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

Diffusion-weighted MR spectroscopy: Consensus, recommendations, and resources from acquisition to modeling

Brain cell structure and function reflect neurodevelopment, plasticity, and aging; and changes can help flag pathological processes such as neurodegeneration and neuroinflammation. Accurate and quantitative methods to noninvasively disentangle cellular structural features are needed and are a substantial focus of brain research. Diffusion-weighted MRS (dMRS) gives access to diffusion properties of endogenous intracellular brain metabolites that are preferentially located inside specific brain cell populations. Despite its great potential, dMRS remains a challenging technique on all levels: from the data acquisition to the analysis, quantification, modeling, and interpretation of results. These challenges were the motivation behind the organization of the Lorentz Center workshop on "Best Practices & Tools for Diffusion MR Spectroscopy" held in Leiden, the Netherlands, in September 2021. During the workshop, the dMRS community established a set of recommendations to execute robust dMRS studies. This paper provides a description of the steps needed for acquiring, processing, fitting, and modeling dMRS data, and provides links to useful resources.

Event-related functional magnetic resonance spectroscopy

Proton-Magnetic Resonance Spectroscopy (MRS) is a non-invasive brain imaging technique used to measure the concentration of different neurochemicals. "Single-voxel" MRS data is typically acquired across several minutes, before individual transients are averaged through time to give a measurement of neurochemical concentrations. However, this approach is not sensitive to more rapid temporal dynamics of neurochemicals, including those that reflect functional changes in neural computation relevant to perception, cognition, motor control and ultimately behaviour. In this review we discuss recent advances in functional MRS (fMRS) that now allow us to obtain event-related measures of neurochemicals. Event-related fMRS involves presenting different experimental conditions as a series of trials that are intermixed. Critically, this approach allows spectra to be acquired at a time resolution in the order of seconds. Here we provide a comprehensive user guide for event-related task designs, choice of MRS sequence, analysis pipelines, and appropriate interpretation of event-related fMRS data. We raise various technical considerations by examining protocols used to quantify dynamic changes in GABA, the primary inhibitory neurotransmitter in the brain. Overall, we propose that although more data is needed, event-related fMRS can be used to measure dynamic changes in neurochemicals at a temporal resolution relevant to computations that support human cognition and behaviour.

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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NMR diffusometry: A new perspective for nanomedicine exploration

Nuclear Magnetic Resonance (NMR) based diffusion methods open new perspectives for nanomedicine characterization and their bioenvironment interaction understanding. This review summarizes the theoretical background of diffusion phenomena. Self-diffusion and mutual diffusion coefficient notions are featured. Principles, advantages, drawbacks, and key challenges of NMR diffusometry spectroscopic and imaging methods are presented. This review article also gives an overview of representative applicative works to the nanomedicine field that can contribute to elucidate important issues. Examples of in vitro characterizations such as identification of formulated species, process monitoring, drug release follow-up, nanomedicine interactions with biological barriers are presented as well as possible transpositions for studying in vivo nanomedicine fate.

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.

In vivo diffusion-weighted MRS using semi-LASER in the human brain at 3 T: Methodological aspects and clinical feasibility

Diffusion-weighted (DW-) MRS investigates non-invasively microstructural properties of tissue by probing metabolite diffusion in vivo. Despite the growing interest in DW-MRS for clinical applications, little has been published on the reproducibility of this technique. In this study, we explored the optimization of a single-voxel DW-semi-LASER sequence for clinical applications at 3 T, and evaluated the reproducibility of the method under different experimental conditions. DW-MRS measurements were carried out in 10 healthy participants and repeated across three sessions. Metabolite apparent diffusion coefficients (ADCs) were calculated from mono-exponential fits (ADC_exp ) up to b = 3300 s/mm² , and from the diffusional kurtosis approach (ADC_K ) up to b = 7300 s/mm² . The inter-subject variabilities of ADCs of N-acetylaspartate + N-acetylaspartylglutamate (tNAA), creatine + phosphocreatine, choline containing compounds, and myo-inositol were calculated in the posterior cingulate cortex (PCC) and in the corona radiata (CR). We explored the effect of physiological motion on the DW-MRS signal and the importance of cardiac gating and peak thresholding to account for signal amplitude fluctuations. Additionally, we investigated the dependence of the intra-subject variability on the acquisition scheme using a bootstrapping resampling method. Coefficients of variation were lower in PCC than CR, likely due to the different sensitivities to motion artifacts of the two regions. Finally, we computed coefficients of repeatability for ADC_exp and performed power calculations needed for designing clinical studies. The power calculation for ADC_exp of tNAA showed that in the PCC seven subjects per group are sufficient to detect a difference of 5% between two groups with an acquisition time of 4 min, suggesting that ADC_exp of tNAA is a suitable marker for disease-related intracellular alteration even in small case-control studies. In the CR, further work is needed to evaluate the voxel size and location that minimize the motion artifacts and variability of the ADC measurements.

