Advanced Diffusion Encoding Methods in MRI / Edition 1

by Daniel Topgaard

Overview

The medical MRI community is by far the largest user of diffusion NMR techniques and this book captures the current surge of methods and provides a primary source to aid adoption in this field.

There is a trend to adapting the more advanced diffusion encoding sequences developed by NMR researchers within the fields of porous media, chemical engineering, and colloid science to medical research. Recently published papers indicate great potential for improved diagnosis of the numerous pathological conditions associated with changes of tissue microstructure that are invisible to conventional diffusion MRI. This book disseminates these recent developments to the wider community of MRI researchers and clinicians. The chapters cover the theoretical basis, hardware and pulse sequences, data analysis and validation, and recent applications aimed at promoting further growth in the field.

This is a fast moving field and chapters are written by key MRI scientists that have contributed to the successful translation of the advanced diffusion NMR methods to the context of medical MRI, from global locations.

Product Details

ISBN-13:	9781788017268
Publisher:	RSC
Publication date:	08/11/2020
Series:	ISSN , #24
Pages:	436
Product dimensions:	6.14(w) x 9.21(h) x (d)

Table of Contents

Diffusion Encoding with General Gradient Waveforms;
Diffusion Anisotropy and Tensor-valued Diffusion Encoding;
Restricted Diffusion and Spectral Content of the Gradient Waveforms;
Disentangling Intercompartment Exchange from Restricted Diffusion;
Resolving Incoherent Flow from Diffusion Using Velocity-compensated Diffusion Encoding;
Estimating Chemical and Microstructural Heterogeneity by Correlating Relaxation Rates and Diffusion Tensors;
Hardware for Generating Modulated Gradient Waveforms with High Precision;
Pulse Sequences Combining Advanced Diffusion Encoding and Image Read-out;
Diagnosing and Alleviating Imaging Artifacts from Eddy Currents and Concomitant Gradients;
Nonparametric Inversion of Advanced Diffusion Data;
Model-based Analysis of Advanced Diffusion Data;
Phantoms for Validating Advanced Diffusion Sequences;
Correlating Advanced Diffusion MRI with Histology