Improved reproducibility of γ-aminobutyric acid measurement from short-echo-time proton MR spectroscopy by linewidth-matched basis sets in LCModel.

γ-Aminobutyric acid (GABA), as the primary inhibitory neurotransmitter, is extremely important for maintaining healthy brain function, and deviations from GABA homeostasis are related to various brain diseases. Short-echo-time (short-TE) proton MR spectroscopy (1 H-MRS) has been employed to measure GABA concentration from various human brain regions at high magnetic fields. The aim of this study was to investigate the effect of spectral linewidth on GABA quantification and explore the application of an optimized basis-set preparation approach using a spectral-linewidth-matched (LM) basis set in LCModel to improve the reproducibility of GABA quantification from short-TE 1 H-MRS. In contrast to the fixed-linewidth basis-set approach, the LM basis-set preparation approach, where all metabolite basis spectra were simulated with a linewidth 4 Hz narrower than that of water, showed a smaller standard deviation of estimated GABA concentration from synthetic spectra with varying linewidths and lineshapes. The test-retest reproducibility was assessed by the mean within-subject coefficient of variation, which improved from 19.2% to 12.0% in the thalamus, from 27.9% to 14.9% in the motor cortex, and from 9.7% to 2.8% in the medial prefrontal cortex using LM basis sets at 7 T. We conclude that spectral linewidth has a large effect on GABA quantification from short-TE 1 H-MRS data and that using LM basis sets in LCModel can improve the reproducibility of GABA quantification.

Deletion of Crtc1 leads to hippocampal neuroenergetic impairments associated with depressive-like behavior.

Mood disorders (MD) are a major burden on society as their biology remains poorly understood, challenging both diagnosis and therapy. Among many observed biological dysfunctions, homeostatic dysregulation, such as metabolic syndrome (MeS), shows considerable comorbidity with MD. Recently, CREB-regulated transcription coactivator 1 (CRTC1), a regulator of brain metabolism, was proposed as a promising factor to understand this relationship. Searching for imaging biomarkers and associating them with pathophysiological mechanisms using preclinical models can provide significant insight into these complex psychiatric diseases and help the development of personalized healthcare. Here, we used neuroimaging technologies to show that deletion of Crtc1 in mice leads to an imaging fingerprint of hippocampal metabolic impairment related to depressive-like behavior. By identifying a deficiency in hippocampal glucose metabolism as the underlying molecular/physiological origin of the markers, we could assign an energy-boosting mood-stabilizing treatment, ebselen, which rescued behavior and neuroimaging markers. Finally, our results point toward the GABAergic system as a potential therapeutic target for behavioral dysfunctions related to metabolic disorders. This study provides new insights on Crtc1's and MeS's relationship to MD and establishes depression-related markers with clinical potential.

PET CMRglc mapping and 1H-MRS show altered glucose uptake and neurometabolic profiles in BDL rats.

Type C hepatic encephalopathy (HE) is a complex neuropsychiatric disorder occurring as a consequence of chronic liver disease. Alterations in energy metabolism have been suggested in type C HE, but in vivo studies on this matter remain sparse and have reported conflicting results. Here, we propose a novel preclinical 18F-FDG PET methodology to compute quantitative 3D maps of the regional cerebral metabolic rate of glucose (CMRglc) from a labelling steady-state PET image of the brain and an image-derived input function. This quantitative approach shows its strength when comparing groups of animals with divergent physiology, such as HE animals. PET CMRglc maps were registered to an atlas and the mean CMRglc from the hippocampus and the cerebellum were associated to the corresponding localized 1H MR spectroscopy acquisitions. This study provides for the first time local and quantitative information on both brain glucose uptake and neurometabolic profile alterations in a rat model of type C HE. A 2-fold lower brain glucose uptake, concomitant with an increase in brain glutamine and a decrease in the main osmolytes, was observed in the hippocampus and in the cerebellum. These novel findings are an important step towards new insights into energy metabolism in the pathophysiology of HE.

Synchronous nonmonotonic changes in functional connectivity and white matter integrity in a rat model of sporadic Alzheimer's disease.

