Selective excitation of myelin water using inversion-recovery-based preparations

In Vivo Myelin Water Quantification Using Diffusion-Relaxation Correlation MRI: A Comparison of 1D and 2D Methods

Multidimensional Magnetic Resonance Imaging (MRI) is a versatile tool for microstructure mapping. We use a diffusion weighted inversion recovery spin echo (DW-IR-SE) sequence with spiral readouts at ultra-strong gradients to acquire a rich diffusion-relaxation data set with sensitivity to myelin water. We reconstruct 1D and 2D spectra with a two-step convex optimization approach and investigate a variety of multidimensional MRI methods, including 1D multi-component relaxometry, 1D multi-component diffusometry, 2D relaxation correlation imaging, and 2D diffusion-relaxation correlation spectroscopic imaging (DR-CSI), in terms of their potential to quantify tissue microstructure, including the myelin water fraction (MWF). We observe a distinct spectral peak that we attribute to myelin water in multi-component T1 relaxometry, T1-T2 correlation, T1-D correlation, and T2-D correlation imaging. Due to lower achievable echo times compared to diffusometry, MWF maps from relaxometry have higher quality. Whilst 1D multi-component T1 data allows much faster myelin mapping, 2D approaches could offer unique insights into tissue microstructure and especially myelin diffusion.

Quantifying myelin in crossing fibers using diffusion-prepared phase imaging: Theory and simulations

PURPOSE

Myelin has long been the target of neuroimaging research. However, most available techniques can only provide a voxel-averaged estimate of myelin content. In the human brain, white matter fiber pathways connecting different brain areas and carrying different functions often cross each other in the same voxel. A measure that can differentiate the degree of myelination of crossing fibers would provide a more specific marker of myelination.

THEORY AND METHODS

One MRI signal property that is sensitive to myelin is the phase accumulation. This sensitivity is used by measuring the phase accumulation of the signal remaining after diffusion-weighting, which is called diffusion-prepared phase imaging (DIPPI). Including diffusion-weighting before estimating the phase accumulation has two distinct advantages for estimating the degree of myelination: (1) It increases the relative contribution of intra-axonal water, whose phase is related linearly to the thickness of the surrounding myelin (in particular the log g-ratio); and (2) it gives directional information, which can be used to distinguish between crossing fibers. Here the DIPPI sequence is described, an approach is proposed to estimate the log g-ratio, and simulations are used and DIPPI data acquired in an isotropic phantom to quantify other sources of phase accumulation.

RESULTS

The expected bias is estimated in the log g-ratio for reasonable in vivo acquisition parameters caused by eddy currents (~4%-10%), remaining extra-axonal signal (~15%), and gradients in the bulk off-resonance field (<10% for most of the brain).

CONCLUSION

This new sequence may provide a g-ratio estimate per fiber population crossing within a voxel.

Deuterium double quantum-filtered NMR studies of peripheral and optic nerves

OBJECTIVE

Characterization of the nerve components by deuterium double quantum-filtered magnetization transfer (DQF-MT) NMR.

METHODS

Nerves were equilibrated in deuterated saline and ²H single-pulse and ²H DQF-MT NMR spectra were measured, enabling the separation of the different water compartments, according to their quadrupolar splittings.

RESULTS

Rat sciatic and brachial nerves and porcine optic nerve immersed in deuterated saline yielded ²H DQF spectra composed of three pairs of quadrupolar-split signals assigned to the water in the collagenous compartments and the myelin bilayer and one narrow signal assigned to the axonal water. Stretching of the nerves, application of osmotic stress and incubation in collagenase did not affect the quadrupolar splitting of the myelin water. The signals of myelin and axonal water were shown to decay during Wallerian degeneration and to rise during maturation. The chemical exchange between the myelin and the intra-axonal water was measured for optic nerve during maturation. The quadrupolar splitting of the signal of myelin water was not sensitive to its orientation relative to the magnetic field. This resembles liquid crystalline behavior, but leaves its mechanism open for interpretation.

CONCLUSIONS

²H DQF-MT NMR characterizes the different components of nerves, the water exchange between them and their changes during processes such as nerve maturation and Wallerian degeneration.

