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Magnetic Resonance Imaging May 2022We propose a method that can provide information about the anisotropy and orientation of diffusion in the brain from only 3 orthogonal gradient directions without...
We propose a method that can provide information about the anisotropy and orientation of diffusion in the brain from only 3 orthogonal gradient directions without imposing additional assumptions. The method is based on the Diffusion Anisotropy (DiA) that measures the distance from a diffusion signal to its isotropic equivalent. The original formulation based on a Spherical Harmonics basis allows to go down to only 3 orthogonal directions in order to estimate the measure. In addition, an alternative simplification and a color-coding representation are also proposed. Acquisitions from a publicly available database are used to test the viability of the proposal. The DiA succeeded in providing anisotropy information from the white matter using only 3 diffusion-encoding directions. The price to pay for such reduced acquisition is an increment in the variability of the data and a subestimation of the metric on those tracts not aligned with the acquired directions. Nevertheless, the calculation of anisotropy information from DMRI is feasible using fewer than 6 gradient directions by using DiA. The method is totally compatible with existing acquisition protocols, and it may provide complementary information about orientation in fast diffusion acquisitions.
Topics: Anisotropy; Brain; Diffusion; Diffusion Magnetic Resonance Imaging; White Matter
PubMed: 35122982
DOI: 10.1016/j.mri.2022.01.014 -
NeuroImage Nov 2016The fractional anisotropy (FA) that can be derived from diffusion tensor imaging (DTI), is ambiguous because it not only depends on the tissue microstructure but also on...
The fractional anisotropy (FA) that can be derived from diffusion tensor imaging (DTI), is ambiguous because it not only depends on the tissue microstructure but also on the axon or fiber orientation distribution within a voxel. Measures of the microscopic diffusion anisotropy, like the microscopic anisotropy index (MA) that can be determined with so-called double-wave-vector (DWV) or double diffusion encoding (DDE) imaging, are independent of this orientation distribution and, thus, offer a more direct and undisguised access to the tissue structure on a cellular or microscopic scale. In this study, FA and MA measurements were performed in a group of aged (>60y), healthy volunteers and compared to the data obtained recently for a group of young (<33y), healthy volunteers to reveal age-related differences. The coefficients-of-variation (CV) determined for the aged group were considerably lower for MA than for FA in average and in most of the 16 ROIs analyzed due to lower between-subject variations of MA. FA differences between the young and the aged group were in line with previous DTI studies. MA was also decreased in the aged group but in more of the 16 ROIs and with a higher significance. Furthermore, MA differences were also observed in frontal brain regions containing fiber crossings that did not reveal significant FA differences, i.e. MA seems to provide a better sensitivity to detect microstructural changes in such regions. In some non-cortical gray matter structures like the putamen, FA was increased but MA was decreased in the aged group which could indicate a coherent fiber orientation in the aged group related to the loss of crossing or fanning fibers. In conclusion, MA not only could improve the detectability of differences of the tissue microstructure but, in conjunction with FA, could also help to identify the underlying changes.
Topics: Aged; Aging; Anisotropy; Brain; Diffusion; Diffusion Magnetic Resonance Imaging; Female; Humans; Image Interpretation, Computer-Assisted; Male; Middle Aged; Reproducibility of Results; Sensitivity and Specificity; White Matter
PubMed: 27436594
DOI: 10.1016/j.neuroimage.2016.07.031 -
Zeitschrift Fur Medizinische Physik Feb 2020Diffusion anisotropy in diffusion tensor imaging (DTI) is commonly quantified with normalized diffusion anisotropy indices (DAIs). Most often, the fractional anisotropy...