Brain glucose hypometabolism has been singled out as an important contributor and possibly main trigger to Alzheimer's disease (AD). Intracerebroventricular injections of streptozotocin (icv-STZ) cause brain glucose hypometabolism without systemic diabetes. Here, a first-time longitudinal study of brain glucose metabolism, functional connectivity and white matter microstructure was performed in icv-STZ rats using PET and MRI. Histological markers of pathology were tested at an advanced stage of disease. STZ rats exhibited altered functional connectivity and intra-axonal damage and demyelination in brain regions typical of AD, in a temporal pattern of acute injury, transient recovery/compensation and chronic degeneration. In the context of sustained glucose hypometabolism, these nonmonotonic trends - also reported in behavioral studies of this animal model as well as in human AD - suggest a compensatory mechanism, possibly recruiting ketone bodies, that allows a partial and temporary repair of brain structure and function. The early acute phase could thus become a valuable therapeutic window to strengthen the recovery phase and prevent or delay chronic degeneration, to be considered both in preclinical and clinical studies of AD. In conclusion, this work reveals the consequences of brain insulin resistance on structure and function, highlights signature nonmonotonic trajectories in their evolution and proposes potent MRI-derived biomarkers translatable to human AD and diabetic populations.

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.

Investigating the regional effect of the chemical shift displacement artefact on the J-modulated lactate signal at ultra high-field.

The present work aims to show the applicability of an analytical model for the optimisation of the STEAM sequence timing parameters for lactate detection at ultra high-field. The effects of the chemical shift displacement artefact on the J-modulated signal for a weakly-coupled spin system were considered in the three applied directions of field gradients and the product operator formalism was used to obtain expressions for the signal modulation in each compartment of the excited volume. The validity of this model was demonstrated experimentally at 7 T in a phantom and acquisitions with optimised parameters were performed on a healthy volunteer. The spectra acquired with TE = 144 ms with the optimised mixing time and TE = 288 ms showed easily detectable lactate peaks in the normal human brain. Additionally, the acquisition with the longer TE resulted in a spectrum with less lipid/macromolecular contamination. The simulations shown here demonstrated that the proposed analytical model is suitable for correctly predicting the resulting lactate signal. With the optimised parameters, it was possible to use a simple sequence with sufficient signal-to-noise ratio to reliably distinguish lactate from overlapping resonances in a healthy brain.

Measurement of brain lactate during visual stimulation using a long TE semi-LASER sequence at 7 T.

Estimation of metabolic changes during neuronal activation represents a challenge for in vivo MRS, especially for metabolites with low concentration and signal overlap, such as lactate. In this work, we aimed to evaluate the feasibility of detecting lactate during brain activation using a long TE (144 ms) semi-LASER sequence at 7 T. 1H spectra were acquired on healthy volunteers ( N=6 ) during a paradigm with 15 min of visual stimulation. Outer-volume signals were further attenuated by the use of saturation slabs, and macromolecular signals in the vicinity of the inverted lactate peak were individually fitted with simulated Lorentzian peaks. All spectra were free of artefacts and highly reproducible across subjects. Lactate was accurately quantified with an average Cramér-Rao lower bound of 8%. Statistically significant ( P<0.05 , one-tailed t -test) increases in lactate ( ∼ 10%) and glutamate ( ∼ 3%) levels during stimulation were detected in the visual cortex. Lactate and glutamate changes were consistent with previous measurements. We demonstrated that quantification of a clear and non-contaminated lactate peak obtained with a long TE sequence has the potential of improving the accuracy of functional MRS studies targeting non-oxidative reaction pathways.

Terminology and concepts for the characterization of in vivo MR spectroscopy methods and MR spectra: Background and experts' consensus recommendations.

With a 40-year history of use for in vivo studies, the terminology used to describe the methodology and results of magnetic resonance spectroscopy (MRS) has grown substantially and is not consistent in many aspects. Given the platform offered by this special issue on advanced MRS methodology, the authors decided to describe many of the implicated terms, to pinpoint differences in their meanings and to suggest specific uses or definitions. This work covers terms used to describe all aspects of MRS, starting from the description of the MR signal and its theoretical basis to acquisition methods, processing and to quantification procedures, as well as terms involved in describing results, for example, those used with regard to aspects of quality, reproducibility or indications of error. The descriptions of the meanings of such terms emerge from the descriptions of the basic concepts involved in MRS methods and examinations. This paper also includes specific suggestions for future use of terms where multiple conventions have emerged or coexisted in the past.

Magnetic resonance spectroscopy in the rodent brain: Experts' consensus recommendations.

