MR Spectra Research Articles

Data-driven determination of 1H-MRS basis set composition.

Metabolite amplitude estimates derived from linear combination modeling of MR spectra depend upon the precise list of constituent metabolite basis functions used (the "basis set"). The absence of clear consensus on the "ideal" composition or objective criteria to determine the suitability of a particular basis set contributes to the poor reproducibility of MRS. In this proof-of-concept study, we demonstrate a novel, data-driven approach for deciding the basis-set composition using Bayesian information criteria (BIC). We have developed an algorithm that iteratively adds metabolites to the basis set using iterative modeling, informed by BIC scores. We investigated two quantitative "stopping conditions", referred to as max-BIC and zero-amplitude, and whether to optimize the selection of basis set on a per-spectrum basis or at the group level. The algorithm was tested using two groups of synthetic in-vivo-like spectra representing healthy brain and tumor spectra, respectively, and the derived basis sets (and metabolite amplitude estimates) were compared to the ground truth. All derived basis sets correctly identified high-concentration metabolites and provided reasonable fits of the spectra. At the single-spectrum level, the two stopping conditions derived the underlying basis set with 77-87% accuracy. When optimizing across a group, basis set determination accuracy improved to 84-92%. Data-driven determination of the basis set composition is feasible. With refinement, this approach could provide a valuable data-driven way to derive or refine basis sets, reducing the operator bias of MRS analyses, enhancing the objectivity of quantitative analyses, and increasing the clinical viability of MRS.

On the impact of B0 shimming algorithms on single-voxel MR spectroscopy.

To assess the impact of different B0 shimming algorithms on MRS. B0 field maps and single-voxel MR spectroscopy were acquired in the prefrontal cortex of five volunteers at 3 T using five different B0 shimming approaches. B0 shimming was achieved using Siemens' proprietary shim algorithm, in addition to the Pseudo-Inverse (PI), Quadratic Programming (QuadProg), Least Squares (LSq), and Gradient optimization (Grad) algorithms. The standard deviation of the shimmed B0 field, as well as the SNR and FWHM of the measured metabolites, was used to evaluate the performance of each B0 shimming algorithm. Compared to Siemens's shim, significant reductions (p < 0.01) in the standard deviation of the B0 field distribution within the MRS voxel were observed for the PI, QuadProg, and Grad algorithms (3.8 Hz, 7.3 Hz, and 3.9 Hz respectively, compared to 11.5 Hz for Siemens), but not for the LSq (12.9 Hz) algorithm. Moreover, significantly increased SNR and reduced FWHM for the N-acetylaspartate metabolite were consistent with the improvement in B0 homogeneity for the aforementioned shimming algorithms. Here, we demonstrate that the choice of B0 shimming algorithm can have a significant impact on the quality of MR spectra and that significant improvements in spectrum quality could be achieved by using alternatives to the default vendor approach.

Non-invasive detection of IDH-1 mutation in brain gliomas based on proton MR spectroscopy

Mutations of isocitrate dehydrogenase (IDH) have important prognostic significance for patients with glial brain tumor. The method of proton MR spectroscopy makes it possible to non-invasively determine the metabolic properties of the tumor tissue at the preoperative stage. The aim of this work was to study the possibility of determining the IDH status, by using magnetic resonance spectroscopy (MRS) to detect the 2-hydroxyglutarate (2HG), a metabolic product of the IDH enzyme. We examined 33 patients with glial tumors varying degrees of malignancy (Gr. 2–4), followed by identification of IDH mutations. IDH mutation identified in 20 cases, according to proton magnetic resonance spectroscopy, was confirmed by immunohistochemistry. Peak of 2HG did not detect in 13 cases on the MR spectrum, and the analysis for IDH did not reveal mutations. Using of proton magnetic resonance spectroscopy showed a high sensitivity of this technique in predicting the mutational status of glial brain tumors, which makes this method an important in preoperative diagnostics.

Model-based frequency-and-phase correction of 1H MRS data with 2D linear-combination modeling.

