Quantum-mechanical simulations for in vivo MR spectroscopy: Principles and possibilities demonstrated with the program NMRScopeB

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.

Brain metabolic derangements examined using 1H MRS and their (in)consistency among different rodent models of depression

Major depressive disorder (MDD) is underlined by neurochemical changes in the brain. Proton magnetic resonance spectroscopy (1H MRS) is a useful tool for their examination as it provides information about the levels of metabolites. This review summarises the current knowledge of 1H MRS findings from rodent models of MDD, assesses the results from both a biological and a technical perspective, and identifies the main sources of bias. From a technical point of view, bias-introducing factors are the diversity of the measured volumes and their positioning in the brain, the data processing, and the metabolite concentration expression. The biological variables are strain, sex, and species, as well as the model itself, and in vivo vs. ex vivo exploration. This review identified some consistency in the 1H MRS findings in the models of MDD: lower levels of glutamine, glutamate + glutamine, and higher levels of myo-inositol and taurine in most of the brain regions of MDD models. This may suggest changes in regional metabolism, neuronal dysregulation, inflammation, and a compensatory effect reaction in the MDD rodent models.

Quantification of short echo time MRS signals with improved version of QUantitation based on quantum ESTimation algorithm

Magnetic resonance spectroscopy offers information about metabolite changes in the organism, which can be used in diagnosis. While short echo time proton spectra exhibit more distinguishable metabolites compared with proton spectra acquired with long echo times, their quantification (and providing estimates of metabolite concentrations) is more challenging. They are hampered by a background signal, which originates mainly from macromolecules (MM) and mobile lipids. An improved version of the quantification algorithm QUantitation based on quantum ESTimation (QUEST), with MM prior knowledge (QUEST-MM), dedicated to proton signals and invoking appropriate prior knowledge on MM, is proposed and tested. From a single acquisition, it enables better metabolite quantification, automatic estimation of the background, and additional automatic quantification of MM components, thus improving its applicability in the clinic. The proposed algorithm may facilitate studies that involve patients with pathological MM in the brain. QUEST-MM and three QUEST-based strategies for quantifying short echo time signals are compared in terms of bias-variance trade-off and Cramér-Rao lower bound estimates. The performances of the methods are evaluated through extensive Monte Carlo studies. In particular, the histograms of the metabolite and MM amplitude distributions demonstrate the performances of the estimators. They showed that QUEST-MM works better than QUEST (Subtract approach) and is a good alternative to QUEST when measured MM signal is unavailable or unsuitable. Quantification with QUEST-MM is shown for 1 H in vivo rat brain signals obtained with the SPECIAL pulse sequence at 9.4 T, and human brain signals obtained, respectively, with STEAM at 4 T and PRESS at 3 T. QUEST-MM is implemented in jMRUI and will be available for public use from version 7.1.

Meta-analysis and open-source database for in vivo brain Magnetic Resonance spectroscopy in health and disease

Proton (1H) Magnetic Resonance Spectroscopy (MRS) is a non-invasive tool capable of quantifying brain metabolite concentrations in vivo. Prioritization of standardization and accessibility in the field has led to the development of universal pulse sequences, methodological consensus recommendations, and the development of open-source analysis software packages. One on-going challenge is methodological validation with ground-truth data. As ground-truths are rarely available for in vivo measurements, data simulations have become an important tool. The diverse literature of metabolite measurements has made it challenging to define ranges to be used within simulations. Especially for the development of deep learning and machine learning algorithms, simulations must be able to produce accurate spectra capturing all the nuances of in vivo data. Therefore, we sought to determine the physiological ranges and relaxation rates of brain metabolites which can be used both in data simulations and as reference estimates. Using the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines, we've identified relevant MRS research articles and created an open-source database containing methods, results, and other article information as a resource. Using this database, expectation values and ranges for metabolite concentrations and T2 relaxation times are established based upon a meta-analyses of healthy and diseased brains.

