Effect of signal-to-noise ratio and spectral linewidth on metabolite quantification at 4 T

Metabolic changes assessed by 1H MR spectroscopy in the corpus callosum of post-COVID patients

OBJECTIVE

Many patients with long COVID experience neurological and psychological symptoms. Signal abnormalities on MR images in the corpus callosum have been reported. Knowledge about the metabolic profile in the splenium of the corpus callosum (CCS) may contribute to a better understanding of the pathophysiology of long COVID.

MATERIALS AND METHODS

Eighty-one subjects underwent proton MR spectroscopy examination. The metabolic concentrations of total N-acetylaspartate (NAA), choline-containing compounds (Cho), total creatine (Cr), myo-inositol (mI), and NAA/Cho in the CCS were statistically compared in the group of patients containing 58 subjects with positive IgG COVID-19 antibodies or positive SARS-CoV-2 qPCR test at least two months before the MR and the group of healthy controls containing 23 subjects with negative IgG antibodies.

RESULTS

An age-dependent effect of SARS-CoV-2 on Cho concentrations in the CCS has been observed. Considering the subjective threshold of age = 40 years, older patients showed significantly increased Cho concentrations in the CCS than older healthy controls (p = 0.02). NAA, Cr, and mI were unchanged. All metabolite concentrations in the CCS of younger post-COVID-19 patients remained unaffected by SARS-CoV-2. Cho did not show any difference between symptomatic and asymptomatic patients (p = 0.91).

DISCUSSION

Our results suggest that SARS-CoV-2 disproportionately increases Cho concentration in the CCS among older post-COVID-19 patients compared to younger ones. The observed changes in Cho may be related to the microstructural reorganization in the CCS also reported in diffusion measurements rather than increased membrane turnover. These changes do not seem to be related to neuropsychological problems of the post-COVID-19 patients. Further metabolic studies are recommended to confirm these observations.

Linewidth-related bias in modelled concentration estimates from GABA-edited 1H-MRS

J-difference-edited MRS is widely used to study GABA in the human brain. Editing for low-concentration target molecules (such as GABA) typically exhibits lower signal-to-noise ratio (SNR) than conventional non-edited MRS, varying with acquisition region, volume and duration. Moreover, spectral lineshape may be influenced by age-, pathology-, or brain-region-specific effects of metabolite T2, or by task-related blood-oxygen level dependent (BOLD) changes in functional MRS contexts. Differences in both SNR and lineshape may have systematic effects on concentration estimates derived from spectral modelling. The present study characterises the impact of lineshape and SNR on GABA+ estimates from different modelling algorithms: FSL-MRS, Gannet, LCModel, Osprey, spant and Tarquin. Publicly available multi-site GABA-edited data (222 healthy subjects from 20 sites; conventional MEGA-PRESS editing; TE = 68 ms) were pre-processed with a standardised pipeline, then filtered to apply controlled levels of Lorentzian and Gaussian linebroadening and SNR reduction. Increased Lorentzian linewidth was associated with a 2-5% decrease in GABA+ estimates per Hz, observed consistently (albeit to varying degrees) across datasets and most algorithms. Weaker, often opposing effects were observed for Gaussian linebroadening. Variations are likely caused by differing baseline parametrization and lineshape constraints between models. Effects of linewidth on other metabolites (e.g., Glx and tCr) varied, suggesting that a linewidth confound may persist after scaling to an internal reference. These findings indicate a potentially significant confound for studies where linewidth may differ systematically between groups or experimental conditions, e.g. due to T2 differences between brain regions, age, or pathology, or varying T2* due to BOLD-related changes. We conclude that linewidth effects need to be rigorously considered during experimental design and data processing, for example by incorporating linewidth into statistical analysis of modelling outcomes or development of appropriate lineshape matching algorithms.

Improving magnetic resonance spectroscopy in the brainstem periaqueductal gray using spectral registration

PURPOSE

Functional understanding of the periaqueductal gray (PAG), a clinically relevant brainstem region, can be advanced using 1 H-MRS. However, the PAG's small size and high levels of physiological noise are methodologically challenging. This study aimed to (1) improve 1 H-MRS quality in the PAG using spectral registration for frequency and phase error correction; (2) investigate whether spectral registration is particularly useful in cases of greater head motion; and (3) examine metabolite quantification using literature-based or individual-based water relaxation times.

METHODS

Spectra were acquired in 33 healthy volunteers (50.1 years, SD = 17.19, 18 females) on a 3 T Philipps MR system using a point-resolved spectroscopy (PRESS) sequence optimized with very selective saturation pulses (OVERPRESS) and voxel-based flip angle calibration (effective volume of interest size: 8.8 × 10.2 × 12.2 mm3 ). Spectra were fitted using LCModel and SNR, NAA peak linewidths and Cramér-Rao lower bounds (CRLBs) were measured after spectral registration and after minimal frequency alignment.

RESULTS

Spectral registration improved SNR by 5% (p = 0.026, median value post-correction: 18.0) and spectral linewidth by 23% (p < 0.001, 4.3 Hz), and reduced the metabolites' CRLBs by 1% to 15% (p < 0.026). Correlational analyses revealed smaller SNR improvements with greater head motion (p = 0.010) recorded using a markerless motion tracking system. Higher metabolite concentrations were detected using individual-based compared to literature-based water relaxation times (p < 0.001).

CONCLUSION

This study demonstrates high-quality 1 H-MRS acquisition in the PAG using spectral registration. This shows promise for future 1 H-MRS studies in the PAG and possibly other clinically relevant brain regions with similar methodological challenges.

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

PURPOSE

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.

METHODS

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.

RESULTS

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.

CONCLUSION

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.