Whole-Brain Imaging of Subvoxel T1-Diffusion Correlation Spectra in Human Subjects

T1 relaxation and water mobility generate eloquent MRI tissue contrasts with great diagnostic value in many neuroradiological applications. However, conventional methods do not adequately quantify the microscopic heterogeneity of these important biophysical properties within a voxel, and therefore have limited biological specificity. We describe a new correlation spectroscopic (CS) MRI method for measuring how T1 and mean diffusivity (MD) co-vary in microscopic tissue environments. We develop a clinical pulse sequence that combines inversion recovery (IR) with single-shot isotropic diffusion encoding (IDE) to efficiently acquire whole-brain MRIs with a wide range of joint T1-MD weightings. Unlike conventional diffusion encoding, the IDE preparation ensures that all subvoxel water pools are weighted by their MDs regardless of the sizes, shapes, and orientations of their corresponding microscopic diffusion tensors. Accordingly, IR-IDE measurements are well-suited for model-free, quantitative spectroscopic analysis of microscopic water pools. Using numerical simulations, phantom experiments, and data from healthy volunteers we demonstrate how IR-IDE MRIs can be processed to reconstruct maps of two-dimensional joint probability density functions, i.e., correlation spectra, of subvoxel T1-MD values. In vivo T1-MD spectra show distinct cerebrospinal fluid and parenchymal tissue components specific to white matter, cortical gray matter, basal ganglia, and myelinated fiber pathways, suggesting the potential for improved biological specificity. The one-dimensional marginal distributions derived from the T1-MD correlation spectra agree well with results from other relaxation spectroscopic and quantitative MRI studies, validating the T1-MD contrast encoding and the spectral reconstruction. Mapping subvoxel T1-diffusion correlations in patient populations may provide a more nuanced, comprehensive, sensitive, and specific neuroradiological assessment of the non-specific changes seen on fluid-attenuated inversion recovery (FLAIR) and diffusion-weighted MRIs (DWIs) in cancer, ischemic stroke, or brain injury.

Multidimensional correlation MRI

Multidimensional correlation spectroscopy is emerging as a novel MRI modality that is well suited for microstructure and microdynamic imaging studies, especially of biological specimens. Conventional MRI methods only provide voxel-averaged and mostly macroscopically averaged information; these methods cannot disentangle intra-voxel heterogeneity on the basis of both water mobility and local chemical interactions. By correlating multiple MR contrast mechanisms and processing the data in an integrated manner, correlation spectroscopy is able to resolve the distribution of water populations according to their chemical and physical interactions with the environment. The use of a non-parametric, phenomenological representation of the multidimensional MR signal makes no assumptions about tissue structure, thereby allowing the study of microscopic structure and composition of complex heterogeneous biological systems. However, until recently, vast data requirements have confined these types of measurement to non-localized NMR applications and prevented them from being widely and successfully used in conjunction with imaging. Recent groundbreaking advancements have allowed this powerful NMR methodology to be migrated to MRI, initiating its emergence as a promising imaging approach. This review is not intended to cover the entire field of multidimensional MR; instead, it focuses on pioneering imaging applications and the challenges involved. In addition, the background and motivation that have led to multidimensional correlation MR development are discussed, along with the basic underlying mathematical concepts. The goal of the present work is to provide the reader with a fundamental understanding of the techniques developed and their potential benefits, and to provide guidance to help refine future applications of this technology.

So You Want to Image Myelin Using MRI: An Overview and Practical Guide for Myelin Water Imaging

Myelin water imaging (MWI) is an MRI imaging biomarker for myelin. This method can generate an in vivo whole-brain myelin water fraction map in approximately 10 minutes. It has been applied in various applications including neurodegenerative disease, neurodevelopmental, and neuroplasticity studies. In this review we start with a brief introduction of myelin biology and discuss the contributions of myelin in conventional MRI contrasts. Then the MRI properties of myelin water and four different MWI methods, which are categorized as T₂ -, T₂ *-, T₁ -, and steady-state-based MWI, are summarized. After that, we cover more practical issues such as availability, interpretation, and validation of these methods. To illustrate the utility of MWI as a clinical research tool, MWI studies for two diseases, multiple sclerosis and neuromyelitis optica, are introduced. Additional topics about imaging myelin in gray matter and non-MWI methods for myelin imaging are also included. Although technical and physiological limitations exist, MWI is a potent surrogate biomarker of myelin that carries valuable and useful information of myelin. Evidence Level: 5 Technical Efficacy: 1 J. MAGN. RESON. IMAGING 2021;53:360-373.

