Abstract

Despite their widespread use in non-invasive studies of porous materials, conventional MRI methods yield ambiguous results for microscopically heterogeneous materials such as brain tissue. While the forward link between microstructure and MRI observables is well understood, the inverse problem of separating the signal contributions from different microscopic pores is notoriously difficult. Here, we introduce an experimental protocol where heterogeneity is resolved by establishing 6D correlations between the individual values of isotropic diffusivity, diffusion anisotropy, orientation of the diffusion tensor, and relaxation rates of distinct populations. Such procedure renders the acquired signal highly specific to the sample’s microstructure, and allows characterization of the underlying pore space without prior assumptions on the number and nature of distinct microscopic environments. The experimental feasibility of the suggested method is demonstrated on a sample designed to mimic the properties of nerve tissue. If matched to the constraints of whole body scanners, this protocol could allow for the unconstrained determination of the different types of tissue that compose the living human brain.

Highlights

  • Magnetic Resonance Imaging (MRI) has been firmly established as the method of choice for non-invasive investigations of the structure of the living human brain

  • Within the typical signal-to-noise ratio (SNR) in MRI, the same data can often be well described with fundamentally different models[30,31], or even distinct parameter sets for the same model[32,33]

  • We have shown that the projection of D unto a sparse basis of (Diso, DΔ, θ, φ) allows us to resolve details that would otherwise be concealed by broad distributions of Deff wherein size, shape and orientation are intrinsically entangled[37,38,39]

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Summary

Introduction

Magnetic Resonance Imaging (MRI) has been firmly established as the method of choice for non-invasive investigations of the structure of the living human brain. We join the DTD and Laplace frameworks into a single experimental method that combines the simple relation between diffusion tensors and microstructure with the sensitivity of R1 and R2 to the chemical composition of the tissue[1,2,3,4,5,6] In this novel approach, a heterogeneous sample is characterized through correlations between the isotropic diffusivity Diso, normalized diffusion anisotropy DΔ, orientation of the diffusion tensor (θ, φ), and relaxation rates R1 and R2

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