From bench to bedside: The mGluR5 system in people with and without Autism Spectrum Disorder and animal model systems

The metabotropic glutamate receptor 5 (mGluR5) is a key regulator of excitatory (E) glutamate and inhibitory (I) γ-amino butyric acid (GABA) signalling in the brain. Despite the close functional ties between mGluR5 and E/I signalling, no-one has directly examined the relationship between mGluR5 and glutamate or GABA in vivo in the human brain of autistic individuals. We measured [¹⁸F] FPEB (¹⁸F-3-fluoro-5-[(pyridin-3-yl)ethynyl]benzonitrile) binding in 15 adults (6 with Autism Spectrum Disorder) using two regions of interest, the left dorsomedial prefrontal cortex and a region primarily composed of left striatum and thalamus. These two regions were mapped out using MEGA-PRESS voxels and then superimposed on reconstructed PET images. This allowed for direct comparison between mGluR5, GABA + and Glx. To better understand the molecular underpinnings of our results we used an autoradiography study of mGluR5 in three mouse models associated with ASD: Cntnap2 knockout, Shank3 knockout, and 16p11.2 deletion. Autistic individuals had significantly higher [¹⁸F] FPEB binding (t (13) = -2.86, p = 0.047) in the left striatum/thalamus region of interest as compared to controls. Within this region, there was a strong negative correlation between GABA + and mGluR5 density across the entire cohort (Pearson's correlation: r (14) = -0.763, p = 0.002). Cntnap2 KO mice had significantly higher mGlu5 receptor binding in the striatum (caudate-putamen) as compared to wild-type (WT) mice (n = 15, p = 0.03). There were no differences in mGluR5 binding for mice with the Shank3 knockout or 16p11.2 deletion. Given that Cntnap2 is associated with a specific striatal deficit of parvalbumin positive GABA interneurons and 'autistic' features, our findings suggest that an increase in mGluR5 in ASD may relate to GABAergic interneuron abnormalities.

1H-MR spectroscopy in grading of cerebral glioma: A new view point, MRS image quality assessment

Background

Noninvasive preoperative prediction of histological grading is essential for clinical management of cerebral glioma.

Purpose

This study aimed to investigate the association between the image quality assessment of 1H magnetic resonance spectroscopy and accurate grading of glioma.

Materials and Methods

98 glioma patients confirmed by pathology were retrospectively recruited in this single-center study. All patients underwent 1H-MRS examination at 3.0T before surgery. According to WHO standards, all cases were divided into two groups: low-grade glioma (grade I and II, 48 cases) and high-grade glioma (grades III and IV, 50 cases). The metabolite ratios in both grades were calculated before and after image quality assessment. The area under the receiver operating characteristic (ROC) curve was used to evaluate the capacity of each ratio in glioma grading.

Results

The Cho/Cr, Cho/NAA and NAA/Cr metabolite ratios had certain differences in each glioma group before and after MRS image quality assessment. In the low-grade glioma group, there was a dramatic difference in the Cho/Cr ratio before and after image quality assessment (p = 0.011). After MRS image quality assessment, the accuracy of glioma grading was significantly improved. The Cho/Cr ratio with 83.3% sensitivity and 93.7% specificity is the best index of glioma grading, with the optimal cutoff value of the Cho/Cr ratio being 3.72.

Conclusion

The image quality of MRS does affect the metabolite ratios and the results of glioma grading. MRS image quality assessment can observably improve the accuracy rate of glioma grading. The Cho/Cr ratio has the best diagnostic performance in differentiating high-grade from low-grade glioma.

What is the optimal schedule for multiparametric MRS? A magnetic resonance fingerprinting perspective

Clinical magnetic resonance spectroscopy (MRS) mainly concerns itself with the quantification of metabolite concentrations. Metabolite relaxation values, which reflect the microscopic state of specific cellular and sub-cellular environments, could potentially hold additional valuable information, but are rarely acquired within clinical scan times. By varying the flip angle, repetition time and echo time in a preset way (termed a schedule), and matching the resulting signals to a pre-generated dictionary - an approach dubbed magnetic resonance fingerprinting - it is possible to encode the spins' relaxation times into the acquired signal, simultaneously quantifying multiple tissue parameters for each metabolite. Herein, we optimized the schedule to minimize the averaged root mean square error (RMSE) across all estimated parameters: concentrations, longitudinal and transverse relaxation time, and transmitter inhomogeneity. The optimal schedules were validated in phantoms and, subsequently, in a cohort of healthy volunteers, in a 4.5 mL parietal white matter single voxel and an acquisition time under 5 minutes. The average intra-subject, inter-scan coefficients of variation (CVs) for metabolite concentrations, T₁ and T₂ relaxation times were found to be 3.4%, 4.6% and 4.7% in-vivo, respectively, averaged over all major singlets. Coupled metabolites were quantified using the short echo time schedule entries and spectral fitting, and reliable estimates of glutamate+glutamine, glutathione and myo-inositol were obtained.

Longitudinal quantification of metabolites and macromolecules reveals age- and sex-related changes in the healthy Fischer 344 rat brain

Normal aging is associated with numerous biological changes, including altered brain metabolism and tissue chemistry. In vivo characterization of the neurochemical profile during aging is possible using magnetic resonance spectroscopy, a powerful noninvasive technique capable of quantifying brain metabolites involved in physiological processes that become impaired with age. A prominent macromolecular signal underlies those of brain metabolites and is particularly visible at high fields; parameterization of this signal into components improves quantification and expands the number of biomarkers comprising the neurochemical profile. The present study reports, for the first time, the simultaneous absolute quantification of brain metabolites and individual macromolecules in aging male and female Fischer 344 rats, measured longitudinally using proton magnetic resonance spectroscopy at 7 T. We identified age- and sex-related changes in neurochemistry, with prominent differences in metabolites implicated in anaerobic energy metabolism, antioxidant defenses, and neuroprotection, as well as numerous macromolecule changes. These findings contribute to our understanding of the neurobiological processes associated with healthy aging, critical for the proper identification and management of pathologic aging trajectories. This article is part of the Virtual Special Issue titled COGNITIVE NEUROSCIENCE OF HEALTHY AND PATHOLOGICAL AGING. The full issue can be found on ScienceDirect athttps://www.sciencedirect.com/journal/neurobiology-of-aging/special-issue/105379XPWJP.

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.