Rapid acquisition diffusion MR spectroscopy of metabolites in human brain

Few studies have focused on metabolite diffusion in the human brain using ¹ H-MRS due to significant technical challenges. Moreover, such studies have required lengthy acquisition times and are therefore impractical to implement clinically. By first characterizing and then minimizing the effects of linear and oscillating eddy currents, which arise from the diffusion gradients, and by implementing phase-cycle and slice-order strategies, as well as introducing a new phase-alignment methodology, we report a method that allows data acquisition requiring 20 seconds per spectrum. This remained feasible, even for b-values >8000 s/mm² , with a rapid acquisition diffusion MRS methodology. It has allowed the nonlinear characterization of signal intensity with multiple b-values, and has improved the measurement of rotationally invariant diffusion parameters via six-direction, six b-value diffusion tensor spectroscopy (DTS) in 12 minutes at 4.7 T. The shorter DTS acquisition will enable its application to white matter regions not aligned with the gradients and permit clinical studies in a feasible time.

Deep learning can accelerate and quantify simulated localized correlated spectroscopy

Nuclear magnetic resonance spectroscopy (MRS) allows for the determination of atomic structures and concentrations of different chemicals in a biochemical sample of interest. MRS is used in vivo clinically to aid in the diagnosis of several pathologies that affect metabolic pathways in the body. Typically, this experiment produces a one dimensional (1D) 1H spectrum containing several peaks that are well associated with biochemicals, or metabolites. However, since many of these peaks overlap, distinguishing chemicals with similar atomic structures becomes much more challenging. One technique capable of overcoming this issue is the localized correlated spectroscopy (L-COSY) experiment, which acquires a second spectral dimension and spreads overlapping signal across this second dimension. Unfortunately, the acquisition of a two dimensional (2D) spectroscopy experiment is extremely time consuming. Furthermore, quantitation of a 2D spectrum is more complex. Recently, artificial intelligence has emerged in the field of medicine as a powerful force capable of diagnosing disease, aiding in treatment, and even predicting treatment outcome. In this study, we utilize deep learning to: (1) accelerate the L-COSY experiment and (2) quantify L-COSY spectra. All training and testing samples were produced using simulated metabolite spectra for chemicals found in the human body. We demonstrate that our deep learning model greatly outperforms compressed sensing based reconstruction of L-COSY spectra at higher acceleration factors. Specifically, at four-fold acceleration, our method has less than 5% normalized mean squared error, whereas compressed sensing yields 20% normalized mean squared error. We also show that at low SNR (25% noise compared to maximum signal), our deep learning model has less than 8% normalized mean squared error for quantitation of L-COSY spectra. These pilot simulation results appear promising and may help improve the efficiency and accuracy of L-COSY experiments in the future.

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.

Multicomponent diffusion analysis reveals microstructural alterations in spinal cord of a mouse model of amyotrophic lateral sclerosis ex vivo