Diffusion anisotropy in diffusion tensor imaging (DTI) is commonly quantified with normalized diffusion anisotropy indices (DAIs). Most often, the fractional anisotropy (FA) is used, but several alternative DAIs have been introduced in attempts to maximize the contrast-to-noise ratio (CNR) in diffusion anisotropy maps. Examples include the scaled relative anisotropy (sRA), the gamma variate anisotropy index (GV), the surface anisotropy (UA), and the lattice index (LI). With the advent of multidimensional diffusion encoding it became possible to determine the presence of microscopic diffusion anisotropy in a voxel, which is theoretically independent of orientation coherence. In accordance with DTI, the microscopic anisotropy is typically quantified by the microscopic fractional anisotropy (μFA). In this work, in addition to the μFA, the four microscopic diffusion anisotropy indices (μDAIs) μsRA, μGV, μUA, and μLI are defined in analogy to the respective DAIs by means of the average diffusion tensor and the covariance tensor. Simulations with three representative distributions of microscopic diffusion tensors revealed distinct CNR differences when differentiating between isotropic and microscopically anisotropic diffusion. q-Space trajectory imaging (QTI) was employed to acquire brain in-vivo maps of all indices. For this purpose, a 15min protocol featuring linear, planar, and spherical tensor encoding was used. The resulting maps were of good quality and exhibited different contrasts, e.g. between gray and white matter. This indicates that it may be beneficial to use more than one μDAI in future investigational studies.
Topics: Anisotropy; Brain; Brain Mapping; Diffusion; Diffusion Tensor Imaging; Humans; Image Processing, Computer-Assisted
PubMed: 30853147
DOI: 10.1016/j.zemedi.2019.01.003 -
Journal of Neuroscience Methods Jan 2021Diffusion Magnetic Resonance Imaging (dMRI) is one of the most important contemporary non-invasive modalities for probing tissue structure at the microscopic scale. The... (Review)
Review
Diffusion Magnetic Resonance Imaging (dMRI) is one of the most important contemporary non-invasive modalities for probing tissue structure at the microscopic scale. The majority of dMRI techniques employ standard single diffusion encoding (SDE) measurements, covering different sequence parameter ranges depending on the complexity of the method. Although many signal representations and biophysical models have been proposed for SDE data, they are intrinsically limited by a lack of specificity. Advanced dMRI methods have been proposed to provide additional microstructural information beyond what can be inferred from SDE. These enhanced contrasts can play important roles in characterizing biological tissues, for instance upon diseases (e.g. neurodegenerative, cancer, stroke), aging, learning, and development. In this review we focus on double diffusion encoding (DDE), which stands out among other advanced acquisitions for its versatility, ability to probe more specific diffusion correlations, and feasibility for preclinical and clinical applications. Various DDE methodologies have been employed to probe compartment sizes (Section 3), decouple the effects of microscopic diffusion anisotropy from orientation dispersion (Section 4), probe displacement correlations, study exchange, or suppress fast diffusing compartments (Section 6). DDE measurements can also be used to improve the robustness of biophysical models (Section 5) and study intra-cellular diffusion via magnetic resonance spectroscopy of metabolites (Section 7). This review discusses all these topics as well as important practical aspects related to the implementation and contrast in preclinical and clinical settings (Section 9) and aims to provide the readers a guide for deciding on the right DDE acquisition for their specific application.
Topics: Anisotropy; Brain; Diffusion; Diffusion Magnetic Resonance Imaging; Magnetic Resonance Imaging; Magnetic Resonance Spectroscopy
PubMed: 33144100
DOI: 10.1016/j.jneumeth.2020.108989 -
Biomechanics and Modeling in... Dec 2020Fluorescence recovery after photobleaching (FRAP) is a widely used technique for studying diffusion in biological tissues. Most of the existing approaches for the...
Fluorescence recovery after photobleaching (FRAP) is a widely used technique for studying diffusion in biological tissues. Most of the existing approaches for the analysis of FRAP experiments assume isotropic diffusion, while only a few account for anisotropic diffusion. In fibrous tissues, such as articular cartilage, tendons and ligaments, diffusion, the main mechanism for molecular transport, is anisotropic and depends on the fibre alignment. In this work, we solve the general diffusion equation governing a FRAP test, assuming an anisotropic diffusivity tensor and using a general initial condition for the case of an elliptical (thereby including the case of a circular) bleaching profile. We introduce a closed-form solution in the spatial coordinates, which can be applied directly to FRAP tests to extract the diffusivity tensor. We validate the approach by measuring the diffusivity tensor of [Formula: see text] FITC-Dextran in porcine medial collateral ligaments. The measured diffusion anisotropy was [Formula: see text] (SE), which is in agreement with that reported in the literature. The limitations of the approach, such as the size of the bleached region and the intensity of the bleaching, are studied using COMSOL simulations.
