Introduction to Diffusion Tensor Imaging

by Mori

• ISBN13: 9780444528285
• ISBN10: 0444528288
• Edition: 1st
• Format: Hardcover
• Copyright: 2007-05-17
• Publisher: Elsevier Science

Summary

The concept of Diffusion Tensor Imaging (DTI) is often difficult to grasp, even for Magnetic Resonance physicists.Introduction to Diffusion Tensor Imaginguses extensive illustrations (not equations) to help readers to understand how DTI works. Emphasis is placed on the interpretation of DTI images, the design of DTI experiments, and the forms of application studies. The theory of DTI is constantly evolving and so there is a need for a textbook that explains how the technique works in a way that is easy to understand -Introduction to Diffusion Tensor Imagingfills this gap. * Uses extensive illustrations to explain the concept of Diffusion Tensor Imaging * Easy to understand, even without a background in physics * Includes sections on image interpretation, experimental design and applications

Table of Contents

Preface	p. ix
Basics of diffusion measurement	p. 1
NMR spectroscopy and MRI can detect signals from water molecules	p. 1
What is diffusion?	p. 3
How to measure diffusion?	p. 4
Anatomy of diffusion measurement	p. 13
A set of unipolar gradients and spin-echo sequence is most widely used for diffusion weighting	p. 13
There are four parameters that affect the amount of signal loss	p. 13
There are several ways of achieving a different degree of diffusion weighting	p. 17
Mathematics of diffusion measurement	p. 19
We need to calculate distribution of signal phases by molecular motion	p. 19
Simple exponential decay describes signal loss by diffusion weighting	p. 27
Diffusion constant can be obtained from the amount of signal loss but not from the signal intensity	p. 27
From two measurements, we can obtain a diffusion constant	p. 30
If there are more than two measurement points, linear least-square fitting is used	p. 31
Principle of diffusion tensor imaging	p. 33
NMR/MRI can measure diffusion constants along an arbitrary axis	p. 33
Diffusion sometimes has directionality	p. 33
Six parameters are needed to uniquely define an ellipsoid	p. 35
Diffusion tensor imaging characterizes the diffusion ellipsoid from multiple diffusion constant measurements along different directions	p. 37
Water molecules probe microscopic properties of their environment	p. 39
Human brain white matter has high diffusion anisotropy	p. 40
Mathematics of diffusion tensor imaging	p. 41
Our task is to determine six parameters of a diffusion ellipsoid	p. 41
We can obtain the six parameters from seven diffusion measurements	p. 43
Determination of the tensor elements from a fitting process	p. 45
Practical aspects of diffusion tensor imaging	p. 49
Two types of motion artifacts: ghosting and coregistration error	p. 49
We use echo-planar imaging to perform diffusion tensor imaging	p. 51
The amount of diffusion-weighting is constrained by the echo time	p. 53
There are various k-space sampling schemes	p. 53
Parallel imaging is good news for DTI	p. 57
Image distortion by eddy current needs special attention	p. 60
DTI results may differ if spatial resolution and SNR are not the same	p. 61
Selection of b-matrix	p. 63
New image contrasts from diffusion tensor imaging: theory, meaning, and usefulness of DTI-based image contrast	p. 69
Two scalar maps (anisotropy and diffusion constant maps) and fiber orientation maps are important outcomes obtained from DTI	p. 69
Scalar maps (anisotropy and diffusion constant maps) and fiber orientation maps are two important images obtained from DTI	p. 70
There are tubular and planar types of anisotropy	p. 72
DTI has several disadvantages	p. 75
There are multiple sources that decrease anisotropy	p. 76
Anisotropy may provide unique information	p. 79
Color-coded maps are a powerful visualization method to reveal white matter anatomy	p. 83
Limitations and improvement of diffusion tensor imaging	p. 85
Tensor model oversimplifies the underlying anatomy	p. 85
There are more sophisticated "non-tensor"-based data processing methods, which require different data acquisition protocols	p. 87
Non-tensor models usually require high b-values	p. 90
Three-dimensional tract reconstruction	p. 93
Three-dimensional trajectories can be reconstructed from DTI data	p. 93
There are two types of reconstruction techniques	p. 93
There are three steps in the tract propagation models	p. 94
Simple streamline tracking can be used to reconstruct a tract	p. 95
There are many limitations to simple tract propagation methods	p. 99
Several approaches are proposed to tackle the limitations	p. 100
Tract editing uses multiple regions of interest	p. 106
Brute-force approach is an effective technique for comprehensive tract reconstruction	p. 110
Accuracy and precision are important factors to be considered	p. 110
Reproducibility of tractography is measurable	p. 113
Tractography reveals macroscopic white matter anatomy	p. 114
There are roughly three types of information obtained from tractography	p. 115
How can we validate tractography?	p. 117
How should we use a tool with unknown accuracy?	p. 119
Quantification is a key to many types of tractography-based studies	p. 120
There are several possible reasons that lead to smaller (or larger) reconstruction results	p. 121
Quantification approaches	p. 125
Improvement of conventional quantification approaches	p. 125
Quantification of anisotropy and tract sizes by DTI	p. 130
Application studies	p. 149
Background of application studies of DTI	p. 149
Examples of application studies	p. 150
References and Suggested Readings	p. 163
Subject Index	p. 175
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