q-Space imaging of the brain

Advanced Diffusion of the Pediatric Brain and Spine

This article discusses new diffusion-weighted imaging (DWI) sequences, diffusion tensor imaging (DTI), and fiber tractography (FT), as well as more advanced diffusion imaging in pediatric brain and spine. Underlying disorder and pathophysiology causing diffusion abnormalities are discussed. Multishot echo planar imaging (EPI) DWI and non-EPI DWI provide higher spatial resolution with less susceptibility artifact and distortion, which are replacing conventional single-shot EPI DWI. DTI and FT have established clinical significance in pediatric brain and spine. This article discusses advanced diffusion imaging, including diffusion kurtosis imaging, neurite orientation dispersion and density imaging, diffusion spectrum imaging, intravoxel incoherent motion, and oscillating-gradient spin-echo.

Recent Advances in Parameter Inference for Diffusion MRI Signal Models

In this paper, fundamentals and recent progress for obtaining biological features quantitatively by using diffusion MRI are reviewed. First, a brief description of diffusion MRI history, application, and development was presented. Then, well-known parametric models including diffusion tensor imaging (DTI), diffusional kurtosis imaging (DKI), and neurite orientation dispersion diffusion imaging (NODDI) are introduced with several classifications in various viewpoints with other modeling schemes. In addition, this review covers mathematical generalization and examples of methodologies for the model parameter inference from conventional fitting to recent machine learning approaches, which is called Q-space learning (QSL). Finally, future perspectives on diffusion MRI parameter inference are discussed with the aspects of imaging modeling and simulation.

The sensitivity of diffusion MRI to microstructural properties and experimental factors

Diffusion MRI is a non-invasive technique to study brain microstructure. Differences in the microstructural properties of tissue, including size and anisotropy, can be represented in the signal if the appropriate method of acquisition is used. However, to depict the underlying properties, special care must be taken when designing the acquisition protocol as any changes in the procedure might impact on quantitative measurements. This work reviews state-of-the-art methods for studying brain microstructure using diffusion MRI and their sensitivity to microstructural differences and various experimental factors. Microstructural properties of the tissue at a micrometer scale can be linked to the diffusion signal at a millimeter-scale using modeling. In this paper, we first give an introduction to diffusion MRI and different encoding schemes. Then, signal representation-based methods and multi-compartment models are explained briefly. The sensitivity of the diffusion MRI signal to the microstructural components and the effects of curvedness of axonal trajectories on the diffusion signal are reviewed. Factors that impact on the quality (accuracy and precision) of derived metrics are then reviewed, including the impact of random noise, and variations in the acquisition parameters (i.e., number of sampled signals, b-value and number of acquisition shells). Finally, yet importantly, typical approaches to deal with experimental factors are depicted, including unbiased measures and harmonization. We conclude the review with some future directions and recommendations on this topic.

Magnetic Resonance Imaging of the Common Marmoset Head

This study evaluated the changes in the intrinsic magnetic resonance (MR) relaxation parameter values (T1; T2, proton density, magnetisation transfer and apparent diffusion coefficient) of the marmoset head, imaged before and after death. Knowing the absolute values of the MR parameters makes it possible to choose an imaging protocol for optimal structural differentiation. The changes between the ante-mortem and post-mortem MR parameters provide an insight into the changing biophysical microenvironment of the post-mortem brain, and allow some of the changes that occur in pathological conditions to be predicted. Diffusion-weighted MR imaging (MRI) was used to map quantitative apparent diffusion coefficient values, and to investigate diffusional anisotropy along the fibre tracts in pre-mortem and post-mortem brain tissue. A three-dimensional data set of the entire marmoset brain demonstrates the ability of three-dimensional MRI to differentiate internal brain structures. MRI is a non-invasive technique which, in principle, permits the same animal to be re-imaged serially and has the potential to probe in vivo brain structural and biophysical changes over an extended period of time. Serial imaging, where each animal acts as its own control, reduces the number of animals required to detect a significant change by minimising the effects of inter-subject variance. MRI therefore provides important scientific and ethical benefits.

Assessing White Matter Pathology in Early-Stage Parkinson Disease Using Diffusion MRI: A Systematic Review

Structural brain white matter (WM) changes such as axonal caliber, density, myelination, and orientation, along with WM-dependent structural connectivity, may be impacted early in Parkinson disease (PD). Diffusion magnetic resonance imaging (dMRI) has been used extensively to understand such pathological WM changes, and the focus of this systematic review is to understand both the methods utilized and their corresponding results in the context of early-stage PD. Diffusion tensor imaging (DTI) is the most commonly utilized method to probe WM pathological changes. Previous studies have suggested that DTI metrics are sensitive in capturing early disease-associated WM changes in preclinical symptomatic regions such as olfactory regions and the substantia nigra, which is considered to be a hallmark of PD pathology and progression. Postprocessing analytic approaches include region of interest-based analysis, voxel-based analysis, skeletonized approaches, and connectome analysis, each with unique advantages and challenges. While DTI has been used extensively to study WM disorganization in early-stage PD, it has several limitations, including an inability to resolve multiple fiber orientations within each voxel and sensitivity to partial volume effects. Given the subtle changes associated with early-stage PD, these limitations result in inaccuracies that severely impact the reliability of DTI-based metrics as potential biomarkers. To overcome these limitations, advanced dMRI acquisition and analysis methods have been employed, including diffusion kurtosis imaging and q-space diffeomorphic reconstruction. The combination of improved acquisition and analysis in DTI may yield novel and accurate information related to WM-associated changes in early-stage PD. In the current article, we present a systematic and critical review of dMRI studies in early-stage PD, with a focus on recent advances in DTI methodology. Yielding novel metrics, these advanced methods have been shown to detect diffuse WM changes in early-stage PD. These findings support the notion of early axonal damage in PD and suggest that WM pathology may go unrecognized until symptoms appear. Finally, the advantages and disadvantages of different dMRI techniques, analysis methods, and software employed are discussed in the context of PD-related pathology.

