Diffusion-weighted spectroscopy: A novel approach to determine macromolecule resonances in short-echo time 1H-MRS

Diffusion of brain metabolites highlights altered brain microstructure in type C hepatic encephalopathy: a 9.4 T preliminary study

Introduction

Type C hepatic encephalopathy (HE) is a decompensating event of chronic liver disease leading to severe motor and cognitive impairment. The progression of type C HE is associated with changes in brain metabolite concentrations measured by 1H magnetic resonance spectroscopy (MRS), most noticeably a strong increase in glutamine to detoxify brain ammonia. In addition, alterations of brain cellular architecture have been measured ex vivo by histology in a rat model of type C HE. The aim of this study was to assess the potential of diffusion-weighted MRS (dMRS) for probing these cellular shape alterations in vivo by monitoring the diffusion properties of the major brain metabolites.

Methods

The bile duct-ligated (BDL) rat model of type C HE was used. Five animals were scanned before surgery and 6- to 7-week post-BDL surgery, with each animal being used as its own control. 1H-MRS was performed in the hippocampus (SPECIAL, TE = 2.8 ms) and dMRS in a voxel encompassing the entire brain (DW-STEAM, TE = 15 ms, diffusion time = 120 ms, maximum b-value = 25 ms/μm2) on a 9.4 T scanner. The in vivo MRS acquisitions were further validated with histological measures (immunohistochemistry, Golgi-Cox, electron microscopy).

Results

The characteristic 1H-MRS pattern of type C HE, i.e., a gradual increase of brain glutamine and a decrease of the main organic osmolytes, was observed in the hippocampus of BDL rats. Overall increased metabolite diffusivities (apparent diffusion coefficient and intra-stick diffusivity-Callaghan's model, significant for glutamine, myo-inositol, and taurine) and decreased kurtosis coefficients were observed in BDL rats compared to control, highlighting the presence of osmotic stress and possibly of astrocytic and neuronal alterations. These results were consistent with the microstructure depicted by histology and represented by a decline in dendritic spines density in neurons, a shortening and decreased number of astrocytic processes, and extracellular edema.

Discussion

dMRS enables non-invasive and longitudinal monitoring of the diffusion behavior of brain metabolites, reflecting in the present study the globally altered brain microstructure in BDL rats, as confirmed ex vivo by histology. These findings give new insights into metabolic and microstructural abnormalities associated with high brain glutamine and its consequences in type C HE.

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.

Diffusion-weighted SPECIAL improves the detection of J-coupled metabolites at ultrahigh magnetic field

PURPOSE

To improve the detection and subsequent estimation of the diffusion properties of strongly J-coupled metabolites in diffusion-weighted MRS (DWS).

METHODS

A new sequence for single-voxel diffusion-weighted 1 H MR spectroscopy, named DW-SPECIAL, is proposed. It combines the semi-adiabatic SPECIAL sequence with a stimulated echo diffusion block. Acquisitions with DW-SPECIAL and STE-LASER, the current gold standard for rodent DWS experiments at high fields, were performed at 14.1T on phantoms and in vivo on the rat brain. The apparent diffusion coefficient and intra-stick diffusivity (Callaghan's model, randomly-oriented sticks) were fitted and compared between the sequences for glutamate, glutamine, myo-inositol, taurine, total NAA, total Cho, total Cr, and the macromolecules.

RESULTS

The shorter TE achieved with DW-SPECIAL (18 ms against 33 ms with STE-LASER) substantially limited the metabolites' signal loss caused by J-evolution. In addition, DW-SPECIAL preserved the main advantages of STE-LASER: absence of cross-terms, diffusion time during a stimulated echo, and limited sensitivity to B1 inhomogeneities. In vivo, compared to STE-LASER, DW-SPECIAL yielded the same spectral quality and reduced the Cramer Rao Lower Bounds for J-coupled metabolites, irrespective of the b-value. DW-SPECIAL also reduced the SD of the metabolites' diffusion estimates based on individual animal fitting without loss of accuracy compared to the fit on the averaged decay.

CONCLUSION

We conclude that due to its reduced TE, DW-SPECIAL can serve as an alternative to STE-LASER when strongly J-coupled metabolites like glutamine are investigated, thereby extending the range of accessible metabolites in the context of DWS acquisitions.