The microstructure changes associated with degeneration of spinal axons in amyotrophic lateral sclerosis (ALS) may be reflected in altered water diffusion properties, potentially detectable with diffusion-weighted (DW) MRI. Prior work revealed the classical mono-exponential model fails to precisely depict decay in DW signal at high b-values. In this study, we aim to investigate signal decay behaviors at ultra-high b-values for non-invasive assessment of spinal cord alterations in the transgenic SOD1^G93A mouse model of ALS. A multiexponential diffusion analysis using regularized non-negative least squares (rNNLS) algorithm was applied to a series of thirty DW MR images with b-values ranging from 0 to 858,022 s/mm² on ex vivo spinal cords of transgenic SOD1^G93A and age-matched control mice. We compared the distributions of measured diffusion coefficient fractions between the groups. The measured diffusion weighted signals in log-scale showed non-linear decay behaviors with increased b-values. Faster signal decays were observed with diffusion gradients applied parallel to the long axis of the spinal cord compared to when oriented in the transverse direction. Multiexponential analysis at the lumbar level in the spinal cord identified ten subintervals. A significant decrease of diffusion coefficient fractions was found in the ranges of [1.63×10⁻⁸,3.70×10⁻⁶] mm²/s (P = 0.0002) and of [6.01×10⁻⁶,4.20×10⁻⁵] mm²/s (P = 0.0388) in SOD1^G93A mice. Anisotropic diffusion signals persisted at ultra-high b-value DWIs of the mouse spinal cord and multiexponential diffusion analysis offers the potential to evaluate microstructural alterations of ALS-affected spinal cord non-invasively.

Diffusion behavior of cerebral metabolites of congenital portal systemic shunt mice assessed noninvasively by diffusion-weighted 1 H magnetic resonance spectroscopy

Diffusion-weighted ¹ H-MRS (DW-MRS) allows for noninvasive investigation of the cellular compartmentalization of cerebral metabolites. DW-MRS applied to the congenital portal systemic shunt (PSS) mouse brain may provide specific insight into alterations of cellular restrictions associated with PSS in humans. At 14.1 T, adult male PSS and their age-matched healthy (Ctrl) mice were studied using DW-MRS covering b-values ranging from 0 to 45 ms/μm² to determine the diffusion behavior of abundant metabolites. The remarkable sensitivity and spectral resolution, in combination with very high diffusion weighting, allowed for precise measurement of the diffusion properties of endogenous N-acetyl-aspartate, total creatine, myo-inositol, total choline with extension to glutamine and glutamate in mouse brains, in vivo. Most metabolites had comparable diffusion properties in PSS and Ctrl mice, suggesting that intracellular distribution space for these metabolites was not affected in the model. The slightly different diffusivity of the slow decaying component of taurine (0.015 ± 0.003 μm² /ms in PSS vs 0.021 ± 0.002 μm² /ms in Ctrl, P < 0.05) might support a cellular redistribution of taurine in the PSS mouse brain.

Optimizing acquisition and fitting conditions for 1 H MR spectroscopy investigations in global brain pathology

PURPOSE

To optimize acquisition and fitting conditions for nonfocal disease in terms of voxel size and use of individual coil element data. Increasing the voxel size yields a higher signal-to-noise ratio, but leads to larger linewidths and more artifacts. Several ways to improve the spectral quality for large voxels are exploited and the optimal use of individual coil signals investigated.

METHODS

Ten human subjects were measured at 3 T using a 64-channel receive head coil with a semi-LASER localization sequence under optimized and deliberately mis-set field homogeneity. Eight different voxel sizes (8 to 99 cm³ ) were probed. Spectra were fitted either as weighted sums of the individual coil elements or simultaneously without summation. Eighteen metabolites were included in the fit model that also included the lineshapes from all coil elements as reflected in water reference data. Fitting errors for creatine, myo-Inositol and glutamate are reported as representative parameters to judge optimal acquisition and evaluation conditions.

RESULTS

Minimal Cramér-Rao lower bounds and thus optimal acquisition conditions were found for a voxel size of ~ 70 cm³ for the representative upfield metabolites. Spectral quality in terms of lineshape and artifact appearance was determined to differ substantially between coil elements. Simultaneous fitting of spectra from individual coil elements instead of traditional fitting of a weighted sum spectrum reduced Cramer-Rao lower bounds by up to 17% for large voxel sizes.

CONCLUSION

The optimal voxel size for best precision in determined metabolite content is surprisingly large. Such an acquisition condition is most relevant for detection of low-concentration metabolites, like NAD⁺ or phenylalanine, but also for longitudinal studies where very small alterations in metabolite content are targeted. In addition, simultaneous fitting of single channel spectra enforcing lineshape and coil sensitivity information proved to be superior to traditional signal combination with subsequent fitting.

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'.

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.

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.

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.

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.