Microstructural Alterations in Hippocampal Subfields Mediate Age-Related Memory Decline in Humans

Aging, even in the absence of clear pathology of dementia, is associated with cognitive decline. Neuroimaging, especially diffusion-weighted imaging, has been highly valuable in understanding some of these changes in live humans, non-invasively. Traditional tensor techniques have revealed that the integrity of the fornix and other white matter tracts significantly deteriorates with age, and that this deterioration is highly correlated with worsening cognitive performance. However, traditional tensor techniques are still not specific enough to indict explicit microstructural features that may be responsible for age-related cognitive decline and cannot be used to effectively study gray matter properties. Here, we sought to determine whether recent advances in diffusion-weighted imaging, including Neurite Orientation Dispersion and Density Imaging (NODDI) and Constrained Spherical Deconvolution, would provide more sensitive measures of age-related changes in the microstructure of the medial temporal lobe. We evaluated these measures in a group of young (ages 20-38 years old) and older (ages 59-84 years old) adults and assessed their relationships with performance on tests of cognition. We found that the fiber density (FD) of the fornix and the neurite density index (NDI) of the fornix, hippocampal subfields (DG/CA3, CA1, and subiculum), and parahippocampal cortex, varied as a function of age in a cross-sectional cohort. Moreover, in the fornix, DG/CA3, and CA1, these changes correlated with memory performance on the Rey Auditory Verbal Learning Test (RAVLT), even after regressing out the effect of age, suggesting that they were capturing neurobiological properties directly related to performance in this task. These measures provide more details regarding age-related neurobiological properties. For example, a change in fiber density could mean a reduction in axonal packing density or myelination, and the increase in NDI observed might be explained by changes in dendritic complexity or even sprouting. These results provide a far more comprehensive view than previously determined on the possible system-wide processes that may be occurring because of healthy aging and demonstrate that advanced diffusion-weighted imaging is evolving into a powerful tool to study more than just white matter properties.

Visualization of Myelin for the Diagnosis and Treatment Monitoring of Multiple Sclerosis

Multiple sclerosis (MS) is a demyelinating disease of the central nervous system (CNS) affecting more than two million people worldwide. As the exact etiology of MS remains elusive, the diagnosis of MS is made by referring to the McDonald diagnostic criteria, which utilizes MRI as a tool to identify "demyelinated" MS lesions. In particular, hyperintense lesions on T2-weighted images (T2WI) or so-called "T2-lesions" are considered to represent demyelinated MS lesions. T2WI, however, lacks myelin specificity, and moreover, remyelination could not be depicted by the use of such modality. For the accurate diagnosis and treatment decision-making, or for the future development of remyelination therapeutics, imaging tools to visualize myelin-specific signals are mandatory. In this chapter, the current use and the limitation of imaging modalities in MS diagnosis and treatment will be reviewed, with the introduction of new imaging method, namely q-space Myelin Map (qMM), to be used for visualization of demyelination and remyelination in MS.

Changing the Currently Held Concept of Cerebrospinal Fluid Dynamics Based on Shared Findings of Cerebrospinal Fluid Motion in the Cranial Cavity Using Various Types of Magnetic Resonance Imaging Techniques

The "cerebrospinal fluid (CSF) circulation theory" of CSF flowing unidirectionally and circulating through the ventricles and subarachnoid space in a downward or upward fashion has been widely recognized. In this review, observations of CSF motion using different magnetic resonance imaging (MRI) techniques are described, findings that are shared among these techniques are extracted, and CSF motion, as we currently understand it based on the results from the quantitative analysis of CSF motion, is discussed, along with a discussion of slower water molecule motion in the perivascular, paravascular, and brain parenchyma. Today, a shared consensus regarding CSF motion is being formed, as follows: CSF motion is not a circulatory flow, but a combination of various directions of flow in the ventricles and subarachnoid space, and the acceleration of CSF motion differs depending on the CSF space. It is now necessary to revise the currently held concept that CSF flows unidirectionally. Currently, water molecule motion in the order of centimeters per second can be detected with various MRI techniques. Thus, we need new MRI techniques with high-velocity sensitivity, such as in the order of 10 μm/s, to determine water molecule movement in the vessel wall, paravascular space, and brain parenchyma. In this paper, the authors review the previous and current concepts of CSF motion in the central nervous system using various MRI techniques.

Brain networks and their relevance for stroke rehabilitation

Stroke has long been regarded as focal disease with circumscribed damage leading to neurological deficits. However, advances in methods for assessing the human brain and in statistics have enabled new tools for the examination of the consequences of stroke on brain structure and function. Thereby, it has become evident that stroke has impact on the entire brain and its network properties and can therefore be considered as a network disease. The present review first gives an overview of current methodological opportunities and pitfalls for assessing stroke-induced changes and reorganization in the human brain. We then summarize principles of plasticity after stroke that have emerged from the assessment of networks. Thereby, it is shown that neurological deficits do not only arise from focal tissue damage but also from local and remote changes in white-matter tracts and in neural interactions among wide-spread networks. Similarly, plasticity and clinical improvements are associated with specific compensatory structural and functional patterns of neural network interactions. Innovative treatment approaches have started to target such network patterns to enhance recovery. Network assessments to predict treatment response and to individualize rehabilitation is a promising way to enhance specific treatment effects and overall outcome after stroke.

Imaging brain microstructure with diffusion MRI: practicality and applications

This article gives an overview of microstructure imaging of the brain with diffusion MRI and reviews the state of the art. The microstructure-imaging paradigm aims to estimate and map microscopic properties of tissue using a model that links these properties to the voxel scale MR signal. Imaging techniques of this type are just starting to make the transition from the technical research domain to wide application in biomedical studies. We focus here on the practicalities of both implementing such techniques and using them in applications. Specifically, the article summarizes the relevant aspects of brain microanatomy and the range of diffusion-weighted MR measurements that provide sensitivity to them. It then reviews the evolution of mathematical and computational models that relate the diffusion MR signal to brain tissue microstructure, as well as the expanding areas of application. Next we focus on practicalities of designing a working microstructure imaging technique: model selection, experiment design, parameter estimation, validation, and the pipeline of development of this class of technique. The article concludes with some future perspectives on opportunities in this topic and expectations on how the field will evolve in the short-to-medium term.