Retrospective frequency-and-phase correction (FPC) methods attempt to remove frequency-and-phase variations between transients to improve the quality of the averaged MR spectrum. However, traditional FPC methods like spectral registration struggle at low SNR. Here, we propose a method that directly integrates FPC into a 2D linear-combination model (2D-LCM) of individual transients ("model-based FPC"). We investigated how model-based FPC performs compared to the traditional approach, i.e., spectral registration followed by 1D-LCM in estimating frequency-and-phase drifts and, consequentially, metabolite level estimates. We created synthetic in-vivo-like 64-transient short-TE sLASER datasets with 100 noise realizations at 5 SNR levels and added randomly sampled frequency and phase variations. We then used this synthetic dataset to compare the performance of 2D-LCM with the traditional approach (spectral registration, averaging, then 1D-LCM). Outcome measures were the frequency/phase/amplitude errors, the SD of those ground-truth errors, and amplitude Cramér Rao lower bounds (CRLBs). We further tested the proposed method on publicly available in-vivo short-TE PRESS data. 2D-LCM estimates (and accounts for) frequency-and-phase variations directly from uncorrected data with equivalent or better fidelity than the conventional approach. Furthermore, 2D-LCM metabolite amplitude estimates were at least as accurate, precise, and certain as the conventionally derived estimates. 2D-LCM estimation of FPC and amplitudes performed substantially better at low-to-very-low SNR. Model-based FPC with 2D linear-combination modeling is feasible and has great potential to improve metabolite level estimation for conventional and dynamic MRS data, especially for low-SNR conditions, for example, long TEs or strong diffusion weighting.

Repeatability of Lac+ measurements in healthy human brain at 3 T.

In vivo quantification of lactate has numerous applications in studying the pathology of both cerebral and musculoskeletal systems. Due to its low concentration (~0.5-1 mM), and overlap with lipid signals, traditional 1H MR spectra acquired in vivo using a small voxel and short echo time often result in an inadequate signal to detect and resolve the lactate peak, especially in healthy human volunteers. In this study, using a semi-LASER acquisition with long echo time (TE= 288 ms) and large voxel size (80 × 70 × 20 mm3), we clearly visualize the combined signal of lactate and threonine. Therefore, we call the signal at 1.33 ppm Lac+ and quantify Lac+ concentration from water suppressed spectra in healthy human brains in vivo. Four participants (22-37 years old; mean age = 28 ± 5.4; three male, one female) were scanned on four separate days, and on each day four measurements were taken. Intra-day values are calculated for each participant by comparing the four measurements on a single day. Inter-day values were calculated using the mean intra-day measurements. The mean intra-participant Lac+ concentration, standard deviation (SD), and coefficient of variation (CV) ranged from 0.49 to 0.61 mM, 0.02 to 0.07 mM, and 4% to 13%, respectively, across four volunteers. The inter-participant Lac+ concentration, SD, and CV was 0.53 mM, ±0.06 mM, and 11%. Repeatability is shown in Lac+ measurement in healthy human brain using a long echo time semi-LASER sequence with a large voxel in about 3.5 min at 3 T.

Age-related differences in macromolecular resonances observed in ultra-short-TE STEAM MR spectra at 7T.

To understand how macromolecular content varies in the human brain with age in a large cohort of healthy subjects. In-vivo 1H-MR spectra were acquired using ultra-short TE STEAM at 7T in the posterior cingulate cortex. Macromolecular content was studied in 147 datasets from a cohort ranging in age from 19 to 89 y. Three fitting approaches were used to evaluate the macromolecular content: (1) a macromolecular resonances model developed for this study; (2) LCModel-simulated macromolecules; and (3) a combination of measured and LCModel-simulated macromolecules. The effect of age on the macromolecular content was investigated by considering age both as a continuous variable (i.e., linear regressions) and as a categorical variable (i.e., multiple comparisons among sub-groups obtained by stratifying data according to age by decade). While weak age-related effects were observed for macromolecular peaks at ˜0.9 (MM09), ˜1.2 (MM12), and ˜1.4 (MM14) ppm, moderate to strong effects were observed for peaks at ˜1.7 (MM17), and ˜2.0 (MM20) ppm. Significantly higher MM17 and MM20 content started from 30 to 40 y of age, while for MM09, MM12, and MM14, significantly higher content started from 60 to 70 y of age. Our findings provide insights into age-related differences in macromolecular contents and strengthen the necessity of using age-matched measured macromolecules during quantification.

