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Multimodal integration of diffusion MRI for better characterization of tissue biology
Author(s) -
Liu Chunlei,
Özarslan Evren
Publication year - 2019
Publication title -
nmr in biomedicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.278
H-Index - 114
eISSN - 1099-1492
pISSN - 0952-3480
DOI - 10.1002/nbm.3939
Subject(s) - diffusion mri , formalism (music) , diffusion , statistical physics , magnetic resonance imaging , computer science , tensor (intrinsic definition) , nuclear magnetic resonance , relaxation (psychology) , physics , mathematics , biology , radiology , neuroscience , medicine , quantum mechanics , geometry , art , musical , visual arts
The contrast in diffusion‐weighted MR images is due to variations of diffusion properties within the examined specimen. Certain microstructural information on the underlying tissues can be inferred through quantitative analyses of the diffusion‐sensitized MR signals. In the first part of the paper, we review two types of approach for characterizing diffusion MRI signals: Bloch's equations with diffusion terms, and statistical descriptions. Specifically, we discuss expansions in terms of cumulants and orthogonal basis functions, the confinement tensor formalism and tensor distribution models. Further insights into the tissue properties may be obtained by integrating diffusion MRI with other techniques, which is the subject of the second part of the paper. We review examples involving magnetic susceptibility, structural tensors, internal field gradients, transverse relaxation and functional MRI. Integrating information provided by other imaging modalities (MR based or otherwise) could be a key to improve our understanding of how diffusion MRI relates to physiology and biology.