Atlas-Based Adaptive Hadamard-Encoded MR Spectroscopic Imaging at 3T

BACKGROUND

This study aimed to develop a time-efficient method of acquiring simultaneous, dual-slice MR spectroscopic imaging (MRSI) for the evaluation of brain metabolism.

METHODS

Adaptive Hadamard-encoded pulses were developed and integrated with atlas-based automatic prescription. The excitation profiles were evaluated via simulation, phantom and volunteer experiments. The feasibility of γ-aminobutyric acid (GABA)-edited dual-slice MRSI was also assessed.

RESULTS

The signal between slices in the dual-band MRSI was less than 1% of the slice profiles. Data from a homemade phantom containing separate, interfacing compartments of creatine and acetate solutions demonstrated ~0.4% acetate signal contamination relative to the amplitude in the excited creatine compartment. The normalized signal-to-noise ratios from atlas-based acquisitions in volunteers were found to be comparable between dual-slice, Hadamard-encoded MRSI and 3D acquisitions. The mean and standard deviation of the coefficients of variation for NAA/Cho from the repeated volunteer scans were 8.2% ± 0.8% and 10.1% ± 3.7% in the top and bottom slices, respectively. GABA-edited, dual-slice MRSI demonstrated simultaneous detection of signals from GABA and coedited macromolecules (GABA+) from both superior grey and deep grey regions of volunteers.

CONCLUSION

This study demonstrated a fully automated dual-slice MRSI acquisition using atlas-based automatic prescription and adaptive Hadamard-encoded pulses.

Meta-analysis and Open-source Database for In Vivo Brain Magnetic Resonance Spectroscopy in Health and Disease

Proton ( 1 H) Magnetic Resonance Spectroscopy (MRS) is a non-invasive tool capable of quantifying brain metabolite concentrations in vivo . Prioritization of standardization and accessibility in the field has led to the development of universal pulse sequences, methodological consensus recommendations, and the development of open-source analysis software packages. One on-going challenge is methodological validation with ground-truth data. As ground-truths are rarely available for in vivo measurements, data simulations have become an important tool. The diverse literature of metabolite measurements has made it challenging to define ranges to be used within simulations. Especially for the development of deep learning and machine learning algorithms, simulations must be able to produce accurate spectra capturing all the nuances of in vivo data. Therefore, we sought to determine the physiological ranges and relaxation rates of brain metabolites which can be used both in data simulations and as reference estimates. Using the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines, we've identified relevant MRS research articles and created an open-source database containing methods, results, and other article information as a resource. Using this database, expectation values and ranges for metabolite concentrations and T 2 relaxation times are established based upon a meta-analyses of healthy and diseased brains.

Physics-informed deep learning approach to quantification of human brain metabolites from magnetic resonance spectroscopy data

PURPOSE

While the recommended analysis method for magnetic resonance spectroscopy data is linear combination model (LCM) fitting, the supervised deep learning (DL) approach for quantification of MR spectroscopy (MRS) and MR spectroscopic imaging (MRSI) data recently showed encouraging results; however, supervised learning requires ground truth fitted spectra, which is not practical. Moreover, this work investigates the feasibility and efficiency of the LCM-based self-supervised DL method for the analysis of MRS data.

METHOD

We present a novel DL-based method for the quantification of relative metabolite concentrations, using quantum-mechanics simulated metabolite responses and neural networks. We trained, validated, and evaluated the proposed networks with simulated and publicly accessible in-vivo human brain MRS data and compared the performance with traditional methods. A novel adaptive macromolecule fitting algorithm is included. We investigated the performance of the proposed methods in a Monte Carlo (MC) study.

RESULT

The validation using low-SNR simulated data demonstrated that the proposed methods could perform quantification comparably to other methods. The applicability of the proposed method for the quantification of in-vivo MRS data was demonstrated. Our proposed networks have the potential to reduce computation time significantly.

