Proton T 1 relaxation times of metabolites in human occipital white and gray matter at 7 T

Neurochemical characteristics of pathological tissues in epilepsy: A preliminary 1H MR spectroscopy study at 7 T

Background and purpose

This study aims to evaluate the neurochemical characteristics of pathological tissues by 1H magnetic resonance spectroscopy (MRS) in patient with pharmaco-resistant focal epilepsy at 7 T.

Methods

Thirteen patients with drug-resistant epilepsy and focal seizure successfully underwent MRS examinations at 7 T MRI scanners. 1H MR spectra were acquired from two voxels (lesion side and contralateral side) using the semi-adiabatic spin-echo full-intensity localized spectroscopy (sSPECIAL) sequence. Metabolite levels were quantified from LCModel and reported as to total creatine ratio.

Results

In comparison to the contralateral side, lesions in focal cortical dysplasia demonstrated significantly reduced macromolecule and N-acetyl aspartate, significantly increased total choline and glycine + myo-inositol, and a distinct reduction trend of glutamate.

Conclusions

We conclude that performing MRS at high magnetic field offered the potential to reveal metabolic alterations in epilepsy lesions that may help to further understand the underlying pathophysiology of the disease.

Age dependency of neurometabolite T1 relaxation times

PURPOSE

To measure T1 relaxation times of metabolites at 3 T in a healthy aging population and investigate age dependence.

METHODS

A cohort of 101 healthy adults was recruited with approximately 10 male and 10 female participants in each "decade" band: 18 to 29, 30 to 39, 40 to 49, 50 to 59, and 60+ years old. Inversion-recovery PRESS data (TE/TR: 30/2000 ms) were acquired at 8 inversion times (TIs) (300, 400, 511, 637, 780, 947, 1148, and 1400 ms) from voxels in white-matter-rich centrum semiovale (CSO) and gray-matter-rich posterior cingulate cortex (PCC). Modeling of TI-series spectra was performed in Osprey 2.5.0. Quantified metabolite amplitudes for total N-acetylaspartate (tNAA2.0), total creatine at 3.0 ppm (tCr3.0), and 3.9 ppm (tCr3.9), total choline (tCho), myo-inositol (mI), and the sum of glutamine and glutamate (Glx) were modeled to calculate T1 relaxation times of metabolites.

RESULTS

T1 relaxation times of tNAA2.0 in CSO and tNAA2.0, tCr3.0, mI, and Glx in PCC decreased with age. These correlations remained significant when controlling for cortical atrophy. T1 relaxation times were significantly different between PCC and CSO for all metabolites except tCr3.0. We also propose linear models for predicting metabolite T1s at 3 T to be used in future aging studies.

CONCLUSION

Metabolite T1 relaxation times change significantly with age, an effect that will be important to consider for accurate quantitative MRS, particularly in studies of aging.

Rosette Spectroscopic Imaging for Whole-Brain Slab Metabolite Mapping at 7T: Acceleration Potential and Reproducibility

Whole-brain proton magnetic resonance spectroscopic imaging (1H-MRSI) is a non-invasive technique for assessing neurochemical distribution in the brain, offering valuable insights into brain functions and neural diseases. It greatly benefits from the improved SNR at ultrahigh field strengths (≥ 7T). However, 1H-MRSI still faces several challenges, such as long acquisition time and severe signal contamination from water and lipids. In this study, 2D and 3D short TR/TE 1H-FID-MRSI sequences using rosette trajectories were developed with nominal spatial resolutions of 4.48 × 4.48 mm2 and 4.48 × 4.48 × 4.50 mm3, respectively. Water signals were suppressed using an optimized Five-variable-Angle-gaussian-pulses-with-ShorT-total-duration (FAST) water suppression scheme of 76 ms, and lipid signals were removed using the L2 regularization method. Metabolic maps of major 1H metabolites were obtained in 5:40 min with 16 averages and 1 average for the 2D and 3D acquisitions, respectively. Excellent intra-session reproducibility was shown, with the coefficients of variance (CV) being lower than 6% for N-Acetyl-L-aspartic acid (NAA), Glutamate (Glu), total Choline (tCho), Creatine and Phosphocreatine (tCr), and Glycine and Myo-inositol (Gly + Ins). To explore the potential of further acceleration, compressed sensing was applied retrospectively to the 3D datasets. The structural similarity index (SSIM) remained above 0.85 and 0.8 until R = 2 and 3 for the metabolite maps of Glu, NAA, tCr, and tCho, indicating the possibility for further reduction of acquisition time to around 2 min.

A neurometabolic mechanism involving dmPFC/dACC lactate in physical effort-based decision-making

Motivation levels vary across individuals, yet the underlying mechanisms driving these differences remain elusive. The dorsomedial prefrontal cortex/dorsal anterior cingulate cortex (dmPFC/dACC) and the anterior insula (aIns) play crucial roles in effort-based decision-making. Here, we investigate the influence of lactate, a key metabolite involved in energy metabolism and signaling, on decisions involving both physical and mental effort, as well as its effects on neural activation. Using proton magnetic resonance spectroscopy and functional MRI in 63 participants, we find that higher lactate levels in the dmPFC/dACC are associated with reduced motivation for physical effort, a relationship mediated by neural activity within this region. Additionally, plasma and dmPFC/dACC lactate levels correlate, suggesting a systemic influence on brain metabolism. Supported by path analysis, our results highlight lactate's role as a modulator of dmPFC/dACC activity, hinting at a neurometabolic mechanism that integrates both peripheral and central metabolic states with brain function in effort-based decision-making.

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

PURPOSE

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.

METHODS

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.

RESULTS

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%.

CONCLUSION

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.

Metabolite T1 relaxation times decrease across the adult lifespan

Relaxation correction is an integral step in quantifying brain metabolite concentrations measured by in vivo magnetic resonance spectroscopy (MRS). While most quantification routines assume constant T1 relaxation across age, it is possible that aging alters T1 relaxation rates, as is seen for T2 relaxation. Here, we investigate the age dependence of metabolite T1 relaxation times at 3 T in both gray- and white-matter-rich voxels using publicly available metabolite and metabolite-nulled (single inversion recovery TI = 600 ms) spectra acquired at 3 T using Point RESolved Spectroscopy (PRESS) localization. Data were acquired from voxels in the posterior cingulate cortex (PCC) and centrum semiovale (CSO) in 102 healthy volunteers across 5 decades of life (aged 20-69 years). All spectra were analyzed in Osprey v.2.4.0. To estimate T1 relaxation times for total N-acetyl aspartate at 2.0 ppm (tNAA2.0) and total creatine at 3.0 ppm (tCr3.0), the ratio of modeled metabolite residual amplitudes in the metabolite-nulled spectrum to the full metabolite signal was calculated using the single-inversion-recovery signal equation. Correlations between T1 and subject age were evaluated. Spearman correlations revealed that estimated T1 relaxation times of tNAA2.0 (rs = -0.27; p < 0.006) and tCr3.0 (rs = -0.40; p < 0.001) decreased significantly with age in white-matter-rich CSO, and less steeply for tNAA2.0 (rs = -0.228; p = 0.005) and (not significantly for) tCr3.0 (rs = -0.13; p = 0.196) in graymatter-rich PCC. The analysis harnessed a large publicly available cross-sectional dataset to test an important hypothesis, that metabolite T1 relaxation times change with age. This preliminary study stresses the importance of further work to measure age-normed metabolite T1 relaxation times for accurate quantification of metabolite levels in studies of aging.