Changes of Myelin Organization in Patients with Alzheimer's Disease Shown by q-Space Myelin Map Imaging

Background

Recent studies detected the aberrant myelination of the central nervous system (CNS) in Alzheimer's disease (AD). Here, we compared the change of myelination between patients with AD and controls by a novel magnetic resonance imaging modality, “q-space myelin map (MM) imaging.”

Methods

Twenty patients with AD and 18 healthy subjects underwent MM imaging. We compared the MM metric between the 2 groups and examined the relationships between the metric and the clinical symptoms of AD.

Results

AD patients showed a significant reduction of MM metric in the hippocampus, insula, precuneus, and anterior cingulate regions. There was also a significant negative correlation between the duration of illness and the MM metric in the temporoparietal region.

Conclusion

Our findings suggest that MM imaging could be a clinically proper modality to estimate the myelination changes in AD patients.

Generalized diffusion spectrum magnetic resonance imaging (GDSI) for model-free reconstruction of the ensemble average propagator

Diffusion spectrum MRI (DSI) provides model-free estimation of the diffusion ensemble average propagator (EAP) and orientation distribution function (ODF) but requires the diffusion data to be acquired on a Cartesian q-space grid. Multi-shell diffusion acquisitions are more flexible and more commonly acquired but have, thus far, only been compatible with model-based analysis methods. Here, we propose a generalized DSI (GDSI) framework to recover the EAP from multi-shell diffusion MRI data. The proposed GDSI approach corrects for q-space sampling density non-uniformity using a fast geometrical approach. The EAP is directly calculated in a preferable coordinate system by multiplying the sampling density corrected q-space signals by a discrete Fourier transform matrix, without any need for gridding. The EAP is demonstrated as a way to map diffusion patterns in brain regions such as the thalamus, cortex and brainstem where the tissue microstructure is not as well characterized as in white matter. Scalar metrics such as the zero displacement probability and displacement distances at different fractions of the zero displacement probability were computed from the recovered EAP to characterize the diffusion pattern within each voxel. The probability averaged across directions at a specific displacement distance provides a diffusion property based image contrast that clearly differentiates tissue types. The displacement distance at the first zero crossing of the EAP averaged across directions orthogonal to the primary fiber orientation in the corpus callosum is found to be larger in the body (5.65 ± 0.09 μm) than in the genu (5.55 ± 0.15 μm) and splenium (5.4 ± 0.15 μm) of the corpus callosum, which corresponds well to prior histological studies. The EAP also provides model-free representations of angular structure such as the diffusion ODF, which allows estimation and comparison of fiber orientations from both the model-free and model-based methods on the same multi-shell data. For the model-free methods, detection of crossing fibers is found to be strongly dependent on the maximum b-value and less sensitive compared to the model-based methods. In conclusion, our study provides a generalized DSI approach that allows flexible reconstruction of the diffusion EAP and ODF from multi-shell diffusion data and data acquired with other sampling patterns.

Microstructural imaging of the human brain with a 'super-scanner': 10 key advantages of ultra-strong gradients for diffusion MRI

The key component of a microstructural diffusion MRI 'super-scanner' is a dedicated high-strength gradient system that enables stronger diffusion weightings per unit time compared to conventional gradient designs. This can, in turn, drastically shorten the time needed for diffusion encoding, increase the signal-to-noise ratio, and facilitate measurements at shorter diffusion times. This review, written from the perspective of the UK National Facility for In Vivo MR Imaging of Human Tissue Microstructure, an initiative to establish a shared 300 mT/m-gradient facility amongst the microstructural imaging community, describes ten advantages of ultra-strong gradients for microstructural imaging. Specifically, we will discuss how the increase of the accessible measurement space compared to a lower-gradient systems (in terms of Δ, b-value, and TE) can accelerate developments in the areas of 1) axon diameter distribution mapping; 2) microstructural parameter estimation; 3) mapping micro-vs macroscopic anisotropy features with gradient waveforms beyond a single pair of pulsed-gradients; 4) multi-contrast experiments, e.g. diffusion-relaxometry; 5) tractography and high-resolution imaging in vivo and 6) post mortem; 7) diffusion-weighted spectroscopy of metabolites other than water; 8) tumour characterisation; 9) functional diffusion MRI; and 10) quality enhancement of images acquired on lower-gradient systems. We finally discuss practical barriers in the use of ultra-strong gradients, and provide an outlook on the next generation of 'super-scanners'.

Accessing the long-time limit in diffusion NMR: The case of singlet assisted diffusive diffraction q-space

The latest developments in the field of long-lived spin states are merged with pulsed-field gradient techniques to extend the diffusion time beyond what is currently achievable in standard q-space diffusive-diffraction studies. The method uses nearly-equivalent spin-1/2 pairs that let diffusion times of the order of many minutes to be measured allowing access to the long-time limit in cavities of macroscopic size (millimeters). A pulse sequence suitable to exploit this regime has been developed and validated with the use of numerical simulations and experiments.

Anisotropic diffusion in stretched hydrogels containing erythrocytes: evidence of cell-shape distortion recorded by PGSE NMR spectroscopy

The remarkable flexibility of human red blood cells (RBCs) allows them to assume a range of shapes in normal and disease states. Biochemical mechanisms and energetic requirements associated with changes in RBC geometry are not well understood because of a lack of experimental procedures to fix and study cells in different morphological forms. By incorporating RBCs into stretchable gelatin hydrogels, we created conditions for adjustable elongation of their normal discocytic shape in all orientations. As the RBC-containing gels were stretched or compressed, the changes in the cell morphology were studied by using ¹ H-PGSE-NMR spectroscopy. Measurements of the apparent diffusion coefficient of water along the three orthogonal directions revealed tuneable anisotropy in the environment of the hydrogel samples. Light microscopy was also used for recording the extent to which RBCs were distorted in a stretched gel that had been set around them. Having demonstrated the applicability of NMR diffusometry to detect morphological changes of immobilised cells, we have laid the groundwork for future investigations of controllably distorted RBCs. Specifically, we expect studies of metabolic and biophysical properties of the physically deformed cells, thus inferring the connection between intracellular physico-chemical processes and RBC morphology. Copyright © 2016 John Wiley & Sons, Ltd.