Myelin volume fraction imaging with MRI

MRI is a valuable tool to assess myelin during development and demyelinating disease processes. While multiexponential T2 and quantitative magnetization transfer measures correlate with myelin content, neither provides the total myelin volume fraction. In many cases correlative measures are adequate; but to assess microstructure of myelin, (e.g. calculate the g-ratio using MRI), an accurate measure of myelin volume fraction is imperative. Using a volumetric model of white matter, we relate MRI measures of myelin to absolute measures of myelin volume fraction and compare them to quantitative histology. We assess our approach in control mice along with two models of hypomyelination and one model of hypermyelination and find strong agreement between MRI and histology amongst models. This work investigates the sensitivities of MRI myelin measures to changes in axon geometry and displays promise for estimating g-ratio from MRI.

Inferring brain tissue composition and microstructure via MR relaxometry

MRI relaxometry is sensitive to a variety of tissue characteristics in a complex manner, which makes it both attractive and challenging for characterizing tissue. This article reviews the most common water proton relaxometry measures, T₁, T₂, and T₂^*, and reports on their development and current potential to probe the composition and microstructure of brain tissue. The development of these relaxometry measures is challenged by the need for suitably accurate tissue models, as well as robust acquisition and analysis methodologies. MRI relaxometry has been established as a tool for characterizing neural tissue, particular with respect to myelination, and the potential for further development exists.

Efficient 2D MRI relaxometry using compressed sensing

Potential applications of 2D relaxation spectrum NMR and MRI to characterize complex water dynamics (e.g., compartmental exchange) in biology and other disciplines have increased in recent years. However, the large amount of data and long MR acquisition times required for conventional 2D MR relaxometry limits its applicability for in vivo preclinical and clinical MRI. We present a new MR pipeline for 2D relaxometry that incorporates compressed sensing (CS) as a means to vastly reduce the amount of 2D relaxation data needed for material and tissue characterization without compromising data quality. Unlike the conventional CS reconstruction in the Fourier space (k-space), the proposed CS algorithm is directly applied onto the Laplace space (the joint 2D relaxation data) without compressing k-space to reduce the amount of data required for 2D relaxation spectra. This framework is validated using synthetic data, with NMR data acquired in a well-characterized urea/water phantom, and on fixed porcine spinal cord tissue. The quality of the CS-reconstructed spectra was comparable to that of the conventional 2D relaxation spectra, as assessed using global correlation, local contrast between peaks, peak amplitude and relaxation parameters, etc. This result brings this important type of contrast closer to being realized in preclinical, clinical, and other applications.

The microstructural correlates of T1 in white matter

PURPOSE

Several studies have shown strong correlations between myelin content and T1 within the brain, and have even suggested that T1 can be used to estimate myelin content. However, other micro-anatomical features such as compartment size are known to affect longitudinal relaxation rates, similar to compartment size effects in porous media.

METHODS

T1 measurements were compared with measured or otherwise published axon size measurements in white matter tracts of the rat spinal cord, rat brain, and human brain.

RESULTS

In both ex vivo and in vivo studies, correlations were present between the relaxation rate 1/T1 and axon size across regions of rat spinal cord with nearly equal myelin content.

CONCLUSION

While myelination is likely the dominant determinant of T1 in white matter, variations in white matter microstructure, independent of myelin volume fraction, may also be reflected in T1 differences between regions or subjects.

Solving 2D Fredholm Integral from Incomplete Measurements Using Compressive Sensing

We present an algorithm to solve the two-dimensional Fredholm integral of the first kind with tensor product structure from a limited number of measurements, with the goal of using this method to speed up nuclear magnetic resonance spectroscopy. This is done by incorporating compressive sensing-type arguments to fill in missing measurements, using a priori knowledge of the structure of the data. In the first step we recover a compressed data matrix from measurements that form a tight frame, and establish that these measurements satisfy the restricted isometry property. Recovery can be done from as few as 10% of the total measurements. In the second and third steps, we solve the zeroth-order regularization minimization problem using the Venkataramanan-Song-Hürlimann algorithm. We demonstrate the performance of this algorithm on simulated data and show that our approach is a realistic approach to speeding up the data acquisition.