Comparison of Multivendor Single-Voxel MR Spectroscopy Data Acquired in Healthy Brain at 26 Sites

Background The hardware and software differences between MR vendors and individual sites influence the quantification of MR spectroscopy data. An analysis of a large data set may help to better understand sources of the total variance in quantified metabolite levels. Purpose To compare multisite quantitative brain MR spectroscopy data acquired in healthy participants at 26 sites by using the vendor-supplied single-voxel point-resolved spectroscopy (PRESS) sequence. Materials and Methods An MR spectroscopy protocol to acquire short-echo-time PRESS data from the midparietal region of the brain was disseminated to 26 research sites operating 3.0-T MR scanners from three different vendors. In this prospective study, healthy participants were scanned between July 2016 and December 2017. Data were analyzed by using software with simulated basis sets customized for each vendor implementation. The proportion of total variance attributed to vendor-, site-, and participant-related effects was estimated by using a linear mixed-effects model. P values were derived through parametric bootstrapping of the linear mixed-effects models (denoted Pboot). Results In total, 296 participants (mean age, 26 years ± 4.6; 155 women and 141 men) were scanned. Good-quality data were recorded from all sites, as evidenced by a consistent linewidth of N-acetylaspartate (range, 4.4-5.0 Hz), signal-to-noise ratio (range, 174-289), and low Cramér-Rao lower bounds (≤5%) for all of the major metabolites. Among the major metabolites, no vendor effects were found for levels of myo-inositol (Pboot > .90), N-acetylaspartate and N-acetylaspartylglutamate (Pboot = .13), or glutamate and glutamine (Pboot = .11). Among the smaller resonances, no vendor effects were found for ascorbate (Pboot = .08), aspartate (Pboot > .90), glutathione (Pboot > .90), or lactate (Pboot = .28). Conclusion Multisite multivendor single-voxel MR spectroscopy studies performed at 3.0 T can yield results that are coherent across vendors, provided that vendor differences in pulse sequence implementation are accounted for in data analysis. However, the site-related effects on variability were more profound and suggest the need for further standardization of spectroscopic protocols. © RSNA, 2020 Online supplemental material is available for this article.

Potential clinical impact of multiparametric quantitative MR spectroscopy in neurological disorders: A review and analysis

PURPOSE

Unlike conventional MR spectroscopy (MRS), which only measures metabolite concentrations, multiparametric MRS also quantifies their longitudinal (T1 ) and transverse (T2 ) relaxation times, as well as the radiofrequency transmitter inhomogeneity (B1+ ). To test whether knowledge of these additional parameters can improve the clinical utility of brain MRS, we compare the conventional and multiparametric approaches in terms of expected classification accuracy in differentiating controls from patients with neurological disorders.

THEORY AND METHODS

A literature review was conducted to compile metabolic concentrations and relaxation times in a wide range of neuropathologies and regions of interest. Simulations were performed to construct receiver operating characteristic curves and compute the associated areas (area under the curve) to examine the sensitivity and specificity of MRS for detecting each pathology in each region. Classification accuracy was assessed using metabolite concentrations corrected using population-averages for T1 , T2 , and B1+ (conventional MRS); using metabolite concentrations corrected using per-subject values (multiparametric MRS); and using an optimal linear multiparametric estimator comprised of the metabolites' concentrations and relaxation constants (multiparametric MRS). Additional simulations were conducted to find the minimal intra-subject precision needed for each parameter.

RESULTS

Compared with conventional MRS, multiparametric approaches yielded area under the curve improvements for almost all neuropathologies and regions of interest. The median area under the curve increased by 0.14 over the entire dataset, and by 0.24 over the 10 instances with the largest individual increases.

CONCLUSIONS

Multiparametric MRS can substantially improve the clinical utility of MRS in diagnosing and assessing brain pathology, motivating the design and use of novel multiparametric sequences.

Quantifying the Metabolic Signature of Multiple Sclerosis by in vivo Proton Magnetic Resonance Spectroscopy: Current Challenges and Future Outlook in the Translation From Proton Signal to Diagnostic Biomarker

Proton magnetic resonance spectroscopy (¹H-MRS) offers a growing variety of methods for querying potential diagnostic biomarkers of multiple sclerosis in living central nervous system tissue. For the past three decades, ¹H-MRS has enabled the acquisition of a rich dataset suggestive of numerous metabolic alterations in lesions, normal-appearing white matter, gray matter, and spinal cord of individuals with multiple sclerosis, but this body of information is not free of seeming internal contradiction. The use of ¹H-MRS signals as diagnostic biomarkers depends on reproducible and generalizable sensitivity and specificity to disease state that can be confounded by a multitude of influences, including experiment group classification and demographics; acquisition sequence; spectral quality and quantifiability; the contribution of macromolecules and lipids to the spectroscopic baseline; spectral quantification pipeline; voxel tissue and lesion composition; T₁ and T₂ relaxation; B₁ field characteristics; and other features of study design, spectral acquisition and processing, and metabolite quantification about which the experimenter may possess imperfect or incomplete information. The direct comparison of ¹H-MRS data from individuals with and without multiple sclerosis poses a special challenge in this regard, as several lines of evidence suggest that experimental cohorts may differ significantly in some of these parameters. We review the existing findings of in vivo¹H-MRS on central nervous system metabolic abnormalities in multiple sclerosis and its subtypes within the context of study design, spectral acquisition and processing, and metabolite quantification and offer an outlook on technical considerations, including the growing use of machine learning, by future investigations into diagnostic biomarkers of multiple sclerosis measurable by ¹H-MRS.

Optimizing acquisition and fitting conditions for 1 H MR spectroscopy investigations in global brain pathology

PURPOSE

To optimize acquisition and fitting conditions for nonfocal disease in terms of voxel size and use of individual coil element data. Increasing the voxel size yields a higher signal-to-noise ratio, but leads to larger linewidths and more artifacts. Several ways to improve the spectral quality for large voxels are exploited and the optimal use of individual coil signals investigated.

METHODS

Ten human subjects were measured at 3 T using a 64-channel receive head coil with a semi-LASER localization sequence under optimized and deliberately mis-set field homogeneity. Eight different voxel sizes (8 to 99 cm³ ) were probed. Spectra were fitted either as weighted sums of the individual coil elements or simultaneously without summation. Eighteen metabolites were included in the fit model that also included the lineshapes from all coil elements as reflected in water reference data. Fitting errors for creatine, myo-Inositol and glutamate are reported as representative parameters to judge optimal acquisition and evaluation conditions.

RESULTS

Minimal Cramér-Rao lower bounds and thus optimal acquisition conditions were found for a voxel size of ~ 70 cm³ for the representative upfield metabolites. Spectral quality in terms of lineshape and artifact appearance was determined to differ substantially between coil elements. Simultaneous fitting of spectra from individual coil elements instead of traditional fitting of a weighted sum spectrum reduced Cramer-Rao lower bounds by up to 17% for large voxel sizes.