Feasibility and implications of using subject-specific macromolecular spectra to model short echo time magnetic resonance spectroscopy data

Expert consensus recommends linear-combination modeling (LCM) of 1 H MR spectra with sequence-specific simulated metabolite basis function and experimentally derived macromolecular (MM) basis functions. Measured MM basis functions are usually derived from metabolite-nulled spectra averaged across a small cohort. The use of subject-specific instead of cohort-averaged measured MM basis functions has not been studied widely. Furthermore, measured MM basis functions are not widely available to non-expert users, who commonly rely on parameterized MM signals internally simulated by LCM software. To investigate the impact of the choice of MM modeling, this study, therefore, compares metabolite level estimates between different MM modeling strategies (cohort-mean measured; subject-specific measured; parameterized) in a lifespan cohort and characterizes its impact on metabolite-age associations. 100 conventional (TE = 30 ms) and metabolite-nulled (TI = 650 ms) PRESS datasets, acquired from the medial parietal lobe in a lifespan cohort (20-70 years of age), were analyzed in Osprey. Short-TE spectra were modeled in Osprey using six different strategies to consider the MM baseline. Fully tissue- and relaxation-corrected metabolite levels were compared between MM strategies. Model performance was evaluated by model residuals, the Akaike information criterion (AIC), and the impact on metabolite-age associations. The choice of MM strategy had a significant impact on the mean metabolite level estimates and no major impact on variance. Correlation analysis revealed moderate-to-strong agreement between different MM strategies (r > 0.6). The lowest relative model residuals and AIC values were found for the cohort-mean measured MM. Metabolite-age associations were consistently found for two major singlet signals (total creatine (tCr])and total choline (tCho)) for all MM strategies; however, findings for metabolites that are less distinguishable from the background signals associations depended on the MM strategy. A variance partition analysis indicated that up to 44% of the total variance was related to the choice of MM strategy. Additionally, the variance partition analysis reproduced the metabolite-age association for tCr and tCho found in the simpler correlation analysis. In summary, the inclusion of a single high signal-to-noise ratio MM basis function (cohort-mean) in the short-TE LCM leads to more lower model residuals and AIC values compared with MM strategies with more degrees of freedom (Gaussian parametrization) or subject-specific MM information. Integration of multiple LCM analyses into a single statistical model potentially allows to identify the robustness in the detection of underlying effects (e.g., metabolite vs. age), reduces algorithm-based bias, and estimates algorithm-related variance.

MP-PCA denoising for diffusion MRS data: promises and pitfalls

Diffusion-weighted (DW) magnetic resonance spectroscopy (MRS) suffers from a lower signal to noise ratio (SNR) compared to conventional MRS owing to the addition of diffusion attenuation. This technique can therefore strongly benefit from noise reduction strategies. In the present work, Marchenko-Pastur principal component analysis (MP-PCA) denoising is tested on Monte Carlo simulations and on in vivo DW-MRS data acquired at 9.4 T in rat brain and at 3 T in human brain. We provide a descriptive study of the effects observed following different MP-PCA denoising strategies (denoising the entire matrix versus using a sliding window), in terms of apparent SNR, rank selection, noise correlation within and across b-values and quantification of metabolite concentrations and fitted diffusion coefficients. MP-PCA denoising yielded an increased apparent SNR, a more accurate B0 drift correction between shots, and similar estimates of metabolite concentrations and diffusivities compared to the raw data. No spectral residuals on individual shots were observed but correlations in the noise level across shells were introduced, an effect which was mitigated using a sliding window, but which should be carefully considered.

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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In vivo macromolecule signals in rat brain 1 H-MR spectra at 9.4T: Parametrization, spline baseline estimation, and T2 relaxation times

PURPOSE

Reliable detection and fitting of macromolecules (MM) are crucial for accurate quantification of brain short-echo time (TE) ¹ H-MR spectra. An experimentally acquired single MM spectrum is commonly used. Higher spectral resolution at ultra-high field (UHF) led to increased interest in using a parametrized MM spectrum together with flexible spline baselines to address unpredicted spectroscopic components. Herein, we aimed to: (1) implement an advanced methodological approach for post-processing, fitting, and parametrization of 9.4T rat brain MM spectra; (2) assess the concomitant impact of the LCModel baseline and MM model (ie, single vs parametrized); and (3) estimate the apparent T₂ relaxation times for seven MM components.

