Anomalous diffusion of brain metabolites evidenced by diffusion-weighted magnetic resonance spectroscopy in vivo

Single-shot diffusion trace spectroscopic imaging using radial echo planar trajectories

PURPOSE

Demonstrate the feasibility and evaluate the performance of single-shot diffusion trace-weighted radial echo planar spectroscopic imaging (Trace DW-REPSI) for quantifying the trace ADC in phantom and in vivo using a 3T clinical scanner.

THEORY AND METHODS

Trace DW-REPSI datasets were acquired in 10 phantom and 10 healthy volunteers, with a maximum b-value of 1601 s/mm2 and diffusion time of 10.75 ms. The self-navigation properties of radial acquisitions were used for corrections of shot-to-shot phase and frequency shift fluctuations of the raw data. In vivo trace ADCs of total NAA (tNAA), total creatine (tCr), and total choline (tCho) extrapolated to pure gray and white matter fractions were compared, as well as trace ADCs estimated in voxels within white or gray matter-dominant regions.

RESULTS

Trace ADCs in phantom show excellent agreement with reported values, and in vivo ADCs agree well with the expected differences between gray and white matter. For tNAA, tCr, and tCho, the trace ADCs extrapolated to pure gray and white matter ranged from 0.18-0.27 and 0.26-0.38 μm2/ms, respectively. In sets of gray and white matter-dominant voxels, the values ranged from 0.21 to 0.27 and 0.24 to 0.31 μm2/ms, respectively. The overestimated trace ADCs from this sequence can be attributed to the short diffusion time.

CONCLUSION

This study presents the first demonstration of the single-shot diffusion trace-weighted spectroscopic imaging sequence using radial echo planar trajectories. The Trace DW-REPSI sequence could provide an estimate of the trace ADC in a much shorter scan time compared to conventional approaches that require three separate measurements.

Single-shot diffusion trace-weighted MR spectroscopy: Comparison with unipolar and bipolar diffusion-weighted point-resolved spectroscopy

This study demonstrates the feasibility and performance of the point-resolved spectroscopy (PRESS)-based, single-shot diffusion trace-weighted sequence in quantifying the trace apparent diffusion coefficient (ADC) in phantom and in vivo using a 3-T MRI/MRS scanner. The single-shot diffusion trace-weighted PRESS sequence was implemented and compared with conventional diffusion-weighted (DW)-PRESS variants using bipolar and unipolar diffusion-sensitizing gradients. Nine phantom datasets were acquired using each sequence, and seven volunteers were scanned in three different brain regions to determine the range and variability of trace ADC values, and to allow a comparison of trace ADCs among the sequences. This sequence results in a comparatively stable range of trace ADC values that are statistically significantly higher than those produced from unipolar and bipolar DW-PRESS sequences. Only total n-acetylaspartate, total creatine, and total choline were reliably estimated in all sequences with Cramér-Rao lower bounds of, at most, 20%. The larger trace ADCs from the single-shot sequences are probably attributable to the shorter diffusion time relative to the other sequences. Overall, this study presents the first demonstration of the single-shot diffusion trace-weighted sequence in a clinical scanner at 3 T. The results show excellent agreement of phantom trace ADCs computed with all sequences, and in vivo ADCs agree well with the expected differences between gray and white matter. The diffusion trace-weighted sequence could provide an estimate of the trace ADC in a shorter scan time (by nearly a factor of 3) compared with conventional DW-PRESS approaches that require three separate orthogonal directions.

Macromolecular background signal and non-Gaussian metabolite diffusion determined in human brain using ultra-high diffusion weighting

Purpose

Definition of a macromolecular MR spectrum based on diffusion properties rather than relaxation time differences and characterization of non‐Gaussian diffusion of brain metabolites with strongly diffusion‐weighted MR spectroscopy.

Methods

Short echo time MRS with strong diffusion‐weighting with b‐values up to 25 ms/μm² at two diffusion times was implemented on a Connectom system and applied in combination with simultaneous spectral and diffusion decay modeling. Motion‐compensation was performed with a combined method based on the simultaneously acquired water and a macromolecular signal.

Results

The motion compensation scheme prevented spurious signal decay reflected in very small apparent diffusion constants for macromolecular signal. Macromolecular background signal patterns were determined using multiple fit strategies. Signal decay corresponding to non‐Gaussian metabolite diffusion was represented by biexponential fit models yielding parameter estimates for human gray matter that are in line with published rodent data. The optimal fit strategies used constraints for the signal decay of metabolites with limited signal contributions to the overall spectrum.

Conclusion

The determined macromolecular spectrum based on diffusion properties deviates from the conventional one derived from longitudinal relaxation time differences calling for further investigation before use as experimental basis spectrum when fitting clinical MR spectra. The biexponential characterization of metabolite signal decay is the basis for investigations into pathologic alterations of microstructure.

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Rat Brain Global Ischemia-Induced Diffusion Changes Revisited: Biophysical Modeling of the Water and NAA MR "Diffusion Signal"

PURPOSE

To assess changes in intracellular diffusion as a mechanism for the reduction in water ADC that accompanies brain injury. Using NAA as a marker of neuronal cytoplasmic diffusion, NAA diffusion was measured before and after global ischemia (immediately postmortem) in the female Sprague-Dawley rat.

METHODS

Diffusion-weighted PRESS spectra, with diffusion encoding in a single direction, were acquired from large voxels of rat brain gray matter in vivo and postischemia employing either pairs of pulsed half-sine-shaped gradients (in vivo and postischemia, b_max  = 19 ms/μm² ) or sinusoidal oscillating gradients (in vivo only) with frequencies of 99.2-250 Hz. A 2D randomly oriented cylinder (neurite) model gave estimates of longitudinal and transverse diffusivities (D_L and D_T , respectively). In this model, D_L represents the "free" diffusivity of NAA, whereas D_T reflects highly restricted diffusion. Using oscillating gradients, the frequency dependence of D_T [D_T (ω)] gave estimates of the cylinder (axon/dendrite) radius.