Neurochemical Predictors of Generalized Learning Induced by Brain Stimulation and Training

Methods of cognitive enhancement for humans are most impactful when they generalize across tasks. However, the extent to which such "transfer" is possible via interventions is widely debated. In addition, the contribution of excitatory and inhibitory processes to such transfer is unknown. Here, in a large-scale neuroimaging individual differences study with humans (both sexes), we paired multitasking training and noninvasive brain stimulation (transcranial direct current stimulation, tDCS) over multiple days and assessed performance across a range of paradigms. In addition, we varied tDCS dosage (1.0 and 2.0 mA), electrode montage (left or right prefrontal regions), and training task (multitasking vs a control task) and assessed GABA and glutamate concentrations via ultrahigh field 7T magnetic resonance spectroscopy. Generalized benefits were observed in spatial attention, indexed by visual search performance, when multitasking training was combined with 1.0 mA stimulation targeting either the left or right prefrontal cortex (PFC). This transfer effect persisted for ∼30 d post intervention. Critically, the transferred benefits associated with right prefrontal tDCS were predicted by pretraining concentrations of glutamate in the PFC. Thus, the effects of this combined stimulation and training protocol appear to be linked predominantly to excitatory brain processes.

Diffusion-weighted SPECIAL improves the detection of J-coupled metabolites at ultrahigh magnetic field

PURPOSE

To improve the detection and subsequent estimation of the diffusion properties of strongly J-coupled metabolites in diffusion-weighted MRS (DWS).

METHODS

A new sequence for single-voxel diffusion-weighted 1 H MR spectroscopy, named DW-SPECIAL, is proposed. It combines the semi-adiabatic SPECIAL sequence with a stimulated echo diffusion block. Acquisitions with DW-SPECIAL and STE-LASER, the current gold standard for rodent DWS experiments at high fields, were performed at 14.1T on phantoms and in vivo on the rat brain. The apparent diffusion coefficient and intra-stick diffusivity (Callaghan's model, randomly-oriented sticks) were fitted and compared between the sequences for glutamate, glutamine, myo-inositol, taurine, total NAA, total Cho, total Cr, and the macromolecules.

RESULTS

The shorter TE achieved with DW-SPECIAL (18 ms against 33 ms with STE-LASER) substantially limited the metabolites' signal loss caused by J-evolution. In addition, DW-SPECIAL preserved the main advantages of STE-LASER: absence of cross-terms, diffusion time during a stimulated echo, and limited sensitivity to B1 inhomogeneities. In vivo, compared to STE-LASER, DW-SPECIAL yielded the same spectral quality and reduced the Cramer Rao Lower Bounds for J-coupled metabolites, irrespective of the b-value. DW-SPECIAL also reduced the SD of the metabolites' diffusion estimates based on individual animal fitting without loss of accuracy compared to the fit on the averaged decay.

CONCLUSION

We conclude that due to its reduced TE, DW-SPECIAL can serve as an alternative to STE-LASER when strongly J-coupled metabolites like glutamine are investigated, thereby extending the range of accessible metabolites in the context of DWS acquisitions.

GABA, glutamate and excitatory-inhibitory ratios measured using short-TE STEAM MRS at 7-Tesla: Effects of macromolecule basis sets and baseline parameters

Rationale and objectives

Macromolecules (MMs) affect the precision and accuracy of neurochemical quantification in magnetic resonance spectroscopy. A measured MM basis is increasingly used in LCModel analysis combined with a spline baseline, whose stiffness is controlled by a parameter named DKNTMN. The effects of measured MM basis and DKNTMN were investigated.

Materials and methods

Twenty-six healthy subjects were prospectively enrolled and scanned twice using a short echo-time Stimulated Echo Acquisition Mode (STEAM) at 7-T. Using LCModel, analyses were conducted using the simulated MM basis (MMsim) with DKNTMN 0.15 and an MM basis measured inhouse (MMmeas) with DKNTMN of 0.15, 0.30, 0.60 and 1.00. Cramér-Rao lower bound (CRLB) and the concentrations of gamma-aminobutyric acid (GABA), glutamate and excitatory-inhibitory ratio (EIR), in addition to MMs were statistically analyzed. Measurement stability was evaluated using coefficient of variation (CV).

Results

CRLBs of GABA were significantly lower when using MMsim than MMmeas; those of glutamate were 2-3. GABA concentrations were significantly higher in the analysis using MMsim than MMmeas where concentrations were significantly higher with DKNTMN of 0.15 or 0.30 than 0.60 or 1.00. Difference in glutamate concentration was not significant. EIRs showed the same difference as in GABA depending on the DKNTMN values. CVs between test-retest scans were relatively stable for glutamate but became larger as DKNTMN increased for GABA and EIR.

Conclusion

Neurochemical quantification depends on the parameters of the basis sets used for fitting. Analysis using MMmeas with DKNTMN of 0.30 conformed best to previous studies and is recommended.

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

BACKGROUND

and rationale: There 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.

AIM

Therefore, 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.

METHODS

Patients (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.

RESULTS

Five children currently 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.

CONCLUSION

Children 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. Attention deficit was observed in one child. Healthy children displayed neurometabolic regional differences as previously reported in adult subjects.

Quantification of GABA concentration measured noninvasively in the human posterior cingulate cortex with 7 T ultra-short-TE MR spectroscopy

PURPOSE

The increased spectral dispersion achieved at ultra-high field permits quantification of γ-aminobutyric acid (GABA) concentrations at ultra-short-TE without editing. This work investigated the influence of spectral quality and different LCModel fitting approaches on quantification of GABA. Additionally, the sensitivity with which cross-sectional and longitudinal variations in GABA concentrations can be observed was characterized.

METHODS

In - vivo spectra were acquired in the posterior cingulate cortex of 10 volunteers at 7 T using a STEAM sequence. Synthetically altered spectra with different levels of GABA signals were used to investigate the reliability of GABA quantification with different LCModel fitting approaches and different realizations of SNR. The synthetically altered spectra were also used to characterize the sensitivity of GABA quantification.

RESULTS

The best LCModel fitting approach used stiff spline baseline, no soft constraints, and measured macromolecules in the basis set. With lower SNR, coefficients of variation increased dramatically. Longitudinal and cross-sectional variations in GABA of 10% could be detected with 79 and 48 participants per group, respectively. However, the small cohort may bias the calculation of the coefficients of variation and of the sample size that would be needed to detect variations in GABA.

CONCLUSION

Reliable quantification of normal and abnormal GABA concentrations was achieved for high quality 7 T spectra using LCModel fitting.

The future is 2D: spectral-temporal fitting of dynamic MRS data provides exponential gains in precision over conventional approaches

PURPOSE

Many MRS paradigms produce 2D spectral-temporal datasets, including diffusion-weighted, functional, and hyperpolarized and enriched (carbon-13, deuterium) experiments. Conventionally, temporal parameters-such as T₂ , T₁ , or diffusion constants-are assessed by first fitting each spectrum independently and subsequently fitting a temporal model (1D fitting). We investigated whether simultaneously fitting the entire dataset using a single spectral-temporal model (2D fitting) would improve the precision of the relevant temporal parameter.

METHODS

We derived a Cramer Rao lower bound for the temporal parameters for both 1D and 2D approaches for 2 experiments: a multi-echo experiment designed to estimate metabolite T₂ s, and a functional MRS experiment designed to estimate fractional change ( δ $$ \delta $$ ) in metabolite concentrations. We investigated the dependence of the relative standard deviation (SD) of T₂ in multi-echo and δ $$ \delta $$ in functional MRS.

RESULTS

When peaks were spectrally distant, 2D fitting improved precision by approximately 20% relative to 1D fitting, regardless of the experiment and other parameter values. These gains increased exponentially as peaks drew closer. Dependence on temporal model parameters was weak to negligible.

CONCLUSION

Our results strongly support a 2D approach to MRS fitting where applicable, and particularly in nuclei such as hydrogen and deuterium, which exhibit substantial spectral overlap.