Diffusion MRI of the spinal cord: from structural studies to pathology

Diffusion MRI is extensively used to study brain microarchitecture and pathologies, and water diffusion appears highly anisotropic in the white matter (WM) of the spinal cord (SC). Despite these facts, the use of diffusion MRI to study the SC, which has increased in recent years, is much less common than that in the brain. In the present review, after a brief outline of early studies of diffusion MRI (DWI) and diffusion tensor MRI (DTI) of the SC, we provide a short survey on DTI and on diffusion MRI methods beyond the tensor that have been used to study SC microstructure and pathologies. After introducing the porous view of WM and describing the q-space approach and q-space diffusion MRI (QSI), we describe other methodologies that can be applied to study the SC. Selected applications of the use of DTI, QSI, and other more advanced diffusion MRI methods to study SC microstructure and pathologies are presented, with some emphasis on the use of less conventional diffusion methodologies. Because of length constraints, we concentrate on structural studies and on a few selected pathologies. Examples of the use of diffusion MRI to study dysmyelination, demyelination as in experimental autoimmune encephalomyelitis and multiple sclerosis, amyotrophic lateral sclerosis, and traumatic SC injury are presented. We conclude with a brief summary and a discussion of challenges and future directions for diffusion MRI of the SC. Copyright © 2016 John Wiley & Sons, Ltd.

Diffusion tensor imaging in abdominal organs

Initially, diffusion tensor imaging (DTI) was mainly applied in studies of the human brain to analyse white matter tracts. As DTI is outstanding for the analysis of tissue´s microstructure, the interest in DTI for the assessment of abdominal tissues has increased continuously in recent years. Tissue characteristics of abdominal organs differ substantially from those of the human brain. Further peculiarities such as respiratory motion and heterogenic tissue composition lead to difficult conditions that have to be overcome in DTI measurements. Thus MR measurement parameters have to be adapted for DTI in abdominal organs. This review article provides information on the technical background of DTI with a focus on abdominal imaging, as well as an overview of clinical studies and application of DTI in different abdominal regions. Copyright © 2015 John Wiley & Sons, Ltd.

Application of q-Space Diffusion MRI for the Visualization of White Matter

White matter abnormalities in the CNS have been reported recently in various neurological and psychiatric disorders. Quantitation of non-Gaussianity for water diffusion by q-space diffusional MRI (QSI) renders biological diffusion barriers such as myelin sheaths; however, the time-consuming nature of this method hinders its clinical application. In the current study, we aimed to refine QSI protocols to enable their clinical application and to visualize myelin signals in a clinical setting. For this purpose, animal studies were first performed to optimize the acquisition protocol of a non-Gaussian QSI metric. The heat map of standardized kurtosis values derived from optimal QSI (myelin map) was then created. Histological validation of the myelin map was performed in myelin-deficient mice and in a nonhuman primate by monitoring its variation during demyelination and remyelination after chemical spinal cord injury. The results demonstrated that it was sensitive enough to depict dysmyelination, demyelination, and remyelination in animal models. Finally, its utility in clinical practice was assessed by a pilot clinical study in a selected group of patients with multiple sclerosis (MS). The human myelin map could be obtained within 10 min with a 3 T MR scanner. Use of the myelin map was practical for visualizing white matter and it sensitively detected reappearance of myelin signals after demyelination, possibly reflecting remyelination in MS patients. Our results together suggest that the myelin map, a kurtosis-related heat map obtainable with time-saving QSI, may be a novel and clinically useful means of visualizing myelin in the human CNS.

SIGNIFICANCE STATEMENT

Myelin abnormalities in the CNS have been gaining increasing attention in various neurological and psychiatric diseases. However, appropriate methods with which to monitor CNS myelin in daily clinical practice have been lacking. In the current study, we introduced a novel MRI modality that produces the "myelin map." The myelin map accurately depicted myelin status in mice and nonhuman primates and in a pilot clinical study of multiple sclerosis patients, suggesting that it is useful in detecting possibly remyelinated lesions. A myelin map of the human brain could be obtained in <10 min using a 3 T scanner and it therefore promises to be a powerful tool for researchers and clinicians examining myelin-related diseases.

Correction for Eddy Current-Induced Echo-Shifting Effect in Partial-Fourier Diffusion Tensor Imaging

In most diffusion tensor imaging (DTI) studies, images are acquired with either a partial-Fourier or a parallel partial-Fourier echo-planar imaging (EPI) sequence, in order to shorten the echo time and increase the signal-to-noise ratio (SNR). However, eddy currents induced by the diffusion-sensitizing gradients can often lead to a shift of the echo in k-space, resulting in three distinct types of artifacts in partial-Fourier DTI. Here, we present an improved DTI acquisition and reconstruction scheme, capable of generating high-quality and high-SNR DTI data without eddy current-induced artifacts. This new scheme consists of three components, respectively, addressing the three distinct types of artifacts. First, a k-space energy-anchored DTI sequence is designed to recover eddy current-induced signal loss (i.e., Type 1 artifact). Second, a multischeme partial-Fourier reconstruction is used to eliminate artificial signal elevation (i.e., Type 2 artifact) associated with the conventional partial-Fourier reconstruction. Third, a signal intensity correction is applied to remove artificial signal modulations due to eddy current-induced erroneous T₂^∗-weighting (i.e., Type 3 artifact). These systematic improvements will greatly increase the consistency and accuracy of DTI measurements, expanding the utility of DTI in translational applications where quantitative robustness is much needed.

q-Space diffusion MRI (QSI) of the disease progression in the spinal cords of the Long Evans shaker: diffusion time and apparent anisotropy

q-Space diffusion MRI (QSI) was used to study the spinal cords of Long Evans shaker (les) rats, a model of dysmyelination, and their age-matched controls at different maturation stages. Diffusion was measured parallel and perpendicular to the fibers of the spinal cords of the two groups and at different diffusion times. The results showed that QSI is able to detect the dysmyelination process that occurs in this model in the different stages of the disease. The differences in the diffusion characteristics of the spinal cords of the two groups were found to be larger when the diffusion time was increased from 22 to 100 ms. We found that the radial mean displacement is a much better parameter than the QSI fractional anisotropy (FA) to document the differences between the two groups. We observed that the degree of myelination affects the diffusion characteristics of the tissues, but has a smaller effect on FA. All of the extracted diffusion parameters that are affected by the degree of myelination are affected in a diffusion time-dependent fashion, suggesting that the terms apparent anisotropy, apparent fractional anisotropy and even apparent root-mean-square displacement (rmsD) are more appropriate.