RESULTS

A 10% decrease in D_L,NAA followed global ischemia, dropping from 0.391 ± 0.012 μm² /ms to 0.350 ± 0.009 μm² /ms. Modeling D_T,NAA (ω) provided an estimate of the neurite radius of 1.0 ± 0.6 μm.

CONCLUSION

Whereas the increase in apparent intraneuronal viscosity suggested by changes in D_L,NAA may contribute to the overall reduction in water ADC associated with brain injury, it is not sufficient to be the sole explanation. Estimates of neurite radius based on D_T (ω) were consistent with literature values.

Mapping complex cell morphology in the grey matter with double diffusion encoding MR: A simulation study

This paper investigates the impact of cell body (namely soma) size and branching of cellular projections on diffusion MR imaging (dMRI) and spectroscopy (dMRS) signals for both standard single diffusion encoding (SDE) and more advanced double diffusion encoding (DDE) measurements using numerical simulations. The aim is to investigate the ability of dMRI/dMRS to characterize the complex morphology of brain cells focusing on these two distinctive features of brain grey matter. To this end, we employ a recently developed computational framework to create three dimensional meshes of neuron-like structures for Monte Carlo simulations, using diffusion coefficients typical of water and brain metabolites. Modelling the cellular structure as realistically connected spherical soma and cylindrical cellular projections, we cover a wide range of combinations of sphere radii and branching order of cellular projections, characteristic of various grey matter cells. We assess the impact of spherical soma size and branching order on the b-value dependence of the SDE signal as well as the time dependence of the mean diffusivity (MD) and mean kurtosis (MK). Moreover, we also assess the impact of spherical soma size and branching order on the angular modulation of DDE signal at different mixing times, together with the mixing time dependence of the apparent microscopic anisotropy (μA), a promising contrast derived from DDE measurements. The SDE results show that spherical soma size has a measurable impact on both the b-value dependence of the SDE signal and the MD and MK diffusion time dependence for both water and metabolites. On the other hand, we show that branching order has little impact on either, especially for water. In contrast, the DDE results show that spherical soma size has a measurable impact on the DDE signal's angular modulation at short mixing times and the branching order of cellular projections significantly impacts the mixing time dependence of the DDE signal's angular modulation as well as of the derived μA, for both water and metabolites. Our results confirm that SDE based techniques may be sensitive to spherical soma size, and most importantly, show for the first time that DDE measurements may be more sensitive to the dendritic tree complexity (as parametrized by the branching order of cellular projections), paving the way for new ways of characterizing grey matter morphology, non-invasively using dMRS and potentially dMRI.

Modeling NO Biotransport in Brain Using a Space-Fractional Reaction-Diffusion Equation

Nitric oxide (NO) is a small gaseous molecule that is involved in some critical biochemical processes in the body such as the regulation of cerebral blood flow and pressure. Infection and inflammatory processes such as those caused by COVID-19 produce a disequilibrium in the NO bioavailability and/or a delay in the interactions of NO with other molecules contributing to the onset and evolution of cardiocerebrovascular diseases. A link between the SARS-CoV-2 virus and NO is introduced. Recent experimental observations of intracellular transport of metabolites in the brain and the NO trapping inside endothelial microparticles (EMPs) suggest the possibility of anomalous diffusion of NO, which may be enhanced by disease processes. A novel space-fractional reaction-diffusion equation to model NO biotransport in the brain is further proposed. The model incorporates the production of NO by synthesis in neurons and by mechanotransduction in the endothelial cells, and the loss of NO due to its reaction with superoxide and interaction with hemoglobin. The anomalous diffusion is modeled using a generalized Fick’s law that involves spatial fractional order derivatives. The predictive ability of the proposed model is investigated through numerical simulations. The implications of the methodology for COVID-19 outlined in the section “Discussion” are purely exploratory.

Cytosolic diffusivity and microscopic anisotropy of N-acetyl aspartate in human white matter with diffusion-weighted MRS at 7 T

Metabolite diffusion measurable in humans in vivo with diffusion-weighted spectroscopy (DW-MRS) provides a window into the intracellular morphology and state of specific cell types. Anisotropic diffusion in white matter is governed by the microscopic properties of the individual cell types and their structural units (axons, soma, dendrites). However, anisotropy is also markedly affected by the macroscopic orientational distribution over the imaging voxel, particularly in DW-MRS, where the dimensions of the volume of interest (VOI) are much larger than those typically used in diffusion-weighted imaging. One way to address the confound of macroscopic structural features is to average the measurements acquired with uniformly distributed gradient directions to mimic a situation where fibers present in the VOI are orientationally uniformly distributed. This situation allows the extraction of relevant microstructural features such as transverse and longitudinal diffusivities within axons and the related microscopic fractional anisotropy. We present human DW-MRS data acquired at 7 T in two different white matter regions, processed and analyzed as described above, and find that intra-axonal diffusion of the neuronal metabolite N-acetyl aspartate is in good correspondence to simple model interpretations, such as multi-Gaussian diffusion from disperse fibers where the transverse diffusivity can be neglected. We also discuss the implications of our approach for current and future applications of DW-MRS for cell-specific measurements.

Current and Emerging MR Methods and Outcome in Rodent Models of Parkinson's Disease: A Review

Parkinson’s disease (PD) is a major neurodegenerative disease characterized by massive degeneration of the dopaminergic neurons in the substantia nigra pars compacta, α-synuclein-containing Lewy bodies, and neuroinflammation. Magnetic resonance (MR) imaging plays a crucial role in the diagnosis and monitoring of disease progression and treatment. A variety of MR methods are available to characterize neurodegeneration and other disease features such as iron accumulation and metabolic changes in animal models of PD. This review aims at giving an overview of how those physiopathological features of PD have been investigated using various MR methods in rodent models. Toxin-based and genetic-based models of PD are first described. MR methods for neurodegeneration evaluation, iron load, and metabolism alterations are then detailed, and the main findings are provided in those models. Ultimately, future directions are suggested for neuroinflammation and neuromelanin evaluations in new animal models.