CONCLUSION

The proposed model-constrained deep neural networks trained in a self-supervised manner can offer fast and efficient quantification of MRS and MRSI data. Our proposed method has the potential to facilitate clinical practice by enabling faster processing of large datasets such as high-resolution MRSI datasets, which may have thousands of spectra.

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.

Laterality in functional and metabolic state of the bulbectomised rat brain detected by ASL and 1H MRS: A pilot study

OBJECTIVES

Pilot study validating the animal model of depression - the bilateral olfactory bulbectomy in rats - by two nuclear magnetic resonance methods, indirectly detecting the metabolic state of the brain. Furthermore, the study focussed on potential differences in brain laterality.

METHODS

Arterial spin labelling assessed cerebral brain flow in prefrontal, sensorimotor, and piriform cortices, nucleus accumbens, hippocampus, thalamus, circle of Willis, and whole brain. Proton magnetic resonance spectroscopy provided information about relative metabolite concentrations in the cortex and hippocampus.

RESULTS

Arterial spin labelling found no differences in cerebral perfusion in the group comparison but revealed lateralisation in the thalamus of the control group and the sensorimotor cortex of the bulbectomized rats. Lower Cho/tCr and Cho/NAA levels were found in the right hippocampus in bulbectomized rats. The differences in lateralisation were shown in the hippocampus: mI/tCr in the control group, Cho/NAA, NAA/tCr, Tau/tCr in the model group, and in the cortex: NAA/tCr, mI/tCr in the control group.

CONCLUSION

Olfactory bulbectomy affects the neuronal and biochemical profile of the rat brain laterally and, as a model of depression, was validated by two nuclear magnetic resonance methods.

Continuous Ingestion of Lacticaseibacillus rhamnosus JB-1 during Chronic Stress Ensures Neurometabolic and Behavioural Stability in Rats

The intestinal microbiome composition and dietary supplementation with psychobiotics can result in neurochemical alterations in the brain, which are possible due to the presence of the brain–gut–microbiome axis. In the present study, magnetic resonance spectroscopy (MRS) and behavioural testing were used to evaluate whether treatment with Lacticaseibacillus rhamnosus JB-1 (JB-1) bacteria alters brain metabolites’ levels and behaviour during continuous exposure to chronic stress. Twenty Wistar rats were subjected to eight weeks of a chronic unpredictable mild stress protocol. Simultaneously, half of them were fed with JB-1 bacteria, and the second half was given a daily placebo. Animals were examined at three-time points: before starting the stress protocol and after five and eight weeks of stress onset. In the elevated plus maze behavioural test the placebo group displayed increased anxiety expressed by almost complete avoidance of exploration, while the JB-1 dietary supplementation mitigated anxiety which resulted in a longer exploration time. Hippocampal MRS measurements demonstrated a significant decrease in glutamine + glutathione concentration in the placebo group compared to the JB-1 bacteria-supplemented group after five weeks of stress. With the progression of stress, the decrease of glutamate, glutathione, taurine, and macromolecular concentrations were observed in the placebo group as compared to baseline. The level of brain metabolites in the JB-1-supplemented rats were stable throughout the experiment, with only the taurine level decreasing between weeks five and eight of stress. These data indicated that the JB-1 bacteria diet might stabilize levels of stress-related neurometabolites in rat brain and could prevent the development of anxiety/depressive-like behaviour.

Diagnostic performance of edited 2HG MR spectroscopy of central glioma in the clinical environment

OBJECTIVE

Oncometabolite D-2-hydroxyglutarate (2HG) is pooled in isocitrate dehydrogenase (IDH)-mutant glioma cells. Detecting 2HG by MR spectroscopy (MRS) has been proven viable in the last decade but has not entirely found its way into the clinical routine. This study aimed to explore the adoption of 2HG MRS while acknowledging factors that influence its performance in the clinical environment.