CONCLUSION

The optimal voxel size for best precision in determined metabolite content is surprisingly large. Such an acquisition condition is most relevant for detection of low-concentration metabolites, like NAD⁺ or phenylalanine, but also for longitudinal studies where very small alterations in metabolite content are targeted. In addition, simultaneous fitting of single channel spectra enforcing lineshape and coil sensitivity information proved to be superior to traditional signal combination with subsequent fitting.

In situ postmortem ethanol quantification in the cerebrospinal fluid by non-water-suppressed proton MRS

Determination of the ethanol concentration in corpses with MRS would allow a reproducible forensic assessment by which evidence is collected in a noninvasive manner. However, although MRS has been successfully used to detect ethanol in vivo, it has not been applied to postmortem ethanol quantification in situ. The present study examined the feasibility of the noninvasive measurement of the ethanol concentration in human corpses with MRS. A total of 15 corpses with suspected alcohol consumption before demise underwent examination in a 3 T whole body scanner. To address the partial overlap of the ethanol and lactate signal in the postmortem spectrum, non-water-suppressed single voxel spectra were recorded in the cerebrospinal fluid (CSF) of the left lateral ventricle via the metabolite cycling technique. The ethanol signals were quantified using the internal water as reference standard, as well as based on a reference signal acquired in a phantom. The measured values were compared with biochemically determined concentrations in the blood (BAC) and CSF (CSFAC). In 8 of the 15 corpses a BAC above zero was determined (range 0.03-1.68 g/kg). In all of these 8 corpses, ethanol was measured in CSF with the proposed MRS protocol. The two applied MRS calibration strategies resulted in similar concentrations. However, the MRS measurements generally overestimated the ethanol concentration by 0.09 g/kg (4%) to 0.72 g/kg (45%) as compared with the CSFAC value. The presented MRS protocol allows the measurement of ethanol in the CSF in human corpses and provides an estimation of the ethanol concentration prior to autopsy. Observed deviations from biochemically determined concentrations are mainly explained by the approximate correction of the relaxation attenuation of the ethanol signal.

Quantitative analysis of spatial averaging effect on chemical shift imaging SNR and noise coherence with k-space sampling schemes

Spatial averaging of multiple voxels from high-resolution chemical shift imaging (hrCSI) is a common strategy for in vivo metabolic studies to achieve a better signal-to-noise ratio (SNR) for a region-of-interest. However, the mechanism about how the spatial averaging approach influences the respective spectral signal and noise and its relevance to the k-space sampling schemes remains unclear. Using three-dimension ¹⁷O CSI technique with the weighted k-space sampling method of Fourier series window, we performed quantitative SNR comparisons between a single low-resolution CSI (lrCSI) voxel (being 27 times larger than the hrCSI voxel size) and the spatially averaged hrCSI voxels with matched sampling volume and location. We demonstrated that the averaged hrCSI voxel spectrum had a large SNR loss (> 4 times) compared to the lrCSI voxel, which was resulted from unmatched increases in signal (~1.9 fold) and noise (~9.3 fold). The signal increase was caused by the spatial overlapping between the adjacent hrCSI voxels. The substantial noise increase was mainly attributed to the strong noise coherence among hrCSI voxels acquired with the weighted k-space sampling. This study presents a quantitative relation between the k-space sampling schemes to an apparent SNR penalty of the spatial averaging approach. The information could be useful for designing CSI acquisition method and determination of optimal spatial resolution for in vivo metabolic imaging studies.

Designing GABA-edited magnetic resonance spectroscopy studies: Considerations of scan duration, signal-to-noise ratio and sample size

BACKGROUND

The relationships between scan duration, signal-to-noise ratio (SNR) and sample size must be considered and understood to design optimal GABA-edited magnetic resonance spectroscopy (MRS) studies.

NEW METHOD

Simulations investigated the effects of signal averaging on SNR, measurement error and group-level variance against a known ground truth. Relative root mean square errors (measurement error) and coefficients of variation (group-level variance) were calculated. GABA-edited data from 18 participants acquired from five voxels were used to examine the relationships between scan duration, SNR and quantitative outcomes in vivo. These relationships were then used to determine the sample sizes required to observe different effect sizes.

RESULTS

In both simulated and in vivo data, SNR increased with the square root of the number of averages. Both measurement error and group-level variance were shown to follow an inverse-square-root function, indicating no significant impact of cumulative artifacts. Comparisons between the first two-thirds of the data and the full dataset showed no statistical difference in group-level variance. There was, however, some variability across the five voxels depending on SNR, which impacted the sample sizes needed to detect group differences in specific brain regions.

COMPARISON WITH EXISTING METHODS

Typical scan durations can be reduced if taking into account a statistically acceptable amount of variance and the magnitudes of predicted effects.

CONCLUSIONS

While scan duration in GABA-edited MRS has typically been considered in terms of SNR, it is more appropriate to think in terms of the amount of measurement error and group-level variance that provides sufficient statistical power.

Comparison of reproducibility of single voxel spectroscopy and whole-brain magnetic resonance spectroscopy imaging at 3T

To date, single voxel spectroscopy (SVS) is the most commonly used MRS technique. SVS is relatively easy to use and provides automated and immediate access to the resulting spectra. However, it is also limited in spatial coverage. A new and very promising MRS technique allows for whole-brain MR spectroscopic imaging (WB-MRSI) with much improved spatial resolution. Establishing the reproducibility of data obtained using SVS and WB-MRSI is an important first step for using these techniques to evaluate longitudinal changes in metabolite concentration. The purpose of this study was to assess and directly compare the reproducibility of metabolite quantification at 3T using SVS and WB-MRSI in 'hand-knob' areas of motor cortices and hippocampi in healthy volunteers. Ten healthy adults were scanned using both SVS and WB-MRSI on three occasions one week apart. N-acetyl aspartate (NAA), creatine (Cr), choline (Cho) and myo-inositol (mI) were quantified using SVS and WB-MRSI with reference to both Cr and H₂ O. The reproducibility of each technique was evaluated using the coefficient of variation (CV), and the correspondence between the two techniques was assessed using Pearson correlation analysis. The measured mean (range) intra-subject CVs for SVS were 5.90 (2.65-10.66)% for metabolites (i.e. NAA, Cho, mI) relative to Cr, and 8.46 (4.21-21.07)% for metabolites (NAA, Cr, Cho, mI) relative to H₂ O. The mean (range) CVs for WB-MRSI were 7.56 (2.78-11.41)% for metabolites relative to Cr, and 7.79 (4.57-14.11)% for metabolites relative to H₂ O. Significant positive correlations were observed between metabolites quantified using SVS and WB-MRSI techniques when the Cr but not H₂ O reference was used. The results demonstrate that reproducibilities of SVS and WB-MRSI are similar for quantifying the four major metabolites (NAA, Cr, Cho, mI); both SVS and WB-MRSI exhibited good reproducibility. Our findings add reference information for choosing the appropriate ¹ H-MRS technique in future studies.

