Quantification of in vivo ³¹P NMR brain spectra using LCModel

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.

Magnetic Field Dependence of Spectral Correlations between 31P-Containing Metabolites in Brain

Spectral correlations between metabolites in ³¹P magnetic resonance spectroscopy (MRS) spectra of human brain were compared at 3 and 7 Tesla, the two commonly used magnetic field strengths for clinical research. It was found that at both field strengths, there are significant correlations between ³¹P-containing metabolites arising from spectral overlap, and their downfield correlations are markedly altered by the background spectral baseline. Overall, the spectral correlations between ³¹P-containing metabolites are markedly reduced at 7 Tesla with the increased chemical shift dispersion and the decreased membrane phospholipid signal. The findings provide the quantitative landscape of pre-existing correlations in ³¹P MRS spectra due to overlapping signals. Detailed procedures for quantifying the pre-existing correlations between ³¹P-containing metabolites are presented to facilitate incorporation of spectral correlations into statistical modeling in clinical correlation studies.

In vivo magnetic resonance <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow><mml:msup><mml:mrow/> <mml:mrow><mml:mn>31</mml:mn></mml:mrow> </mml:msup> </mml:mrow> </mml:math> P-Spectral Analysis With Neural Networks: 31P-SPAWNN

PURPOSE

We have introduced an artificial intelligence framework, 31P-SPAWNN, in order to fully analyze phosphorus-31 ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics> <mml:mrow><mml:msup><mml:mrow/> <mml:mrow><mml:mn>31</mml:mn></mml:mrow> </mml:msup> </mml:mrow> <mml:annotation>$$ {}^{31} $$</mml:annotation></mml:semantics> </mml:math> P) magnetic resonance spectra. The flexibility and speed of the technique rival traditional least-square fitting methods, with the performance of the two approaches, are compared in this work.

THEORY AND METHODS

Convolutional neural network architectures have been proposed for the analysis and quantification of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics> <mml:mrow><mml:msup><mml:mrow/> <mml:mrow><mml:mn>31</mml:mn></mml:mrow> </mml:msup> </mml:mrow> <mml:annotation>$$ {}^{31} $$</mml:annotation></mml:semantics> </mml:math> P-spectroscopy. The generation of training and test data using a fully parameterized model is presented herein. In vivo unlocalized free induction decay and three-dimensional <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics> <mml:mrow><mml:msup><mml:mrow/> <mml:mrow><mml:mn>31</mml:mn></mml:mrow> </mml:msup> </mml:mrow> <mml:annotation>$$ {}^{31} $$</mml:annotation></mml:semantics> </mml:math> P-magnetic resonance spectroscopy imaging data were acquired from healthy volunteers before being quantified using either 31P-SPAWNN or traditional least-square fitting techniques.

RESULTS

The presented experiment has demonstrated both the reliability and accuracy of 31P-SPAWNN for estimating metabolite concentrations and spectral parameters. Simulated test data showed improved quantification using 31P-SPAWNN compared with LCModel. In vivo data analysis revealed higher accuracy at low signal-to-noise ratio using 31P-SPAWNN, yet with equivalent precision. Processing time using 31P-SPAWNN can be further shortened up to two orders of magnitude.

CONCLUSION

The accuracy, reliability, and computational speed of the method open new perspectives for integrating these applications in a clinical setting.

Signal-to-Noise Ratio Enhancement of Single-Voxel In Vivo 31P and 1H Magnetic Resonance Spectroscopy in Mice Brain Data Using Low-Rank Denoising