Correlation between skeletal muscle acetylcarnitine and phosphocreatine metabolism during submaximal exercise and recovery: interleaved 1H/31P MRS 7 T study

Acetylcarnitine is an essential metabolite for maintaining metabolic flexibility and glucose homeostasis. The in vivo behavior of muscle acetylcarnitine content during exercise has not been shown with magnetic resonance spectroscopy. Therefore, this study aimed to explore the behavior of skeletal muscle acetylcarnitine during rest, plantar flexion exercise, and recovery in the human gastrocnemius muscle under aerobic conditions. Ten lean volunteers and nine overweight volunteers participated in the study. A 7 T whole-body MR system with a double-tuned surface coil was used to acquire spectra from the gastrocnemius medialis. An MR-compatible ergometer was used for the plantar flexion exercise. Semi-LASER-localized 1H MR spectra and slab-localized 31P MR spectra were acquired simultaneously in one interleaved exercise/recovery session. The time-resolved interleaved 1H/31P MRS acquisition yielded excellent data quality. A between-group difference in acetylcarnitine metabolism over time was detected. Significantly slower τPCr recovery, τPCr on-kinetics, and lower Qmax in the overweight group, compared to the lean group was found. Linear relations between τPCr on-kinetics, τPCr recovery, VO2max and acetylcarnitine content were identified. In conclusion, we are the first to show in vivo changes of skeletal muscle acetylcarnitine during acute exercise and immediate exercise recovery with a submaximal aerobic workload using interleaved 1H/31P MRS at 7 T.

Universal dynamic fitting of magnetic resonance spectroscopy.

Dynamic (2D) MRS is a collection of techniques where acquisitions of spectra are repeated under varying experimental or physiological conditions. Dynamic MRS comprises a rich set of contrasts, including diffusion-weighted, relaxation-weighted, functional, edited, or hyperpolarized spectroscopy, leading to quantitative insights into multiple physiological or microstructural processes. Conventional approaches to dynamic MRS analysis ignore the shared information between spectra, and instead proceed by independently fitting noisy individual spectra before modeling temporal changes in the parameters. Here, we propose a universal dynamic MRS toolbox which allows simultaneous fitting of dynamic spectra of arbitrary type. A simple user-interface allows information to be shared and precisely modeled across spectra to make inferences on both spectral and dynamic processes. We demonstrate and thoroughly evaluate our approach in three types of dynamic MRS techniques. Simulations of functional and edited MRS are used to demonstrate the advantages of dynamic fitting. Analysis of synthetic functional 1H-MRS data shows a marked decrease in parameter uncertainty as predicted by prior work. Analysis with our tool replicates the results of two previously published studies using the original in vivo functional and diffusion-weighted data. Finally, joint spectral fitting with diffusion orientation models is demonstrated in synthetic data. A toolbox for generalized and universal fitting of dynamic, interrelated MR spectra has been released and validated. The toolbox is shared as a fully open-source software with comprehensive documentation, example data, and tutorials.

Fast high-resolution prospective motion correction for single-voxel spectroscopy.

To develop a fast high-resolution image-based motion correction method using spiral navigators with multislice-to-volume registration. A semi-LASER sequence was modified to include a multislice spiral navigator for prospective motion correction (∼305 ms including acquisition, processing, and feedback) as well as shim and frequency navigators for prospective shim and frequency correction (∼100 ms for each). MR spectra were obtained in the prefrontal cortex in five healthy subjects at 3 T with and without prospective motion and shim correction. The effect of key navigator parameters (number of slices, image resolution, and excitation flip angle) on registration accuracy was assessed using simulations. Without prospective motion and shim correction, spectral quality degraded significantly in the presence of voluntary motion. In contrast, with prospective motion and shim correction, spectral quality was improved (metabolite linewidth = 6.7 ± 0.6 Hz, SNR= 67 ± 9) and in good agreement with baseline data without motion (metabolite linewidth = 6.9 ± 0.9 Hz, SNR = 73 ± 9). In addition, there was no significant difference in metabolites concentrations measured without motion and with prospective motion and shim correction in the presence of motion. Simulations showed that the registration precision was comparable when using three navigator slices with 3 mm resolution and when using the entire volume (all slices) with 8 mm resolution. The proposed motion correction scheme allows fast and precise prospective motion and shim correction for single-voxel spectroscopy at 3 T. With 3 mm resolution, only a few navigator slices are necessary to achieve excellent motion correction performance.