METHODS

Thirty-nine MR spectra were acquired and reported prospectively in patients with suspected glioma using a 3 T system with Mescher-Garwood point-resolved spectroscopy (MEGA-PRESS) sequence utilizing averaged free induction decay (FID) signals. Postprocessing and evaluation of spectra were performed with jMRUI and LCModel. 2HG concentration estimates, 2HG/Cr ratio, together with quality measures, including Cramér-Rao lower bounds (CRLBs), full-width at half-maximum (FWHM) values, and signal-to-noise ratio (SNR) were calculated using LCModel. Immunohistochemistry and genomic analysis results used as a ground truth were available for 15 patients.

RESULTS

The threshold for test positivity was set according to the ROC curve at 1 mM. Calculated sensitivity was 57.14% (95% CI 0.20-0.88), specificity 87.5% (95% CI 0.46-0.99), positive predictive value 80%, and negative predictive value 70%. Overall diagnostic accuracy was 73.33% (95% CI 0.45-0.92). The 2HG/Cr ratio with the cutoff value 0.085 significantly improved sensitivity and overall diagnostic accuracy [85.71%, 95% CI 0.42-1.00 and 86.67%, (95% CI 0.60-0.98), respectively].

CONCLUSION

Multiple factors compromising spectral quality in the clinical adoption of edited 2HG MRS resulted in diminished sensitivity but clinically acceptable specificity. Furthermore, the 2HG/Cr ratio performs better than the sole 2HG concentration estimate in the pre-operative setting.

Neurochemical abnormalities in chronic fatigue syndrome: a pilot magnetic resonance spectroscopy study at 7 Tesla

RATIONALE

Chronic fatigue syndrome (CFS) is a common and burdensome illness with a poorly understood pathophysiology, though many of the characteristic symptoms are likely to be of brain origin. The use of high-field proton magnetic resonance spectroscopy (MRS) enables the detection of a range of brain neurochemicals relevant to aetiological processes that have been linked to CFS, for example, oxidative stress and mitochondrial dysfunction.

METHODS

We studied 22 CFS patients and 13 healthy controls who underwent MRS scanning at 7 T with a voxel placed in the anterior cingulate cortex. Neurometabolite concentrations were calculated using the unsuppressed water signal as a reference.

RESULTS

Compared to controls, CFS patients had lowered levels of glutathione, total creatine and myo-inositol in anterior cingulate cortex. However, when using N-acetylaspartate as a reference metabolite, only myo-inositol levels continued to be significantly lower in CFS participants.

CONCLUSIONS

The changes in glutathione and creatine are consistent with the presence of oxidative and energetic stress in CFS patients and are potentially remediable by nutritional intervention. A reduction in myo-inositol would be consistent with glial dysfunction. However, the relationship of the neurochemical abnormalities to the causation of CFS remains to be established, and the current findings require prospective replication in a larger sample.

Saturation transfer MRI is sensitive to neurochemical changes in the rat brain due to chronic unpredictable mild stress

Chemical exchange saturation transfer (CEST) MRI was performed for the evaluation of cerebral metabolic changes in a rat model of depressive-like disease induced by chronic unpredictable mild stress (CUMS). CEST Z-spectra were acquired on a 7 T MRI with two saturation B₁ amplitudes (0.5 and 0.75 µT) to measure the magnetization transfer ratio (MTR), CEST and relayed nuclear Overhauser effect (rNOE). Cerebral cortex and hippocampus were examined in two groups of animals: healthy control (n = 10) and stressed (n = 14), the latter of which was exposed to eight weeks of the CUMS protocol. The stressed group Z-spectrum parameters, primarily MTRs, were significantly lower than in controls, at all selected frequency offsets (3.5, 3.0, 2.0, - 3.2, - 3.6 ppm) in the cortex (the largest difference of ~ 3.5% at - 3.6 ppm, p = 0.0005) and the hippocampus (MTRs measured with a B₁ = 0.5 µT). The hippocampal rNOE contributions decreased significantly in the stressed brains. Glutamate concentration (assessed using ELISA) and MTR at 3 ppm correlated positively in both brain regions. GABA concentration also correlated positively with CEST contributions in both cerebral areas, while such correlation with MTR was positive in hippocampus, and nonsignificant in cortex. Results indicate that CEST is sensitive to neurometabolic changes following chronic stress exposure.