Magnetic resonance spectroscopy (MRS) is a noninvasive technique for measuring metabolite concentration. It can be used for preclinical small animal brain studies using rodents to provide information about neurodegenerative diseases and metabolic disorders. However, data acquisition from small volumes in a limited scan time is technically challenging due to its inherently low sensitivity. To mitigate this problem, this study investigated the feasibility of a low-rank denoising method in enhancing the quality of single voxel multinuclei (³¹P and ¹H) MRS data at 9.4 T. Performance was evaluated using in vivo MRS data from a normal mouse brain (³¹P and ¹H) and stroke mouse model (¹H) by comparison with signal-to-noise ratios (SNRs), Cramer-Rao lower bounds (CRLBs), and metabolite concentrations of a linear combination of model analysis results. In ³¹P MRS data, low-rank denoising resulted in improved SNRs and reduced metabolite quantification uncertainty compared with the original data. In ¹H MRS data, the method also improved the SNRs, CRLBs, but it performed better for ³¹P MRS data with relatively simpler patterns compared to the ¹H MRS data. Therefore, we suggest that the low-rank denoising method can improve spectra SNR and metabolite quantification uncertainty in single-voxel in vivo ³¹P and ¹H MRS data, and it might be more effective for ³¹P MRS data. The main contribution of this study is that we demonstrated the effectiveness of the low-rank denoising method on small-volume single-voxel MRS data. We anticipate that our results will be useful for the precise quantification of low-concentration metabolites, further reducing data acquisition voxel size, and scan time in preclinical MRS studies.

Phosphorus MRS of healthy human spleen

Phosphorus (³¹ P-) MRS in vivo enables detection and quantification of important phosphorus-containing metabolites in biological tissues. ³¹ P-MRS of the normal spleen is challenging due to the relatively small volume and the larger distance between the spleen and surface coil. However, reference spectra of the healthy spleen are invaluable in studies of splenic malignancies and benign causes of splenomegaly, as well as in the study of its physiology. The purpose of this work was to investigate the feasibility of localized ³¹ P-MRS of healthy spleen in situ in a clinically acceptable measurement time using a clinical 3 T MR scanner. In this work, ³¹ P spectra of five healthy volunteers were measured using single-voxel image-selected in vivo spectroscopy (ISIS). The measurement sequence was augmented by broadband proton decoupling and nuclear Overhauser effect enhancement. It is demonstrated that localized ³¹ P-MRS of the spleen in situ using single-voxel ISIS is feasible on a clinical 3 T scanner in a clinically acceptable acquisition time. However, results have to be corrected for the transmitter excitation profile, and chemical shift displacement errors need to be taken into consideration during placement of the volume of interest. Results presented here could be used as a reference in future studies of splenomegaly caused by haematological malignancies.

Phosphorus transversal relaxation times and metabolite concentrations in the human brain at 9.4 T

A method to estimate phosphorus (³¹ P) transversal relaxation times (T₂ s) of coupled spin systems is demonstrated. Additionally, intracellular and extracellular pH and relaxation-corrected metabolite concentrations are reported. Echo time (TE) series of ³¹ P metabolite spectra were acquired using stimulated echo acquisition mode (STEAM) localization. Spectra were fitted using LCModel with accurately modeled Versatile Simulation, Pulses and Analysis (VeSPA) basis sets accounting for J-evolution of the coupled spin systems. T₂ s were estimated by fitting a single exponential two-parameter model across the TE series. Fitted inorganic phosphate frequencies were used to calculate pH, and estimated relaxation times were used to determine the relaxation-corrected brain metabolite concentrations on an assumption of 3 mM γ-ATP. The method was demonstrated in healthy human brain at a field strength of 9.4 T. T₂ times of ATP and nicotinamide adenine dinucleotide (NAD) were shortest between 8 and 20 ms, followed by T₂ s of inorganic phosphate between 25 and 50 ms, and phosphocreatine with a T₂ of 100 ms. Phosphomonoesters and phosphodiesters had the longest T₂ s of about 130 ms. The measured T₂ s are comparable with literature values and fit in a decreasing trend with increasing field strengths. Calculated pHs and metabolite concentrations are also comparable with literature values.

The NADPARK study: A randomized phase I trial of nicotinamide riboside supplementation in Parkinson's disease

We conducted a double-blinded phase I clinical trial to establish whether nicotinamide adenine dinucleotide (NAD) replenishment therapy, via oral intake of nicotinamide riboside (NR), is safe, augments cerebral NAD levels, and impacts cerebral metabolism in Parkinson's disease (PD). Thirty newly diagnosed, treatment-naive patients received 1,000 mg NR or placebo for 30 days. NR treatment was well tolerated and led to a significant, but variable, increase in cerebral NAD levels-measured by ³¹phosphorous magnetic resonance spectroscopy-and related metabolites in the cerebrospinal fluid. NR recipients showing increased brain NAD levels exhibited altered cerebral metabolism, measured by ¹⁸fluoro-deoxyglucose positron emission tomography, and this was associated with mild clinical improvement. NR augmented the NAD metabolome and induced transcriptional upregulation of processes related to mitochondrial, lysosomal, and proteasomal function in blood cells and/or skeletal muscle. Furthermore, NR decreased the levels of inflammatory cytokines in serum and cerebrospinal fluid. Our findings nominate NR as a potential neuroprotective therapy for PD, warranting further investigation in larger trials.