Compartmental diffusion and microstructural properties of human brain gray and white matter studied with double diffusion encoding magnetic resonance spectroscopy of metabolites and water

Double diffusion encoding (DDE) of the water signal offers a unique ability to separate the effect of microscopic anisotropic diffusion in structural units of tissue from the overall macroscopic orientational distribution of cells. However, the specificity in detected microscopic anisotropy is limited as the signal is averaged over different cell types and across tissue compartments. Performing side-by-side water and metabolite DDE spectroscopic (DDES) experiments provides complementary measures from which intracellular and extracellular microscopic fractional anisotropies (μFA) and diffusivities can be estimated. Metabolites are largely confined to the intracellular space and therefore provide a benchmark for intracellular μFA and diffusivities of specific cell types. By contrast, water DDES measurements allow examination of the separate contributions to water μFA and diffusivity from the intra- and extracellular spaces, by using a wide range of b values to gradually eliminate the extracellular contribution. Here, we aimed to estimate tissue and compartment specific human brain microstructure by combining water and metabolites DDES experiments. We performed our DDES measurements in two brain regions that contain widely different amounts of white matter (WM) and gray matter (GM): parietal white matter (PWM) and occipital gray matter (OGM) in a total of 20 healthy volunteers at 7 Tesla. Metabolite DDES measurements were performed at b = 7199 s/mm², while water DDES measurements were performed with a range of b values from 918 to 7199 s/mm². The experimental framework we employed here resulted in a set of insights pertaining to the morphology of the intracellular and extracellular spaces in both gray and white matter. Results of the metabolite DDES experiments in both PWM and OGM suggest a highly anisotropic intracellular space within neurons and glia, with the possible exception of gray matter glia. The water μFA obtained from the DDES results at high b values in both regions converged with that of the metabolite DDES, suggesting that the signal from the extracellular space is indeed effectively suppressed at the highest b value. The μFA measured in the OGM significantly decreased at lower b values, suggesting a considerably lower anisotropy of the extracellular space in GM compared to WM. In PWM, the water μFA remained high even at the lowest b value, indicating a high degree of organization in the interstitial space in WM. Tortuosity values in the cytoplasm for water and tNAA, obtained with correlation analysis of microscopic parallel diffusivity with respect to GM/WM tissue fraction in the volume of interest, are remarkably similar for both molecules, while exhibiting a clear difference between gray and white matter, suggesting a more crowded cytoplasm and more complex cytomorphology of neuronal cell bodies and dendrites in GM than those found in long-range axons in WM.

Double diffusion encoding and applications for biomedical imaging

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.

Challenges for biophysical modeling of microstructure

The biophysical modeling efforts in diffusion MRI have grown considerably over the past 25 years. In this review, we dwell on the various challenges along the journey of bringing a biophysical model from initial design to clinical implementation, identifying both hurdles that have been already overcome and outstanding issues. First, we describe the critical initial task of selecting which features of tissue microstructure can be estimated using a model and which acquisition protocol needs to be implemented to make the estimation possible. The model performance should necessarily be tested in realistic numerical simulations and in experimental data - adapting the fitting strategy accordingly, and parameter estimates should be validated against complementary techniques, when/if available. Secondly, the model performance and validity should be explored in pathological conditions, and, if appropriate, dedicated models for pathology should be developed. We build on examples from tumors, ischemia and demyelinating diseases. We then discuss the challenges associated with clinical translation and added value. Finally, we single out four major unresolved challenges that are related to: the availability of a microstructural ground truth, the validation of model parameters which cannot be accessed with complementary techniques, the development of a generalized standard model for any brain region and pathology, and the seamless communication between different parties involved in the development and application of biophysical models of diffusion.

Revisiting double diffusion encoding MRS in the mouse brain at 11.7T: Which microstructural features are we sensitive to?

Brain metabolites, such as N-acetylaspartate or myo-inositol, are constantly probing their local cellular environment under the effect of diffusion. Diffusion-weighted NMR spectroscopy therefore presents unparalleled potential to yield cell-type specific microstructural information. Double diffusion encoding (DDE) consists in applying two diffusion blocks, where gradient's direction in the second block is varied during the course of the experiment. Unlike single diffusion encoding, DDE measurements at long mixing time display some angular modulation of the signal amplitude which reflects microscopic anisotropy (μA), while requiring relatively low gradient strength. This angular dependence has been formerly used to quantify cell fiber diameter using a model of isotropically oriented infinite cylinders. However, how additional features of the cell microstructure (such as cell body diameter, fiber length and branching) may also influence the DDE signal has been little explored. Here, we used a cryoprobe as well as state-of-the-art post-processing to perform DDE acquisitions with high accuracy and precision in the mouse brain at 11.7 ​T. We then compared our results to simulated DDE datasets obtained in various 3D cell models in order to pinpoint which features of cell morphology may influence the most the angular dependence of the DDE signal. While the infinite cylinder model poorly fits our experimental data, we show that incorporating branched fiber structure in our model allows more realistic interpretation of the DDE signal. Lastly, data acquired in the short mixing time regime suggest that some sensitivity to cell body diameter might be retrieved, although additional experiments would be required to further support this statement.

Glutamate diffusion in the rat brain in vivo under light and deep anesthesia conditions

PURPOSE

Glutamate (Glu) is the most abundant neurotransmitter in the human central nervous system and glutamatergic neurotransmission has been implicated in many common and severe neuropsychiatric disorders. In vivo MRS techniques have been developed to measure brain Glu concentration to investigate the pathophysiology of various brain disorders. However, it is difficult to interpret Glu signal changes because Glu plays multiple roles in the brain and is found in multiple microenvironments including cytosolic, vesicular, and extracellular.

METHODS

In vivo diffusion-weighted MRS (DW-MRS) with low to very high b-values was performed on the rat prefrontal cortex at 9.4T under both light and deep anesthetic conditions to examine Glu diffusion properties.