Designing GABA-edited magnetic resonance spectroscopy studies: Considerations of scan duration, signal-to-noise ratio and sample size

BACKGROUND

The relationships between scan duration, signal-to-noise ratio (SNR) and sample size must be considered and understood to design optimal GABA-edited magnetic resonance spectroscopy (MRS) studies.

NEW METHOD

Simulations investigated the effects of signal averaging on SNR, measurement error and group-level variance against a known ground truth. Relative root mean square errors (measurement error) and coefficients of variation (group-level variance) were calculated. GABA-edited data from 18 participants acquired from five voxels were used to examine the relationships between scan duration, SNR and quantitative outcomes in vivo. These relationships were then used to determine the sample sizes required to observe different effect sizes.

RESULTS

In both simulated and in vivo data, SNR increased with the square root of the number of averages. Both measurement error and group-level variance were shown to follow an inverse-square-root function, indicating no significant impact of cumulative artifacts. Comparisons between the first two-thirds of the data and the full dataset showed no statistical difference in group-level variance. There was, however, some variability across the five voxels depending on SNR, which impacted the sample sizes needed to detect group differences in specific brain regions.

COMPARISON WITH EXISTING METHODS

Typical scan durations can be reduced if taking into account a statistically acceptable amount of variance and the magnitudes of predicted effects.

CONCLUSIONS

While scan duration in GABA-edited MRS has typically been considered in terms of SNR, it is more appropriate to think in terms of the amount of measurement error and group-level variance that provides sufficient statistical power.

Interleaved 31 P MRS imaging of human frontal and occipital lobes using dual RF coils in combination with single-channel transmitter-receiver and dynamic B0 shimming

In vivo 31 P magnetic resonance spectroscopy (MRS) provides a unique tool for the non-invasive study of brain energy metabolism and mitochondrial function. The assessment of bioenergetic impairment in different brain regions is essential to understand the pathophysiology and progression of human brain diseases. This article presents a simple and effective approach which allows the interleaved measurement of 31 P spectra and imaging from two distinct human brain regions of interest with dynamic B0 shimming capability. A transistor-transistor logic controller was employed to actively switch the single-channel X-nuclear radiofrequency (RF) transmitter-receiver between two 31 P RF surface coils, enabling the interleaved acquisition of two 31 P free induction decays (FIDs) from human occipital and frontal lobes within the same repetition time. Linear gradients were incorporated into the RF pulse sequence to perform the first-order dynamic shimming to further improve spectral resolution. The overall results demonstrate that the approach provides a cost-effective and time-efficient solution for reliable 31 P MRS measurement of cerebral phosphate metabolites and adenosine triphosphate (ATP) metabolic fluxes from two human brain regions with high detection sensitivity and spectral quality at 7 T. The same design concept can be extended to acquire multiple spectra from more than two brain regions or can be employed for other magnetic resonance applications beyond the 31 P spin.

Big GABA: Edited MR spectroscopy at 24 research sites

Magnetic resonance spectroscopy (MRS) is the only biomedical imaging method that can noninvasively detect endogenous signals from the neurotransmitter γ-aminobutyric acid (GABA) in the human brain. Its increasing popularity has been aided by improvements in scanner hardware and acquisition methodology, as well as by broader access to pulse sequences that can selectively detect GABA, in particular J-difference spectral editing sequences. Nevertheless, implementations of GABA-edited MRS remain diverse across research sites, making comparisons between studies challenging. This large-scale multi-vendor, multi-site study seeks to better understand the factors that impact measurement outcomes of GABA-edited MRS. An international consortium of 24 research sites was formed. Data from 272 healthy adults were acquired on scanners from the three major MRI vendors and analyzed using the Gannet processing pipeline. MRS data were acquired in the medial parietal lobe with standard GABA+ and macromolecule- (MM-) suppressed GABA editing. The coefficient of variation across the entire cohort was 12% for GABA+ measurements and 28% for MM-suppressed GABA measurements. A multilevel analysis revealed that most of the variance (72%) in the GABA+ data was accounted for by differences between participants within-site, while site-level differences accounted for comparatively more variance (20%) than vendor-level differences (8%). For MM-suppressed GABA data, the variance was distributed equally between site- (50%) and participant-level (50%) differences. The findings show that GABA+ measurements exhibit strong agreement when implemented with a standard protocol. There is, however, increased variability for MM-suppressed GABA measurements that is attributed in part to differences in site-to-site data acquisition. This study's protocol establishes a framework for future methodological standardization of GABA-edited MRS, while the results provide valuable benchmarks for the MRS community.

Towards a neurochemical profile of the amygdala using short-TE 1 H magnetic resonance spectroscopy at 3 T

The amygdala plays a key role in emotional learning and in the processing of emotions. As disturbed amygdala function has been linked to several psychiatric conditions, a knowledge of its biochemistry, especially neurotransmitter levels, is highly desirable. The spin echo full intensity acquired localized (SPECIAL) sequence, together with a transmit/receive coil, was used to perform very short-TE magnetic resonance spectroscopy at 3 T to determine the neurochemical profile in a spectroscopic voxel containing the amygdala in 21 healthy adult subjects. For spectral analysis, advanced data processing was applied in combination with a macromolecule baseline measured in the anterior cingulate for spectral fitting. The concentrations of total N-acetylaspartate, total creatine, total choline, myo-inositol and, for the first time, glutamate were quantified with high reliability (uncertainties far below 10%). For these metabolites, the inter-individual variability, reflected by the relative standard deviations for the cohort studied, varied between 12% (glutamate) and 22% (myo-inositol). Glutamine and glutathione could also be determined, albeit with lower precision. Retest on four subjects showed good reproducibility. The devised method allows the determination of metabolite concentrations in the amygdala voxel, including glutamate, provides an estimation of glutamine and glutathione, and may help in the study of disturbed amygdala metabolism in pathologies such as anxiety disorder, autism and major depression.

