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Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases

Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases

Published on: July 28, 2013

STRUCTURAL CONNECTIVITY VIA THE TENSOR-BASED MORPHOMETRY.

Seung-Goo Kim¹, Moo K Chung, Jamie L Hanson

¹Department of Brain and Cognitive Sciences, Seoul National University, Korea.

Proceedings. IEEE International Symposium on Biomedical Imaging

|November 2, 2013

Summary

This summary is machine-generated.

This study introduces a novel computational framework using tensor-based morphometry (TBM) and T1-weighted MRI to analyze white matter connectivity. The method reveals topological alterations in brain networks of maltreated children without diffusion tensor imaging (DTI).

Keywords:

Jacobian determinant brain network maltreatment structural connectivity tensor-based morphometry

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Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

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Published on: November 8, 2012

Area of Science:

Neuroimaging
Computational Neuroscience
Brain Network Analysis

Background:

Tensor-based morphometry (TBM) is established for voxel-level tissue volume analysis.
Existing white matter connectivity studies often rely on diffusion tensor imaging (DTI).
There is a need for alternative methods to assess brain network topology.

Purpose of the Study:

To present a novel computational framework for white matter connectivity investigation using TBM.
To develop a data-driven approach for constructing brain network graphs without predefined parcellation.
To apply the framework to detect topological alterations in maltreated children's brain networks.

Main Methods:

Utilized T1-weighted magnetic resonance imaging (MRI) data, excluding diffusion tensor imaging (DTI).
Developed the 'ε-neighbor method,' a data-driven approach for brain network graph construction.
Applied tensor-based morphometry (TBM) to analyze topological changes in white matter connectivity.

Main Results:

Successfully constructed brain network graphs using only T1-weighted MRI.
The novel framework identified topological alterations in white matter connectivity.
Demonstrated the applicability of the method in a cohort of maltreated children.

Conclusions:

The proposed TBM-based framework offers a novel approach to white matter connectivity analysis.
This method bypasses the need for diffusion tensor imaging (DTI) and predetermined parcellations.
The findings highlight potential topological changes in the brain networks of maltreated children.