RESULTS

Significant alterations in Glu diffusion as well as reduced Glu concentration were observed under deep anesthesia compared with superficial anesthesia in the absence of similar changes in NAA or creatine.

CONCLUSION

The modifications in Glu diffusion under deep anesthesia might reflect changes in Glu microenvironment. The present work shows that Glu DW-MRS could be an important tool to explore Glu physiology with changing levels of neuronal activity and synaptic function.

Diffusion-weighted magnetic resonance spectroscopy enables cell-specific monitoring of astrocyte reactivity in vivo

Reactive astrocytes exhibit hypertrophic morphology and altered metabolism. Deciphering astrocytic status would be of great importance to understand their role and dysregulation in pathologies, but most analytical methods remain highly invasive or destructive. The diffusion of brain metabolites, as non-invasively measured using diffusion-weighted magnetic resonance spectroscopy (DW-MRS) in vivo, depends on the structure of their micro-environment. Here we perform advanced DW-MRS in a mouse model of reactive astrocytes to determine how cellular compartments confining metabolite diffusion are changing. This reveals myo-inositol as a specific intra-astrocytic marker whose diffusion closely reflects astrocytic morphology, enabling non-invasive detection of astrocyte hypertrophy (subsequently confirmed by confocal microscopy ex vivo). Furthermore, we measure massive variations of lactate diffusion properties, suggesting that intracellular lactate is predominantly astrocytic under control conditions, but predominantly neuronal in case of astrocyte reactivity. This indicates massive remodeling of lactate metabolism, as lactate compartmentation is tightly linked to the astrocyte-to-neuron lactate shuttle mechanism.

Apparent diffusion coefficients of the five major metabolites measured in the human brain in vivo at 3T

PURPOSE

To measure the apparent diffusion coefficients (ADC) of five main metabolites in the human brain at 3T with PRESS and STEAM, avoiding measurement biases because of cross-terms. Cross-terms arise from interactions between slice-selection and spoiler gradients in the localized spectroscopy sequence and the diffusion gradients.

METHODS

Diffusion-weighted spectra were acquired from the prefrontal cortex in five healthy subjects using STEAM (echo time [TE]/mixing time [TM]/pulse repetition time [TR] = 21.22/105/3000 ms, b-values = 0 and 3172 s/mm2 ) and PRESS (TE/TR = 54.2/3000 ms, b-values = 0 and 2204 s/mm2 ). Diffusion weighting was applied using bipolar gradients in three orthogonal directions. Post-processed spectra were analyzed with LCModel, and the trace/3 ADC values were calculated.

RESULTS

Comparable trace/3 ADC values (0.14-0.18 µm2 /ms) were obtained for five main metabolites with both methods. These metabolites were quantified with Cramér-Rao lower bounds below 15%.

CONCLUSION

The ADC values of the five main metabolites were successfully measured in the human brain at 3T with eliminated directional dependence. Both STEAM and PRESS can be used to probe the diffusivity of metabolites in normal brain and various pathologies on the clinical scanner with slightly higher precision achieved with STEAM for glutamate and myo-inositol. Magn Reson Med 79:2896-2901, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Decompressive craniectomy protects against hippocampal edema and behavioral deficits at an early stage of a moderately controlled cortical impact brain injury model in adult male rats

A decompressive craniectomy (DC) has been shown to be a life-saving therapeutic treatment for traumatic brain injury (TBI) patients, which also might result in post-operative behavioral dysfunction. However, there is still no definite conclusion about whether the behavioral dysfunction already existed at an early stage after the DC operation or is just a long-term post-operation complication. Therefore, the aim of the present study was to analyze whether DC treatment was beneficial to behavioral function at an early stage post TBI. In this study, we established a controlled cortical impact injury rat model to evaluate the therapeutic effect of DC treatment on behavioral deficits at 1 d, 2 d, 3 d and 7 d after TBI. Our results showed that rats suffered significant behavioral and mood deficits after TBI compared to the control group, while decompressive craniectomy treatment could normalize MMP-9 expression levels and reduce hippocampal edema formation, stabilize the expression of Synapsin I, which was a potential indicator of maintaining the hippocampal synaptic function, thus counteracting behavioral but not mood decay in rats subjected to TBI. In conclusion, decompressive craniectomy, excepting for its life-saving effect, could also play a potential beneficial neuroprotective role on behavioral but not mood deficits at an early stage of moderate traumatic brain injury in rats.

Brain Metabolite Diffusion from Ultra-Short to Ultra-Long Time Scales: What Do We Learn, Where Should We Go?

In vivo diffusion-weighted MR spectroscopy (DW-MRS) allows measuring diffusion properties of brain metabolites. Unlike water, most metabolites are confined within cells. Hence, their diffusion is expected to purely reflect intracellular properties, opening unique possibilities to use metabolites as specific probes to explore cellular organization and structure. However, interpretation and modeling of DW-MRS, and more generally of intracellular diffusion, remains difficult. In this perspective paper, we will focus on the study of the time-dependency of brain metabolite apparent diffusion coefficient (ADC). We will see how measuring ADC over several orders of magnitude of diffusion times, from less than 1 ms to more than 1 s, allows clarifying our understanding of brain metabolite diffusion, by firmly establishing that metabolites are neither massively transported by active mechanisms nor massively confined in subcellular compartments or cell bodies. Metabolites appear to be instead diffusing in long fibers typical of neurons and glial cells such as astrocytes. Furthermore, we will evoke modeling of ADC time-dependency to evaluate the effect of, and possibly quantify, some structural parameters at various spatial scales, departing from a simple model of hollow cylinders and introducing additional complexity, either short-ranged (such as dendritic spines) or long-ranged (such as cellular fibers ramification). Finally, we will discuss the experimental feasibility and expected benefits of extending the range of diffusion times toward even shorter and longer values.