Probing white-matter microstructure with higher-order diffusion tensors and susceptibility tensor MRI

Diffusion MRI has become an invaluable tool for studying white matter microstructure and brain connectivity. The emergence of quantitative susceptibility mapping and susceptibility tensor imaging (STI) has provided another unique tool for assessing the structure of white matter. In the highly ordered white matter structure, diffusion MRI measures hindered water mobility induced by various tissue and cell membranes, while susceptibility sensitizes to the molecular composition and axonal arrangement. Integrating these two methods may produce new insights into the complex physiology of white matter. In this study, we investigated the relationship between diffusion and magnetic susceptibility in the white matter. Experiments were conducted on phantoms and human brains in vivo. Diffusion properties were quantified with the diffusion tensor model and also with the higher order tensor model based on the cumulant expansion. Frequency shift and susceptibility tensor were measured with quantitative susceptibility mapping and susceptibility tensor imaging. These diffusion and susceptibility quantities were compared and correlated in regions of single fiber bundles and regions of multiple fiber orientations. Relationships were established with similarities and differences identified. It is believed that diffusion MRI and susceptibility MRI provide complementary information of the microstructure of white matter. Together, they allow a more complete assessment of healthy and diseased brains.

Accelerated diffusion spectrum imaging in the human brain using compressed sensing

We developed a novel method to accelerate diffusion spectrum imaging using compressed sensing. The method can be applied to either reduce acquisition time of diffusion spectrum imaging acquisition without losing critical information or to improve the resolution in diffusion space without increasing scan time. Unlike parallel imaging, compressed sensing can be applied to reconstruct a sub-Nyquist sampled dataset in domains other than the spatial one. Simulations of fiber crossings in 2D and 3D were performed to systematically evaluate the effect of compressed sensing reconstruction with different types of undersampling patterns (random, gaussian, Poisson disk) and different acceleration factors on radial and axial diffusion information. Experiments in brains of healthy volunteers were performed, where diffusion space was undersampled with different sampling patterns and reconstructed using compressed sensing. Essential information on diffusion properties, such as orientation distribution function, diffusion coefficient, and kurtosis is preserved up to an acceleration factor of R = 4.

Accurate noninvasive measurement of cell size and compartment shape anisotropy in yeast cells using double-pulsed field gradient MR

The accurate characterization of pore morphology is of great interest in a wide range of scientific disciplines. Conventional single-pulsed field gradient (s-PFG) diffusion MR can yield compartmental size and shape only when compartments are coherently ordered using q-space approaches that necessitate strong gradients. However, double-PFG (d-PFG) methodology can provide novel microstructural information even when specimens are characterized by polydispersity in size and shape, and even when anisotropic compartments are randomly oriented. In this study, for the first time, we show that angular d-PFG experiments can be used to accurately measure cellular size and shape anisotropy of fixed yeast cells employing relatively weak gradients. The cell size, as measured by light microscopy, was found to be 5.32 ± 0.83 µm, whereas the results from noninvasive angular d-PFG experiments yielded a cell size of 5.46 ± 0.45 µm. Moreover, the low compartment shape anisotropy of the cells could be inferred from experiments conducted at long mixing times. Finally, similar experiments were conducted in a phantom comprising anisotropic compartments that were randomly oriented, showing that angular d-PFG MR provides novel information on compartment eccentricity that could not be accessed using conventional methods. Angular d-PFG methodology seems to be promising for the accurate estimation of compartment size and compartment shape anisotropy in heterogeneous systems in general, and biological cells and tissues in particular.

Diffusion MR imaging: basic principles

From their origin as simple techniques primarily used for detecting acute cerebral ischemia, diffusion MR imaging techniques have rapidly evolved into a versatile set of tools that provide the only noninvasive means of characterizing brain microstructure and connectivity, becoming a mainstay of both clinical and investigational brain MR imaging. In this article, the basic principles required for understanding diffusion MR imaging techniques are reviewed with clinical neuroradiologists in mind.

Diffusion tensor imaging of cerebral white matter integrity in cognitive aging

In this article we review recent research on diffusion tensor imaging (DTI) of white matter (WM) integrity and the implications for age-related differences in cognition. Neurobiological mechanisms defined from DTI analyses suggest that a primary dimension of age-related decline in WM is a decline in the structural integrity of myelin, particularly in brain regions that myelinate later developmentally. Research integrating behavioral measures with DTI indicates that WM integrity supports the communication among cortical networks, particularly those involving executive function, perceptual speed, and memory (i.e., fluid cognition). In the absence of significant disease, age shares a substantial portion of the variance associated with the relation between WM integrity and fluid cognition. Current data are consistent with one model in which age-related decline in WM integrity contributes to a decreased efficiency of communication among networks for fluid cognitive abilities. Neurocognitive disorders for which older adults are at risk, such as depression, further modulate the relation between WM and cognition, in ways that are not as yet entirely clear. Developments in DTI technology are providing a new insight into both the neurobiological mechanisms of aging WM and the potential contribution of DTI to understanding functional measures of brain activity. This article is part of a Special Issue entitled: Imaging Brain Aging and Neurodegenerative disease.