Glutathione in the nucleus accumbens regulates motivation to exert reward-incentivized effort

Emerging evidence is implicating mitochondrial function and metabolism in the nucleus accumbens in motivated performance. However, the brain is vulnerable to excessive oxidative insults resulting from neurometabolic processes, and whether antioxidant levels in the nucleus accumbens contribute to motivated performance is not known. Here, we identify a critical role for glutathione (GSH), the most important endogenous antioxidant in the brain, in motivation. Using proton magnetic resonance spectroscopy at ultra-high field in both male humans and rodent populations, we establish that higher accumbal GSH levels are highly predictive of better, and particularly, steady performance over time in effort-related tasks. Causality was established in in vivo experiments in rats that, first, showed that downregulating GSH levels through micro-injections of the GSH synthesis inhibitor buthionine sulfoximine in the nucleus accumbens impaired effort-based reward-incentivized performance. In addition, systemic treatment with the GSH precursor N-acetyl-cysteine increased accumbal GSH levels in rats and led to improved performance, potentially mediated by a cell-type-specific shift in glutamatergic inputs to accumbal medium spiny neurons. Our data indicate a close association between accumbal GSH levels and an individual’s capacity to exert reward-incentivized effort over time. They also suggest that improvement of accumbal antioxidant function may be a feasible approach to boost motivation.

Quantitative T1-relaxation corrected metabolite mapping of 12 metabolites in the human brain at 9.4 T

Magnetic resonance spectroscopic imaging (MRSI) is a non-invasive imaging modality that enables observation of metabolites. Applications of MRSI for neuroimaging have shown promise for monitoring and detecting various diseases. This study builds off previously developed techniques of short TR, ¹H FID MRSI by correcting for T₁-weighting of the metabolites and utilizing an internal water reference to produce quantitative (mmol kg^-1) metabolite maps. This work reports and shows quantitative metabolite maps for 12 metabolites for a single slice. Voxel-specific T₁-corrections for water are common in MRSI studies; however, most studies use either averaged T₁-relaxation times to correct for T₁-weighting of metabolites or omit this correction step entirely. This work employs the use of voxel-specific T₁-corrections for metabolites in addition to water. Utilizing averaged T₁-relaxation times for metabolites can bias metabolite maps for metabolites that have strong differences between T₁-relaxation for GM and WM (i.e. Glu). This work systematically compares quantitative metabolite maps to single voxel quantitative results and qualitatively compares metabolite maps to previous works.

On the relationship between GABA+ and glutamate across the brain

Equilibrium between excitation and inhibition (E/I balance) is key to healthy brain function. Conversely, disruption of normal E/I balance has been implicated in a range of central neurological pathologies. Magnetic resonance spectroscopy (MRS) provides a non-invasive means of quantifying in vivo concentrations of excitatory and inhibitory neurotransmitters, which could be used as diagnostic biomarkers. Using the ratio of excitatory and inhibitory neurotransmitters as an index of E/I balance is common practice in MRS work, but recent studies have shown inconsistent evidence for the validity of this proxy. This is underscored by the fact that different measures are often used in calculating E/I balance such as glutamate and Glx (glutamate and glutamine). Here we used a large MRS dataset obtained at ultra-high field (7 T) measured from 193 healthy young adults and focused on two brain regions - prefrontal and occipital cortex - to resolve this inconsistency. We find evidence that there is an inter-individual common ratio between GABA+ (γ-aminobutyric acid and macromolecules) and Glx in the occipital, but not prefrontal cortex. We further replicate the prefrontal result in a legacy dataset (n = 78) measured at high-field (3 T) strength. By contrast, with ultra-high field MRS data, we find extreme evidence that there is a common ratio between GABA+ and glutamate in both prefrontal and occipital cortices, which cannot be explained by participant demographics, signal quality, fractional tissue volume, or other metabolite concentrations. These results are consistent with previous electrophysiological and theoretical work supporting E/I balance. Our findings indicate that MRS-detected GABA+ and glutamate (but not Glx), are a reliable measure of E/I balance .

Macromolecular background signal and non-Gaussian metabolite diffusion determined in human brain using ultra-high diffusion weighting

Purpose

Definition of a macromolecular MR spectrum based on diffusion properties rather than relaxation time differences and characterization of non‐Gaussian diffusion of brain metabolites with strongly diffusion‐weighted MR spectroscopy.

Methods

Short echo time MRS with strong diffusion‐weighting with b‐values up to 25 ms/μm² at two diffusion times was implemented on a Connectom system and applied in combination with simultaneous spectral and diffusion decay modeling. Motion‐compensation was performed with a combined method based on the simultaneously acquired water and a macromolecular signal.

Results

The motion compensation scheme prevented spurious signal decay reflected in very small apparent diffusion constants for macromolecular signal. Macromolecular background signal patterns were determined using multiple fit strategies. Signal decay corresponding to non‐Gaussian metabolite diffusion was represented by biexponential fit models yielding parameter estimates for human gray matter that are in line with published rodent data. The optimal fit strategies used constraints for the signal decay of metabolites with limited signal contributions to the overall spectrum.

Conclusion

The determined macromolecular spectrum based on diffusion properties deviates from the conventional one derived from longitudinal relaxation time differences calling for further investigation before use as experimental basis spectrum when fitting clinical MR spectra. The biexponential characterization of metabolite signal decay is the basis for investigations into pathologic alterations of microstructure.

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γ-aminobutyric acid measurement in the human brain at 7 T: Short echo-time or Mescher-Garwood editing

The purposes of the current study were to introduce a Mescher-Garwood (MEGA) semi-adiabatic spin-echo full-intensity localization (MEGA-sSPECIAL) sequence with macromolecule (MM) subtraction and to compare the test-retest reproducibility of γ-aminobutyric acid (GABA) measurements at 7 T using the sSPECIAL and MEGA-sSPECIAL sequences. The MEGA-sSPECIAL editing scheme using asymmetric adiabatic and highly selective Gaussian pulses was used to compare its GABA measurement reproducibility with that of short echo-time (TE) sSPECIAL. Proton magnetic resonance spectra were acquired in the motor cortex (M1) and medial prefrontal cortex (mPFC) using the sSPECIAL (TR/TE = 4000/16 ms) and MEGA-sSPECIAL sequences (TR/TE = 4000/80 ms). The metabolites were quantified using LCModel with unsuppressed water spectra. The concentrations are reported in institutional units. The test-retest reproducibility was evaluated by scanning each subject twice. Between-session reproducibility was assessed using coefficients of variation (CVs), Pearson's r correlation coefficients, and intraclass correlation coefficients (ICCs). Intersequence agreement was evaluated using Pearson's r correlation coefficients and Bland-Altman plots. Regarding GABA measurements by sSPECIAL, the GABA concentrations were 0.92 ± 0.31 (IU) in the M1 and 1.56 ± 0.49 (IU) in the mPFC. This demonstrated strong between-session correlation across both regions (r = 0.81, p < 0.01; ICC = 0.82). The CVs between the two scans were 21.8% in the M1 and 10.2% in the mPFC. On the other hand, the GABA measurements by MEGA-sSPECIAL were 0.52 ± 0.04 (IU) in the M1 and 1.04 ± 0.24 (IU) in the mPFC. MEGA-sSPECIAL demonstrated strong between-session correlation across the two regions (r = 0.98, p < 0.001; ICC = 0.98) and lower CVs than sSPECIAL, providing 4.1% in the M1 and 5.8% in the mPFC. The MEGA-editing method showed better reproducibility of GABA measurements in both brain regions compared with the short-TE sSPECIAL method. Thus it is a more sensitive method with which to detect small changes in areas with low GABA concentrations. In GABA-rich brain regions, GABA measurements can be achieved reproducibly using both methods.

Inter-subject stability and regional concentration estimates of 3D-FID-MRSI in the human brain at 7 T

PURPOSE

Recently, a 3D-concentric ring trajectory (CRT)-based free induction decay (FID)-MRSI sequence was introduced for fast high-resolution metabolic imaging at 7 T. This technique provides metabolic ratio maps of almost the entire brain within clinically feasible scan times, but its robustness has not yet been thoroughly investigated. Therefore, we have assessed quantitative concentration estimates and their variability in healthy volunteers using this approach.

