Abstract

Biophysical models that describe the outcome of white matter diffusion MRI experiments have various degrees of complexity. While the simplest models assume equal-sized and parallel axons, more elaborate ones may include distributions of axon diameters and axonal orientation dispersions. These microstructural features can be inferred from diffusion-weighted signal attenuation curves by solving an inverse problem, validated in several Monte Carlo simulation studies. Model development has been paralleled by microscopy studies of the microstructure of excised and fixed nerves, confirming that axon diameter estimates from diffusion measurements agree with those from microscopy. However, results obtained in vivo are less conclusive. For example, the amount of slowly diffusing water is lower than expected, and the diffusion-encoded signal is apparently insensitive to diffusion time variations, contrary to what may be expected. Recent understandings of the resolution limit in diffusion MRI, the rate of water exchange, and the presence of microscopic axonal undulation and axonal orientation dispersions may, however, explain such apparent contradictions. Knowledge of the effects of biophysical mechanisms on water diffusion in tissue can be used to predict the outcome of diffusion tensor imaging (DTI) and of diffusion kurtosis imaging (DKI) studies. Alterations of DTI or DKI parameters found in studies of pathologies such as ischemic stroke can thus be compared with those predicted by modelling. Observations in agreement with the predictions strengthen the credibility of biophysical models; those in disagreement could provide clues of how to improve them. DKI is particularly suited for this purpose; it is performed using higher b-values than DTI, and thus carries more information about the tissue microstructure. The purpose of this review is to provide an update on the current understanding of how various properties of the tissue microstructure and the rate of water exchange between microenvironments are reflected in diffusion MRI measurements. We focus on the use of biophysical models for extracting tissue-specific parameters from data obtained with single PGSE sequences on clinical MRI scanners, but results obtained with animal MRI scanners are also considered. While modelling of white matter is the central theme, experiments on model systems that highlight important aspects of the biophysical models are also reviewed.

Highlights

  • The diffusion MRI experiment uses magnetic field gradients to label spins, as described pedagogically elsewhere [1, 2]

  • We focus on the use of biophysical models for extracting tissue-specific parameters from data obtained with single pulsed-gradient spin-echo (PGSE) sequences on clinical MRI scanners, but results obtained with animal MRI scanners are considered

  • Such double pulsed-field gradient (d-PFG) experiments were later employed for investigations of microscopic anisotropy [7,8,9,10], estimation of compartment sizes [10, 11], and increasing the sensitivity to water exchange [12, 13]

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Summary

Introduction

The diffusion MRI experiment uses magnetic field gradients to label spins, as described pedagogically elsewhere [1, 2]. Special cases of this model allow si to be inferred from constant-gradient experiments, in which g is fixed while td is varied [92, 93] This approach provides accurate estimates of si, but for long diffusion times and values of gmax above those normally available with clinical MRI scanners. Instead of the approach used in constant-gradient experiments of only collecting limited data, a large set of experimental conditions with varying values of d, td and b can be acquired This allows the full two-compartment exchange model to be fitted to the data. Another study performed a similar evaluation using a protocol with d = 30 ms, td = 30–60 ms, and bmax = 20 ms/lm2 [68] These two studies showed that the two-compartment model generally provides accurate estimates of the values that were used in the simulation, except for d below the resolution limit.

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