MR diffusion kurtosis imaging for neural tissue characterization

In conventional diffusion tensor imaging (DTI), water diffusion distribution is described as a 2nd-order three-dimensional (3D) diffusivity tensor. It assumes that diffusion occurs in a free and unrestricted environment with a Gaussian distribution of diffusion displacement, and consequently that diffusion weighted (DW) signal decays with diffusion factor (b-value) monoexponentially. In biological tissue, complex cellular microstructures make water diffusion a highly hindered or restricted process. Non-monoexponential decays are experimentally observed in both white matter and gray matter. As a result, DTI quantitation is b-value dependent and DTI fails to fully utilize the diffusion measurements that are inherent to tissue microstructure. Diffusion kurtosis imaging (DKI) characterizes restricted diffusion and can be readily implemented on most clinical scanners. It provides a higher-order description of water diffusion process by a 2nd-order 3D diffusivity tensor as in conventional DTI together with a 4th-order 3D kurtosis tensor. Because kurtosis is a measure of the deviation of the diffusion displacement profile from a Gaussian distribution, DKI analyses quantify the degree of diffusion restriction or tissue complexity without any biophysical assumption. In this work, the theory of diffusion kurtosis and DKI including the directional kurtosis analysis is revisited. Several recent rodent DKI studies from our group are summarized, and DKI and DTI compared for their efficacy in detecting neural tissue alterations. They demonstrate that DKI offers a more comprehensive approach than DTI in describing the complex water diffusion process in vivo. By estimating both diffusivity and kurtosis, it may provide improved sensitivity and specificity in MR diffusion characterization of neural tissues.

Multiple q-shell diffusion propagator imaging

Many recent high angular resolution diffusion imaging (HARDI) reconstruction techniques have been introduced to infer an orientation distribution function (ODF) of the underlying tissue structure. These methods are more often based on a single-shell (one b-value) acquisition and can only recover angular structure information contained in the ensemble average propagator (EAP) describing the three-dimensional (3D) average diffusion process of water molecules. The EAP can thus provide richer information about complex tissue microstructure properties than the ODF by also considering the radial part of the diffusion signal. In this paper, we present a novel technique for analytical EAP reconstruction from multiple q-shell acquisitions. The solution is based on a Laplace equation by part estimation between the diffusion signal for each shell acquisition. This simplifies greatly the Fourier integral relating diffusion signal and EAP, which leads to an analytical, linear and compact EAP reconstruction. An important part of the paper is dedicated to validate the diffusion signal estimation and EAP reconstruction on real datasets from ex vivo phantoms. We also illustrate multiple q-shell diffusion propagator imaging (mq-DPI) on a real in vivo human brain and perform a qualitative comparison against state-of-the-art diffusion spectrum imaging (DSI) on the same subject. mq-DPI is shown to reconstruct robust EAP from only several different b-value shells and less diffusion measurements than DSI. This opens interesting perspectives for new q-space sampling schemes and tissue microstructure investigation.

In vivo generalized diffusion tensor imaging (GDTI) using higher-order tensors (HOT)

Generalized diffusion tensor imaging (GDTI) using higher-order tensor (HOT) statistics generalizes the technique of diffusion tensor imaging by including the effect of nongaussian diffusion on the signal of MRI. In GDTI-HOT, the effect of nongaussian diffusion is characterized by higher-order tensor statistics (i.e., the cumulant tensors or the moment tensors), such as the covariance matrix (the second-order cumulant tensor), the skewness tensor (the third-order cumulant tensor), and the kurtosis tensor (the fourth-order cumulant tensor). Previously, Monte Carlo simulations have been applied to verify the validity of this technique in reconstructing complicated fiber structures. However, no in vivo implementation of GDTI-HOT has been reported. The primary goal of this study is to establish GDTI-HOT as a feasible in vivo technique for imaging nongaussian diffusion. We show that probability distribution function of the molecular diffusion process can be measured in vivo with GDTI-HOT and be visualized with three-dimensional glyphs. By comparing GDTI-HOT to fiber structures that are revealed by the highest resolution diffusion-weighted imaging (DWI) possible in vivo, we show that the GDTI-HOT can accurately predict multiple fiber orientations within one white matter voxel. Furthermore, through bootstrap analysis we demonstrate that in vivo measurement of HOT elements is reproducible, with a small statistical variation that is similar to that of diffusion tensor imaging.

On high b diffusion imaging in the human brain: ruminations and experimental insights

Interest in the manner in which brain tissue signal decays with b factor in diffusion imaging schemes has grown in recent years following the observation that the decay curves depart from purely monoexponential decay behavior. Regardless of the model or fitting function proposed for characterizing sufficiently sampled decay curves (vide infra), the departure from monoexponentiality spells increased tissue characterization potential. The degree to which this potential can be harnessed to improve specificity, sensitivity and spatial localization of diseases in brain, and other tissues, largely remains to be explored. Furthermore, the degree to which currently popular diffusion tensor imaging methods, including visually impressive white matter fiber "tractography" results, have almost completely ignored the nonmonoexponential nature of the basic signal decay with b factor is worthy of communal introspection. Here we limit our attention to a review of the basic experimental features associated with brain water signal diffusion decay curves as measured over extended b-factor ranges, the simple few parameter fitting functions that have been proposed to characterize these decays and the more involved models, e.g.,"ruminations," which have been proposed to account for the nonmonoexponentiality to date.

About "axial" and "radial" diffusivities

This article presents the potential problems arising from the use of "axial" and "radial" diffusivities, derived from the eigenvalues of the diffusion tensor, and their interpretation in terms of the underlying biophysical properties, such as myelin and axonal density. Simulated and in vivo data are shown. The simulations demonstrate that a change in "radial" diffusivity can cause a fictitious change in "axial" diffusivity and vice versa in voxels characterized by crossing fibers. The in vivo data compare the direction of the principle eigenvector in four different subjects, two healthy and two affected by multiple sclerosis, and show that the angle, alpha, between the principal eigenvectors of corresponding voxels of registered datasets is greater than 45 degrees in areas of low anisotropy, severe pathology, and partial volume. Also, there are areas of white matter pathology where the "radial" diffusivity is 10% greater than that of the corresponding normal tissue and where the direction of the principal eigenvector is altered by more than 45 degrees compared to the healthy case. This should strongly discourage researchers from interpreting changes of the "axial" and "radial" diffusivities on the basis of the underlying tissue structure, unless accompanied by a thorough investigation of their mathematical and geometrical properties in each dataset studied.