METHODS

A single inversion recovery sequence combined with advanced AMARES prior knowledge was used to eliminate the metabolite residuals, fit, and parametrize 10 MM components directly from 9.4T rat brain in vivo ¹ H-MR spectra at different TEs. Monte Carlo simulations were also used to assess the concomitant influence of parametrized MM and DKNTMN parameter in LCModel.

RESULTS

A very stiff baseline (DKNTMN ≥ 1 ppm) in combination with a single MM spectrum led to deviations in metabolite concentrations. For some metabolites the parametrized MM showed deviations from the ground truth for all DKNTMN values. Adding prior knowledge on parametrized MM improved MM and metabolite quantification. The apparent T₂ ranged between 12 and 24 ms for seven MM peaks.

CONCLUSION

Moderate flexibility in the spline baseline was required for reliable quantification of real/experimental spectra based on in vivo and Monte Carlo data. Prior knowledge on parametrized MM improved MM and metabolite quantification.

Contribution of macromolecules to brain 1 H MR spectra: Experts' consensus recommendations

Proton MR spectra of the brain, especially those measured at short and intermediate echo times, contain signals from mobile macromolecules (MM). A description of the main MM is provided in this consensus paper. These broad peaks of MM underlie the narrower peaks of metabolites and often complicate their quantification but they also may have potential importance as biomarkers in specific diseases. Thus, separation of broad MM signals from low molecular weight metabolites enables accurate determination of metabolite concentrations and is of primary interest in many studies. Other studies attempt to understand the origin of the MM spectrum, to decompose it into individual spectral regions or peaks and to use the components of the MM spectrum as markers of various physiological or pathological conditions in biomedical research or clinical practice. The aim of this consensus paper is to provide an overview and some recommendations on how to handle the MM signals in different types of studies together with a list of open issues in the field, which are all summarized at the end of the paper.

Separation of Metabolites and Macromolecules for Short-TE 1H-MRSI Using Learned Component-Specific Representations

Short-echo-time (TE) proton magnetic resonance spectroscopic imaging (MRSI) allows for simultaneously mapping a number of molecules in the brain, and has been recognized as an important tool for studying in vivo biochemistry in various neuroscience and disease applications. However, separation of the metabolite and macromolecule (MM) signals present in the short-TE data with significant spectral overlaps remains a major technical challenge. This work introduces a new approach to solve this problem by integrating imaging physics and representation learning. Specifically, a mixed unsupervised and supervised learning-based strategy was developed to learn the metabolite and MM-specific low-dimensional representations using deep autoencoders. A constrained reconstruction formulation is proposed to integrate the MRSI spatiospectral encoding model and the learned representations as effective constraints for signal separation. An efficient algorithm was developed to solve the resulting optimization problem with provable convergence. Simulation and experimental results have been obtained to demonstrate the component-specific representation power of the learned models and the capability of the proposed method in separating metabolite and MM signals for practical short-TE [Formula: see text]-MRSI data.

Excitatory/inhibitory neuronal metabolic balance in mouse hippocampus upon infusion of [U-13C6]glucose

Hippocampus plays a critical role in linking brain energetics and behavior typically associated to stress exposure. In this study, we aimed to simultaneously assess excitatory and inhibitory neuronal metabolism in mouse hippocampus in vivo by applying ¹⁸FDG-PET and indirect ¹³C magnetic resonance spectroscopy (¹H-[¹³C]-MRS) at 14.1 T upon infusion of uniformly ¹³C-labeled glucose ([U-¹³C₆]Glc). Improving the spectral fitting by taking into account variable decoupling efficiencies of [U-¹³C₆]Glc and refining the compartmentalized model by including two γ-aminobutyric acid (GABA) pools permit us to evaluate the relative contributions of glutamatergic and GABAergic metabolism to total hippocampal neuroenergetics. We report that GABAergic activity accounts for ∼13% of total neurotransmission (V_NT) and ∼27% of total neuronal TCA cycle (V_TCA) in mouse hippocampus suggesting a higher V_TCA/V_NT ratio for inhibitory neurons compared to excitatory neurons. Finally, our results provide new strategies and tools for bringing forward the developments and applications of ¹³C-MRS in specific brain regions of small animals.