Spectral data de-noising using semi-classical signal analysis: application to localized MRS

In this paper, we propose a new post-processing technique called semi-classical signal analysis (SCSA) for MRS data de-noising. Similar to Fourier transformation, SCSA decomposes the input real positive MR spectrum into a set of linear combinations of squared eigenfunctions equivalently represented by localized functions with shape derived from the potential function of the Schrödinger operator. In this manner, the MRS spectral peaks represented as a sum of these 'shaped like' functions are efficiently separated from noise and accurately analyzed. The performance of the method is tested by analyzing simulated and real MRS data. The results obtained demonstrate that the SCSA method is highly efficient in localized MRS data de-noising and allows for an accurate data quantification.

Forecasting the quality of water-suppressed 1 H MR spectra based on a single-shot water scan

PURPOSE

To investigate whether an initial non-water-suppressed acquisition that provides information about the signal-to-noise ratio (SNR) and linewidth is enough to forecast the maximally achievable final spectral quality and thus inform the operator whether the foreseen number of averages and achieved field homogeneity is adequate.

METHODS

A large range of spectra with varying SNR and linewidth was simulated and fitted with popular fitting programs to determine the dependence of fitting errors on linewidth and SNR. A tool to forecast variance based on a single acquisition was developed and its performance evaluated on simulated and in vivo data obtained at 3 Tesla from various brain regions and acquisition settings.

RESULTS

A strong correlation to real uncertainties in estimated metabolite contents was found for the forecast values and the Cramer-Rao lower bounds obtained from the water-suppressed spectra.

CONCLUSION

It appears to be possible to forecast the best-case errors associated with specific metabolites to be found in model fits of water-suppressed spectra based on a single water scan. Thus, nonspecialist operators will be able to judge ahead of time whether the planned acquisition can possibly be of sufficient quality to answer the targeted clinical question or whether it needs more averages or improved shimming. Magn Reson Med 78:441-451, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Illness versus substance use effects on the frontal white matter in early phase schizophrenia: A 4Tesla (1)H-MRS study

OBJECTIVE

Young adults with early phase schizophrenia often report a past or current pattern of illicit substance use and/or alcohol misuse. Still, little is known about the cumulative and separate effects of each stressor on white matter tissue, at this vulnerable period of brain development.

METHODS

Participants involved 24 healthy controls with a past or current history of sustained illicit drug use and/or alcohol misuse (users), 23 healthy controls without such history (normative data), and 27 users with early phase schizophrenia. (1)H-MRS data were acquired from a large frontal volume encompassing 95% of white matter, using a 4Tesla scanner (LASER sequence, TR/TE 3200/46ms).

RESULTS

Reduced levels of choline-containing compounds (Cho) were specific to the effect of illness (Cohen's d=0.68), with 22% of the variance in Cho levels accounted for by duration of illness. Reduced levels of myoInositol (d=1.10) and creatine plus phosphocreatine (d=1.07) were specific to the effects of illness plus substance use. Effect of substance use on its own was revealed by reductions in levels of glutamate plus glutamine (d=0.83) in control users relative to normative data.

CONCLUSIONS

The specific effect of illness on white matter might indicate a decreased synthesis of membrane phospholipids or alternatively, reduced membrane cellular density. In terms of limitations, this study did not include patients without a lifetime history of substance use (non-users), and the specific effect of each substance used could not be studied separately.

Forebrain deletion of the vesicular acetylcholine transporter results in deficits in executive function, metabolic, and RNA splicing abnormalities in the prefrontal cortex

One of the key brain regions in cognitive processing and executive function is the prefrontal cortex (PFC), which receives cholinergic input from basal forebrain cholinergic neurons. We evaluated the contribution of synaptically released acetylcholine (ACh) to executive function by genetically targeting the vesicular acetylcholine transporter (VAChT) in the mouse forebrain. Executive function was assessed using a pairwise visual discrimination paradigm and the 5-choice serial reaction time task (5-CSRT). In the pairwise test, VAChT-deficient mice were able to learn, but were impaired in reversal learning, suggesting that these mice present cognitive inflexibility. Interestingly, VAChT-targeted mice took longer to reach criteria in the 5-CSRT. Although their performance was indistinguishable from that of control mice during low attentional demand, increased attentional demand revealed striking deficits in VAChT-deleted mice. Galantamine, a cholinesterase inhibitor used in Alzheimer's disease, significantly improved the performance of control mice, but not of VAChT-deficient mice on the 5-CSRT. In vivo magnetic resonance spectroscopy showed altered levels of two neurochemical markers of neuronal function, taurine and lactate, suggesting altered PFC metabolism in VAChT-deficient mice. The PFC of these mice displayed a drastic reduction in the splicing factor heterogeneous nuclear ribonucleoprotein A2/B1 (hnRNPA2/B1), whose cholinergic-mediated reduction was previously demonstrated in Alzheimer's disease. Consequently, several key hnRNPA2/B1 target transcripts involved in neuronal function present changes in alternative splicing in VAChT-deficient mice, including pyruvate kinase M, a key enzyme involved in lactate metabolism. We propose that VAChT-targeted mice can be used to model and to dissect the neurochemical basis of executive abnormalities.

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

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

(1)H MR spectroscopy with external reference solution at 1.5 T for differentiating malignant and benign breast lesions: comparison using qualitative and quantitative approaches

OBJECTIVE

To compare the diagnostic capability of proton ((1)H) magnetic resonance spectroscopy (MRS) in differentiating benign from malignant breast lesions on the basis of qualitative and quantitative approaches.

METHODS

We performed single-voxel (1)H MRS for 208 breast lesions, identified a clear total composite choline compounds (tCho) peak of signal-to-noise of ≥2 to represent malignancy (qualitative approach), and regarded tCho concentration equal to or greater than the cut-off value to represent malignancy (quantitative approach). We compared the diagnostic ability of both approaches using the Akaike information criterion (AIC) and McFadden's R (2).