Prospective motion correction for cervical spinal cord MRS.

To develop prospective motion correction for single-voxel MRS in the human cervical spinal cord. A motion MR navigator was implemented using reduced field-of-view 2D-selective RF excitation together with EPI readout. A short-echo semi-LASER sequence (TE = 30 ms) was updated to incorporate this real-time image-based motion navigator, as well as real-time shim and frequency navigators. Five healthy participants were studied at 3 T with a 64-channel head-neck receive coil. Single-voxel MRS data were measured in a voxel located at the C3-5 vertebrae level. The motion navigator was used to correct for translations in the X-Y plane and was validated by assessing spectral quality with and without prospective correction in the presence of subject motion. Without prospective correction, motion resulted in severe lipid contamination in the MR spectra. With prospective correction, the quality of spinal cord MR spectra in the presence of motion was similar to that obtained in the absence of motion, with comparable spectral signal-to-noise ratio and linewidth and no significant lipid contamination. Prospective motion and B0 correction allow acquisition of good-quality MR spectra in the human cervical spinal cord in the presence of motion. This new technique should facilitate reliable acquisition of spinal cord MR spectra in both research and clinical settings.

Evaluation of deep learning models for quality control of MR spectra.

While 3D MR spectroscopic imaging (MRSI) provides valuable spatial metabolic information, one of the hurdles for clinical translation is its interpretation, with voxel-wise quality control (QC) as an essential and the most time-consuming step. This work evaluates the accuracy of machine learning (ML) models for automated QC filtering of individual spectra from 3D healthy control and patient datasets. A total of 53 3D MRSI datasets from prior studies (30 neurological diseases, 13 brain tumors, and 10 healthy controls) were included in the study. Three ML models were evaluated: a random forest classifier (RF), a convolutional neural network (CNN), and an inception CNN (ICNN) along with two hybrid models: CNN + RF, ICNN + RF. QC labels used for training were determined manually through consensus of two MRSI experts. Normalized and cropped real-valued spectra was used as input. A cross-validation approach was used to separate datasets into training/validation/testing sets of aggregated voxels. All models achieved a minimum AUC of 0.964 and accuracy of 0.910. In datasets from neurological disease and controls, the CNN model produced the highest AUC (0.982), while the RF model achieved the highest AUC in patients with brain tumors (0.976). Within tumor lesions, which typically exhibit abnormal metabolism, the CNN AUC was 0.973 while that of the RF was 0.969. Data quality inference times were on the order of seconds for an entire 3D dataset, offering drastic time reduction compared to manual labeling. ML methods accurately and rapidly performed automated QC. Results in tumors highlights the applicability to a variety of metabolic conditions.

19F VT NMR: Novel Tm3+ and Ce3+ Complexes Provide New Insight into Temperature Measurement Using Molecular Sensors.

In the past few decades, magnetic resonance spectroscopy (MRS) and MR imaging (MRI) have developed into a powerful non-invasive tool for medical diagnostic and therapy. Especially 19F MR shows promising potential because of the properties of the fluorine atom and the negligible background signals in the MR spectra. The detection of temperature in a living organism is quite difficult and usually, external thermometers or fibers are used. Temperature determination via MRS needs temperature-sensitive contrast agents. This article reports first results of solvent and structural influences on the temperature sensitivity of 19F NMR signals of chosen molecules. By using this chemical shift sensitivity, a local temperature can be determined with a high precision. Based on this preliminary study, we synthesized five metal complexes and compared the results of all variable temperature measurements temperature. It is shown that the highest 19F MR signal temperature dependence is detectable for a fluorine nucleus in a Tm3+-complex.