Erythrocyte-shape evolution recorded with fast-measurement NMR diffusion-diffraction

PURPOSE

To monitor red blood cell (RBC) shape evolution by (1)H(2)O diffusion-diffraction NMR in time steps comparable to those required for the acquisition of a (31)P NMR spectrum; thus, to correlate RBC mean diameter with ATP concentration after poisoning with NaF.

MATERIALS AND METHODS

Pulsed-field gradient-stimulated echo (PFGSTE) diffusion experiments were recorded on (1)H(2)O in RBC suspensions. Under conditions of restricted diffusion, q-space experiments report on mean RBC diameter. To decrease experiment time, the phase cycling of radiofrequency (RF) pulses was cut to two transients by using unbalanced pairs of gradient pulses. Data processing used a recent digital filter. Differential interference contrast (DIC) light microscopy also recorded shape changes. (31)P NMR spectroscopy gave estimates of mean ATP concentration.

RESULTS

NaF caused RBC-shape evolution from discocytes, through various forms of echinocytes, to spherocytes, over approximately 6 h and approximately 10 h at 37 degrees C and 25 degrees C, respectively. ATP declined to approximately 0.5 its normal concentration before the first stage of discocyte transformation; the concentration was 0.0 after approximately 1.5 h and 3.0 h, respectively, at the two temperatures.

CONCLUSION

RBC shape was readily monitored by NMR with a temporal resolution that was useful for correlations with both DIC microscopy and (31)P NMR spectra.

The effect of experimental parameters on the signal decay in double-PGSE experiments: negative diffractions and enhancement of structural information

Double pulsed gradient spin echo (d-PGSE) experiment has been recently suggested for detecting microscopic anisotropy in macroscopically isotropic samples. This sequence is complex and has many variables, including, intra alia, combinations of directions and amplitudes of the pulsed gradients, diffusion times in each of the encoding periods and the mixing time period. The effect of these experimental parameters of the d-PGSE sequence was studied in an array of water filled microcapillaries of micron diameters. We found that negative diffractions occur, as indeed predicted by recently published simulations. We also found differential effects of prolongation of the mixing time between collinear and orthogonal d-PGSE experiments. The d-PGSE experiment in the collinear direction perpendicular to the long axis of the cylinder exhibited a marked dependence on the mixing time, while the orthogonal d-PGSE experiment exhibited no such dependence at all. Interestingly, one of the most important predictions by the simulations was that the d-PGSE sequence could potentially discriminate between compartments of different sizes better than the single PGSE (s-PGSE) and it seems that our experimental results indeed corroborate these predictions.

Three-dimensional water diffusion in impermeable cylindrical tubes: theory versus experiments

Characterizing diffusion of gases and liquids within pores is important in understanding numerous transport processes and affects a wide range of practical applications. Previous measurements of the pulsed gradient stimulated echo (PGSTE) signal attenuation, E(q), of water within nerves and impermeable cylindrical microcapillary tubes showed it to be exquisitely sensitive to the orientation of the applied wave vector, q, with respect to the tube axis in the high-q regime. Here, we provide a simple three-dimensional model to explain this angular dependence by decomposing the average propagator, which describes the net displacement of water molecules, into components parallel and perpendicular to the tube wall, in which axial diffusion is free and radial diffusion is restricted. The model faithfully predicts the experimental data, not only the observed diffraction peaks in E(q) when the diffusion gradients are approximately normal to the tube wall, but their sudden disappearance when the gradient orientation possesses a small axial component. The model also successfully predicts the dependence of E(q) on gradient pulse duration and on gradient strength as well as tube inner diameter. To account for the deviation from the narrow pulse approximation in the PGSTE sequence, we use Callaghan's matrix operator framework, which this study validates experimentally for the first time. We also show how to combine average propagators derived for classical one-dimensional and two-dimensional models of restricted diffusion (e.g. between plates, within cylinders) to construct composite three-dimensional models of diffusion in complex media containing pores (e.g. rectangular prisms and/or capped cylinders) having a distribution of orientations, sizes, and aspect ratios. This three-dimensional modeling framework should aid in describing diffusion in numerous biological systems and in a myriad of materials sciences applications.

The effect of the diffusion time and pulse gradient duration ratio on the diffraction pattern and the structural information estimated from q-space diffusion MR: experiments and simulations

q-Space diffusion MRI (QSI) provides a means of obtaining microstructural information about porous materials and neuronal tissues from diffusion data. However, the accuracy of this structural information depends on experimental parameters used to collect the MR data. q-Space diffusion MR performed on clinical scanners is generally collected with relatively long diffusion gradient pulses, in which the gradient pulse duration, delta, is comparable to the diffusion time, Delta. In this study, we used phantoms, consisting of ensembles of microtubes, and mathematical models to assess the effect of the ratio of the diffusion time and the duration of the diffusion pulse gradient, i.e., Delta/delta, on the MR signal attenuation vs. q, and on the measured structural information extracted therefrom. We found that for Delta/delta approximately 1, the diffraction pattern obtained from q-space MR data are shallower than when the short gradient pulse (SGP) approximation is satisfied. For long delta the estimated compartment size is, as expected, smaller than the real size. Interestingly, for Delta/delta approximately 1 the diffraction peaks are shifted to even higher q-values, even when delta is kept constant, giving the impression that the restricted compartments are even smaller than they are. When phantoms composed of microtubes of different diameters are used, it is more difficult to estimate the diameter distribution in this regime. Excellent agreement is found between the experimental results and simulations that explicitly account for the use of long duration gradient pulses. Using such experimental data and this mathematical framework, one can estimate the true compartment dimensions when long and finite gradient pulses are used even when Delta/delta approximately 1.