In vivo MRS is a non-invasive measurement technique used not only in humans, but also in animal models using high-field magnets. MRS enables the measurement of metabolite concentrations as well as metabolic rates and their modifications in healthy animals and disease models. Such data open the way to a deeper understanding of the underlying biochemistry, related disturbances and mechanisms taking place during or prior to symptoms and tissue changes. In this work, we focus on the main preclinical 1H, 31P and 13C MRS approaches to study brain metabolism in rodent models, with the aim of providing general experts' consensus recommendations (animal models, anesthesia, data acquisition protocols). An overview of the main practical differences in preclinical compared with clinical MRS studies is presented, as well as the additional biochemical information that can be obtained in animal models in terms of metabolite concentrations and metabolic flux measurements. The properties of high-field preclinical MRS and the technical limitations are also described.

In vivo characterization of brain metabolism by 1 H MRS, 13 C MRS and 18 FDG PET reveals significant glucose oxidation of invasively growing glioma cells.

Glioblastoma are notorious for their highly invasive growth, diffusely infiltrating adjacent brain structures that precludes complete resection, and is a major obstacle for cure. To characterize this "invisible" tumor part, we designed a high resolution multimodal imaging approach assessing in vivo the metabolism of invasively growing glioma xenografts in the mouse brain. Animals were subjected longitudinally to magnetic resonance imaging (MRI) and 1 H spectroscopy (MRS) at ultra high field (14.1 Tesla) that allowed the measurement of 16 metabolic biomarkers to characterize the metabolic profiles. As expected, the neuronal functionality was progressively compromised as indicated by decreasing N-acetyl aspartate, glutamate and gamma-aminobutyric acid and reduced neuronal TCA cycle (-58%) and neurotransmission (-50%). The dynamic metabolic changes observed, captured differences in invasive growth that was modulated by re-expression of the tumor suppressor gene WNT inhibitory factor 1 (WIF1) in the orthotopic xenografts that attenuates invasion. At late stage mice were subjected to 13 C MRS with infusion of [1,6-13 C]glucose and 18 FDG positron emission tomography (PET) to quantify cell-specific metabolic fluxes involved in glucose metabolism. Most interestingly, this provided the first in vivo evidence for significant glucose oxidation in glioma cells. This suggests that the infiltrative front of glioma does not undergo the glycolytic switch per se, but that environmental triggers may induce metabolic reprograming of tumor cells.

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.

Progress towards in vivo brain 13C-MRS in mice: Metabolic flux analysis in small tissue volumes.

The combination of dynamic 13C MRS data under infusion of 13C-labelled substrates and compartmental models of cerebral metabolism enabled in vivo measurement of metabolic fluxes with a quantitative and distinct determination of cellular-specific activities. The non-invasive nature and the chemical specificity of the 13C dynamic data obtained in those tracer experiments makes it an attractive approach offering unique insights into cerebral metabolism. Genetically engineered mice present a wealth of disease models particularly interesting for the neuroscience community. Nevertheless, in vivo13C NMR studies of the mouse brain are only recently appearing in the field due to the numerous challenges linked to the small mouse brain volume and the difficulty to follow the mouse physiological parameters within the NMR system during the infusion experiment. This review will present the progresses in the quest for a higher in vivo13C signal-to-noise ratio up to the present state of the art techniques, which made it feasible to assess glucose metabolism in different regions of the mouse brain. We describe how experimental results were integrated into suitable compartmental models and how a deep understanding of cerebral metabolism depends on the reliable detection of 13C in the different molecules and carbon positions.

MRS studies of neuroenergetics and glutamate/glutamine exchange in rats: Extensions to hyperammonemic models.

In vivo Magnetic Resonance Spectroscopy is a useful tool to characterize brain biochemistry as well as its alteration in a large number of major central nervous system diseases. The present review will focus on the study of the glutamate-glutamine cycle, an important biochemical pathway in excitatory neurotransmission, analyzed using in vivo MRS of different accessible nuclei: 1H, 13C, 15N and 31P. The different methodological aspects of data acquisition, processing and absolute quantification of the MRS data for each nucleus will be presented, as well as the description of the mathematical modeling approach to interpret the MRS measurements in terms of biochemical kinetics. The unique advantages of MRS, especially its non-invasive nature enabling longitudinal monitoring of brain disease progression and/or effect of treatment is illustrated in the particular context of hyperammonemic disorders with a specific focus on animal models. We review the current possibilities given by in vivo MRS to investigate some of the molecular mechanisms involved in hyperammonemic disorders and to give a better understanding of the process of development of hepatic encephalopathy, a severe neuropsychiatric disorder that frequently accompanies liver disease.

1H and 31P magnetic resonance spectroscopy in a rat model of chronic hepatic encephalopathy: in vivo longitudinal measurements of brain energy metabolism.

