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Measuring Connectivity in the Primary Visual Pathway in Human Albinism Using Diffusion Tensor Imaging and Tractography

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Diffusion tensor-based regional gray matter tissue segmentation using the international consortium for brain mapping

Khader M Hasan¹, Richard E Frye

¹Department of Diagnostic and Interventional Imaging, University of Texas Medical School at Houston, Houston, Texas, USA. Khader.M.Hasan@uth.tmc.edu

Human Brain Mapping

|August 28, 2010

Summary

This study presents a new diffusion tensor imaging (DTI) method to measure brain region volumes, like the putamen. The DTI-based approach accurately tracks age-related brain changes and correlates with existing methods, offering efficient neuroimaging analysis.

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

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Area of Science:

Neuroimaging
Radiology
Brain Anatomy

Background:

Diffusion tensor imaging (DTI) is crucial for analyzing white matter (WM) tracts.
Existing DTI methods primarily focus on WM tract integrity.
Accurate segmentation of gray matter and cerebrospinal fluid (CSF) using DTI remains a challenge.

Purpose of the Study:

To extend a validated DTI method for whole-brain segmentation of CSF, gray matter, and WM.
To provide regional volume and DTI metrics for WM tracts and cortical/subcortical gray matter.
To validate the DTI-based segmentation approach for measuring regional brain volumes and their association with age.

Main Methods:

Extended a previously validated DTI segmentation method.
Implemented DTI-based regional segmentation using Statistical Parametric Mapping (SPM) and established brain atlases.
Calculated left putamen volume and fractional anisotropy (FA) in 136 healthy individuals (aged 15.8-62.8 years).
Validated putamen volume measurements against FreeSurfer in a subset of 31 participants.

Main Results:

The DTI-based method successfully segmented whole-brain tissues and provided regional metrics.
Putamen volume significantly decreased with age (r = -0.30; P < 0.001).
Putamen fractional anisotropy (FA) significantly increased with age (r = 0.5; P < 0.00001).
DTI-derived putamen volume showed good correlation with FreeSurfer measurements (r = 0.396, P < 0.05).

Conclusions:

The novel DTI-based segmentation approach provides routine volumetry, enhancing DTI examination utility.
This method eliminates the need for separate scans for volumetry, improving efficiency.
The labeled volumes can enhance fiber tracking accuracy and have potential for automated analysis in large datasets for clinical research.