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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

Volumetric navigators for real-time motion correction in diffusion tensor imaging.

A Alhamud¹, M Dylan Tisdall, Aaron T Hess

¹MRC/UCT Medical Imaging Research Unit, Department of Human Biology, University of Cape Town, Observatory, South Africa. alkk1973@gmail.com

Magnetic Resonance in Medicine

|January 17, 2012

Summary

This summary is machine-generated.

A novel 3D echo planar imaging navigator effectively corrects prospective motion in diffusion tensor imaging. This technique significantly improves fractional anisotropy and mean diffusivity measurements, overcoming limitations of previous methods.

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Diffusion Imaging in the Rat Cervical Spinal Cord

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Published on: April 7, 2015

Area of Science:

Magnetic Resonance Imaging
Neuroimaging
Biophysics

Background:

Diffusion tensor imaging (DTI) is sensitive to head motion.
Existing prospective motion correction (PMC) methods have limitations.
Accurate DTI requires robust motion correction.

Purpose of the Study:

Introduce a novel 3D echo planar imaging (EPI) navigator for PMC in diffusion-weighted images (DWIs).
Evaluate the effectiveness of the novel navigator in correcting motion artifacts.
Assess the impact of the navigator on diffusion parameters.

Main Methods:

Developed a 3D EPI navigator with b-value independent contrast.
Acquired water phantom and human brain data using standard and navigated DTI sequences.
Analyzed fractional anisotropy (FA) and mean diffusivity (MD) using mean and whole-brain histogram metrics.

Main Results:

The navigator did not affect the diffusion sequence.
Head motion caused significant shifts in FA and MD histograms, even after retrospective correction.
The novel PMC technique substantially recovered FA and MD histogram metrics.

Conclusions:

The 3D EPI navigator provides effective PMC for DWIs.
This method mitigates motion-induced biases in DTI metrics.
The technique offers an improvement over existing PMC strategies.