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.

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 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.

A practical guide to in vivo proton magnetic resonance spectroscopy at high magnetic fields

Localized proton magnetic resonance spectroscopy (¹H-MRS) is a noninvasive tool for measuring in vivo neurochemical information in animal and human brains. With the increase of magnetic field strength, whereas localized ¹H-MRS benefits from higher sensitivity and spectral dispersion, it is challenged by increased spatial inhomogeneity of the B₀ and B₁ fields, larger chemical shift displacement error, and shortened T₂ relaxation times of metabolites. Advanced localized ¹H-MRS methodologies developed for high magnetic fields have shown promising results and allow the measurement of neurochemical profiles with up to 19 brain metabolites, including less-abundant metabolites, such as glutathione, glycine, γ-aminobutyric acid and ascorbate. To provide a practical guide for conducting in vivo¹H-MRS studies at high magnetic field strength, we reviewed various essential technical aspects from data acquisition (hardware requirements, B₁ and B₀ inhomogeneity, water suppression, localization sequences and acquisition strategies) to data processing (frequency and phase correction, spectral quality control, spectral fitting and concentration referencing). Additionally, we proposed guidelines for choosing the most appropriate data acquisition and processing approaches to maximize the achievable neurochemical information.

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.

The age dependence of T2 relaxation times of N-acetyl aspartate, creatine and choline in the human brain at 3 and 4T

Knowledge of the T2 age dependence is of importance for MRS clinical studies involving subject groups with a wide age range. A number of studies have focused on the age dependence of T2 values in the human brain, with rather conflicting results. The aim of this study was to analyze the age dependence of T2 values of N-acetyl aspartate (NAA), creatine (Cr) and choline (Cho) in the human brain using data acquired at 3T and 4T and to assess the influence of the macromolecule (MM) baseline handling on the obtained results. Two distinct groups of young and elderly controls have been measured at 3T (TE = 30-540 ms, 9 young and 11 elderly subjects) and 4T (TE = 10-180 ms, 18 young and 14 elderly subjects) using single-voxel spectroscopy. In addition, MM spectra were measured from two subjects using the inversion-recovery technique at 4T. All spectra were processed with LCModel using basis sets with different MM signals (measured or simulated) and also with MM signals included for a different TE range. Individual estimated T2 values were statistically analyzed using the R programming language for the age dependence of T2 values as well as the influence of the MM baseline handling. A significant decrease of T2 values of NAA and Cr in elderly subjects compared with young subjects was confirmed. The same trend was observed for Cho. Significantly higher T2 values calculated using the measured MM baseline for all studied metabolites at 4T were observed for both young and elderly subjects. To conclude, while the handling of MM and lipid signals may have a significant effect on estimated T2 values, we confirmed the age dependence of T2 values of NAA and Cr and the same trend for Cho in the human brain. Copyright © 2016 John Wiley & Sons, Ltd.

Separation of small metabolites and lipids in spectra from biopsies by diffusion-weighted HR-MAS NMR: a feasibility study

High Resolution Magic Angle Spinning (HR-MAS) NMR allows metabolic characterization of biopsies. HR-MAS spectra from tissues of most organs show strong lipid contributions that are overlapping metabolite regions, which hamper metabolite estimation. Metabolite quantification and analysis would benefit from a separation of lipids and small metabolites. Generally, a relaxation filter is used to reduce lipid contributions. However, the strong relaxation filter required to eliminate most of the lipids also reduces the signals for small metabolites. The aim of our study was therefore to investigate different diffusion editing techniques in order to employ diffusion differences for separating lipid and small metabolite contributions in the spectra from different organs for unbiased metabonomic analysis. Thus, 1D and 2D diffusion measurements were performed, and pure lipid spectra that were obtained at strong diffusion weighting (DW) were subtracted from those obtained at low DW, which include both small metabolites and lipids. This subtraction yielded almost lipid free small metabolite spectra from muscle tissue. Further improved separation was obtained by combining a 1D diffusion sequence with a T2-filter, with the subtraction method eliminating residual lipids from the spectra. Similar results obtained for biopsies of different organs suggest that this method is applicable in various tissue types. The elimination of lipids from HR-MAS spectra and the resulting less biased assessment of small metabolites have potential to remove ambiguities in the interpretation of metabonomic results. This is demonstrated in a reproducibility study on biopsies from human muscle.