Differentiating brown and white adipose tissues by high-resolution diffusion NMR spectroscopy

There are two types of fat tissues, white adipose tissue (WAT) and brown adipose tissue (BAT), which essentially perform opposite functions in whole body energy metabolism. There is a large interest in identifying novel biophysical properties of WAT and BAT by a quantitative and easy-to-run technique. In this work, we used high-resolution pulsed field gradient diffusion NMR spectroscopy to study the apparent diffusion coefficient (ADC) of fat molecules in rat BAT and WAT samples. The ADC of fat in BAT and WAT from rats fed with a chow diet was compared with that of rats fed with a high-fat diet to monitor how the diffusion properties change due to obesity-associated parameters such as lipid droplet size, fatty acid chain length, and saturation. Feeding a high-fat diet resulted in increased saturation, increased chain lengths, and reduced ADC of fat in WAT. The ADC of fat was lower in BAT relative to WAT in rats fed both chow and high-fat diets. Diffusion of fat was restricted in BAT due to the presence of small multilocular lipid droplets. Our findings indicate that in vivo diffusion might be a potential way for better delineation of BAT and WAT in both lean and obese states.

Diffusion-weighted J-resolved spectroscopy

PURPOSE

To develop a novel diffusion-weighted magnetic resonance spectroscopy (DW-MRS) technique in conjunction with J-resolved spatially localized spectroscopy (JPRESS) to measure the apparent diffusion coefficients (ADCs) of brain metabolites beyond N-acetylaspartic acid (NAA), creatine (Cr), and choline (Cho) at 3T. This technique will be useful to probe tissue microstructures in vivo, as the various metabolites have different physiological characteristics.

METHODS

Two JPRESS spectra were collected (high b-value and low b-value), and the ADCs of 16 different metabolites were estimated. Two analysis pipelines were developed: 1) a 2D pipeline that uses ProFit software to extract ADCs from metabolites not typically accessible at 3T and 2) a 1D pipeline that uses TARQUIN software to extract the metabolite concentrations from each line in the 2D dataset, allowing for scaling as well as validation.

RESULTS

The ADCs of 16 different metabolites were estimated from within six subjects in parietal white matter. There was excellent agreement between the results obtained from the 1D and 2D pipelines for NAA, Cr, and Cho.

CONCLUSION

The proposed technique provided consistent estimates for the ADCs of NAA, Cr, Cho, glutamate + glutamine, and myo-inositol in all subjects and additionally glutathione and scyllo-inositol in all but one subject. Magn Reson Med 78:1235-1245, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Diffusion tensor spectroscopic imaging of the human brain in children and adults

PURPOSE

We developed diffusion tensor spectroscopic imaging (DTSI), based on proton-echo-planar-spectroscopic imaging (PEPSI), and evaluated the feasibility of mapping brain metabolite diffusion in adults and children.

METHODS

PRESS prelocalized DTSI at 3 Tesla (T) was performed using navigator-based correction of movement-related phase errors and cardiac gating with compensation for repetition time (TR) related variability in T₁ saturation. Mean diffusivity (MD) and fractional anisotropy (FA) of total N-acetyl-aspartate (tNAA), total creatine (tCr), and total choline (tCho) were measured in eight adults (17-60 years) and 10 children (3-24 months) using b_max  = 1734 s/mm² , 1 cc and 4.5 cc voxel sizes, with nominal scan times of 17 min and 8:24 min. Residual movement-related phase encoding ghosting (PEG) was used as a regressor across scans to correct overestimation of MD.

RESULTS

After correction for PEG, metabolite slice-averaged MD estimated at 20% PEG were lower (P < 0.042) for adults (0.17/0.20/0.18 × 10^-3 mm² /s) than for children (0.26/0.27/0.24 × 10^-3 mm² /s). Extrapolated to 0% PEG, the MD estimates decreased further (0.09/0.11/0.11 × 10^-3 mm² /s versus 0.15/0.16/0.15 × 10^-3 mm² /s). Slice-averaged FA of tNAA (P = 0.049), tCr (P = 0.067), and tCho (P = 0.003) were higher in children.

CONCLUSION

This high-speed DTSI approach with PEG regression allows for estimation of metabolite MD and FA with improved tolerance to movement. Our preliminary data suggesting age-related changes support DTSI as a sensitive technique for investigating intracellular markers of biological processes. Magn Reson Med 78:1246-1256, 2017. © 2016 International Society for Magnetic Resonance in Medicine.