Relaxation time mapping in multiple sclerosis

Several relaxation mapping techniques have been proposed to quantitatively assess disease-related brain tissue changes in multiple sclerosis. Newer developments also account for the distribution of hydrogen protons in different tissue compartments, and therefore provide markers for myelin and macromolecular content. This article will cover the broad spectrum of the pulse sequences and analysis techniques related to this topic that are currently available. Various technical and practical limitations linked with specific approaches will be discussed. These include acquisition time, accuracy and precision, radiofrequency absorption and limited coverage of the brain. Finally, the application of these techniques in the context of multiple sclerosis will be reviewed.

Compartment-specific enhancement of white matter and nerve ex vivo using chromium

Chromium--Cr(VI) in the form of potassium dichromate--has been shown to specifically enhance white matter signal. The proposed mechanism for this enhancement is reduction of diamagnetic Cr(VI) to paramagnetic chromium species by oxidizable myelin lipids. The purpose of the study herein was to better understand the microanatomical basis of this enhancement (i.e., the relative enhancement of myelin, intra-axonal, and extra-axonal water). Toward this end, integrated T(1)-T(2) measurements were performed in potassium dichromate loaded (hereafter referred to as chromated) rat brains, rat optic nerve samples, and frog sciatic nerve samples ex vivo. In control optic nerve and white matter, two T(1)-T(2) components were resolved, representing myelin and nonmyelin water (intra- and extra-axonal water). Following chromation, three T(1)-T(2) components were resolved in these same tissues. Results from similar measurements in sciatic nerve-all three components are resolvable in control and chromated samples-and quantitative histologic analysis suggest that this additional T(1)-T(2) component is due to a splitting of the nonmyelin water component into intra- and extra-axonal water components. This compartment-specific enhancement may provide unique contrast for MR histology, as well as allow one to probe the compartmental basis of various contrast mechanisms in neural tissue.

Myelin water weighted diffusion tensor imaging

In this study we describe our development and implementation of a magnetization transfer (MT) prepared stimulated-echo diffusion tensor imaging (DTI) technique that can be made sensitive to the microanatomy of myelin tissue. The short echo time (TE) enabled by the stimulated-echo acquisition preserves significant signal from the short T(2) component (myelin water), and the MT preparation further provides differentiating sensitization to this signal. It was found that this combined strategy could provide sufficient sensitivity in our first attempt to image myelin microstructure. Compared to the diffusion tensor derived from the conventional DTI technique, the myelin water weighted (MWW) tensor has the same principal diffusion direction but exhibits a significant increase in fractional anisotropy (FA), which is mainly due to a decrease in radial diffusivity. These findings are consistent with the microstructural organization of the myelin sheaths that wrap around the axons in the white matter and therefore hinder radial diffusion. Given that many white matter diseases (e.g. multiple sclerosis) begin with a degradation of myelin microanatomy but not a loss of myelin content (e.g. loosening of the myelin sheaths), our newly implemented MWW DTI has the potential to lead to improved assessment of myelin pathology and early detection of demyelination.

Development, simulation, and validation of NMR relaxation-based exchange measurements

Two-dimensional (2D) nuclear magnetic resonance correlation experiments have recently been proposed as a means for studying exchange in porous media. Most notable of these is the T(2)-T(2) relaxation exchange spectroscopy (REXSY) experiment. Unfortunately, quantifying exchange with this method requires a relatively long, three-dimensional acquisition. To reduce acquisition times, novel 2D methods for quantifying exchange were developed. For each method, model equations were derived (for an arbitrary N-pool system), tested via simulation studies, and validated via experimental studies in an aqueous urea model system. Results indicate that the novel methods outperform REXSY-in terms of uncertainty per unit time for the fitted exchange rate-for certain model systems. The relative merits of each method are discussed in the text.

Diffusion of myelin water

We studied compartmentally specific characteristics of water diffusion in excised frog sciatic nerve by combining T1 or T2 selective acquisitions with pulse-gradient spin-echo (PGSE) diffusion weighting, with the specific objective of characterizing myelin water diffusion. Combining a PGSE with a Carr-Purcell-Meiboom-Gill (CPMG) acquisition provided apparent diffusion coefficients (ADCs) for each of the three T2 components found in nerve, including the short-lived component believed to be derived from myelin water. Double-inversion-recovery (DIR) preparation provided an alternate means of discriminating myelin water, and in combination with PGSE provided somewhat different measures of ADC. The DIR measures yielded myelin water ADCs of 0.37 microm2/ms (parallel to nerve) and 0.13 microm2/ms (perpendicular to nerve). These ADC estimates were postulated to be more accurate than those based on T2 discrimination, although the difference between the two findings is not clear.