current neuroimaging problems. In this work, we present a diffusion maps clustering method applied to diffusion MRI in order to segment complex white matter fiber bundles. It is well known that diffusion tensor imaging (DTI) is restricted in complex fiber regions with crossings and this is why recent high-angular resolution diffusion imaging (HARDI) such as Q-Ball imaging (QBI) has been introduced to overcome these limitations. QBI reconstructs the diffusion orientation distribution function (ODF), a spherical function that has its maxima agreeing with the underlying fiber populations. In this paper, we use a spherical harmonic ODF representation as input to the diffusion maps clustering method. We first show the advantage of using diffusion maps clustering over classical methods such as N-Cuts and Laplacian eigenmaps. In particular, our ODF diffusion maps requires a smaller number of hypothesis from the input data, reduces the number of artifacts in the segmentation, and automatically exhibits the number of clusters segmenting the Q-Ball image by using an adaptive scale-space parameter. We also show that our ODF diffusion maps clustering can reproduce published results using the diffusion tensor (DT) clustering with N-Cuts on simple synthetic images without crossings. On more complex data with crossings, we show that our ODF-based method succeeds to separate fiber bundles and crossing regions whereas the DT-based methods generate artifacts and exhibit wrong number of clusters. Finally, we show results on a real-brain dataset where we segment well-known fiber bundles.

scholarly journals High angular resolution diffusion imaging reveals intravoxel white matter fiber heterogeneity

2002 ◽  
Vol 48 (4) ◽  
pp. 577-582 ◽  
Author(s):  
David S. Tuch ◽  
Timothy G. Reese ◽  
Mette R. Wiegell ◽  
Nikos Makris ◽  
John W. Belliveau ◽  
...  
Keyword(s):  
White Matter ◽  
Angular Resolution ◽  
Diffusion Imaging ◽  
High Angular Resolution

Abstract TP119: Tibia Fracture Leads to Long-Lasting Memory Dysfunction in Mice Through Enhanced Blood-Brain Barrie Breakdown in the Hippocampus and White Matter Damage

Stroke ◽  
2020 ◽  
Vol 51 (Suppl_1) ◽  
Author(s):  
Jinhao Huang ◽  
Haiyan Lyu ◽  
Kang Hou ◽  
Leandro Barbosa Do Prado ◽  
Chaoliang Tang ◽  
...  
Keyword(s):  
White Matter ◽  
Basal Ganglia ◽  
Underlying Mechanism ◽  
Contralateral Side ◽  
Tibia Fracture ◽  
White Matter Injury ◽  
Memory Dysfunction ◽  
White Matter Damage ◽  
Blood Brain ◽  
Stroke Group

Background and Purpose: Tibia fracture (BF) causes long-lasting memory dysfunction in stroke mice, which is associated with microglia accumulation in the hippocampus ipsilateral to the stroke injury. The underlying mechanism is unclear. Hypothesis: BF exacerbates blood brain barrier (BBB) breakdown and fibrin extravasation in the hippocampus enhancing white matter damage of stroke mice. Method: C57 mice (8-weeks) were randomly assigned to BF, stroke (pMCAO), BF+stroke (BF 6h before stroke) and sham groups. The integrity of BBB, fibrin deposition and CD68 + cells infiltration in the hippocampus were analyzed 3 days and the white matter injury in the basal ganglia was analyzed 8 weeks after the surgeries. Results: Compared to BF group, stroke and BF+stroke groups had lower level of claudin-5, fewer pericytes, more extravascular fibrin and CD68 + cells in the ipsilateral side of stroke 3 days after the injuries. BF+stroke group had the lowest level of claudin-5, fewest pericytes, highest extravascular fibrin and most CD68 + cells among the three groups. BF+stroke group also had a lower level of claudin-5 and fewer CD13 + pericytes in the contralateral side than the other two groups. Compared to sham group, the white matter bundle areas in the basal ganglia were reduced in stroke and BF+stroke groups in both contralateral and ipsilateral sides 8 weeks after the injuries. Stroke and BF+stroke groups also has smaller white matter bundle areas in the ipsilateral than contralateral side, and the white matter bundle areas in the contralateral side of BF+stroke group were also smaller than stroke group. Conclusion: BF shortly before stroke causes long-lasting memory dysfunction in mice through enhancing BBB breakdown and fibrin extravasation in the hippocampus, which exacerbates neuroinflammation and white matter damage.

Diffusion Imaging Methods in Language Sciences

2019 ◽  
pp. 211-228
Author(s):  
Stephanie J. Forkel ◽  
Marco Catani
Keyword(s):  
White Matter ◽  
Human Brain ◽  
Animal Studies ◽  
Diffusion Imaging ◽  
Imaging Methods ◽  
Diffusion Tractography ◽  
Fast Pace ◽  
Normal Language ◽  
First Time

The field of neuroanatomy of language is moving forward at a fast pace. This progression is partially due to the development of diffusion tractography, which has been used to describe white matter connections in the living human brain. For the field of neurolinguistics, this advancement is timely and important for two reasons. First, it allows clinical researchers to liberate themselves from neuroanatomical models of language derived from animal studies. Second, for the first time, it offers the possibility of testing network correlates of neurolinguistic models directly in the human brain. This chapter introduces the reader to general principles of diffusion imaging and tractography. Examples of its applications to normal language and its disorders will be used to explicate its potentials and limitations.

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