METHODS

We acquired whole-brain 3D-CRT-FID-MRSI at 7 T in 15 min with 3.4 mm nominal isometric resolution in 24 volunteers (12 male, 12 female, mean age 27 ± 6 years). Concentration estimate maps were calculated for 15 metabolites using internal water referencing and evaluated in 55 different regions of interest (ROIs) in the brain. Data quality, mean metabolite concentrations, and their inter-subject coefficients of variation (CVs) were compared for all ROIs.

RESULTS

Of 24 datasets, one was excluded due to motion artifacts. The concentrations of total choline, total creatine, glutamate, myo-inositol, and N-acetylaspartate in 44 regions were estimated within quality thresholds. Inter-subject CVs (mean over 44 ROIs/minimum/maximum) were 9%/5%/19% for total choline, 10%/6%/20% for total creatine, 11%/7%/24% for glutamate, 10%/6%/19% for myo-inositol, and 9%/6%/19% for N-acetylaspartate.

DISCUSSION

We defined the performance of 3D-CRT-based FID-MRSI for metabolite concentration estimate mapping, showing which metabolites could be robustly quantified in which ROIs with which inter-subject CVs expected. However, the basal brain regions and lesser-signal metabolites in particular remain as a challenge due susceptibility effects from the proximity to nasal and auditory cavities. Further improvement in quantification and the mitigation of B0 /B1 -field inhomogeneities will be necessary to achieve reliable whole-brain coverage.

The macromolecular MR spectrum does not change with healthy aging

PURPOSE

To acquire the mobile macromolecule (MM) spectrum from healthy participants, and to investigate changes in the signals with age and sex.

METHODS

102 volunteers (49 M/53 F) between 20 and 69 years were recruited for in vivo data acquisition in the centrum semiovale (CSO) and posterior cingulate cortex (PCC). Spectral data were acquired at 3T using PRESS localization with a voxel size of 30 × 26 × 26 mm³ , pre-inversion (TR/TI 2000/600 ms) and CHESS water suppression. Metabolite-nulled spectra were modeled to eliminate residual metabolite signals, which were then subtracted out to yield a "clean" MM spectrum using the Osprey software. Pearson's correlation coefficient was calculated between integrals and age for the 14 MM signals. One-way ANOVA was performed to determine differences between age groups. An independent t-test was carried out to determine differences between sexes.

RESULTS

MM spectra were successfully acquired in 99 (CSO) and 96 (PCC) of 102 subjects. No significant correlations were seen between age and MM signals. One-way ANOVA also suggested no age-group differences for any MM peak (all p > .004). No differences were observed between sex groups. WM and GM voxel fractions showed a significant (p < .05) negative linear association with age in the WM-predominant CSO (R = -0.29) and GM-predominant PCC regions (R = -0.57) respectively while CSF increased significantly with age in both regions.

CONCLUSION

Our findings suggest that a pre-defined MM basis function can be used for linear combination modeling of metabolite data from different age and sex groups.

Assessment of measurement precision in single-voxel spectroscopy at 7 T: Toward minimal detectable changes of metabolite concentrations in the human brain in vivo

PURPOSE

To introduce a study design and statistical analysis framework to assess the repeatability, reproducibility, and minimal detectable changes (MDCs) of metabolite concentrations determined by in vivo MRS.

METHODS

An unbalanced nested study design was chosen to acquire in vivo MRS data within different repeatability and reproducibility scenarios. A spin-echo, full-intensity acquired localized (SPECIAL) sequence was employed at 7 T utlizing three different inversion pulses: a hyperbolic secant (HS), a gradient offset independent adiabaticity (GOIA), and a wideband, uniform rate, smooth truncation (WURST) pulse. Metabolite concentrations, Cramér-Rao lower bounds (CRLBs) and coefficients of variation (CVs) were calculated. Both Bland-Altman analysis and a restricted maximum-likelihood estimation (REML) analysis were performed to estimate the different variance contributions of the repeatability and reproducibility of the measured concentration. A Bland-Altmann analysis of the spectral shape was performed to assess the variance of the spectral shape, independent of quantification model influences.

RESULTS

For the used setup, minimal detectable changes of brain metabolite concentrations were found to be between 0.40 µmol/g and 2.23 µmol/g. CRLBs account for only 16 % to 74 % of the total variance of the metabolite concentrations. The application of gradient-modulated inversion pulses in SPECIAL led to slightly improved repeatability, but overall reproducibility appeared to be limited by differences in positioning, calibration, and other day-to-day variations throughout different sessions.

CONCLUSION

A framework is introduced to estimate the precision of metabolite concentrations obtained by MRS in vivo, and the minimal detectable changes for 13 metabolite concentrations measured at 7 T using SPECIAL are obtained.

Relaxation-corrected macromolecular model enables determination of 1 H longitudinal T1 -relaxation times and concentrations of human brain metabolites at 9.4T

PURPOSE

Ultrahigh field MRS has improved characterization of the neurochemical profile. To compare results obtained at 9.4T to those from lower field strengths, it is of interest to quantify the concentrations of metabolites measured. Thus, measuring T₁ -relaxation times is necessary to correct for T₁ -weighting that occurs in acquisitions for single-voxel spectroscopy and spectroscopic imaging. A macromolecule (MM) simulation model was developed to fit MM contributions to the short TE inversion series used to measure T₁ -relaxation times.

METHODS

An inversion series with seven time points was acquired with metabolite-cycled STEAM to estimate T₁ -relaxation times of metabolites. A short TE was employed in this study to retain signals from metabolites with short T₂ -relaxation times and J-couplings. The underlying macromolecule spectrum was corrected by developing a sequence-specific, relaxation-corrected simulated MM model. Quantification of metabolite peaks was performed using internal water referencing and relaxation corrections.

RESULTS

T₁ -relaxation times for metabolites range from approximately 750 to approximately 2000 ms and approximately 1000 to approximately 2400 ms in gray matter (GM)- and white matter (WM)- rich voxels, respectively. Quantification of metabolites was compared between GM and WM voxels, as well as between results that used a simulated MM spectrum against those that used an experimentally acquired MM spectrum. Metabolite concentrations are reported in mmol/kg quantities.

CONCLUSION

T₁ -relaxation times are reported for nonsinglet resonances for the first time at 9.4T by use of a MM simulation model to account for contributions from the MM spectrum. In addition to T₁ -relaxation times, quantification results of metabolites from GM- and WM-rich voxels are reported.

Metabolic and transcriptomic profiles of glioblastoma invasion revealed by comparisons between patients and corresponding orthotopic xenografts in mice

The invasive behavior of glioblastoma, the most aggressive primary brain tumor, is considered highly relevant for tumor recurrence. However, the invasion zone is difficult to visualize by Magnetic Resonance Imaging (MRI) and is protected by the blood brain barrier, posing a particular challenge for treatment. We report biological features of invasive growth accompanying tumor progression and invasion based on associated metabolic and transcriptomic changes observed in patient derived orthotopic xenografts (PDOX) in the mouse and the corresponding patients’ tumors. The evolution of metabolic changes, followed in vivo longitudinally by ¹H Magnetic Resonance Spectroscopy (¹H MRS) at ultra-high field, reflected growth and the invasive properties of the human glioblastoma transplanted into the brains of mice (PDOX). Comparison of MRS derived metabolite signatures, reflecting temporal changes of tumor development and invasion in PDOX, revealed high similarity to spatial metabolite signatures of combined multi-voxel MRS analyses sampled across different areas of the patients’ tumors. Pathway analyses of the transcriptome associated with the metabolite profiles of the PDOX, identified molecular signatures of invasion, comprising extracellular matrix degradation and reorganization, growth factor binding, and vascular remodeling. Specific analysis of expression signatures from the invaded mouse brain, revealed extent of invasion dependent induction of immune response, recapitulating respective signatures observed in glioblastoma. Integrating metabolic profiles and gene expression of highly invasive PDOX provided insights into progression and invasion associated mechanisms of extracellular matrix remodeling that is essential for cell–cell communication and regulation of cellular processes. Structural changes and biochemical properties of the extracellular matrix are of importance for the biological behavior of tumors and may be druggable. Ultra-high field MRS reveals to be suitable for in vivo monitoring of progression in the non-enhancing infiltration zone of glioblastoma.