In Vivo Multidimensional Brain Imaging in Huntington's Disease Animal Models

Huntington's disease (HD) is a genetic neurodegenerative disorder caused by an abnormal expansion of a CAG repeat located in the gene encoding for huntingtin protein. This mutation induces the expression of a polyglutamine stretch in the mutated protein resulting in the modification of various biological properties of the wild-type protein and the progressive appearance of motor, cognitive, and psychiatric disorders that are typically associated to this condition. Although the exact neuropathological mechanisms of degeneration are still not fully understood, HD pathology is characterized by severe neuronal losses in various brain regions including the basal ganglia and many cortical areas. Early signs of astrogliosis may precede actual neuronal degeneration. Early metabolic impairment at least in part associated with mitochondrial complex II deficiency may play a key role in huntingtin-induced mechanisms of neurodegeneration. Clinical trials are actively prepared including various gene-silencing approaches aiming at decreasing mutated huntingtin production. However, with the lack of a specific imaging biomarker capable of visualizing mutated huntingtin or huntingtin aggregates, there is a need for surrogate markers of huntingtin neurodegeneration. MRI and caudate nucleus atrophy is one of the most sensitive imaging biomarkers of HD. As such it can be used as a means to study disease progression and potential halting of the neurodegenerative process by therapeutic intervention, but this marker relies on actual neuronal loss which is a somewhat a late event in the pathology. As a means to develop, characterize and evaluate new, potentially earlier biomarkers of HD pathology we have recently embarked on a series of NMR developments looking for brain imaging techniques that allow for noninvasive longitudinal evaluation/characterization of functional alterations in animal models of HD. This chapter describes an assemblage of innovative NMR methods that have proved useful in detecting pathological cell dysfunctions in various preclinical models of HD.

Distinguishing neuronal from astrocytic subcellular microstructures using in vivo Double Diffusion Encoded 1H MRS at 21.1 T

Measuring cellular microstructures non-invasively and achieving specificity towards a cell-type population within an interrogated in vivo tissue, remains an outstanding challenge in brain research. Magnetic Resonance Spectroscopy (MRS) provides an opportunity to achieve cellular specificity via the spectral resolution of metabolites such as N-Acetylaspartate (NAA) and myo-Inositol (mI), which are considered neuronal and astrocytic markers, respectively. Yet the information typically obtained with MRS describes metabolic concentrations, diffusion coefficients or relaxation rates rather than microstructures. Understanding how these metabolites are compartmentalized is a challenging but important goal, which so far has been mainly addressed using diffusion models. Here, we present direct in vivo evidence for the confinement of NAA and mI within sub-cellular components, namely, the randomly oriented process of neurons and astrocytes, respectively. Our approach applied Relaxation Enhanced MRS at ultrahigh (21.1 T) field, and used its high ¹H sensitivity to measure restricted diffusion correlations for NAA and mI using a Double Diffusion Encoding (DDE) filter. While very low macroscopic anisotropy was revealed by spatially localized Diffusion Tensor Spectroscopy, DDE displayed characteristic amplitude modulations reporting on confinements in otherwise randomly oriented anisotropic microstructures for both metabolites. This implies that for the chosen set of parameters, the DDE measurements had a biased sensitivity towards NAA and mI sited in the more confined environments of neurites and astrocytic branches, than in the cell somata. These measurements thus provide intrinsic diffusivities and compartment diameters, and revealed subcellular neuronal and astrocytic morphologies in normal in vivo rat brains. The relevance of these measurements towards human applications—which could in turn help understand CNS plasticity as well as diagnose brain diseases—is discussed.

Diffusion-weighted MRS of acetate in the rat brain

Acetate has been proposed as an astrocyte-specific energy substrate for metabolic studies in the brain. The determination of the relative contribution of the intracellular and extracellular compartments to the acetate signal using diffusion-weighted magnetic resonance spectroscopy can provide an insight into the cellular environment and distribution volume of acetate in the brain. In the present study, localized ¹ H nuclear magnetic resonance (NMR) spectroscopy employing a diffusion-weighted stimulated echo acquisition mode (STEAM) sequence at an ultra-high magnetic field (14.1 T) was used to investigate the diffusivity characteristics of acetate and N-acetylaspartate (NAA) in the rat brain in vivo during prolonged acetate infusion. The persistence of the acetate resonance in ¹ H spectra acquired at very large diffusion weighting indicated restricted diffusion of acetate and was attributed to intracellular spaces. However, the significantly greater diffusion of acetate relative to NAA suggests that a substantial fraction of acetate is located in the extracellular space of the brain. Assuming an even distribution for acetate in intracellular and extracellular spaces, the diffusion properties of acetate yielded a smaller volume of distribution for acetate relative to water and glucose in the rat brain.

Longitudinal MR spectroscopy of neurodegeneration in multiple sclerosis with diffusion of the intra-axonal constituent N-acetylaspartate

Multiple sclerosis (MS) is a pathologically complex CNS disease: inflammation, demyelination, and neuroaxonal degeneration occur concurrently and may depend on one another. Current therapies are aimed at the immune-mediated, inflammatory destruction of myelin, whereas axonal degeneration is ongoing and not specifically targeted. Diffusion-weighted magnetic resonance spectroscopy can measure the diffusivity of metabolites in vivo, such as the axonal/neuronal constituent N-acetylaspartate, allowing compartment-specific assessment of disease-related changes. Previously, we found significantly lower N-acetylaspartate diffusivity in people with MS compared to healthy controls (Wood et al., 2012) suggesting that this technique can measure axonal degeneration and could be useful in developing neuroprotective agents. In this longitudinal study, we found that N-acetylaspartate diffusivity decreased by 8.3% (p < 0.05) over 6 months in participants who were experiencing clinical or MRI evidence of inflammatory activity (n = 13), whereas there was no significant change in N-acetylaspartate diffusivity in the context of clinical and radiological stability (n = 6). As N-acetylaspartate diffusivity measurements are thought to more specifically reflect the intra-axonal space, these data suggest that N-acetylaspartate diffusivity can report on axonal health on the background of multiple pathological processes in MS, both cross-sectionally and longitudinally.

