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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

Efficient gradient calibration based on diffusion MRI.

Irvin Teh¹, Mahon L Maguire^1,2, Jürgen E Schneider^1,2

¹Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom.

Magnetic Resonance in Medicine

|January 11, 2016

Summary

This summary is machine-generated.

This study introduces a new method for calibrating magnetic resonance imaging (MRI) gradient systems. The technique accurately corrects gradient nonlinearities, significantly improving image quality in diffusion MRI.

Keywords:

cyclooctane diffusion MRI gradient calibration gradient nonlinearity quantitative MRI

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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
Physics

Background:

Gradient system calibration is crucial for Magnetic Resonance Imaging (MRI) quality assurance.
Gradient nonlinearities can introduce significant errors in diffusion MRI measurements.

Purpose of the Study:

To propose and validate a method for calibrating MRI gradient systems.
To correct gradient nonlinearities using diffusion MRI measurements.

Main Methods:

Simulated gradient scaling errors in diffusion MRI acquisition.
Acquired data in a phantom and determined corrections for gradient scaling and nonlinearity.
Validated the calibration using diffusion tensor imaging and high-resolution anatomical MRI.

Main Results:

Reduced errors in apparent diffusion coefficients from ±9.2% to ±0.8%.
Minimized geometric measurement errors from -5.5% to +4.5% down to -0.97% to +0.23%.
Markedly reduced image distortions caused by gradient nonlinearity.

Conclusions:

The proposed gradient calibration method is accurate and efficient.
The approach utilizes readily available materials for setup.
Improves accuracy in both anatomical and diffusion MRI to within ±1%.