Abstract
Characterization of porous media is essential in a wide range of biomedical and industrial applications. Microstructural features can be probed non-invasively by diffusion magnetic resonance imaging (dMRI). However, diffusion encoding in conventional dMRI may yield similar signatures for very different microstructures, which represents a significant limitation for disentangling individual microstructural features in heterogeneous materials. To solve this problem, we propose an augmented multidimensional diffusion encoding (MDE) framework, which unlocks a novel encoding dimension to assess time-dependent diffusion specific to structures with different microscopic anisotropies. Our approach relies on spectral analysis of complex but experimentally efficient MDE waveforms. Two independent contrasts to differentiate features such as cell shape and size can be generated directly by signal subtraction from only three types of measurements. Analytical calculations and simulations support our experimental observations. Proof-of-concept experiments were applied on samples with known and distinctly different microstructures. We further demonstrate substantially different contrasts in different tissue types of a post mortem brain. Our simultaneous assessment of restriction size and shape may be instrumental in studies of a wide range of porous materials, enable new insights into the microstructure of biological tissues or be of great value in diagnostics.
Highlights
A wide variety of materials are porous in nature
The problem of entangled information is common in nuclear magnetic resonance (NMR) studies of solids and porous media, and the research community has learned to address this by multidimensional encoding approaches
The augmented multidimensional diffusion encoding (MDE) protocol was implemented on a 4.7 T preclinical MRI system and experiments were conducted on four phantoms with well-known microstructures as well as on a post mortem monkey brain tissue
Summary
Characterizing the microstructure of such materials is key to understand for example the state and function of biological tissues, elasto-mechanic properties of materials, or texture of food products and rocks This range of porous materials can be non-invasively studied by diffusion magnetic resonance imaging (dMRI)[1]. Different microstructural information may be entangled in the encoding process, leading to low specificity of conventional dMRI. This problem is acute in tissue, which consists of diverse compartments residing within a typical millimeter-size imaging voxel. This diffusion encoding approach, known as double diffusion encoding, has recently been applied in a number of MRI studies[17]
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