Magnetic resonance Spectrum simulator (MARSS), a novel software package for fast and computationally efficient basis set simulation

The aim of this study was to develop a novel software platform for the simulation of magnetic resonance spin systems, capable of simulating a large number of spatial points (128³ ) for large in vivo spin systems (up to seven coupled spins) in a time frame of the order of a few minutes. The quantum mechanical density-matrix formalism is applied, a coherence pathway filter is utilized for handling unwanted coherence pathways, and the 1D projection method, which provides a substantial reduction in computation time for a large number of spatial points, is extended to include sequences of an arbitrary number of RF pulses. The novel software package, written in MATLAB, computes a basis set of 23 different metabolites (including the two anomers of glucose, seven coupled spins) with 128³ spatial points in 26 min for a three-pulse experiment on a personal desktop computer. The simulated spectra are experimentally verified with data from both phantom and in vivo MEGA-sLASER experiments. Recommendations are provided regarding the various assumptions made when computing a basis set for in vivo MRS with respect to the number of spatial points simulated and the consideration of relaxation.

Parameterization of metabolite and macromolecule contributions in interrelated MR spectra of human brain using multidimensional modeling

Macromolecular signals are crucial constituents of short echo-time ¹ H MR spectra with potential clinical implications in themselves as well as essential ramifications for the quantification of the usually targeted metabolites. Their parameterization, needed for general fitting models, is difficult because of their unknown composition. Here, a macromolecular signal parameterization together with metabolite signal quantification including relaxation properties is investigated by multidimensional modeling of interrelated 2DJ inversion-recovery (2DJ-IR) datasets. Simultaneous and iterative procedures for defining the macromolecular background (MMBG) as mono-exponentially or generally decaying signals over TE are evaluated. Varying prior knowledge and restrictions in the metabolite evaluation are tested to examine their impact on results and fitting stability for two sets of three-dimensional spectra acquired with metabolite-cycled PRESS from cerebral gray and white matter locations. One dataset was used for model optimization, and also examining the influence of prior knowledge on estimated parameters. The most promising model was applied to a second dataset. It turned out that the mono-exponential decay model appears to be inadequate to represent TE-dependent signal features of the MMBG. TE-adapted MMBG spectra were therefore determined. For a reliable overall quantification of implicated metabolite concentrations and relaxation times, a general fitting model had to be constrained in terms of the number of fitting variables and the allowed parameter space. With such a model in place, fitting precision for metabolite contents and relaxation times was excellent, while fitting accuracy is difficult to judge and bias was likely influenced by the type of fitting constraints enforced. In summary, the parameterization of metabolite and macromolecule contributions in interrelated MR spectra has been examined by using multidimensional modeling on complex 2DJ-IR datasets. A tightly restricted model allows fitting of individual subject data with high fitting precision documented in small Cramér-Rao lower bounds, good repeatability values and a relatively small spread of estimated concentration and relaxation values for a healthy subject cohort.

Lower Lactate Levels and Lower Intracellular pH in Patients with IDH-Mutant versus Wild-Type Gliomas

BACKGROUND AND PURPOSE

Preclinical evidence points toward a metabolic reprogramming in isocitrate dehydrogenase (IDH) mutated tumor cells with down-regulation of the expression of genes that encode for glycolytic metabolism. We noninvasively investigated lactate and Cr concentrations, as well as intracellular pH using ¹H/phosphorus 31 (³¹P) MR spectroscopy in a cohort of patients with gliomas.