High field brain proton magnetic resonance spectroscopy and volumetry in children with chronic, compensated liver disease – A pilot study

BackgroundThere is increasing evidence that children or young adults having acquired liver disease in childhood display neurocognitive impairment which may become more apparent as they grow older. The molecular, cellular and morphological underpinnings of this clinical problem are incompletely understood. AimTherefore, we used the advantages of highly-resolved proton magnetic resonance spectroscopy at ultra-high magnetic field to analyze the neurometabolic profile and brain morphometry of children with chronic, compensated liver disease, hypothesizing that with high field spectroscopy we would identify early evidence of rising brain glutamine and decreased myoinositol, such as has been described both in animals and humans with more significant liver disease. MethodsPatients (n = 5) and age-matched controls (n = 19) underwent 7T MR scans and short echo time 1H MR spectra were acquired using the semi-adiabatic SPECIAL sequence in two voxels located in gray and white matter dominated prefrontal cortex, respectively. A 3D MP2RAGE sequence was also acquired for brain volumetry and T1 mapping. Liver disease had to have developed at least 6 months before entering the study. Subjects underwent routine blood analysis and neurocognitive testing using validated methods within 3 months of MRI and MRS. ResultsFive children aged 8–16 years with liver disease acquired in childhood were included. Baseline biological characteristics were similar among patients. There were no statistically significant differences between subjects and controls in brain metabolite levels or brain volumetry. Finally, there were minor neurocognitive fluctuations including attention deficit in one child, but none fell in the statistically significant range. ConclusionChildren with chronic, compensated liver disease did not display an abnormal neurometabolic profile, neurocognitive abnormalities, or signal intensity changes in the globus pallidus. Despite the absence of neurometabolic changes, it is an opportunity to emphasize that it is only by developing the use of 1H MRS at high field in the clinical arena that we will understand the significance and generalizability of these findings in children with CLD. Healthy children displayed neurometabolic regional differences as previously reported in adult subjects.

Denoising single MR spectra by deep learning: Miracle or mirage?

The inherently poor SNR of MRS measurements presents a significant hurdle to its clinical application. Denoising by machine or deep learning (DL) was proposed as a remedy. It is investigated whether such denoising leads to lower estimate uncertainties or whether it essentially reduces noise in signal-free areas only. Noise removal based on supervised DL with U-nets was implemented using simulated 1 H MR spectra of human brain in two approaches: (1) via time-frequency domain spectrograms and (2) using 1D spectra as input. Quality of denoising was evaluated in three ways: (1) by an adapted fit quality score, (2) by traditional model fitting, and (3) by quantification via neural networks. Visually appealing spectra were obtained; hinting that denoising is well-suited for MRS. However, an adapted denoising score showed that noise removal is inhomogeneous and more efficient for signal-free areas. This was confirmed by quantitative analysis of traditional fit results as well as DL quantitation following DL denoising. DL denoising, although apparently successful as judged by mean squared errors, led to substantially biased estimates in both implementations. The implemented DL-based denoising techniques may be useful for display purposes, but do not help quantitative evaluations, confirming expectations based on estimation theory: Cramér Rao lower bounds defined by the original data and the appropriate fitting model cannot be circumvented in an unbiased way for single data sets, unless additional prior knowledge can be incurred in the form of parameter restrictions/relations or applicable substates.

Assessment of the sensitivity of 2 H MR spectroscopy measurements of [2,3-2 H2 ]fumarate metabolism for detecting tumor cell death.

Imaging the metabolism of [2,3-2 H2 ]fumarate to produce malate can be used to detect tumor cell death post-treatment. Here, we assess the sensitivity of the technique for detecting cell death by lowering the concentration of injected [2,3-2 H2 ]fumarate and by varying the extent of tumor cell death through changes in drug concentration. Mice were implanted subcutaneously with human triple negative breast cancer cells (MDA-MB-231) and injected with 0.1, 0.3, and 0.5 g/kg [2,3-2 H2 ]fumarate before and after treatment with a multivalent TRAlL-R2 agonist (MEDI3039) at 0.1, 0.4, and 0.8 mg/kg. Tumor conversion of [2,3-2 H2 ]fumarate to [2,3-2 H2 ]malate was assessed from a series of 13 spatially localized 2 H MR spectra acquired over 65 min using a pulse-acquire sequence with a 2-ms BIR4 adiabatic excitation pulse. Tumors were then excised and stained for histopathological markers of cell death: cleaved caspase 3 (CC3) and DNA damage (terminal deoxynucleotidyl transferase dUTP nick end labeling [TUNEL]). The rate of malate production and the malate/fumarate ratio plateaued at tumor fumarate concentrations of 2 mM, which were obtained with injected [2,3-2 H2 ]fumarate concentrations of 0.3 g/kg and above. Tumor malate concentration and the malate/fumarate ratio increased linearly with the extent of cell death determined histologically. At an injected [2,3-2 H2 ]fumarate concentration of 0.3 g/kg, 20% CC3 staining corresponded to a malate concentration of 0.62 mM and a malate/fumarate ratio of 0.21. Extrapolation indicated that there would be no detectable malate at 0% CC3 staining. The use of low and nontoxic fumarate concentrations and the production of [2,3-2 H2 ]malate at concentrations that are within the range that can be detected clinically suggest this technique could translate to the clinic.