Chronic liver disease (CLD) leads to a spectrum of neuropsychiatric disorders named hepatic encephalopathy (HE). Even though brain energy metabolism is believed to be altered in chronic HE, few studies have explored energy metabolism in CLD-induced HE, and their findings were inconsistent. The aim of this study was to characterize for the first time in vivo and longitudinally brain metabolic changes in a rat model of CLD-induced HE with a focus on energy metabolism, using the methodological advantages of high field proton and phosphorus Magnetic Resonance Spectroscopy (1H- and 31P-MRS). Wistar rats were bile duct ligated (BDL) and studied before BDL and at post-operative weeks 4 and 8. Glutamine increased linearly over time (+146 %) together with plasma ammonium (+159 %). As a compensatory effect, other brain osmolytes decreased: myo-inositol (-36 %), followed by total choline and creatine. A decrease in the neurotransmitters glutamate (-17 %) and aspartate (-28 %) was measured only at week 8, while no significant changes were observed for lactate and phosphocreatine. Among the other energy metabolites measured by 31P-MRS, we observed a non-significant decrease in ATP together with a significant decrease in ADP (-28 %), but only at week 8 after ligation. Finally, brain glutamine showed the strongest correlations with changes in other brain metabolites, indicating its importance in type C HE. In conclusion, mild alterations in some metabolites involved in energy metabolism were observed but only at the end stage of the disease when edema and neurological changes are already present. Therefore, our data indicate that impaired energy metabolism is not one of the major causes of early HE symptoms in the established model of type C HE.

New technologies - new insights into the pathogenesis of hepatic encephalopathy.

Hepatic encephalopathy (HE) is a neuropsychiatric syndrome which frequently accompanies acute or chronic liver disease. It is characterized by a variety of symptoms of different severity such as cognitive deficits and impaired motor functions. Currently, HE is seen as a consequence of a low grade cerebral oedema associated with the formation of cerebral oxidative stress and deranged cerebral oscillatory networks. However, the pathogenesis of HE is still incompletely understood as liver dysfunction triggers exceptionally complex metabolic derangements in the body which need to be investigated by appropriate technologies. This review summarizes technological approaches presented at the ISHEN conference 2014 in London which may help to gain new insights into the pathogenesis of HE. Dynamic in vivo 13C nuclear magnetic resonance spectroscopy was performed to analyse effects of chronic liver failure in rats on brain energy metabolism. By using a genomics approach, microRNA expression changes were identified in plasma of animals with acute liver failure which may be involved in interorgan interactions and which may serve as organ-specific biomarkers for tissue damage during acute liver failure. Genomics were also applied to analyse glutaminase gene polymorphisms in patients with liver cirrhosis indicating that haplotype-dependent glutaminase activity is an important pathogenic factor in HE. Metabonomics represents a promising approach to better understand HE, by capturing the systems level metabolic changes associated with disease in individuals, and enabling monitoring of metabolic phenotypes in real time, over a time course and in response to treatment, to better inform clinical decision making. Targeted fluxomics allow the determination of metabolic reaction rates thereby discriminating metabolite level changes in HE in terms of production, consumption and clearance.

In vivo quantification of neuro-glial metabolism and glial glutamate concentration using 1H-[13C] MRS at 14.1T.

Astrocytes have recently become a major center of interest in neurochemistry with the discoveries on their major role in brain energy metabolism. An interesting way to probe this glial contribution is given by in vivo (13) C NMR spectroscopy coupled with the infusion labeled glial-specific substrate, such as acetate. In this study, we infused alpha-chloralose anesthetized rats with [2-(13) C]acetate and followed the dynamics of the fractional enrichment (FE) in the positions C4 and C3 of glutamate and glutamine with high sensitivity, using (1) H-[(13) C] magnetic resonance spectroscopy (MRS) at 14.1T. Applying a two-compartment mathematical model to the measured time courses yielded a glial tricarboxylic acid (TCA) cycle rate (Vg ) of 0.27 ± 0.02 µmol/g/min and a glutamatergic neurotransmission rate (VNT ) of 0.15 ± 0.01 µmol/g/min. Glial oxidative ATP metabolism thus accounts for 38% of total oxidative metabolism measured by NMR. Pyruvate carboxylase (VPC ) was 0.09 ± 0.01 µmol/g/min, corresponding to 37% of the glial glutamine synthesis rate. The glial and neuronal transmitochondrial fluxes (Vx (g) and Vx (n) ) were of the same order of magnitude as the respective TCA cycle fluxes. In addition, we estimated a glial glutamate pool size of 0.6 ± 0.1 µmol/g. The effect of spectral data quality on the fluxes estimates was analyzed by Monte Carlo simulations. In this (13) C-acetate labeling study, we propose a refined two-compartment analysis of brain energy metabolism based on (13) C turnover curves of acetate, glutamate and glutamine measured with state of the art in vivo dynamic MRS at high magnetic field in rats, enabling a deeper understanding of the specific role of glial cells in brain oxidative metabolism. In addition, the robustness of the metabolic fluxes determination relative to MRS data quality was carefully studied.