Assessment of metabolic fluxes in the mouse brain in vivo using 1H-[13C] NMR spectroscopy at 14.1 Tesla

(13)C magnetic resonance spectroscopy (MRS) combined with the administration of (13)C labeled substrates uniquely allows to measure metabolic fluxes in vivo in the brain of humans and rats. The extension to mouse models may provide exclusive prospect for the investigation of models of human diseases. In the present study, the short-echo-time (TE) full-sensitivity (1)H-[(13)C] MRS sequence combined with high magnetic field (14.1 T) and infusion of [U-(13)C6] glucose was used to enhance the experimental sensitivity in vivo in the mouse brain and the (13)C turnover curves of glutamate C4, glutamine C4, glutamate+glutamine C3, aspartate C2, lactate C3, alanine C3, γ-aminobutyric acid C2, C3 and C4 were obtained. A one-compartment model was used to fit (13)C turnover curves and resulted in values of metabolic fluxes including the tricarboxylic acid (TCA) cycle flux VTCA (1.05 ± 0.04 μmol/g per minute), the exchange flux between 2-oxoglutarate and glutamate Vx (0.48 ± 0.02 μmol/g per minute), the glutamate-glutamine exchange rate V(gln) (0.20 ± 0.02 μmol/g per minute), the pyruvate dilution factor K(dil) (0.82 ± 0.01), and the ratio for the lactate conversion rate and the alanine conversion rate V(Lac)/V(Ala) (10 ± 2). This study opens the prospect of studying transgenic mouse models of brain pathologies.

Is the macromolecule signal tissue-specific in healthy human brain? A (1)H MRS study at 7 Tesla in the occipital lobe

PURPOSE

The macromolecule signal plays a key role in the precision and the accuracy of the metabolite quantification in short-TE (1) H MR spectroscopy. Macromolecules have been reported at 1.5 Tesla (T) to depend on the cerebral studied region and to be age specific. As metabolite concentrations vary locally, information about the profile of the macromolecule signal in different tissues may be of crucial importance.

METHODS

The aim of this study was to investigate, at 7T for healthy subjects, the neurochemical profile differences provided by macromolecule signal measured in two different tissues in the occipital lobe, predominantly composed of white matter tissue or of grey matter tissue.

RESULTS

White matter-rich macromolecule signal was relatively lower than the gray matter-rich macromolecule signal from 1.5 to 1.8 ppm and from 2.3 to 2.5 ppm with mean difference over these regions of 7% and 12% (relative to the reference peak at 0.9 ppm), respectively. The neurochemical profiles, when using either of the two macromolecule signals, were similar for 11 reliably quantified metabolites (CRLB < 20%) with relatively small concentration differences (< 0.3 μmol/g), except Glu (± 0.8 μmol/g).

CONCLUSION

Given the small quantification differences, we conclude that a general macromolecule baseline provides a sufficiently accurate neurochemical profile in occipital lobe at 7T in healthy human brain.

Quantification of the neurochemical profile using simulated macromolecule resonances at 3 T

The broad resonances underlying the entire (1) H NMR spectrum of the brain, ascribed to macromolecules, can influence metabolite quantification. At the intermediate field strength of 3 T, distinct approaches for the determination of the macromolecule signal, previously used at either 1.5 or 7 T and higher, may become equivalent. The aim of this study was to evaluate, at 3 T for healthy subjects using LCModel, the impact on the metabolite quantification of two different macromolecule approaches: (i) experimentally measured macromolecules; and (ii) mathematically estimated macromolecules. Although small, but significant, differences in metabolite quantification (up to 23% for glutamate) were noted for some metabolites, 10 metabolites were quantified reproducibly with both approaches with a Cramer-Rao lower bound below 20%, and the neurochemical profiles were therefore similar. We conclude that the mathematical approximation can provide sufficiently accurate and reproducible estimation of the macromolecule contribution to the (1) H spectrum at 3 T.