Are Cramér-Rao lower bounds an accurate estimate for standard deviations in in vivo magnetic resonance spectroscopy?

Due to inherent time constraints for in vivo experiments, it is infeasible to repeat multiple MRS scans to estimate standard deviations on the desired measured parameters. As such, the Cramér-Rao lower bounds (CRLBs) have become the routine method to approximate standard deviations for in vivo experiments. Cramér-Rao lower bounds, however, as the name suggests, are theoretically a lower bound on the standard deviation and it is not clear if and under what circumstances this approximation is valid. Realistic synthetic 3 T spectra were used to investigate the relationship between estimated CRLBs, true CRLBs and standard deviations. Here we demonstrate that, although the CRLBs are theoretically truly a lower bound on the standard deviation (not an equality) for the problem typically encountered in quantification, they are still an adequate approximation to standard deviation as long as the model perfectly characterizes the data. In the case when the macromolecule basis deviates from the measured macromolecules it was shown that the CRLBs can deviate from standard deviations by approximately 50% for N-acetylaspartic acid, creatine and glutamate and of the order of 100% or more for myo-inositol and γ-aminobutyric acid. In the case when the model perfectly reflects the data the CRLBs are within approximately 10% of standard deviations for all metabolites. The result of the CRLB being within 10% of standard deviations means that, for an accurate model, novel quantification methods such as machine learning or deep learning will not be able to obtain substantially more precise estimates for the desired parameters than traditional maximum-likelihood estimation.

Reduced Hippocampal Glutamate and Posterior Cingulate N-Acetyl Aspartate in Mild Cognitive Impairment and Alzheimer's Disease Is Associated with Episodic Memory Performance and White Matter Integrity in the Cingulum: A Pilot Study

Identification of biological changes underlying the early symptoms of Alzheimer's disease (AD) will help to identify and stage individuals prior to symptom onset. The limbic system, which supports episodic memory and is impaired early in AD, is a primary target. In this study, brain metabolism and microstructure evaluated by high field (7 Tesla) proton magnetic resonance spectroscopy (1H-MRS) and diffusion tensor imaging (DTI) were evaluated in the limbic system of eight individuals with mild cognitive impairment (MCI), nine with AD, and sixteen normal elderly controls (NEC). Left hippocampal glutamate and posterior cingulate N-acetyl aspartate concentrations were reduced in MCI and AD compared to NEC. Differences in DTI metrics indicated volume and white matter loss along the cingulum in AD compared to NEC. Metabolic and microstructural changes were associated with episodic memory performance assessed using Craft Story 21 Recall and Benson Complex Figure Copy. The current study suggests that metabolite concentrations measured using 1H-MRS may provide insight into the underlying metabolic and microstructural processes of episodic memory impairment.

Repeatability of proton magnetic resonance spectroscopy of the brain at 7 T: effect of scan time on semi-localized by adiabatic selective refocusing and short-echo time stimulated echo acquisition mode scans and their comparison

Background

Proton magnetic resonance spectroscopy (MRS) provides a unique opportunity for in vivo measurements of the brain's metabolic profile. Two methods of mainstream data acquisition are compared at 7 T, which provides certain advantages as well as challenges. The two representative methods have seldom been compared in terms of measured metabolite concentrations and different scan times. The current study investigated proton MRS of the posterior cingulate cortex using a semi-localized by adiabatic selective refocusing (sLASER) sequence and a short echo time (TE) stimulated echo acquisition mode (sSTEAM) sequence, and it compared their reliability and repeatability at 7 T using a 32-channel head coil.

Methods

Sixteen healthy subjects were prospectively enrolled and scanned twice with an off-bed interval between scans. The scan parameters for sLASER were a TR/TE of 6.5 s/32 ms and 32 and 48 averages (sLASER×32 and sLASER×48, respectively). The scan parameters for sSTEAM were a TR/TE of 4 s/5 ms and 32, 48, and 64 averages (sSTEAM4×32, sSTEAM4×48, and sSTEAM4×64, respectively) in addition to that with a TR/TE of 8 s/5 ms and 32 averages (sSTEAM8×32). Data were analyzed using LCModel. Metabolites quantified with Cramér-Rao lower bounds (CRLBs) >50% were classified as not detected, and metabolites quantified with mean or median CRLBs ≤20% were included for further analysis. The SNR, CRLBs, coefficient of variation (CV), and metabolite concentrations were statistically compared using the Shapiro-Wilk test, one-way ANOVA, or the Friedman test.

Results

The sLASER spectra for N-acetylaspartate + N-acetylaspartylglutamate (tNAA) and glutamate (Glu) had a comparable or higher SNR than sSTEAM spectra. Ten metabolites had lower CRLBs than prefixed thresholds: aspartate (Asp), γ-aminobutyric acid (GABA), glutamine (Gln), Glu, glutathione (GSH), myo-inositol (Ins), taurine (Tau), the total amount of phosphocholine + glycerophosphocholine (tCho), creatine + phosphocreatine (tCr), and tNAA. Performance of the two sequences was satisfactory except for GABA, for which sLASER yielded higher CRLBs (≥18%) than sSTEAM. Some significant differences in CRLBs were noted, but they were ≤2% except for GABA and Gln. Signal averaging significantly lowered CRLBs for some metabolites but only by a small amount. Measurement repeatability as indicated by median CVs was ≤10% for Gln, Glu, Ins, tCho, tCr, and tNAA in all scans, and that for Asp, GABA, GSH, and Tau was ≥10% under some scanning conditions. The CV for GABA according to sLASER was significantly higher than that according to sSTEAM, whereas the CV for Ins was higher according to sSTEAM. An increase in signal averaging contribute little to lower CVs except for Ins.

Conclusions

Both sequences quantified brain metabolites with a high degree of precision and repeatability. They are comparable except for GABA, for which sSTEAM would be a better choice.

Realistic head-shaped phantom with brain-mimicking metabolites for 7 T spectroscopy and spectroscopic imaging

PURPOSE

Moving to ultra-high fields (≥7 T), the inhomogeneity of both RF (B1 ) and static (B0 ) magnetic fields increases, which further motivates us to design a realistic head-shaped phantom, especially for spectroscopic imaging. Such phantoms provide images similar to the human brain and serve as a reliable tool for developing and examining methods in MRI. This study aims to develop and characterize a realistic head-shaped phantom filled with brain-mimicking metabolites for MRS and magnetic resonance spectroscopic imaging in a 7 T MRI scanner.

METHODS

A 3D head-shaped container with three sections-mimicking brain, muscle and precranial lipid-was constructed. The phantom was designed to provide robustness to heating, mechanical damage and leakage, with easy refilling. The head's shape and the agarose mixture were optimized to provide B0 and B1 distributions and T1 /T2 relaxation values similar to those of human brain. Eight brain-tissue-mimicking metabolites were included for spectroscopy. The phantom was evaluated for localized spectroscopy, fast spectroscopic imaging and fat suppression.

RESULTS

The B0 and B1 maps showed distribution similar to that of human brain, with increased B0 inhomogeneity near the nasal and ear areas and reduced B1 in the temporal lobe and brain stem regions, as expected in vivo. The metabolites' concentrations were verified by single-voxel spectroscopy, showing an average deviation of 11%. Fast spectroscopic imaging and imaging with fat suppression were demonstrated.

CONCLUSION

A 3D head-shaped phantom for human brain imaging and spectroscopic imaging in 7 T MRI was demonstrated, making it a realistic phantom for methodology development at 7 T.

