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Quantifying brain microstructure with diffusion MRI: Theory and parameter estimation
Author(s) -
Novikov Dmitry S.,
Fieremans Els,
Jespersen Sune N.,
Kiselev Valerij G.
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.3998
Subject(s) - diffusion mri , context (archaeology) , diffusion , statistical physics , granularity , brain tissue , computer science , mesoscopic physics , biological system , neuroscience , physics , biology , magnetic resonance imaging , condensed matter physics , medicine , paleontology , radiology , operating system , thermodynamics
We review, systematize and discuss models of diffusion in neuronal tissue, by putting them into an overarching physical context of coarse‐graining over an increasing diffusion length scale. From this perspective, we view research on quantifying brain microstructure as occurring along three major avenues. The first avenue focusses on transient, or time‐dependent, effects in diffusion. These effects signify the gradual coarse‐graining of tissue structure, which occurs qualitatively differently in different brain tissue compartments. We show that transient effects contain information about the relevant length scales for neuronal tissue, such as the packing correlation length for neuronal fibers, as well as the degree of structural disorder along the neurites. The second avenue corresponds to the long‐time limit, when the observed signal can be approximated as a sum of multiple nonexchanging anisotropic Gaussian components. Here, the challenge lies in parameter estimation and in resolving its hidden degeneracies. The third avenue employs multiple diffusion encoding techniques, able to access information not contained in the conventional diffusion propagator. We conclude with our outlook on future directions that could open exciting possibilities for designing quantitative markers of tissue physiology and pathology, based on methods of studying mesoscopic transport in disordered systems.