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Register a new userCompartmental diffusion and microstructural properties of human brain gray and white matter studied with double diffusion encoding magnetic resonance spectroscopy of metabolites and water
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Double diffusion encoding (DDE) magnetic resonance measurements of the water signal offers a unique ability to separate the effect of microscopic anisotropic diffusion in structural units of tissue from the overall macroscopic orientational distribution of cells. However, the specificity in detected microscopic anisotropy is limited as the signal is averaged over different cell types and across tissue compartments. Performing side-by-side metabolite DDE spectroscopy (DDES) and water DDES in which a wide range of b-values is used to gradually eliminate the extracellular contribution provides complementary measures from which intracellular and extracellular microscopic fractional anisotropies ($mu$FA) and diffusivities can be estimated. Metabolites are largely confined to the intracellular space and therefore provide a benchmark for intracellular diffusivity of specific cell types. Here, we aimed to estimate tissue- and compartment-specific human brain microstructure by combining water and metabolites DDES experiments. We performed DDES in human subjects in two brain regions that contain widely different amounts of white matter (WM) and gray matter (GM): parietal white matter (PWM) and occipital gray matter (OGM) on a 7 T MRI scanner. Results of the metabolite DDES experiments in both PWM and OGM suggest a highly anisotropic intracellular space within neurons and glia, with the possible exception of gray matter glia. Tortuosity values in the cytoplasm for water and tNAA, obtained with correlation analysis of microscopic parallel diffusivity with respect to GM/WM tissue fraction in the volume of interest, are remarkably similar for both molecules, while exhibiting a clear difference between gray and white matter, suggesting a more crowded cytoplasm and more complex cytomorphology of neuronal cell bodies and dendrites in GM than those found in long-range axons in WM.
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Diffusion pore imaging is an extension of diffusion-weighted nuclear magnetic resonance imaging enabling the direct measurement of the shape of arbitrarily formed, closed pores by probing diffusion restrictions using the motion of spin-bearing particles. Examples of such pores comprise cells in biological tissue or oil containing cavities in porous rocks. All pores contained in the measurement volume contribute to one reconstructed image, which reduces the problem of vanishing signal at increasing resolution present in conventional magnetic resonance imaging. It has been previously experimentally demonstrated that pore imaging using a combination of a long and a narrow magnetic field gradient pulse is feasible. In this work, an experimental verification is presented showing that pores can be imaged using short gradient pulses only. Experiments were carried out using hyperpolarized xenon gas in well-defined pores. The phase required for pore image reconstruction was retrieved from double diffusion encoded (DDE) measurements, while the magnitude could either be obtained from DDE signals or classical diffusion measurements with single encoding. The occurring image artifacts caused by restrictions of the gradient system, insufficient diffusion time, and by the phase reconstruction approach were investigated. Employing short gradient pulses only is advantageous compared to the initial long-narrow approach due to a more flexible sequence design when omitting the long gradient and due to faster convergence to the diffusion long-time limit, which may enable application to larger pores.
Cross-term spatiotemporal encoding (xSPEN) is a recently introduced imaging approach delivering single-scan 2D NMR images with unprecedented resilience to field inhomogeneities. The method relies on performing a pre-acquisition encoding and a subsequent image read out while using the disturbing frequency inhomogeneities as part of the image formation processes, rather than as artifacts to be overwhelmed by the application of external gradients. This study introduces the use of this new single-shot MRI technique as a diffusion-monitoring tool, for accessing regions that have hitherto been unapproachable by diffusion-weighted imaging (DWI) methods. In order to achieve this, xSPEN MRIs intrinsic diffusion weighting effects are formulated using a customized, spatially-localized b-matrix analysis; with this, we devise a novel diffusion-weighting scheme that both exploits and overcomes xSPENs strong intrinsic weighting effects. The ability to provide reliable and robust diffusion maps in challenging head and brain regions, including the eyes and the optic nerves, is thus demonstrated in humans at 3T; new avenues for imaging other body regions are also briefly discussed.
It is well known that water inside hydrophobic nano-channels diffuses faster than bulk water. Recent theoretical studies have shown that this enhancement depends on the size of the hydrophobic nanochannels. However, experimental evidence of this dependence is lacking. Here, by combining two-dimensional Nuclear Magnetic Resonance (NMR) diffusion-relaxation D-T2eff spectroscopy in the stray field of a superconducting magnet, and Molecular Dynamics (MD) simulations, we analyze the size dependence of water dynamics inside carbon nanotubes (CNTs) of different diameters (1.1 nm to 6.0 nm), in the temperature range of 265K to 305K. Depending on the CNTs diameter, the nanotube water is shown to resolve in two or more tubular components acquiring different self-diffusion coefficients. Most notable, a favourable CNTs diameter range 3.0-4.5 nm is experimentally verified for the first time, in which water molecule dynamics at the centre of the CNTs exhibit distinctly non-Arrhenius behaviour, characterized by ultrafast diffusion and extraordinary fragility, a result of significant importance in the efforts to understand water behaviour in hydrophobic nanochannels.
A large number of mathematical models have been proposed to describe the measured signal in diffusion-weighted (DW) magnetic resonance imaging (MRI) and infer properties about the white matter microstructure. However, a head-to-head comparison of DW-MRI models is critically missing in the field. To address this deficiency, we organized the White Matter Modeling Challenge during the International Symposium on Biomedical Imaging (ISBI) 2015 conference. This competition aimed at identifying the DW-MRI models that best predict unseen DW data. in vivo DW-MRI data was acquired on the Connectom scanner at the A.A.Martinos Center (Massachusetts General Hospital) using gradients strength of up to 300 mT/m and a broad set of diffusion times. We focused on assessing the DW signal prediction in two regions: the genu in the corpus callosum, where the fibres are relatively straight and parallel, and the fornix, where the configuration of fibres is more complex. The challenge participants had access to three-quarters of the whole dataset, and their models were ranked on their ability to predict the remaining unseen quarter of data. In this paper we provide both an overview and a more in-depth description of each evaluated model, report the challenge results, and infer trends about the model characteristics that were associated with high model ranking. This work provides a much needed benchmark for DW-MRI models. The acquired data and model details for signal prediction evaluation are provided online to encourage a larger scale assessment of diffusion models in the future.
Nuclear magnetic resonance (NMR) diffusion measurements are widely used to derive parameters indirectly related to the microstructure of biological tissues and porous media. However, a direct imaging of cell or pore shapes and sizes would be of high interest. For a long time, determining pore shapes by NMR diffusion acquisitions seemed impossible, because the necessary phase information could not be preserved. Here we demonstrate experimentally using the measurement technique which we have recently proposed theoretically that the shape of arbitrary closed pores can be imaged by diffusion acquisitions, which yield the phase information. For this purpose, we use hyperpolarized xenon gas in well-defined geometries. The signal can be collected from the whole sample which mainly eliminates the problem of vanishing signal at increasing resolution of conventional NMR imaging. This could be used to non-invasively gain structural information inaccessible so far such as pore or cell shapes, cell density or axon integrity.
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