Lipid-suppressed and tissue-fraction corrected metabolic distributions in human central brain structures using 2D 1 H magnetic resonance spectroscopic imaging at 7 T

INTRODUCTION

Magnetic resonance spectroscopic imaging (MRSI) has the potential to add a layer of understanding of the neurobiological mechanisms underlying brain diseases, disease progression, and treatment efficacy. Limitations related to metabolite fitting of low signal-to-noise ratios data, signal variations due to partial-volume effects, acquisition and extracranial lipid artifacts, along with clinically relevant aspects such as scan time constraints, are among the challenges associated with in vivo MRSI.

METHODS

The aim of this work was to address some of these factors and to develop an acquisition, reconstruction, and postprocessing pipeline to derive lipid-suppressed metabolite values of central brain structures based on free-induction decay measurements made using a 7 T MR scanner. Anatomical images were used to perform high-resolution (1 mm³ ) partial-volume correction to account for gray matter, white matter (WM), and cerebral-spinal fluid signal contributions. Implementation of automatic quality control thresholds and normalization of metabolic maps from 23 subjects to the Montreal Neurological Institute (MNI) standard atlas facilitated the creation of high-resolution average metabolite maps of several clinically relevant metabolites in central brain regions, while accounting for macromolecular distributions. Partial-volume correction improved the delineation of deep brain nuclei. We report average metabolite values including glutamate + glutamine (Glx), glycerophosphocholine, choline and phosphocholine (tCho), (phospo)creatine, myo-inositol and glycine (mI-Gly), glutathione, N-acetyl-aspartyl glutamate(and glutamine), and N-acetyl-aspartate in the basal ganglia, central WM (thalamic radiation, corpus callosum) as well as insular cortex and intracalcarine sulcus.

CONCLUSION

MNI-registered average metabolite maps facilitate group-based analysis, thus offering the possibility to mitigate uncertainty in variable MRSI data.

A semi-LASER, single-voxel spectroscopic sequence with a minimal echo time of 20.1 ms in the human brain at 3 T

An optimized semi-LASER sequence that is capable of acquiring artefact-free data with an echo time (TE) of 20.1 ms on a standard clinical 3 T MR system was developed. Simulations were performed to determine the optimal TEs that minimize the expected Cramér-Rao lower bound (CRLB) as proxy for quantification accuracy of metabolites. Optimized RF pulses, crusher gradients and phase cycling were used to achieve the shortest TE in a semi-LASER sequence to date on a clinical system. Synthetic spectra were simulated using the density matrix formalism for TEs spanning from 20.1 to 220.1 ms. These simulations were used to calculate the expected CRLB for each of the 18 metabolites typically considered in ¹ H MRS. High quality spectra were obtained in six healthy volunteers in the prefrontal cortex, which is known for spurious echoes due to its proximity to the paranasal sinuses, and in the parietal-occipital cortex. Spectral transients were sufficient in quality to enable phase and frequency alignment prior to summation over all repetitions. Automated high-quality water suppression was obtained for all voxels without manual adjustment. The shortest TE minimized the CRLB for all brain metabolites except glycine due to its overlap with myo-inositol at this TE. It is also demonstrated that the CRLBs increase rapidly with TE for certain coupled metabolites.

A novel method to measure T1 -relaxation times of macromolecules and quantification of the macromolecular resonances

PURPOSE

Macromolecular peaks underlying metabolite spectra influence the quantification of metabolites. Therefore, it is important to understand the extent of contribution from macromolecules (MMs) in metabolite quantification. However, to model MMs more accurately in spectral fitting, differences in T₁ relaxation times among individual MM peaks must be considered. Characterization of T₁ -relaxation times for all individual MM peaks using a single inversion recovery technique is difficult due to eventual contributions from metabolites. On the contrary, a double inversion recovery (DIR) technique provided flexibility to acquire MM spectra spanning a range of longitudinal magnetizations with minimal metabolite influence. Thus, a novel method to determine T₁ -relaxation times of individual MM peaks is reported in this work.

METHODS

Extensive Bloch simulations were performed to determine inversion time combinations for a DIR technique that yielded adequate MM signal with varying longitudinal magnetizations while minimizing metabolite contributions. MM spectra were acquired using DIR-metabolite-cycled semi-LASER sequence. LCModel concentrations were fitted to the DIR signal equation to calculate T₁ -relaxation times.

RESULTS

T₁ -relaxation times of MMs range from 204 to 510 ms and 253 to 564 ms in gray- and white-matter rich voxels respectively at 9.4T. Additionally, concentrations of 13 MM peaks are reported.

CONCLUSION

A novel DIR method is reported in this work to calculate T₁ -relaxation times of MMs in the human brain. T₁ -relaxation times and relaxation time corrected concentrations of individual MMs are reported in gray- and white-matter rich voxels for the first time at 9.4T.

Determination of Brain Metabolite T 1 Without Interference From Macromolecule Relaxation

BACKGROUND

J-coupled metabolites are often measured at a predetermined echo time in the presence of macromolecule signals, which complicates the measurement of metabolite T₁ .

PURPOSE

To evaluate the feasibility and benefits of measuring metabolite T₁ relaxation times without changing the overlapping macromolecule baseline signals.

STUDY TYPE

Prospective.

SUBJECTS

Five healthy volunteers (three females and two males; age = 27 ± 7 years).

FIELD STRENGTH/SEQUENCE

7T scanner using a point resolved spectroscopy (PRESS)-based spectral editing MR spectroscopy (MRS) sequence with inversion recovery (IR).

ASSESSMENT

F-tests were performed to evaluate if the new approach, which fitted all the spectra together and used the same baselines for the three different IR settings, significantly reduced the variances of the metabolite T₁ values compared to a conventional fitting approach.

STATISTICAL TESTS

Cramer-Rao lower bound (CRLB), within-subject coefficient of variation, and F-test.

RESULTS

The T₁ relaxation times of N-acetylaspartate (NAA), total creatine (tCr), total choline (tCho), myo-inositol (mI), and glutamate (Glu) were determined with CRLB values below 6%. Glutamine (Gln) T₁ was determined with a 17% CRLB, and the T₁ of γ-aminobutyric acid (GABA) was determined with a 34% CRLB. The new approach significantly reduced the variances (F-test P < 0.05) of NAA, Glu, Gln, tCr, tCho, and mI T₁ s compared to the conventional approach.

DATA CONCLUSION

Keeping macromolecule signals intact by using only long IR times allowed the use of a single macromolecule spectral model for different IR settings and significantly reduced the variances of NAA, Glu, Gln, tCr, tCho, and mI T₁ s.

LEVEL OF EVIDENCE

1 TECHNICAL EFFICACY STAGE: 1.

Elevated homocarnosine and GABA in subject on isoniazid as assessed through 1H MRS at 7T

Typical magnetic resonance spectroscopy J-editing methods designed to quantify GABA suffer from contamination of both overlapping macromolecules and homocarnosine signal, introducing potential confounds. The aim of this study was to develop a novel method to assess accurately both the relative concentrations of homocarnosine as well as GABA free from overlapping creatine, homocarnosine and macromolecule signal. A novel method which utilized the combination of echo time STEAM and MEGA-sLASER magnetic resonance spectroscopy experiments at 7T were used to quantify the concentration of GABA and homocarnsoine independently, which are typically quantified in tandem. The metabolites GABA and homocarnosine were measured in brain of 6 healthy control subjects, and in a single subject medicated with isoniazid. It was found that (16.6±10.2)% of the supposed GABA signal in the brain originated from homocarnosine, and that isoniazid caused significantly elevated concentration of GABA and homocarnosine in a single subject compared to controls.