In vivo diffusion MRS investigation of non-water molecules in biological tissues

Diffusion MRS of non-water molecules offers great potential in directly revealing various tissue microstructures and physiology at both cellular and subcellular levels. In brain, ¹ H diffusion MRS has been demonstrated as a new tool for probing normal tissue microstructures and their pathological changes. In skeletal muscle, ¹ H diffusion MRS could characterize slow and restricted intramyocellular lipid diffusion, providing a sensitive marker for metabolic alterations, while ³¹ P diffusion MRS can measure ATP and PCr diffusion, which may reflect the capacity of cellular energy transport, complementing the information from frequently used ³¹ P MRS in muscle. In intervertebral disk, ¹ H diffusion MRS can directly monitor extracellular matrix integrity by quantifying the mobility of macromolecules such as proteoglycans and collagens. In tumor tissue, ¹³ C diffusion MRS could probe intracellular glycolytic metabolism, while ¹ H diffusion MRS may separate the spectrally overlapped lactate and lipid resonances. In this review, recent diffusion MRS studies of these biologically relevant non-water molecules under normal and diseased conditions will be presented. Technical considerations for diffusion MRS experiments will be discussed. With advances in MRI hardware and diffusion methodology, diffusion MRS of non-water molecules is expected to provide increasingly valuable and biologically specific information on tissue microstructures and physiology, complementing the traditional diffusion MRI of small and ubiquitous water molecules. Copyright © 2016 John Wiley & Sons, Ltd.

Low-bandwidth space/frequency component separation for quantitative imaging

Quantitative MRI is often used to analyse multicomponent systems. The analysis requires the contributions from different species to be isolated. Species with distinct chemical shifts can be separated by using a low acquisition bandwidth, which is easy to achieve in common quantitative imaging protocols. The bandwidth reduction leads to separation of NMR contributions from different species in the image space. This new method was implemented and tested on two multicomponent systems containing several spectrally and spatially unresolved components with both distinctly different and similar diffusion coefficients and relaxation times. Separation was achieved with routine MRI diffusion and relaxation measurement pulse sequences in a microimaging environment for water/polyethylene glycol solution and for chloroform/TMS/polyethylene glycol solution. Conventional monoexponential fitting was used to determine diffusion coefficients and relaxation times from the spectrally separated data, whereas biexponential or triexponential fitting was required in the unseparated reference experiments. In the two-component sample, the variation in the determined fast diffusing components was on the same order of magnitude for all experiments, while the variation in the slow diffusing polyethylene glycol was larger when no separation was present. The separation technique provided lower variability for all the determined diffusion coefficients and relaxation times in the three-component sample. The low-bandwidth separation method can provide separation of multicomponent systems based on the chemical shift difference between the species. The accuracy of the technique is comparable with the commonly used methods for bicomponent system analysis and surpasses those when there are more than two components in the sample. Copyright © 2016 John Wiley & Sons, Ltd.

Probing metabolite diffusion at ultra-short time scales in the mouse brain using optimized oscillating gradients and "short"-echo-time diffusion-weighted MRS

Measuring diffusion at ultra-short time scales may yield information about short-range intracellular structure and cytosol viscosity. However, reaching such time scales usually requires oscillating gradients, which in turn imply long echo times T_E . Here we propose a new kind of stretched oscillating gradient that allows us to increase diffusion-weighting b while preserving spectral and temporal properties of the gradient modulation. We used these optimized gradients to measure metabolite diffusion in the mouse brain down to effective diffusion times of 1 ms while keeping T_E relatively short (60 ms). At such T_E , a significant macromolecule signal could still be observed and used as an internal reference of approximately null diffusivity, which proved critical to discard datasets corrupted by some motion artifact. The methods introduced here may be useful to improve the accuracy and precision of metabolite apparent diffusion coefficient measurements with oscillating gradients.

New paradigm to assess brain cell morphology by diffusion-weighted MR spectroscopy in vivo

The brain is one of the most complex organs, and tools are lacking to assess its cellular morphology in vivo. Here we combine original diffusion-weighted magnetic resonance (MR) spectroscopy acquisition and novel modeling strategies to explore the possibility of quantifying brain cell morphology noninvasively. First, the diffusion of cell-specific metabolites is measured at ultra-long diffusion times in the rodent and primate brain in vivo to observe how cell long-range morphology constrains metabolite diffusion. Massive simulations of particles diffusing in synthetic cells parameterized by morphometric statistics are then iterated to fit experimental data. This method yields synthetic cells (tentatively neurons and astrocytes) that exhibit striking qualitative and quantitative similarities with histology (e.g., using Sholl analysis). With our approach, we measure major interspecies difference regarding astrocytes, whereas dendritic organization appears better conserved throughout species. This work suggests that the time dependence of metabolite diffusion coefficient allows distinguishing and quantitatively characterizing brain cell morphologies noninvasively.

Metabolite diffusion up to very high b in the mouse brain in vivo: Revisiting the potential correlation between relaxation and diffusion properties

PURPOSE

To assess the potential correlation between metabolites diffusion and relaxation in the mouse brain, which is of importance for interpreting and modeling metabolite diffusion based on pure geometry, irrespective of relaxation properties (multicompartmental relaxation or surface relaxivity).

METHODS

A new diffusion-weighted magnetic resonance spectroscopy sequence is introduced, dubbed "STE-LASER," which presents several nice properties, in particular the absence of cross-terms with selection gradients and a very clean localization. Metabolite diffusion is then measured in a large voxel in the mouse brain at 11.7 Tesla using a cryoprobe, resulting in excellent signal-to-noise ratio, up to very high b-values under different echo time, mixing time, and diffusion time combinations.

RESULTS

Our results suggest that the correlation between relaxation and diffusion properties is extremely small or even nonexistent for metabolites in the mouse brain.

