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Model‐based estimation of microscopic anisotropy using diffusion MRI: a simulation study
Author(s) -
Ianuş Andrada,
Drobnjak Ivana,
Alexander Daniel C.
Publication year - 2016
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.3496
Subject(s) - isotropy , anisotropy , monte carlo method , eccentricity (behavior) , perpendicular , orientation (vector space) , diffusion , statistical physics , diffusion mri , biological system , physics , materials science , computational physics , geometry , algorithm , computer science , mathematics , statistics , optics , magnetic resonance imaging , medicine , radiology , biology , political science , law , thermodynamics
Non‐invasive estimation of cell size and shape is a key challenge in diffusion MRI. This article presents a model‐based approach that provides independent estimates of pore size and eccentricity from diffusion MRI data. The technique uses a geometric model of finite cylinders with gamma‐distributed radii to represent pores of various sizes and elongations. We consider both macroscopically isotropic substrates and substrates of semi‐coherently oriented anisotropic pores and we use Monte Carlo simulations to generate synthetic data. We compare the sensitivity of single and double diffusion encoding (SDE and DDE) sequences to the size distribution and eccentricity, and further analyse different protocols of DDE sequences with parallel and/or perpendicular pairs of gradients. We show that explicitly accounting for size distribution is necessary for accurate microstructural parameter estimates, and a model that assumes a single size yields biased eccentricity values. We also find that SDE sequences support estimates, although DDE sequences with mixed parallel and perpendicular gradients enhance accuracy. In the case of macroscopically anisotropic substrates, this model‐based approach can be extended to a rotationally invariant framework to provide features of pore shape (specifically eccentricity) in the presence of size distribution and orientation dispersion. Copyright © 2016 John Wiley & Sons, Ltd.