In Vitro 31P MR Chemical Shifts of In Vivo-Detectable Metabolites at 3T as a Basis Set for a Pilot Evaluation of Skeletal Muscle and Liver 31P Spectra with LCModel Software

Most in vivo ³¹P MR studies are realized on 3T MR systems that provide sufficient signal intensity for prominent phosphorus metabolites. The identification of these metabolites in the in vivo spectra is performed by comparing their chemical shifts with the chemical shifts measured in vitro on high-field NMR spectrometers. To approach in vivo conditions at 3T, a set of phantoms with defined metabolite solutions were measured in a 3T whole-body MR system at 7.0 and 7.5 pH, at 37 °C. A free induction decay (FID) sequence with and without ¹H decoupling was used. Chemical shifts were obtained of phosphoenolpyruvate (PEP), phosphatidylcholine (PtdC), phosphocholine (PC), phosphoethanolamine (PE), glycerophosphocholine (GPC), glycerophosphoetanolamine (GPE), uridine diphosphoglucose (UDPG), glucose-6-phosphate (G6P), glucose-1-phosphate (G1P), 2,3-diphosphoglycerate (2,3-DPG), nicotinamide adenine dinucleotide (NADH and NAD⁺), phosphocreatine (PCr), adenosine triphosphate (ATP), adenosine diphosphate (ADP), and inorganic phosphate (Pi). The measured chemical shifts were used to construct a basis set of ³¹P MR spectra for the evaluation of ³¹P in vivo spectra of muscle and the liver using LCModel software (linear combination model). Prior knowledge was successfully employed in the analysis of previously acquired in vivo data.

Acquisition and quantification pipeline for in vivo hyperpolarized 13 C MR spectroscopy

PURPOSE

The goal of this study was to combine a specialized acquisition method with a new quantification pipeline to accurately and efficiently probe the metabolism of hyperpolarized ¹³ C-labeled compounds in vivo. In this study, we tested our approach on [2-¹³ C]pyruvate and [1-¹³ C]α-ketoglutarate data in rat orthotopic brain tumor models at 3T.

METHODS

We used a multiband metabolite-specific radiofrequency (RF) excitation in combination with a variable flip angle scheme to minimize substrate polarization loss and measure fast metabolic processes. We then applied spectral-temporal denoising using singular value decomposition to enhance spectral quality. This was combined with LCModel-based automatic ¹³ C spectral fitting and flip angle correction to separate overlapping signals and rapidly quantify the different metabolites.

RESULTS

Denoising improved the metabolite signal-to-noise ratio (SNR) by approximately 5. It also improved the accuracy of metabolite quantification as evidenced by a significant reduction of the Cramer Rao lower bounds. Furthermore, the use of the automated and user-independent LCModel-based quantification approach could be performed rapidly, with the kinetic quantification of eight metabolite peaks in a 12-spectrum array achieved in less than 1 minute.

CONCLUSION

The specialized acquisition method combined with denoising and a new quantification pipeline using LCModel for the first time for hyperpolarized ¹³ C data enhanced our ability to monitor the metabolism of [2-¹³ C]pyruvate and [1-¹³ C]α-ketoglutarate in rat orthotopic brain tumor models in vivo. This approach could be broadly applicable to other hyperpolarized agents both preclinically and in the clinical setting.

ProFit-1D-A 1D fitting software and open-source validation data sets

PURPOSE

Accurate and precise MRS fitting is crucial for metabolite concentration quantification of ¹ H-MRS spectra. LCModel, a spectral fitting software, has shown to have certain limitations to perform advanced spectral fitting by previous literature. Herein, we propose an open-source spectral fitting algorithm with adaptive spectral baseline determination and more complex cost functions.