Crossing fibers, diffractions and nonhomogeneous magnetic field: correction of artifacts by bipolar gradient pulses

In recent years, diffusion tensor imaging (DTI) and its variants have been used to describe fiber orientations and q-space diffusion MR was proposed as a means to obtain structural information on a micron scale. Therefore, there is an increasing need for complex phantoms with predictable microcharacteristics to challenge different indices extracted from the different diffusion MR techniques used. The present study examines the effect of diffusion pulse sequence on the signal decay and diffraction patterns observed in q-space diffusion MR performed on micron-scale phantoms of different geometries and homogeneities. We evaluated the effect of the pulse gradient stimulated-echo, the longitudinal eddy current delay (LED) and the bipolar LED (BPLED) pulse sequences. Interestingly, in the less homogeneous samples, the expected diffraction patterns were observed only when diffusion was measured with the BPLED sequence. We demonstrated the correction ability of bipolar diffusion gradients and showed that more accurate physical parameters are obtained when such a diffusion gradient scheme is used. These results suggest that bipolar gradient pulses may result in more accurate data if incorporated into conventional diffusion-weighted imaging and DTI.

Evaluation of the accuracy and angular resolution of q-ball imaging

Q-ball imaging (QBI) has been proposed for the mapping of multiple intravoxel fiber structures using the Funk-Radon transform on high angular resolution diffusion images (HARDI). However, the accuracy and the angular resolution of QBI to define fiber orientations and its dependence on diffusion imaging parameters remain unclear. The phantom models, made up of sheets of parallel capillaries filled with water, were designed to evaluate the accuracy and the angular resolution of QBI at different |q| values. With an inner diameter of 20 mum and an outer diameter of 90 mum, the capillaries afforded a restrictive environment compared with the diffusion measurement scale. Further, the angular resolutions of QBI at various |q| value were also quantified on the corpus callosum in the human brain. The full width at half maximum (FWHM) of the main lobe of normalized orientation distribution function (nODF) was calculated and adopted to quantify the angular resolution of QBI. With the phantom model, a higher |q| value resulted in worse accuracy but better angular resolution for QBI. The same trend where a higher |q| value yielded a better angular resolution was also observed in the human study. Upon comparison of QBI with T2WI, QBI with |q|=277 cm(-1) (b=3000 s/mm(2)) was found to be insufficient to differentiate capillaries crossing at 45 degrees . However, when encoding with |q|=320, 358, and 392 cm(-1) (b=4000, 5000, and 6000 s/mm(2)), the deviation angles between the primary ODF and the 45 degrees phantoms were -4.91 degrees +/-2.72 degrees , -1.37 degrees +/-2.32 degrees , and -0.69 degrees +/-1.54 degrees with adequate signal-to-noise ratio (SNR). These results were consistent with the FWHM-nODF, which showed that a |q| value of 320 cm(-1) was the threshold to resolve capillaries intersecting at 45 degrees . Additionally, it was demonstrated in both the phantom model and the human brain that QBI encoding with lower |q| values may result in underestimation of the orientations of the crossing fibers. In conclusion, QBI was found to accurately resolve crossing fiber orientations and was highly dependent on the selected |q| value.

Magnetic resonance in porous media: recent progress

Recent years have seen significant progress in the NMR study of porous media from natural and industrial sources and of cultural significance such as paintings. This paper provides a brief outline of the recent technical development of NMR in this area. These advances are relevant for broad NMR applications in material characterization.

q-Space diffusion of myelin-deficient spinal cords

The apparent water diffusion anisotropy in white matter (WM) of excised spinal cords of myelin-deficient (md) rats and their age-matched controls was studied by high-b-value q-space diffusion MRS and MRI at different diffusion times. Non-monoexponential signal decay was observed at long diffusion times. The mean displacements in the md spinal cords were found to be higher than those of the controls. The apparent anisotropy (AA) of the fast-diffusing component was found to decrease more dramatically with the increase in diffusion time for the md spinal cords as compared with controls, whereas the AA of the slow-diffusing component in the controls was found to increase with the increase in diffusion time while that of the md cords decreased with the increase in diffusion time. When diffusion MRI was performed, similar diffusion anisotropy was extracted for the md and control spinal cords at diffusion times of 22 and 50 ms. Only at a diffusion time of about 200 ms was a significant difference obtained in the AA of the two groups. This originates from the much smaller increase in the mean displacement perpendicular to the fiber direction in the control group vs. the md group when the diffusion time was increased.

High b-value q-space diffusion MRS of nerves: structural information and comparison with histological evidence

High b-value q-space diffusion MRS was used to study the diffusion characteristics of formalin-fixed swine optic and sciatic nerves over a large range of diffusion times (3.7-99.3 ms). The very short diffusion time range was studied with a 1 ms resolution. The displacement distribution profiles obtained were fitted to a bi-Gaussian function, and structural parameters were extracted from the q-space diffusion MRS data. This structural information was correlated with axon sizes obtained by histological examination. It was found that high b-value q-space diffusion MRS can easily distinguish between the two nerve types. The root mean square displacements (rmsds) of both the slow and fast diffusing components of the optic nerves were found to be smaller than those of the sciatic nerves. When the rmsd was plotted against the square root of the diffusion time (t(d)(1/2)), it was found that all four components showed an increase in rmsd; this increase was significantly smaller than expected from the Einstein equation. However, the most restricted component is the slow diffusing component of the optic nerve. This is also the only diffusing component that shows a large change in the slope (i.e. a 'breaking point') of the plot of rmsd as a function of t(d)(1/2). This rmsd is very similar to the mean axon size of these optic nerves determined histologically. Such a change in slope was less apparent for the slow diffusing component of sciatic nerves, which showed a wider distribution of axon size in histological images. The fast diffusing components of both nerve types showed only a small gradual change in the slope of rmsd plotted against t(d)(1/2). These findings are discussed in the context of component assignment, origin of restriction, and relationships between the structural information extracted from q-space diffusion MRS and histological examination.