Magnetic resonance spectroscopy investigation in the right human hippocampus following spinal cord injury.

Preclinical studies have shown that cognitive impairments following spinal cord injury (SCI), such as impaired spatial memory, are linked to inflammation, neurodegeneration, and reduced neurogenesis in the right hippocampus. This cross-sectional study aims to characterize metabolic and macrostructural changes in the right hippocampus and their association to cognitive function in traumatic SCI patients. Within this cross-sectional study, cognitive function was assessed in 28 chronic traumatic SCI patients and 18 age-, sex-, and education-matched healthy controls by a visuospatial and verbal memory test. A magnetic resonance spectroscopy (MRS) and structural MRI protocol was performed in the right hippocampus of both groups to quantify metabolic concentrations and hippocampal volume, respectively. Group comparisons investigated changes between SCI patients and healthy controls and correlation analyses investigated their relationship to memory performance. Memory performance was similar in SCI patients and healthy controls. The quality of the recorded MR spectra was excellent in comparison to the best-practice reports for the hippocampus. Metabolite concentrations and volume of the hippocampus measured based on MRS and MRI were not different between two groups. Memory performance in SCI patients and healthy controls was not correlated with metabolic or structural measures. This study suggests that the hippocampus may not be pathologically affected at a functional, metabolic, and macrostructural level in chronic SCI. This points toward the absence of significant and clinically relevant trauma-induced neurodegeneration in the hippocampus.

Measurement of neuro-energetics and neurotransmission in the rat olfactory bulb using 1H and 1H-[13C] NMR spectroscopy.

The olfactory bulb (OB) plays a fundamental role in the sense of smell and has been implicated in several pathologies, including Alzheimer's disease. Despite its importance, high metabolic activity and unique laminar architecture, the OB is not frequently studied using MRS methods, likely due to the small size and challenging location. Here we present a detailed metabolic characterization of OB metabolism, in terms of both static metabolite concentrations using 1H MRS and metabolic fluxes associated with neuro-energetics and neurotransmission by tracing the dynamic 13C flow from intravenously administered [1,6-13C2]-glucose, [2-13C]-glucose and [2-13C]-acetate to downstream metabolites, including [4-13C]-glutamate, [4-13C]-glutamine and [2-13C]-GABA. The unique laminar architecture and associated metabolism of the OB, distinctly different from that of the cerebral cortex, is characterized by elevated GABA and glutamine levels, as well as increased GABAergic and astroglial energy metabolism and neurotransmission. The results show that, despite the technical challenges, high-quality 1H and 1H-[13C] MR spectra can be obtained from the rat OB in vivo. The derived metabolite concentrations and metabolic rates demonstrate a unique metabolic profile for the OB. The metabolic model provides a solid basis for future OB studies on functional activation or pathological conditions.

Identification of new resonances in downfield 1 H MRS of human calf muscle in vivo: Potentially metabolite precursors for skeletal muscle NAD.