Topics: Animals; Anisotropy; Biological Transport; Computer Simulation; Diffusion; Fluorescence Recovery After Photobleaching; Medial Collateral Ligament, Knee; Microscopy, Electron, Scanning; Models, Biological; Models, Theoretical; Swine; Tendons
PubMed: 32562093
DOI: 10.1007/s10237-020-01346-z -
Journal of the American Chemical Society Feb 2018Metal-organic frameworks are promising materials for energy-efficient gas separations, but little is known about the diffusion of adsorbates in materials featuring...
Metal-organic frameworks are promising materials for energy-efficient gas separations, but little is known about the diffusion of adsorbates in materials featuring one-dimensional porosity at the nanoscale. An understanding of the interplay between framework structure and gas diffusion is crucial for the practical application of these materials as adsorbents or in mixed-matrix membranes, since the rate of gas diffusion within the adsorbent pores impacts the required size (and therefore cost) of the adsorbent column or membrane. Here, we investigate the diffusion of CO within the pores of Zn(dobpdc) (dobpdc = 4,4'-dioxidobiphenyl-3,3'-dicarboxylate) using pulsed field gradient (PFG) nuclear magnetic resonance (NMR) spectroscopy and molecular dynamics (MD) simulations. The residual chemical shift anisotropy for pore-confined CO allows PFG NMR measurements of self-diffusion in different crystallographic directions, and our analysis of the entire NMR line shape as a function of the applied field gradient provides a precise determination of the self-diffusion coefficients. In addition to observing CO diffusion through the channels parallel to the crystallographic c axis (self-diffusion coefficient D = (5.8 ± 0.1) × 10 m s at a pressure of 625 mbar CO), we unexpectedly find that CO is also able to diffuse between the hexagonal channels in the crystallographic ab plane (D = (1.9 ± 0.2) × 10 m s), despite the walls of these channels appearing impermeable by single-crystal X-ray crystallography and flexible lattice MD simulations. Observation of such unexpected diffusion in the ab plane suggests the presence of defects that enable effective multidimensional CO transport in a metal-organic framework with nominally one-dimensional porosity.
Topics: Anisotropy; Biphenyl Compounds; Carbon Dioxide; Dicarboxylic Acids; Diffusion; Metal-Organic Frameworks; Zinc
PubMed: 29300483
DOI: 10.1021/jacs.7b09453 -
Journal of Neuroscience Methods Jan 2021Diffusion encoding along multiple spatial directions per signal acquisition can be described in terms of a b-tensor. The benefit of tensor-valued diffusion encoding is... (Review)
Review
Diffusion encoding along multiple spatial directions per signal acquisition can be described in terms of a b-tensor. The benefit of tensor-valued diffusion encoding is that it unlocks the 'shape of the b-tensor' as a new encoding dimension. By modulating the b-tensor shape, we can control the sensitivity to microscopic diffusion anisotropy which can be used as a contrast mechanism; a feature that is inaccessible by conventional diffusion encoding. Since imaging methods based on tensor-valued diffusion encoding are finding an increasing number of applications we are prompted to highlight the challenge of designing the optimal gradient waveforms for any given application. In this review, we first establish the basic design objectives in creating field gradient waveforms for tensor-valued diffusion MRI. We also survey additional design considerations related to limitations imposed by hardware and physiology, potential confounding effects that cannot be captured by the b-tensor, and artifacts related to the diffusion encoding waveform. Throughout, we discuss the expected compromises and tradeoffs with an aim to establish a more complete understanding of gradient waveform design and its impact on accurate measurements and interpretations of data.
Topics: Anisotropy; Artifacts; Diffusion; Diffusion Magnetic Resonance Imaging; Diffusion Tensor Imaging
PubMed: 33242529
DOI: 10.1016/j.jneumeth.2020.109007 -
Magnetic Resonance in Medicine Dec 1996Indices of diffusion anisotropy calculated from diffusion coefficients acquired in two or three perpendicular directions are rotationally variant. In living monkey...