Metabolite concentration changes associated with positive and negative BOLD responses in the human visual cortex: A functional MRS study at 7 Tesla

Negative blood oxygenation-level dependent (BOLD) signal observed during task execution in functional magnetic resonance imaging (fMRI) can be caused by different mechanisms, such as a blood-stealing effect or neuronal deactivation. Electrophysiological recordings showed that neuronal deactivation underlies the negative BOLD observed in the occipital lobe during visual stimulation. In this study, the metabolic demand of such a response was studied by measuring local metabolite concentration changes during a visual checkerboard stimulation using functional magnetic resonance spectroscopy (fMRS) at 7 Tesla. The results showed increases of glutamate and lactate concentrations during the positive BOLD response, consistent with previous fMRS studies. In contrast, during the negative BOLD response, decreasing concentrations of glutamate, lactate and gamma-aminobutyric acid (GABA) were found, suggesting a reduction of glycolytic and oxidative metabolic demand below the baseline. Additionally, the respective changes of the BOLD signal, glutamate and lactate concentrations of both groups suggest that a local increase of inhibitory activity might occur during the negative BOLD response.

NMR Relaxation Measurements on Complex Samples Based on Real-Time Pure Shift Techniques

Longitudinal spin-lattice relaxation (T₁) and transverse spin-spin relaxation (T₂) reveal valuable information for studying molecular dynamics in NMR applications. Accurate relaxation measurements from conventional 1D proton spectra are generally subject to challenges of spectral congestion caused by J coupling splittings and spectral line broadenings due to magnetic field inhomogeneity. Here, we present an NMR relaxation method based on real-time pure shift techniques to overcome these two challenges and achieve accurate measurements of T₁ and T₂ relaxation times from complex samples that contain crowded NMR resonances even under inhomogeneous magnetic fields. Both theoretical analyses and detailed experiments are performed to demonstrate the effectiveness and ability of the proposed method for accurate relaxation measurements on complex samples and its practicability to non-ideal magnetic field conditions.

Advanced single voxel 1 H magnetic resonance spectroscopy techniques in humans: Experts' consensus recommendations

Conventional proton MRS has been successfully utilized to noninvasively assess tissue biochemistry in conditions that result in large changes in metabolite levels. For more challenging applications, namely, in conditions which result in subtle metabolite changes, the limitations of vendor-provided MRS protocols are increasingly recognized, especially when used at high fields (≥3 T) where chemical shift displacement errors, B0 and B1 inhomogeneities and limitations in the transmit B1 field become prominent. To overcome the limitations of conventional MRS protocols at 3 and 7 T, the use of advanced MRS methodology, including pulse sequences and adjustment procedures, is recommended. Specifically, the semiadiabatic LASER sequence is recommended when TE values of 25-30 ms are acceptable, and the semiadiabatic SPECIAL sequence is suggested as an alternative when shorter TE values are critical. The magnetic field B0 homogeneity should be optimized and RF pulses should be calibrated for each voxel. Unsuppressed water signal should be acquired for eddy current correction and preferably also for metabolite quantification. Metabolite and water data should be saved in single shots to facilitate phase and frequency alignment and to exclude motion-corrupted shots. Final averaged spectra should be evaluated for SNR, linewidth, water suppression efficiency and the presence of unwanted coherences. Spectra that do not fit predefined quality criteria should be excluded from further analysis. Commercially available tools to acquire all data in consistent anatomical locations are recommended for voxel prescriptions, in particular in longitudinal studies. To enable the larger MRS community to take advantage of these advanced methods, a list of resources for these advanced protocols on the major clinical platforms is provided. Finally, a set of recommendations are provided for vendors to enable development of advanced MRS on standard platforms, including implementation of advanced localization sequences, tools for quality assurance on the scanner, and tools for prospective volume tracking and dynamic linear shim corrections.

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.

Lactate measurement by neurochemical profiling in the dorsolateral prefrontal cortex at 7T: accuracy, precision, and relaxation times

PURPOSE

This assesses the potential of measuring lactate in the human brain using three non-editing MRS methods at 7T and compares the accuracy and precision of the methods.

METHODS

¹ H MRS data were measured in the right dorsolateral prefrontal cortex using a semi-adiabatic spin-echo full-intensity acquired localized sequence with three different protocols: (I) TE = 16 ms, (II) TE = 110 ms, and (III) TE = 16 ms, TI = 300 ms. T₁ and T₂ relaxation times of lactate were also measured. Simulated spectra were generated for three protocols with known concentrations, using a range of spectral linewidths and SNRs to assess the effect of data quality on the measurement precision and accuracy.

RESULTS

Lactate was quantified in all three protocols with mean Cramér-Rao lower bound of 8% (I), 13% (II), and 7% (III). The T₁ and T₂ relaxation times of lactate were 1.9 ± 0.2 s and 94 ± 13 ms, respectively. Simulations predicted a spectral linewidth-associated underestimation of lactate measurement. Simulations, phantom and in vivo results showed that protocol II was most affected by this underestimation. In addition, the estimation error was insensitive to a broad range of spectral linewidth with protocol I. Within-session coefficient of variances of lactate were 6.1 ± 7.9% (I), 22.3 ± 12.3% (II), and 5.1 ± 5.4% (III), respectively.

CONCLUSION

We conclude that protocols I and III have the potential to measure lactate at 7T with good reproducibility, whereas the measurement accuracy and precision depend on spectral linewidth and SNR, respectively. Moreover, simulation is valuable for the optimization of measurement protocols in future study design and the correction for measurement bias.

7 T Magnetic Resonance Spectroscopic Imaging in Multiple Sclerosis: How Does Spatial Resolution Affect the Detectability of Metabolic Changes in Brain Lesions?

OBJECTIVES

The aim of this study was to assess the utility of increased spatial resolution of magnetic resonance spectroscopic imaging (MRSI) at 7 T for the detection of neurochemical changes in multiple sclerosis (MS)-related brain lesions.

MATERIALS AND METHODS

This prospective, institutional review board-approved study was performed in 20 relapsing-remitting MS patients (9 women/11 men; mean age ± standard deviation, 30.8 ± 7.7 years) after receiving written informed consent. Metabolic patterns in MS lesions were compared at 3 different spatial resolutions of free induction decay MRSI with implemented parallel imaging acceleration: 2.2 × 2.2 × 8 mm; 3.4 × 3.4 × 8 mm; and 6.8 × 6.8 × 8 mm voxel volumes, that is, matrix sizes of 100 × 100, 64 × 64, and 32 × 32, respectively. The quality of data was assessed by signal-to-noise ratio and Cramér-Rao lower bounds. Statistical analysis was performed using Wilcoxon signed-rank tests with correction for multiple testing.

RESULTS

Seventy-seven T2-hyperintense MS lesions were investigated (median volume, 155.7 mm; range, 10.8-747.0 mm). The mean metabolic ratios in lesions differed significantly between the 3 MRSI resolutions (ie, 100 × 100 vs 64 × 64, 100 × 100 vs 32 × 32, and 64 × 64 vs 32 × 32; P < 0.001). With the ultra-high resolution (100 × 100), we obtained 40% to 80% higher mean metabolic ratios and 100% to 150% increase in maximum metabolic ratios in the MS lesions compared with the lowest resolution (32 × 32), while maintaining good spectral quality (signal-to-noise ratio >12, Cramér-Rao lower bounds <20%) and measurement time of 6 minutes. There were 83% of MS lesions that showed increased myo-inositol/N-acetylaspartate with the 100 × 100 resolution, but only 66% were distinguishable with the 64 × 64 resolution and 35% with the 32 × 32 resolution.

CONCLUSIONS

Ultra-high-resolution MRSI (~2 × 2 × 8 mm voxel volume) can detect metabolic alterations in MS, which cannot be recognized by conventional MRSI resolutions, within clinically acceptable time.

