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Updated: Aug 23, 2025

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

Mapping the Impact of Non-Linear Gradient Fields on Diffusion MRI Tensor Estimation.

Praitayini Kanakaraj¹, Colin B Hansen¹, Francois Rheault²

¹Department of Computer Science, Vanderbilt University, Nashville, TN, USA.

Proceedings of Spie--The International Society for Optical Engineering

|October 28, 2022

Summary

This summary is machine-generated.

Gradient nonlinearities in diffusion-weighted MRI (DW-MRI) distort images, affecting tractography and microstructure analysis. This study quantifies these errors, showing lower fractional anisotropy (FA) is more susceptible to gradient field corruption.

Keywords:

Magnetic resonance distortion gradient non-linearity tensor simulation

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Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases

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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:

Medical Imaging
Biophysics
Neuroimaging

Background:

Non-linear gradients in diffusion-weighted MRI (DW-MRI) introduce significant artifacts.
These artifacts, including distortion and phase errors, complicate the interpretation of tractography and tissue microstructure.
Understanding the impact of gradient nonlinearities is crucial for accurate DW-MRI data analysis.

Purpose of the Study:

To empirically assess the impact of non-linear gradient fields on diffusion tensor properties.
To quantify the consequences of gradient nonlinearities on key diffusion metrics.
To provide insights for correcting gradient-related inaccuracies in DW-MRI.

Main Methods:

Introduced empirically derived gradient nonlinear fields at various orientations.
Assessed the impact on diffusion tensor properties: fractional anisotropy (FA), mean diffusivity (MD), and principal eigenvector (PEV).
Analyzed the relationship between true FA values and the corruption introduced by non-linear fields.

Main Results:

Lower FA values are more susceptible to gradient nonlinearities (LR fields).
LR fields with determinants <1 or >1 significantly corrupt tensor properties.
Apparent MD decreases with negative determinant LR fields; positive determinants show the opposite effect.
LR fields impact PEV more significantly at lower FA values.

Conclusions:

Gradient nonlinearities can lead to substantial changes in estimated FA, MD, and PEV.
The orientation of the non-linear field influences the direction and magnitude of the corruption.
This characterization aids in selecting appropriate correction techniques for DW-MRI inaccuracies.