MATERIALS AND METHODS

Thirty prospectively enrolled, mostly untreated patients with gliomas met the spectral quality criteria (World Health Organization II [n = 7], III [n = 16], IV [n = 7]; IDH-mutant [n = 23]; IDH wild-type [n = 7]; 1p/19q codeletion [n = 9]). MR imaging protocol included 3D ³¹P chemical shift imaging and ¹H single-voxel spectroscopy (point-resolved spectroscopy sequence at TE = 30 ms and TE = 97 ms with optimized echo spacing for detection of 2-hydroxyglutarate) from the tumor area. Values for absolute metabolite concentrations were calculated (phantom replacement method). Intracellular pH was determined from ³¹P chemical shift imaging.

RESULTS

At TE = 97 ms, lactate peaks can be fitted with little impact of lipid/macromolecule contamination. We found a significant difference in lactate concentrations, lactate/Cr ratios, and intracellular pH when comparing tumor voxels of patients with IDH-mutant with those of patients with IDH wild-type gliomas, with reduced lactate levels and near-normal intracellular pH in patients with IDH-mutant gliomas. We additionally found evidence for codependent effects of 1p/19q codeletion and IDH mutations with regard to lactate concentrations for World Health Organization tumor grades II and III, with lower lactate levels in patients exhibiting the codeletion. There was no statistical significance when comparing lactate concentrations between IDH-mutant World Health Organization II and III gliomas.

CONCLUSIONS

We found indirect evidence for metabolic reprogramming in IDH-mutant tumors with significantly lower lactate concentrations compared with IDH wild-type tumors and a near-normal intracellular pH.

Dietary supplementation with Lactobacillus rhamnosus JB-1 restores brain neurochemical balance and mitigates the progression of mood disorder in a rat model of chronic unpredictable mild stress

Major depressive disorder is a stress-related disease associated with brain metabolic dysregulation in the glutamine-glutamate/γ-aminobutyric acid (Gln-Glu/GABA) cycle. Recent studies have demonstrated that microbiome-gut-brain interactions have the potential to influence mental health. The hypothesis of this study was that Lactobacillus rhamnosus JB-1 (LR-JB1™) dietary supplementation has a positive impact on neuro-metabolism which can be quantified in vivo using magnetic resonance spectroscopy (MRS). A rat model of depressive-like disorder, chronic unpredictable mild stress (CUMS), was used. Baseline comparisons of MRS and behavior were obtained in a control group and in a stressed group subjected to CUMS. Of the 22 metabolites measured using MRS, stressed rats had significantly lower concentrations of GABA, glutamate, glutamine + glutathione, glutamate + glutamine, total creatine, and total N-acetylaspartate (tNAA). Stressed rats were then separated into 2 groups and supplemented with either LR-JB1™ or placebo and re-evaluated after 4 weeks of continued CUMS. The LR-JB1™ microbiotic diet restored these metabolites to levels previously observed in controls, while the placebo diet resulted in further significant decrease of glutamate, total choline, and tNAA. LR-JB1™ treated animals also exhibited calmer and more relaxed behavior, as compared with placebo treated animals. In summary, significant cerebral biochemical downregulation of major brain metabolites following prolonged stress were measured in vivo using MRS, and these decreases were reversed using a microbiotic dietary supplement of LR-JB1™, even in the presence of continued stress, which also resulted in a reduction of stress-induced behavior in a rat model of depressive-like disorder.

Ultralong TE In Vivo 1 H MR Spectroscopy of Omega-3 Fatty Acids in Subcutaneous Adipose Tissue at 7 T

BACKGROUND

Omega-3 (n-3) fatty acids (FA) play and important role in neural development and other metabolic diseases such as obesity and diabetes. The knowledge about the in vivo content and distribution of n-3 FA in human body tissues is not well established and the standard quantification of FA is invasive and costly.