Which prior knowledge? Quantification of in vivo brain 13C MR spectra following 13C glucose infusion using AMARES.

The recent developments in high magnetic field 13C magnetic resonance spectroscopy with improved localization and shimming techniques have led to important gains in sensitivity and spectral resolution of 13C in vivo spectra in the rodent brain, enabling the separation of several 13C isotopomers of glutamate and glutamine. In this context, the assumptions used in spectral quantification might have a significant impact on the determination of the 13C concentrations and the related metabolic fluxes. In this study, the time domain spectral quantification algorithm AMARES (advanced method for accurate, robust and efficient spectral fitting) was applied to 13 C magnetic resonance spectroscopy spectra acquired in the rat brain at 9.4 T, following infusion of [1,6-(13)C2 ] glucose. Using both Monte Carlo simulations and in vivo data, the goal of this work was: (1) to validate the quantification of in vivo 13C isotopomers using AMARES; (2) to assess the impact of the prior knowledge on the quantification of in vivo 13C isotopomers using AMARES; (3) to compare AMARES and LCModel (linear combination of model spectra) for the quantification of in vivo 13C spectra. AMARES led to accurate and reliable 13C spectral quantification similar to those obtained using LCModel, when the frequency shifts, J-coupling constants and phase patterns of the different 13C isotopomers were included as prior knowledge in the analysis.

Subject classification and cross-time prediction based on functional connectivity and white matter microstructure features in a rat model of Alzheimer's using machine learning.

BACKGROUND: The pathological process of Alzheimer's disease (AD) typically takes decades from onset to clinical symptoms. Early brain changes in AD include MRI-measurable features such as altered functional connectivity (FC) and white matter degeneration. The ability of these features to discriminate between subjects without a diagnosis, or their prognostic value, is however not established. METHODS: The main trigger mechanism of AD is still debated, although impaired brain glucose metabolism is taking an increasingly central role. Here, we used a rat model of sporadic AD, based on impaired brain glucose metabolism induced by an intracerebroventricular injection of streptozotocin (STZ). We characterized alterations in FC and white matter microstructure longitudinally using functional and diffusion MRI. Those MRI-derived measures were used to classify STZ from control rats using machine learning, and the importance of each individual measure was quantified using explainable artificial intelligence methods. RESULTS: Overall, combining all the FC and white matter metrics in an ensemble way was the best strategy to discriminate STZ rats, with a consistent accuracy over 0.85. However, the best accuracy early on was achieved using white matter microstructure features, and later on using FC. This suggests that consistent damage in white matter in the STZ group might precede FC. For cross-timepoint prediction, microstructure features also had the highest performance while, in contrast, that of FC was reduced by its dynamic pattern which shifted from early hyperconnectivity to late hypoconnectivity. CONCLUSIONS: Our study highlights the MRI-derived measures that best discriminate STZ vs control rats early in the course of the disease, with potential translation to humans.

In Vivo Metabolism of [1,6-13C2]Glucose Reveals Distinct Neuroenergetic Functionality between Mouse Hippocampus and Hypothalamus.

Glucose is a major energy fuel for the brain, however, less is known about specificities of its metabolism in distinct cerebral areas. Here we examined the regional differences in glucose utilization between the hypothalamus and hippocampus using in vivo indirect 13C magnetic resonance spectroscopy (1H-[13C]-MRS) upon infusion of [1,6-13C2]glucose. Using a metabolic flux analysis with a 1-compartment mathematical model of brain metabolism, we report that compared to hippocampus, hypothalamus shows higher levels of aerobic glycolysis associated with a marked gamma-aminobutyric acid-ergic (GABAergic) and astrocytic metabolic dependence. In addition, our analysis suggests a higher rate of ATP production in hypothalamus that is accompanied by an excess of cytosolic nicotinamide adenine dinucleotide (NADH) production that does not fuel mitochondria via the malate-aspartate shuttle (MAS). In conclusion, our results reveal significant metabolic differences, which might be attributable to respective cell populations or functional features of both structures.