CONCLUSION

The present work strongly supports the interpretation and modeling of metabolite diffusion primarily based on geometry, irrespective of relaxation properties, at least under current experimental conditions. Magn Reson Med 77:1390-1398, 2017. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

Reproducibility and optimization of in vivo human diffusion-weighted MRS of the corpus callosum at 3 T and 7 T

Diffusion-weighted MRS (DWS) of brain metabolites enables the study of cell-specific alterations in tissue microstructure by probing the diffusion of intracellular metabolites. In particular, the diffusion properties of neuronal N-acetylaspartate (NAA), typically co-measured with N-acetylaspartyl glutamate (NAAG) (NAA + NAAG = tNAA), have been shown to be sensitive to intraneuronal/axonal damage in pathologies such as stroke and multiple sclerosis. Lacking, so far, are empirical assessments of the reproducibility of DWS measures across time and subjects, as well as a systematic investigation of the optimal acquisition parameters for DWS experiments, both of which are sorely needed for clinical applications of the method. In this study, we acquired comprehensive single-volume DWS datasets of the human corpus callosum at 3 T and 7 T. We investigated the inter- and intra-subject variability of empirical and modeled diffusion properties of tNAA [D(avg) (tNAA) and D(model) (tNAA), respectively]. Subsequently, we used a jackknife-like resampling approach to explore the variance of these properties in partial data subsets reflecting different total scan durations. The coefficients of variation (C(V)) and repeatability coefficients (C(R)) for D(avg) (tNAA) and D(model) (tNAA) were calculated for both 3 T and 7 T, with overall lower variability in the 7 T results. Although this work is limited to the estimation of the diffusion properties in the corpus callosum, we show that a careful choice of diffusion-weighting conditions at both field strengths allows the accurate measurement of tNAA diffusion properties in clinically relevant experimental time. Based on the resampling results, we suggest optimized acquisition schemes of 13-min duration at 3T and 10-min duration at 7 T, whilst retaining low variability (C(V) ≈ 8%) for the tNAA diffusion measures. Power calculations for the estimation of D(model )(tNAA) and D(avg) (tNAA) based on the suggested schemes show that less than 21 subjects per group are sufficient for the detection of a 10% effect between two groups in case-control studies.

Quantification of cell size using temporal diffusion spectroscopy

PURPOSE

A new approach has been developed to quantify cell sizes and intracellular volume fractions using temporal diffusion spectroscopy with diffusion-weighted acquisitions.

METHODS

Temporal diffusion spectra may be used to characterize tissue microstructure by measuring the effects of restrictions over a range of diffusion times. Oscillating gradients have been used previously to probe variations on cellular and subcellular scales, but their ability to accurately measure cell sizes larger than 10 μm is limited. By combining measurements made using oscillating gradient spin echo (OGSE) and a conventional pulsed gradient spin echo (PGSE) acquisition with a single, relatively long diffusion time, we can accurately quantify cell sizes and intracellular volume fractions.

RESULTS

Based on a two compartment model (incorporating intra- and extracellular spaces), accurate estimates of cell sizes and intracellular volume fractions were obtained in vitro for (i) different cell types with sizes ranging from 10 to 20 μm, (ii) different cell densities, and (iii) before and after anticancer treatment.

CONCLUSION

Hybrid OGSE-PGSE acquisitions sample a larger region of temporal diffusion spectra and can accurately quantify cell sizes over a wide range. Moreover, the maximum gradient strength used was lower than 15 G/cm, suggesting that this approach is translatable to practical MR imaging.

Brain intracellular metabolites are freely diffusing along cell fibers in grey and white matter, as measured by diffusion-weighted MR spectroscopy in the human brain at 7 T

Due to the specific compartmentation of brain metabolites, diffusion-weighted magnetic resonance spectroscopy opens unique insight into neuronal and astrocytic microstructures. The apparent diffusion coefficient (ADC) of brain metabolites depends on various intracellular parameters including cytosol viscosity and molecular crowding. When diffusion time (t d) is long enough, the size and geometry of the compartment in which the metabolites diffuse strongly influence metabolites ADC. In a previous study, performed in the macaque brain, we measured neuronal and astrocytic metabolites ADC at long t d (from 86 to 1,011 ms) in a large voxel enclosing an equal proportion of white and grey matter. We showed that metabolites apparently diffuse freely along the axis of dendrites, axons and astrocytic processes. To assess potential differences between these two tissue types, here we measured for the first time in the Human brain the t d-dependency of metabolites trace/3 ADC at 7 teslas using a localized diffusion-weighted STEAM sequence, in parietal and occipital voxels, respectively, containing mainly white and grey matter. We show that, in both tissues and over the observed timescale (t d varying from 92 to 712 ms) metabolite ADC reaches a non-zero plateau, suggesting that metabolites are not confined inside subcellular regions such as cell bodies, or inside subcellular compartments such as organelles, but are rather free to diffuse in the whole fiber-like structure of neurons and astrocytes. Beyond the fundamental insights into intracellular compartmentation of metabolites, this work also provides a new framework for interpreting results of neuroimaging techniques based on molecular diffusion, such as diffusion-weighted magnetic resonance spectroscopy and imaging.

Diffusion-weighted chemical shift imaging of human brain metabolites at 7T

PURPOSE

Diffusion-weighted chemical shift imaging (DW-CSI) of brain metabolites poses significant challenges associated with the acquisition of spectroscopic data in the presence of strong diffusion weighting gradients. We present a reproducible DW-CSI acquisition and processing scheme that addresses most of the potential sources of instability and provides reproducible and anatomically meaningful diffusion-weighted and apparent diffusion coefficient (ADC) metabolite maps.

METHODS

A real-time navigator-based acquisition scheme was used, allowing instantaneous reacquisition of corrupted k-space data and postprocessing correction of gradient-induced phase fluctuations. Eddy current correction based on residual water resonance was implemented and improved the quality of the data significantly.

RESULTS

Highly reproducible diffusion-weighted metabolite maps of three highest concentration brain metabolites are shown. The navigator-based accept/reject strategy and the postacquisition corrections improved the stability of the DW-CSI signal and the reproducibility of the resulting DW-CSI maps significantly. The metabolite ADC values could be related to the underlying tissue cellular composition.