RESULTS

Histologically, 169 lesions were malignant; 39 were benign. The qualitative approach demonstrated 84.6 % sensitivity and 51.3 % specificity for differentiating malignant and benign lesions. The mean tCho concentration was 1.13 mmol/kg for malignancy, 0.43 mmol/kg for benignity. The optimal cut-off point was 0.61 mmol/kg, use of which achieved 68.1 % sensitivity and 79.4 % specificity. Calculated AIC and R (2) score suggested the superiority of the quantitative approach for differentiating malignancy.

CONCLUSIONS

Quantitative MRS provides higher specificity than qualitative MRS for differentiating malignant from benign lesions and could be more useful as an additional examination in routine breast MR imaging.

Improved myo-inositol detection through Carr-Purcell PRESS: a tool for more sensitive mild cognitive impairment diagnosis

A 3-T study is presented, comparing the ability of two (1) H spectroscopy pulse sequences, Carr-Purcell point resolved spectroscopy (CPRESS; TE = 45 msec), and conventional PRESS (TE = 35 msec), to separate between groups of 20 normal control (NC) and 20 mild cognitive impairment (MCI) subjects. Both sequences showed higher myo-inositol (mI) and mI/N-acetyl-aspartate (NAA) levels in the posterior cingulate gyrus of the MCI subjects. The increased intrasubject repeatability of mI and mI/NAA CPRESS measurements (∼ 6% vs. 9% for PRESS) translated into decreased intraclass variability. A 22% intraclass mI PRESS variability was reduced to 16% for CPRESS, and an 18% intraclass mI/NAA PRESS variability was reduced to 12% for CPRESS for the group of NC subjects. Similar results were observed for the MCI subjects. Decreased intraclass variability led to improved separation between NC and MCI subjects (P = 0.017 for PRESS and P < 0.0001 for CPRESS mI/NAA, the best NC/MCI discriminant for each method). Seventy-five percent sensitivity at eighty percent specificity was demonstrated by mI/NAA CPRESS measurements in separating NC from MCI subjects. High correlations were also observed between subject performance on a number of neuropsychological tests (probing verbal memory, visuoconstruction performance, and visual motor integration) and the mI/NAA ratio; higher correlation coefficients (with stronger statistical significance) were consistently evident for CPRESS than for PRESS data.

Magnetic resonance spectroscopy biomarkers in premanifest and early Huntington disease

OBJECTIVES

To evaluate in vivo brain metabolite differences in control subjects, individuals with premanifest Huntington disease (pre-HD), and individuals with early HD using ¹H magnetic resonance spectroscopy (MRS) and to assess their relationship with motor performance.

METHODS

Eighty-five participants (30 controls, 25 pre-HD, and 30 early HD) were recruited as part of the TRACK-HD study. Eighty-four were scanned at 3 T with single-voxel spectroscopy in the left putamen. Disease burden score was >220 among pre-HD individuals. Subjects underwent TRACK-HD motor assessment including Unified Huntington's Disease Rating Scale (UHDRS) motor scoring and a novel quantitative motor battery. Statistical analyses included linear regression and one-way analysis of variance.

RESULTS

Total N-acetylaspartate (tNAA), a neuronal integrity marker, was lower in early HD (∼15%) vs controls (p < 0.001). N-acetylaspartate (NAA), a constituent of tNAA, was lower in pre-HD (∼8%) and early HD (∼17%) vs controls (p < 0.05). The glial cell marker, myo-inositol (mI), was 50% higher in early HD vs pre-HD (p < 0.01). In early HD, mI correlated with UHDRS motor score (R² = 0.23, p < 0.05). Across pre-HD and early HD, tNAA correlated with performance on a tongue pressure task (R² = 0.30, p < 0.0001) and with disease burden score (R² = 0.17, p < 0.005).

CONCLUSIONS

We demonstrate lower putaminal tNAA in early HD compared to controls in a cross-section of subjects. A novel biomarker role for mI in early HD was also identified. These findings resolve disagreement in the literature about the role of MRS as an HD biomarker. We conclude that putaminal MRS measurements of NAA and mI are promising potential biomarkers of HD onset and progression.

Metabolic correlatives of brain activity in a FOS epilepsy patient

The correlation and the interactions between neuronal activity and underlying metabolic dynamics are still a matter of debate, especially in pathological conditions. This study reports findings obtained on a subject suffering from fixation-off sensitivity (FOS) epilepsy, exploited as a model system of triggerable anomalous electrical activity. Functional Magnetic Resonance Spectroscopy was used to investigate the metabolic response to visual spike-inducing stimuli in a single voxel placed in the temporo-occipital lobe of a FOS epilepsy patient. MRS measurements were additionally performed on a control group of five healthy volunteers. The FOS patient also underwent an EEG session with the same stimulus paradigm. Uniquely in the FOS patient, glutamate and glutamine concentration increased during the first 10 min of stimulation and then returned to baseline. On the other hand, FOS-induced epileptic activity (spiking) endured throughout all the stimulation epoch. The observed metabolic dynamics may be likely linked to a complex interplay between alterations of the metabolic pathways of glutamate and modulation of the neuronal activity.

Optimized glutamate detection at 3T

PURPOSE

To identify the pulse sequence and acquisition parameters that result in the most accurate and repeatable measurements of glutamate (Glu) concentration in the brain at 3T.

MATERIALS AND METHODS

Simulations were performed to compare the accuracy and repeatability of 11 pulse sequences and acquisition parameters, within four general classes (PRESS, STEAM, Carr-Purcell PRESS [CPRESS] and TE averaged PRESS [JPRESS]), the majority of which were previously suggested as optimal for Glu detection. Three of the simulated acquisitions were implemented in a clinical scanner and measures of repeatability in vivo were compared to their simulated values.

RESULTS

Good agreement was demonstrated between simulated and experimentally determined measures of repeatability. Among the acquisitions considered, a CPRESS sequence with minimal echo time, together with, possibly, a short TE PRESS sequence, result in the most repeatable within session Glu measurements, while slightly overestimating the Glu concentration. Excellent accuracy is demonstrated by the simulations for a JPRESS sequence, at the expense of lower repeatability than optimal PRESS or CPRESS sequences.

CONCLUSION

Further proof of concept is presented toward validation of a simulation approach to understand pulse sequence performance in measuring the concentration of a given metabolite. Improved within session Glu measurement repeatability is predicted for CPRESS and demonstrated in vivo.