THEORY

The MRS spectra are characterized by several parameters, which reflect the environment of the contributing metabolites, properties of the acquisition sequence, or additional disturbances. Fitting parameters should accurately describe these parameters. Baselines are also a major contributor to MRS spectra, in which smoothness of the spline baselines used for fitting can be adjusted based on the properties of the spectra. Three different cost functions used for the minimization problem were also investigated.

METHODS

The newly developed ProFit-1D fitting algorithm is systematically evaluated for simulations of several types of possible in vivo parameter variations. Although accuracy and precision are tested with simulated spectra, spectra measured in vivo at 9.4 T are used for testing precision using subsets of averages. ProFit-1D fitting results are also compared with LCModel.

RESULTS

Both ProFit-1D and LCModel fitted the spectra well with induced parameter and baseline variations. ProFit-1D proved to be more accurate than LCModel for simulated spectra. However, LCModel showed a somewhat increased precision for some spectral simulations and for in vivo data.

CONCLUSION

The open-source ProFit-1D fitting algorithm demonstrated high accuracy while maintaining precise metabolite concentration quantification. Finally, through the newly proposed cost functions, new ways to improve fitting were shown.

Cerebral phosphoester signals measured by 31P magnetic resonance spectroscopy at 3 and 7 Tesla

Abnormal cell membrane metabolism is associated with many neuropsychiatric disorders. Free phosphomonoesters and phosphodiesters, which can be detected by in vivo 31P magnetic resonance spectroscopy (MRS), are important cell membrane building blocks. However, the quantification of phosphoesters has been highly controversial even in healthy individuals due to overlapping signals from macromolecule membrane phospholipids (MP). In this study, high signal-to-noise ratio (SNR) cerebral 31P MRS spectra were acquired from healthy volunteers at both 3 and 7 Tesla. Our results indicated that, with minimal spectral interference from MP, the [phosphocreatine (PCr)]/[phosphocholine (PC) + glycerophosphocholine (GPC)] ratio measured at 7 Tesla agreed with its value expected from biochemical constraints. In contrast, the 3 Tesla [PCr]/[PC+GPC] ratio obtained using standard spectral fitting procedures was markedly smaller than the 7 Tesla ratio and than the expected value. The analysis suggests that the commonly used spectral model for MP may fail to capture its complex spectral features at 3 Tesla, and that additional prior knowledge is necessary to reliably quantify the phosphoester signals at low magnetic field strengths when spectral overlapping is significant.

PCA denoising and Wiener deconvolution of 31 P 3D CSI data to enhance effective SNR and improve point spread function

Purpose

This study evaluates the performance of 2 processing methods, that is, principal component analysis‐based denoising and Wiener deconvolution, to enhance the quality of phosphorus 3D chemical shift imaging data.

Methods

Principal component analysis‐based denoising increases the SNR while maintaining spectral information. Wiener deconvolution reduces the FWHM of the voxel point spread function, which is increased by Hamming filtering or Hamming‐weighted acquisition. The proposed methods are evaluated using simulated and in vivo 3D phosphorus chemical shift imaging data by 1) visual inspection of the spatial signal distribution; 2) SNR calculation of the PCr peak; and 3) fitting of metabolite basis functions.

Results

With the optimal order of processing steps, we show that the effective SNR of in vivo phosphorus 3D chemical shift imaging data can be increased. In simulations, we show we can preserve phosphorus‐containing metabolite peaks that had an SNR < 1 before denoising. Furthermore, using Wiener deconvolution, we were able to reduce the FWHM of the voxel point spread function with only partially reintroducing Gibb‐ringing artifacts while maintaining the SNR. After data processing, fitting of the phosphorus‐containing metabolite signals improved.

Conclusion

In this study, we have shown that principal component analysis‐based denoising in combination with regularized Wiener deconvolution allows increasing the effective spectral SNR of in vivo phosphorus 3D chemical shift imaging data, with reduction of the FWHM of the voxel point spread function. Processing increased the effective SNR by at least threefold compared to Hamming weighted acquired data and minimized voxel bleeding. With these methods, fitting of metabolite amplitudes became more robust with decreased fitting residuals.