CONCLUSION

Robust investigation of DW-CSI of brain metabolites is feasible and may provide information complementary to that obtained from more sensitive but less specific methods such as diffusion tensor imaging.

The interaction between apparent diffusion coefficients and transverse relaxation rates of human brain metabolites and water studied by diffusion-weighted spectroscopy at 7 T

The dependence of apparent diffusion coefficients (ADCs) of molecules in biological tissues on an acquisition-specific timescale is a powerful mechanism for studying tissue microstructure. Unlike water, metabolites are confined mainly to intracellular compartments, thus providing higher specificity to tissue microstructure. Compartment-specific structural and chemical properties may also affect molecule transverse relaxation times (T₂). Here, we investigated the correlation between diffusion and relaxation for N-acetylaspartate, creatine and choline compounds in human brain white matter in vivo at 7 T, and compared them with those of water under the same experimental conditions. Data were acquired in a volume of interest in parietal white matter at two different diffusion times, Δ = 44 and 246 ms, using a matrix of three echo times (T(E)) and five diffusion weighting values (up to 4575 s/mm²). Significant differences in the dependence of the ADCs on T(E) were found between water and metabolites, as well as among the different metabolites. A significant decrease in water ADC as a function of TE was observed only at the longest diffusion time (p < 0.001), supporting the hypothesis that at least part of the restricted water pool can be associated with longer T₂, as suggested by previous studies in vitro. Metabolite data showed an increase of creatine (p < 0.05) and N-acetylaspartate (p < 0.05) ADCs with TE at Δ = 44 ms, and a decrease of creatine (p < 0.05) and N-acetylaspartate (p = 0.1) ADCs with TE at Δ = 246 ms. No dependence of choline ADC on TE was observed. The metabolite results suggest that diffusion and relaxation properties are dictated not only by metabolite distribution in different cell types, but also by other mechanisms, such as interactions with membranes, exchange between "free" and "bound" states or interactions with microsusceptibility gradients.

Proton diffusion tensor spectroscopy of metabolites in human muscle in vivo

PURPOSE

To study the apparent diffusivity and its directionality for metabolites of skeletal muscle in humans in vivo by (1) H magnetic resonance spectroscopy.

METHODS

The diffusion tensors were determined on a 3 Tesla MR system using optimized acquisition and processing methods including an adapted STEAM sequence with orientation-dependent diffusion weighting, pulse-triggering with individually adapted delays, eddy-current correction schemes, median filtering, and simultaneous prior-knowledge fitting of all related spectra.

RESULTS

The average apparent diffusivities, as well as the fractional anisotropies of taurine (ADCav=0.74 × 10(-3) s/mm(2) , FA=0.46), creatine (ADCav =0.41 × 10(-3) s/mm(2) , FA=0.33), trimethylammonium compounds (ADCav =0.48 × 10(-3) s/mm(2) , FA=0.34), carnosine (ADCav =0.46 × 10(-3) s/mm(2) , FA=0.47), and water (ADCav=1.5 × 10(-3) s/mm(2) , FA=0.36) were estimated. The diffusivities of most metabolites and water were significantly different from each other. Diffusion was found to be anisotropic and the diffusion tensors showed tensor correlation coefficients close to 1 and were hence found to be essentially coaligned. The magnitudes of apparent metabolite diffusivities were largely ordered according to molecular weight, with taurine as the smallest molecule diffusing fastest, both along and across the fiber direction.

CONCLUSION

Diffusivities, directional dependence of diffusion and fractional anisotropies of (1) H MRS-visible muscle metabolites were presented. It was shown that metabolites share diffusion directionality with water and have similar fractional anisotropies, hinting at similar diffusion barriers.

Microstructural organization of axons in the human corpus callosum quantified by diffusion-weighted magnetic resonance spectroscopy of N-acetylaspartate and post-mortem histology

Diffusion-weighted magnetic resonance spectroscopy of brain metabolites offers unique access to compartment-specific microstructural information on neural tissue. Here, we investigated in detail the diffusion characteristics of the neuronal/axonal markers N-acetylaspartate + N-acetyl aspartyl glutamate (tNAA) in a small region of the human corpus callosum at 7 T. The diffusion-weighted spectroscopy data were analyzed by fitting to a model in which information about cross-callosal tract orientation within the spectroscopy volume, obtained from diffusion tensor imaging data, was incorporated. We estimated the microscopic misalignment of axons (σ φ  = 18.6° ± 3.0°) in excellent agreement with independent histological results (σ φ  = 18.1° ± 4.6°) obtained from microscopic analysis of axonal orientations in the body of the corpus callosum from post-mortem human brain slices. We also robustly quantified the diffusion coefficient of tNAA (0.51 ± 0.06 × 10(-3) mm(2)/s) in axonal cytoplasm, unbiased by the tract curvature. This work supports the notion that microscopic axonal misalignment is a dominant microstructural property in white matter tracts and has a strong impact on the evaluation of tissue microstructure using diffusion information, and should therefore be taken into consideration in the evaluation of white matter microstructure. Additionally, this study enabled robust and unbiased assessment of the cytosolic diffusion coefficient of tNAA, a potential biomarker for axonopathy and neuronal degeneration.

Axonal and glial microstructural information obtained with diffusion-weighted magnetic resonance spectroscopy at 7T

Diffusion-weighted magnetic resonance spectroscopy (DWS) offers unique access to compartment-specific microstructural information on tissue, and potentially sensitive detection of compartment-specific changes in disease. The specificity of DWS is, however, offset by its relative low sensitivity, intrinsic to all MRS-based methods, and further exacerbated by the signal loss due to the diffusion weighting and long echo times. In this work we first provide an experimental example for the type of compartment-specific information that can be obtained with DWS from a small volume of interest (VOI) in brain white matter. We then propose and discuss a strategy for the analysis of DWS data, which includes the use of models of diffusion in compartments with simple geometries. We conclude with a broader discussion of the potential role of DWS in the characterization of tissue microstructure and the complementarity of DWS with less-specific but more sensitive microstructural tools such as diffusion tensor imaging.