Quantification issues of in vivo (1) H NMR spectroscopy of the rat brain investigated at 16.4 T

The accuracy and precision of the quantification of metabolite concentrations in in vivo (1) H NMR spectroscopy are affected by linewidth and signal-to-noise ratio (SNR). To study the effect of both factors in in vivo (1) H NMR spectra acquired at ultrahigh field, a reference spectrum was generated by summing nine in vivo (1) H NMR spectra obtained in rat brain with a STEAM sequence at 16.4 T. By progressive deterioration of linewidth and SNR, 6400 single spectra were generated. In an accuracy study, the variation in the mean concentrations of five metabolites was mainly dependent on SNR, whereas 11 metabolites were predominantly susceptible to the linewidth. However, the standard deviations of the concentrations obtained were dependent almost exclusively on the SNR. An insignificant correlation was found between most of the heavily overlapping metabolite peaks, indicating independent and reliable quantification. Two different approaches for the consideration of macromolecular signals were evaluated. The use of prior knowledge derived by parameterization of a metabolite-nulled spectrum demonstrated improved fitting quality, with reduced Cramér-Rao lower bounds, compared to the calculation of a regularized spline baseline.

Cerebral glutamine metabolism under hyperammonemia determined in vivo by localized (1)H and (15)N NMR spectroscopy

Brain glutamine synthetase (GS) is an integral part of the glutamate-glutamine cycle and occurs in the glial compartment. In vivo Magnetic Resonance Spectroscopy (MRS) allows noninvasive measurements of the concentrations and synthesis rates of metabolites. (15)N MRS is an alternative approach to (13)C MRS. Incorporation of labeled (15)N from ammonia in cerebral glutamine allows to measure several metabolic reactions related to nitrogen metabolism, including the glutamate-glutamine cycle. To measure (15)N incorporation into the position 5N of glutamine and position 2N of glutamate and glutamine, we developed a novel (15)N pulse sequence to simultaneously detect, for the first time, [5-(15)N]Gln and [2-(15)N]Gln+Glu in vivo in the rat brain. In addition, we also measured for the first time in the same experiment localized (1)H spectra for a direct measurement of the net glutamine accumulation. Mathematical modeling of (1)H and (15)N MRS data allowed to reduce the number of assumptions and provided reliable determination of GS (0.30±0.050 μmol/g per minute), apparent neurotransmission (0.26±0.030 μmol/g per minute), glutamate dehydrogenase (0.029±0.002 μmol/g per minute), and net glutamine accumulation (0.033±0.001 μmol/g per minute). These results showed an increase of GS and net glutamine accumulation under hyperammonemia, supporting the concept of their implication in cerebral ammonia detoxification.

A two-compartment mathematical model of neuroglial metabolism using [1-(11)C] acetate

The purpose of this study was to develop a two-compartment metabolic model of brain metabolism to assess oxidative metabolism from [1-(11)C] acetate radiotracer experiments, using an approach previously applied in (13)C magnetic resonance spectroscopy (MRS), and compared with an one-tissue compartment model previously used in brain [1-(11)C] acetate studies. Compared with (13)C MRS studies, (11)C radiotracer measurements provide a single uptake curve representing the sum of all labeled metabolites, without chemical differentiation, but with higher temporal resolution. The reliability of the adjusted metabolic fluxes was analyzed with Monte-Carlo simulations using synthetic (11)C uptake curves, based on a typical arterial input function and previously published values of the neuroglial fluxes V(tca)(g), V(x), V(nt), and V(tca)(n) measured in dynamic (13)C MRS experiments. Assuming V(x)(g)=10 × V(tca)(g) and V(x)(n)=V(tca)(n), it was possible to assess the composite glial tricarboxylic acid (TCA) cycle flux V(gt)(g) (V(gt)(g)=V(x)(g) × V(tca)(g)/(V(x)(g)+V(tca)(g))) and the neurotransmission flux V(nt) from (11)C tissue-activity curves obtained within 30 minutes in the rat cortex with a beta-probe after a bolus infusion of [1-(11)C] acetate (n=9), resulting in V(gt)(g)=0.136±0.042 and V(nt)=0.170±0.103 μmol/g per minute (mean±s.d. of the group), in good agreement with (13)C MRS measurements.