Abnormal Brain Bioenergetics in First-Episode Psychosis

BACKGROUND

Converging evidence indicates impaired brain energy metabolism in schizophrenia and other psychotic disorders. Creatine kinase (CK) is pivotal in providing adenosine triphosphate in the cell and maintaining its levels when energy demand is increased. However, the activity of CK has not been investigated in patients with first-episode schizophrenia spectrum disorders.

METHODS

Using in vivo phosphorus magnetization transfer spectroscopy, we measured CK first-order forward rate constant (k f ) in the frontal lobe, in patients with first-episode psychosis (FEP; n = 16) and healthy controls (n = 34), at rest.

RESULTS

CK k f was significantly reduced in FEP compared to healthy controls. There were no differences in other energy metabolism-related measures, including phosphocreatine (PCr) or ATP, between groups. We also found increase in glycerol-3-phosphorylcholine, a putative membrane breakdown product, in patients.

CONCLUSIONS

The results of this study indicate that brain bioenergetic abnormalities are already present early in the course of schizophrenia spectrum disorders. Future research is needed to identify the relationship of reduced CK k f with psychotic symptoms and to test treatment alternatives targeting this pathway. Increased glycerol-3-phosphorylcholine is consistent with earlier studies in medication-naïve patients and later studies in first-episode schizophrenia, and suggest enhanced synaptic pruning.

In vivo 31P magnetic resonance spectroscopy study of mouse cerebral NAD content and redox state during neurodevelopment

Nicotinamide adenine dinucleotide (NAD) is an important cofactor of energy-producing pathways. The redox ratio (NAD⁺/NADH) reflects the cellular oxidoreductive state. Oxidative stress and redox dysregulation have been suggested to contribute to various neurological diseases. The assessment of NAD content has been recently demonstrated in large animals and human brains by ³¹P magnetic resonance spectroscopy. However, its measurement in small rodents has never been attempted. The purpose of this study was to investigate, in vivo, the NAD content during mouse brain neurodevelopment. ³¹P-MR-spectra were acquired in the mouse brain at postnatal days P20, P40, P90 and P250 at 14.1 T using a 3D-localization sequence. High spectral quality was achieved at 14.1 T. NAD⁺ and NADH were quantified with mean Cramér-Rao lower bound of 10% and 14%, respectively. An increase in NAD⁺/NADH was observed from P20 to P250 due to a decrease in [NADH]. The intracellular pH was significantly reduced with age, while the free [Mg²⁺] in the brain was significantly increased. This study demonstrates for the first time the feasibility of the measurement of NAD content in vivo in mouse brains during development, which opens the prospect of longitudinally studying energy metabolism and redox dysfunction in mouse models of brain pathology.

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.

Constrained Magnetic Resonance Spectroscopic Imaging by Learning Nonlinear Low-Dimensional Models

Magnetic resonance spectroscopic imaging (MRSI) is a powerful molecular imaging modality but has very limited speed, resolution, and SNR tradeoffs. Construction of a low-dimensional model to effectively reduce the dimensionality of the imaging problem has recently shown great promise in improving these tradeoffs. This paper presents a new approach to model and reconstruct the spectroscopic signals by learning a nonlinear low-dimensional representation of the general MR spectra. Specifically, we trained a deep neural network to capture the low-dimensional manifold, where the high-dimensional spectroscopic signals reside. A regularization formulation is proposed to effectively integrate the learned model and physics-based data acquisition model for MRSI reconstruction with the capability to incorporate additional spatiospectral constraints. An efficient numerical algorithm was developed to solve the associated optimization problem involving back-propagating the trained network. Simulation and experimental results were obtained to demonstrate the representation power of the learned model and the ability of the proposed formulation in producing SNR-enhancing reconstruction from the practical MRSI data.