PURPOSE

To detect omega-3 (n-3 CH3 ) and non-omega-3 (CH3 ) methyl group resonance lines with echo times up to 1200 msec, in oils, for the assessment of n-3 FA content, and the n-3 FA fraction in adipose tissue in vivo.

STUDY TYPE

Prospective technical development.

POPULATION

Three oils with different n-3 FA content and 24 healthy subjects.

FIELD STRENGTH/SEQUENCE

Single-voxel MR spectroscopy (SVS) with a point-resolved spectroscopy (PRESS) sequence with an echo time (TE) of 1000 msec at 7 T.

ASSESSMENT

Knowledge about the J-coupling evolution of both CH3 resonances was used for the optimal detection of the n-3 CH3 resonance line at a TE of 1000 msec. The accuracy of the method in oils and in vivo was validated from a biopsy sample with gas chromatography analysis.

STATISTICAL TESTS

SVS data were compared to gas chromatography with the Pearson correlation coefficient.

RESULTS

T2 relaxation times in oils were assessed as follows: CH2 , 65 ± 22 msec; CH3 , 325 ± 7 msec; and n-3 CH3 , 628 ± 34 msec. The n-3 FA fractions from oil phantom experiments (n = 3) were in agreement with chromatography analysis and the comparison of in vivo obtained data with the results of chromatography analysis (n = 5) yielded a significant correlation (P = 0.029).

DATA CONCLUSION

PRESS with ultralong-TE can detect and quantify the n-3 CH3 signal in vivo at 7 T.

LEVEL OF EVIDENCE

1 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;50:71-82.

In vivo Metabolic Profiles as Determined by 31P and short TE 1H MR-Spectroscopy : No Difference Between Patients with IDH Wildtype and IDH Mutant Gliomas

PURPOSE

Previous ex vivo spectroscopic data from tissue samples revealed differences in phospholipid metabolites between isocitrate dehydrogenase mutated (IDHmut) and IDH wildtype (IDHwt) gliomas. We investigated whether these changes can be found in vivo using ¹H-decoupled ³¹P magnetic resonance spectroscopic imaging (MRSI) with 3D chemical shift imaging (CSI) at 3 T in patients with low and high-grade gliomas.

METHODS

The study included 33 prospectively enrolled, mostly untreated patients who met spectral quality criteria according to the World Health Organization (WHO II n = 7, WHO III n = 17, WHO IV n = 9; 25 patients IDHmut, 8 patients IDHwt). The MRSI protocol included ¹H decoupled ³¹P MRSI with 3D CSI (3D ³¹P CSI), 2D ¹H CSI and a ¹H single voxel spectroscopy sequence (TE 30 ms) from the tumor area. For ¹H MRS, absolute metabolite concentration values were calculated (phantom replacement method). For ³¹P MRS, metabolite intensity ratios were calculated for the choline (C) and ethanolamine (E)-containing metabolites.

RESULTS

In our patient cohort we did not find significant differences for the ratio of phosphocholine (PC) and phosphoethanolamine (PE), PC/PE, (p = 0.24) for IDHmut compared to IDHwt gliomas. Furthermore, we found no elevated ratios of glycerophosphocholine (GPC) and glycerophosphoethanolamine (GPE), GPC/GPE, (p = 0.68) or GPC/PE (p = 0.12) for IDHmut gliomas. Even the ratio (PC+GPC)/(PE+GPE) showed no significant differences with respect to mutation status (p = 0.16). Nonetheless, changes related to tumor grade regarding intracellular pH (pH_i) and phospholipid metabolism as well as absolute metabolite concentrations of co-registered 2D ¹H CSI data for tumor and control tissue showed the anticipated results.

CONCLUSION

Using 3D-CSI data acquisition, in vivo ³¹P MR spectroscopic measurement of phospholipid metabolites could not distinguish between IDHmut and IDHwt.