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Updated: May 5, 2026

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

Linear rotationally invariant kurtosis measures from double diffusion encoding MRI.

Hunter G Moss¹, Thorsten Feiweier², Andreana Benitez³

¹Center for Biomedical Imaging, Medical University of South Carolina, Charleston, SC, USA; Department of Neuroscience, Medical University of South Carolina, Charleston, SC, United States of America.

Magnetic Resonance Imaging

|April 28, 2025

Summary

This summary is machine-generated.

Double diffusion encoding MRI kurtosis measures can classify multiple Gaussian compartment models based on microscopic anisotropy or water exchange. Simplified methods allow for accurate estimation of these important diffusion MRI metrics.

Keywords:

Brain Double diffusion encoding MRI Kurtosis Kärger model Microscopic anisotropy Rotational invariants Water exchange

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Last Updated: May 5, 2026

Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases

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Advanced Diffusion Imaging in The Hippocampus of Rats with Mild Traumatic Brain Injury

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Published on: August 14, 2019

Area of Science:

Diffusion MRI physics
Biophysical modeling
Neuroimaging analysis

Background:

Double diffusion encoding (DDE) MRI provides advanced diffusion metrics beyond traditional diffusion tensor imaging.
Multiple Gaussian compartment (MGC) models are used to represent complex water diffusion in biological tissues.
Understanding microscopic anisotropy and water exchange is crucial for accurate tissue microstructure characterization.

Purpose of the Study:

To fully characterize linear rotationally invariant kurtosis measures from DDE MRI.
To demonstrate the utility of these measures in differentiating MGC models.
To present simplified acquisition and analysis protocols for kurtosis measure estimation.

Main Methods:

Derivation and identification of four fundamental DDE MRI kurtosis invariants.
Application of invariants to classify MGC models based on anisotropy and exchange.
Investigation of exchange effects on microscopic fractional anisotropy (μFA).
Development and validation of simplified DDE MRI acquisition and analysis schemes.

Main Results:

Kurtosis invariants align with MGC models exhibiting microscopic anisotropy in brain regions.
Evidence suggests water exchange influences μFA estimates in gray matter.
The proposed simplified methods were successfully demonstrated on human brain data.

Conclusions:

DDE MRI kurtosis measures effectively distinguish MGC models with microscopic anisotropy or water exchange.
Simple acquisition and analysis schemes enable reliable estimation of these invariants.
Findings support the use of MGC models with microscopic anisotropy and highlight the significance of water exchange in brain diffusion modeling.