Automated multicomponent phospholipid analysis using 31P NMR spectroscopy: example of vegetable lecithin and krill oil

Nuclear magnetic resonance (NMR) spectroscopy is widely applied in the field of metabolomics due to its quantitative nature and the reproducibility of data generated. However, one of the main challenges in routine NMR analysis is to obtain valuable information from large datasets of raw data in a high-throughput, automatic, and reproducible manner. In this study, a method to automatically annotate and quantify 12 phospholipids (PLs) in vegetable lecithin (soy, sunflower, rape) and krill oil is introduced. Automated routines were written in MATLAB environment for quantification of phosphatidylcholine (PC), phosphatidylinositol (PI), lyso-phosphatidylcholine (LPC), phosphatidylserine (PS), phosphatidylethanolamine (PE), diphosphatidylglycerol or cardiolipin (DPG), phosphatidylglycerol (PG), and lyso-phosphatidylethanolamine (LPE) in lecithin and of PC, PC-ether, LPC, PE, N-acyl phosphatidylethanolamine (APE), and LPE in krill oil matrix. The routine includes NMR spectra import, extraction of data points, peaking of local minima and local maxima in the data, integration, quantitation against internal standard, reporting of results as Word file, and their importing in our internal database. Our extensive studies on a representative set of more than 1000 lecithin (soy, rape, sunflower) and krill samples showed that the routine can automatically and accurately calculate the concentrations of all PLs. No systematic or proportional differences between automated and manual evaluation were detected. The developed automated program produces accurate results and requires less than 5 s for each analysis. This tool is already used in high-throughput PL analysis of krill and lecithin and will be adjusted to other matrices (egg, milk, chocolate, etc.) as well.

CO2 induced pHi changes in the brain of polar fish: a TauCEST application

Chemical exchange saturation transfer (CEST) from taurine to water (TauCEST) can be used for in vivo mapping of taurine concentrations as well as for measurements of relative changes in intracellular pH (pH_i ) at temperatures below 37°C. Therefore, TauCEST offers the opportunity to investigate acid-base regulation and neurological disturbances of ectothermic animals living at low temperatures, and in particular to study the impact of ocean acidification (OA) on neurophysiological changes of fish. Here, we report the first in vivo application of TauCEST imaging. Thus, the study aimed to investigate the TauCEST effect in a broad range of temperatures (1-37°C) and pH (5.5-8.0), motivated by the high taurine concentration measured in the brains of polar fish. The in vitro data show that the TauCEST effect is especially detectable in the low temperature range and strictly monotonic for the relevant pH range (6.8-7.5). To investigate the specificity of TauCEST imaging for the brain of polar cod (Boreogadus saida) at 1.5°C simulations were carried out, indicating a taurine contribution of about 65% to the in vivo expected CEST effect, if experimental parameters are optimized. B. saida was acutely exposed to three different CO₂ concentrations in the sea water (control normocapnia; comparatively moderate hypercapnia OA_m  = 3300 μatm; high hypercapnia OA_h  = 4900 μatm). TauCEST imaging of the brain showed a significant increase in the TauCEST effect under the different CO₂ concentrations of about 1.5-3% in comparison with control measurements, indicative of changes in pH_i or metabolite concentration. Consecutive recordings of ¹ H MR spectra gave no support for a concentration induced change of the in vivo observed TauCEST effect. Thus, the in vivo application of TauCEST offers the possibility of mapping relative changes in pH_i in the brain of polar cod during exposure to CO₂ .

Nutritional Ketosis Increases NAD+/NADH Ratio in Healthy Human Brain: An in Vivo Study by 31P-MRS

Ketones represent an important alternative fuel for the brain under glucose hypo-metabolic conditions induced by neurological diseases or aging, however their metabolic consequences in healthy brain remain unclear. Here we report that ketones can increase the redox NAD⁺/NADH ratio in the resting brain of healthy young adults. As NAD is an important energetic and signaling metabolic modulator, these results provide mechanistic clues on how nutritional ketosis might contribute to the preservation of brain health.

Evidence for a "metabolically inactive" inorganic phosphate pool in adenosine triphosphate synthase reaction using localized 31P saturation transfer magnetic resonance spectroscopy in the rat brain at 11.7 T

With the increased spectral resolution made possible at high fields, a second, smaller inorganic phosphate resonance can be resolved on (31)P magnetic resonance spectra in the rat brain. Saturation transfer was used to estimate de novo adenosine triphosphate synthesis reaction rate. While the main inorganic phosphate pool is used by adenosine triphosphate synthase, the second pool is inactive for this reaction. Accounting for this new pool may not only help us understand (31)P magnetic resonance spectroscopy metabolic profiles better but also better quantify adenosine triphosphate synthesis.