Indices of diffusion anisotropy calculated from diffusion coefficients acquired in two or three perpendicular directions are rotationally variant. In living monkey brain, these indices severely underestimate the degree of diffusion anisotropy. New indices calculated from the entire diffusion tensor are rotationally invariant (RI). They show that anisotropy is highly variable in different white matter regions depending on the degree of coherence of fiber tract directions. In structures with a regular, parallel fiber arrangement, water diffusivity in the direction parallel to the fibers (Dparallel approximately 1400-1800 x 10(-6) mm2/s) is almost 10 times higher than the average diffusivity in directions perpendicular to them (D + D)/2 [corrected] approximately 150-300 x 10(-6) mm2/s), and is almost three times higher than previously reported. In structures where the fiber pattern is less coherent (e.g., where fiber bundles merge), diffusion anisotropy is significantly reduced. However, RI anisotropy indices are still susceptible to noise contamination. Monte Carlo simulations show that these indices are statistically biased, particularly those requiring sorting of the eigenvalues of the diffusion tensor based on their magnitude. A new intervoxel anisotropy index is proposed that locally averages inner products between diffusion tensors in neighboring voxels. This "lattice" RI index has an acceptably low error variance and is less susceptible to bias than any other RI anisotropy index proposed to date.
Topics: Animals; Anisotropy; Brain; Diffusion; Haplorhini; Magnetic Resonance Imaging; Monte Carlo Method; Water
PubMed: 8946355
DOI: 10.1002/mrm.1910360612 -
Magnetic Resonance in Medicine Jun 2001The diffusion in voxels with multidirectional fibers can be quite complicated and not necessarily well characterized by the standard diffusion tensor model. High angular...
The diffusion in voxels with multidirectional fibers can be quite complicated and not necessarily well characterized by the standard diffusion tensor model. High angular resolution diffusion-weighted acquisitions have recently been proposed as a method to investigate such voxels, but the reconstruction methods proposed require sophisticated estimation schemes. We present here a simple algorithm for the identification of diffusion anisotropy based upon the variance of the estimated apparent diffusion coefficient (ADC) as a function of measurement direction. The rationale for this method is discussed, and results in normal human subjects acquired with a novel diffusion-weighted stimulated-echo spiral acquisition are presented which distinguish areas of anisotropy that are not apparent in the relative anisotropy maps derived from the standard diffusion tensor model. Published 2001 Wiley-Liss, Inc.
Topics: Algorithms; Anisotropy; Brain; Diffusion; Humans; Image Enhancement; Image Processing, Computer-Assisted; Magnetic Resonance Imaging; Reference Values
PubMed: 11378869
DOI: 10.1002/mrm.1125 -
Journal of Magnetic Resonance Imaging :... Mar 2008To develop a reliable technique for diffusion imaging of the human spinal cord at 1.5 Tesla and to assess potential differences in diffusion anisotropy in...
PURPOSE
To develop a reliable technique for diffusion imaging of the human spinal cord at 1.5 Tesla and to assess potential differences in diffusion anisotropy in cross-sectional images.
MATERIALS AND METHODS
A single-shot echo-planar imaging sequence with double spin-echo diffusion preparation was optimized regarding cerebrospinal fluid artifacts, effective resolution, and contrast-to-noise ratios. Eleven healthy volunteers participated in the study for quantitative characterization of diffusion anisotropy in white matter (WM) and gray matter (GM) by means of two diffusion encoding schemes: octahedral-six-directions for fractional anisotropy (FA) evaluation and orthogonal-three-directions for anisotropy index (AI) calculation.
RESULTS
Pulse-trigger gated sequences with optimal matrix size (read x phase = 64 x 32) and b-value (700 s/mm(2)) allowed the acquisition of high-resolved images (voxel size = 0.9 x 0.9 x 5.0 mm(3)). The GM butterfly shape was recognizable in both AI and FA maps. Both encoding schemes yielded high diffusion anisotropy in dorsal WM (FA = 0.79 +/- 0.07; AI = 0.39 +/- 0.04). Lateral WM showed slightly lower anisotropy (FA = 0.69 +/- 0.08; AI = 0.35 +/- 0.03) than dorsal WM. Clearly smaller anisotropy was found in regions containing GM (FA = 0.45 +/- 0.06; AI = 0.21 +/- 0.05).
CONCLUSION
Diffusion anisotropy data of the spinal cord can be obtained in a clinical setting. Its application seems promising for the assessment of neurological disorders.
Topics: Adult; Anisotropy; Artifacts; Cerebrospinal Fluid; Diffusion; Echo-Planar Imaging; Female; Humans; Male; Middle Aged; Spinal Cord; Water
PubMed: 18224672
DOI: 10.1002/jmri.21252