The purpose of this study was to identify and characterize newly discovered resonances appearing in the downfield proton MR spectrum (DF 1 H MRS) of the human calf muscle in vivo at 7T. Downfield 1 H MRS was performed on the calf muscle of five healthy volunteers at 7T. A spectrally selective 90° E-BURP RF pulse with an excitation center frequency at 10.3 ppm and an excitation bandwidth of 2 ppm was used for DF 1 H MRS acquisition. In all participants, we observed new resonances at 9.7, 10.1, 10.3, and 10.9 ppm in the DF 1 H MRS. Phantom experiments at 37°C strongly suggest the new resonance at 9.7 ppm could be from H2-proton of the nicotinamide rings in nicotinamide riboside (NR) and nicotinamide mononucleotide (NMN) while the resonance at 10.1 ppm could be attributed to the indole -NH proton of L-tryptophan. We observed that the resonances at 10.1 and 10.9 ppm are significantly suppressed when the water resonance is saturated, indicating that these peaks have either 1 H chemical exchange or cross-relaxation with water. Conversely, the resonances at 9.7 and 10.3 ppm exhibit moderate signal reduction in the presence of water saturation. We have identified new proton resonances in vivo in human calf muscle occurring at chemical shifts of 9.7, 10.1, 10.3, and 10.9 ppm. These preliminary results are promising for investigating the role of NR/NMN and L-tryptophan metabolism in understanding the de novo and salvage pathways of NAD+ synthesis in skeletal muscle.

Hyperpolarized δ-[1- 13C]gluconolactone imaging visualizes response to TERT or GABPB1 targeting therapy for glioblastoma

TERT promoter mutations are a hallmark of glioblastoma (GBM). Accordingly, TERT and GABPB1, a subunit of the upstream mutant TERT promoter transcription factor GABP, are being considered as promising therapeutic targets in GBM. We recently reported that the expression of TERT or GABP1 modulates flux via the pentose phosphate pathway (PPP). Here, we investigated whether 13C magnetic resonance spectroscopy (MRS) of hyperpolarized (HP) δ- [1-13C]gluconolactone can serve to image the reduction in PPP flux following TERT or GABPB1 silencing. We investigated two different human GBM cell lines stably expressing shRNAs targeting TERT or GABPB1, as well as doxycycline-inducible shTERT or shGABPB1cells. MRS studies were performed on live cells and in vivo tumors, and dynamic sets of 13C MR spectra were acquired following injection of HP δ-[1-13C]gluconolactone. HP 6-phosphogluconolactone (6PG), the product of δ-[1-13C]gluconolactone via the PPP, was significantly reduced in TERT or GABPB1-silenced cells or tumors compared to controls in all our models. Furthermore, a positive correlation between TERT expression and 6PG levels was observed. Our data indicate that HP δ-[1-13C]gluconolactone, an imaging tool with translational potential, could serve to monitor TERT expression and its silencing with therapies that target either TERT or GABPB1 in mutant TERT promoter GBM patients.

Spectral peak areas do not vary according to spectral averaging scheme used in functional MRS experiments at 3 T with interleaved visual stimulation

Abstract Brain response to visual stimulation can be probed quantitatively using functional magnetic resonance spectroscopy (fMRS), which relies on the blood oxygenation level dependent (BOLD) contrast mechanism. BOLD effect in fMRS is associated with changes in the areas, widths, and heights of the MR spectra. This study investigated the effect of spectral averaging scheme (NEX value) on BOLD changes in the spectra. Using a visual stimulus at 8 Hz in single and interleaved stimulation paradigms, the BOLD effects in spectra acquired from the occipital brain region of three healthy volunteers (mean age ± SD = 32.7 ± 3.5 years) were compared for two fMRS data sets acquired with two NEX values (“2” and “8”) available on a 3 T MR scanner. BOLD signal changes were estimated as percentage changes in spectral areas, heights, and widths of six cerebral metabolites and water using the SAGE software package (version 7). There was a general trend of lower BOLD effects with NEX = 8 in both stimulation paradigms. In the single stimulation paradigm, NEX = 8 was associated with significantly lower N-acetyl aspartate (NAA) spectral height (p = 0.03), creatine (p = 0.04) and choline (p = 0.02) spectral widths, and NAA (p = 0.03), water (p &lt; 0.01), and glutamate (p = 0.02) spectral areas. In the interleaved stimulation paradigm, NEX = 8 was associated with significantly lower glutamate spectral height (p = 0.02), water (p = 0.03), and glutamine (p = 0.03) spectral widths, but there was no significant difference in all spectral areas between the two NEX values. Even though the two NEX values offered some differences in observable BOLD effects, their spectral areas were not significantly different in the interleaved visual stimulation experiments.