Time-resolved functional 1H MR spectroscopic detection of glutamate concentration changes in the brain during acute heat pain stimulation

Non-invasive in vivo detection of cortical neurotransmitter concentrations and their changes in the presence of pain may help to better understand the biochemical principles of pain processing in the brain. In the present study acute heat pain related changes of the excitatory neurotransmitter glutamate were investigated in the anterior insular cortex of healthy volunteers by means of time-resolved functional proton magnetic resonance spectroscopy ((1)H-MRS). Dynamic metabolite changes were estimated with a temporal resolution of five seconds by triggering data acquisition to the time course of the cyclic stimulus application. An overall increase of glutamate concentration up to 18% relative to the reference non-stimulus condition was observed during the application of short pain stimuli.

Spectral resolution amelioration by deconvolution (SPREAD) in MR spectroscopic imaging

PURPOSE

To develop, implement, and evaluate a novel postprocessing method for enhancing the spectral resolution of in vivo MR spectroscopic imaging (MRSI) data.

MATERIALS AND METHODS

Magnetic field inhomogeneity across the imaging volume was determined by acquiring MRI datasets with two differing echo times. The lineshapes of the MRSI spectra were derived from these field maps by simulating an MRSI scan of a virtual sample whose resonance frequencies varied according to the observed variations in the magnetic field. By deconvolving the lineshapes from the measured MRSI spectra, the linebroadening effects of the field inhomogeneities were reduced significantly.

RESULTS

Both phantom and in vivo proton MRSI spectra exhibited significantly enhanced spectral resolutions and improved spectral lineshapes following application of our method. Quantitative studies on a phantom show that, on average, the full width at half maximum of water peaks was reduced 42%, the full width at tenth maximum was reduced 38%, and the asymmetries of the peaks were reduced 86%.

CONCLUSION

Our method reduces the linebroadening and lineshape distortions caused by magnetic field inhomogeneities. It substantially improves the spectral resolution and lineshape of MRSI data.

Which pulse sequence is optimal for myo-inositol detection at 3T?

Optimized myo-inositol (mI) detection is important for diagnosing and monitoring a multitude of pathological conditions of the brain. Simulations are presented in this work, performed to decide which pulse sequence has the most significant advantage in terms of improving repeatability and accuracy of mI measurements at 3T over the pulse sequence used typically in the clinic, a TE = 35 ms PRESS sequence. Five classes of pulse sequences, four previously suggested for optimized mI detection (a short TE PRESS, a Carr-Purcell PRESS sequence, an optimized STEAM sequence, an optimized zero quantum filter), and one optimized for mI detection in this work (a single quantum filter) were compared to a standard, TE = 35 ms pulse sequence. While limiting the SNR of an acquisition to the equivalent SNR of a spectrum acquired in 5 min from an 8 cc voxel, it was found through simulations that the most repeatable mI measurements would be obtained with a Carr-Purcell sequence. This sequence was implemented in a clinical scanner, and improved mI measurements were demonstrated in vivo.

Comment on "Magnetic resonance spectroscopy identifies neural progenitor cells in the live human brain"

Manganas et al. (Reports, 9 November 2007, p. 980) reported the discovery of a biomarker specific for neural progenitor cells detectable using magnetic resonance spectroscopy. A new algorithm was developed to extract the biomarker from noisy in vivo data. We question how this algorithm was validated, because the biomarker overlaps with peaks from nonspecific lipid signals.

Low-grade glioma: correlation of short echo time 1H-MR spectroscopy with 23Na MR imaging

BACKGROUND AND PURPOSE

There is considerable variability in the clinical behavior and treatment response of low-grade (WHO grade II) gliomas. The purpose of this work was to characterize the metabolic profile of low-grade gliomas by using short echo time (1)H-MR spectroscopy and to correlate metabolite levels with MR imaging-measured sodium ((23)Na) signal intensity. Based on previous studies, we hypothesized decreased N-acetylaspartate (NAA) and increased myo-inositol (mIns), choline (Cho), glutamate (Glu), and (23)Na signal intensity in glioma tissue.

MATERIALS AND METHODS

Institutional ethics committee approval and informed consent were obtained for all of the subjects. Proton ((1)H-MR) spectroscopy (TR/TE = 2200/46 ms) and sodium ((23)Na) MR imaging were performed at 4T in 13 subjects (6 women and 7 men; mean age, 44 years) with suspected low-grade glioma. Absolute metabolite levels were quantified, and relative (23)Na levels were measured in low-grade glioma and compared with the contralateral side in the same patients. Two-sided Student t tests were used to test for statistical significance.

RESULTS

Significant decreases were observed for NAA (P < .001) and Glu (P = .004), and increases were observed for mIns (P = .003), Cho (P = .025), and sodium signal intensity (P < .001) in low-grade glioma tissue. Significant correlations (r(2) > 0.25) were observed between NAA and Glu (P < .05) and between NAA and mIns (P < .01). Significant correlations were also observed between (23)Na signal intensity and NAA (P < .01) and between (23)Na signal intensity and Glu (P < .01). Ratios of NAA/mIns, NAA/(23)Na, and NAA/Cho were altered in glioma tissue (P < .001); however based on the t statistic, NAA/(23)Na (t = 9.6) was the most significant, followed by NAA/mIns (t = 6.1), and NAA/Cho (t = 5.0).

CONCLUSION

Although Glu concentration is reduced and mIns concentration is elevated in low-grade glioma tissue, the NAA/(23)Na ratio was the most sensitive indicator of pathologic tissue.

Limits of a localized magnetic resonance spectroscopy assay for ex vivo myocardial triacylglycerol

Localized magnetic resonance spectroscopy (LMRS) promises a powerful non-invasive means to determine myocardial triacylglycerol (TAG) in a clinical setting. Here, the linearity, specificity, robustness, precision, and accuracy of an ex vivo mouse-heart LMRS TAG assay are assessed by quantifying the spatial, spectral, and relaxation-induced uncertainties. The protocol, which is based on localization by adiabatic selective refocusing (LASER) using frequency offset corrected inversion (FOCI) pulses, alternating gradient polarity, and simple post-processing, is shown to have good characteristics. The presented protocol has a benchmark, phantom-based, accuracy of 3%, and when applied to ex vivo mouse hearts the accuracy is 6%, making the LMRS assay comparable to the typical destructive bioanalytical assay.