Whole-slice mapping of GABA and GABA+ at 7T via adiabatic MEGA-editing, real-time instability correction, and concentric circle readout

An adiabatic MEscher-GArwood (MEGA)-editing scheme, using asymmetric hyperbolic secant editing pulses, was developed and implemented in a B1+-insensitive, 1D-semiLASER (Localization by Adiabatic SElective Refocusing) MR spectroscopic imaging (MRSI) sequence for the non-invasive mapping of γ-aminobutyric acid (GABA) over a whole brain slice. Our approach exploits the advantages of edited-MRSI at 7T while tackling challenges that arise with ultra-high-field-scans. Spatial-spectral encoding, using density-weighted, concentric circle echo planar trajectory readout, enabled substantial MRSI acceleration and an improved point-spread-function, thereby reducing extracranial lipid signals. Subject motion and scanner instabilities were corrected in real-time using volumetric navigators optimized for 7T, in combination with selective reacquisition of corrupted data to ensure robust subtraction-based MEGA-editing. Simulations and phantom measurements of the adiabatic MEGA-editing scheme demonstrated stable editing efficiency even in the presence of ±0.15 ppm editing frequency offsets and B1+ variations of up to ±30% (as typically encountered in vivo at 7T), in contrast to conventional Gaussian editing pulses. Volunteer measurements were performed with and without global inversion recovery (IR) to study regional GABA levels and their underlying, co-edited, macromolecular (MM) signals at 2.99 ppm. High-quality in vivo spectra allowed mapping of pure GABA and MM-contaminated GABA+ (GABA + MM) along with Glx (Glu + Gln), with high-resolution (eff. voxel size: 1.4 cm3) and whole-slice coverage in 24 min scan time. Metabolic ratio maps of GABA/tNAA, GABA+/tNAA, and Glx/tNAA were correlated linearly with the gray matter fraction of each voxel. A 2.15-fold increase in gray matter to white matter contrast was observed for GABA when enabling IR, which we attribute to the higher abundance of macromolecules at 2.99 ppm in the white matter than in the gray matter. In conclusion, adiabatic MEGA-editing with 1D-semiLASER selection is as a promising approach for edited-MRSI at 7T. Our sequence capitalizes on the benefits of ultra-high-field MRSI while successfully mitigating the challenges related to B0/B1+ inhomogeneities, prolonged scan times, and motion/scanner instability artifacts. Robust and accurate 2D mapping has been shown for the neurotransmitters GABA and Glx.

The application of magnetic resonance fingerprinting to single voxel proton spectroscopy

Magnetic resonance fingerprinting has been proposed as a method for undersampling k-space while simultaneously yielding multiparametric tissue maps. In the context of single voxel spectroscopy, fingerprinting can provide a unified framework for parameter estimation. We demonstrate the utility of such a magnetic resonance spectroscopic fingerprinting (MRSF) framework for simultaneously quantifying metabolite concentrations, T₁ and T₂ relaxation times and transmit inhomogeneity for major singlets of N-acetylaspartate, creatine and choline. This is achieved by varying T_R , T_E and the flip angle of the first pulse in a PRESS sequence between successive excitations (i.e. successive T_R values). The need for multiparametric schemes such as MRSF for accurate medical diagnostics is demonstrated with the aid of realistic in vivo simulations; these show that certain schemes lead to substantial increases to the area under receiver operating characteristics of metabolite concentrations, when viewed as classifiers of pathologies. Numerical simulations and phantom and in vivo experiments using several different schedules of variable length demonstrate superior precision and accuracy for metabolite concentrations and longitudinal relaxation, and similar performance for the quantification of transverse relaxation.

1H MR spectroscopy of the motor cortex immediately following transcranial direct current stimulation at 7 Tesla

Transcranial direct current stimulation (tDCS) is a form of non-invasive brain stimulation that may modulate cortical excitability, metabolite concentration, and human behaviour. The supplementary motor area (SMA) has been largely ignored as a potential target for tDCS neurorehabilitation but is an important region in motor compensation after brain injury with strong efferent connections to the primary motor cortex (M1). The objective of this work was to measure tissue metabolite changes in the human motor cortex immediately following tDCS. We hypothesized that bihemispheric tDCS would change levels of metabolites involved in neuromodulation including N-acetylaspartate (NAA), glutamate (Glu), and creatine (tCr). In this single-blind, randomized, cross-over study, fifteen healthy adults aged 21–60 participated in two 7T MRI sessions, to identify changes in metabolite concentrations by magnetic resonance spectroscopy. Immediately after 20 minutes of tDCS, there were no significant changes in metabolite levels or metabolite ratios comparing tDCS to sham. However there was a trend toward increased NAA/tCr concentration (p = 0.08) in M1 under the stimulating cathode. There was a strong, positive correlation between the change in the absolute concentration of NAA and the change in the absolute concentration of tCr (p<0.001) suggesting an effect of tDCS. Both NAA and creatine are important markers of neurometabolism. Our findings provide novel insight into the modulation of neural metabolites in the motor cortex immediately following application of bihemispheric tDCS.

Errors in 1 H-MRS estimates of brain metabolite concentrations caused by failing to take into account tissue-specific signal relaxation

Accurate measurement of brain metabolite concentrations with proton magnetic resonance spectroscopy (¹ H-MRS) can be problematic because of large voxels with mixed tissue composition, requiring adjustment for differing relaxation rates in each tissue if absolute concentration estimates are desired. Adjusting for tissue-specific metabolite signal relaxation, however, also requires a knowledge of the relative concentrations of the metabolite in gray (GM) and white (WM) matter, which are not known a priori. Expressions for the estimation of the molality and molarity of brain metabolites with ¹ H-MRS are extended to account for tissue-specific relaxation of the metabolite signals and examined under different assumptions with simulated and real data. Although the modified equations have two unknowns, and hence are unsolvable explicitly, they are nonetheless useful for the estimation of the effect of tissue-specific metabolite relaxation rates on concentration estimates under a range of assumptions and experimental parameters using simulated and real data. In simulated data using reported GM and WM T₁ and T₂ times for N-acetylaspartate (NAA) at 3 T and a hypothetical GM/WM NAA ratio, errors of 6.5-7.8% in concentrations resulted when TR = 1.5 s and TE = 0.144 s, but were reduced to less than 0.5% when TR = 6 s and TE = 0.006 s. In real data obtained at TR/TE = 1.5 s/0.04 s, the difference in the results (4%) was similar to that obtained with simulated data when assuming tissue-specific relaxation times rather than GM-WM-averaged times. Using the expressions introduced in this article, these results can be extrapolated to any metabolite or set of assumptions regarding tissue-specific relaxation. Furthermore, although serving to bound the problem, this work underscores the challenge of correcting for relaxation effects, given that relaxation times are generally not known and impractical to measure in most studies. To minimize such effects, the data should be acquired with pulse sequence parameters that minimize the effect of signal relaxation.

Altered macromolecular pattern and content in the aging human brain

The resonances originating from proteins underlie those of metabolites in brain ¹ H nuclear magnetic resonance (NMR) spectra. These resonances have different physical properties from those of metabolites, such as shorter T₁ and T₂ relaxation time constants. The age dependence of the macromolecular pattern and content in the human brain was investigated with a focus on adults over 66 years of age using ultrahigh-field in vivo magnetic resonance spectroscopy. Eighteen young and 23 cognitively normal older adults were studied at 7 T. Metabolite spectra were acquired in the occipital cortex and the posterior cingulate cortex with single-voxel stimulated echo acquisition mode (STEAM) spectroscopy in 14 young and 20 older adults. Macromolecular spectra were acquired in the occipital cortex using an inversion recovery STEAM sequence in four young and three older adults. The macromolecular pattern was apparent over the 0.5-4.5-ppm range in the inversion recovery spectra and the 0.5-2-ppm range in the metabolite spectra. Macromolecular content was quantified from metabolite spectra using LCModel and from inversion recovery spectra using integration. Age-associated differences in the macromolecular pattern were apparent via both types of spectra, with the largest difference observed for the 1.7- and 2-ppm macromolecular resonances. A higher macromolecular content was observed in the older adults for both brain regions. Age-specific macromolecular spectra are needed when comparing metabolite spectra from subjects of differing ages because of age-associated differences in macromolecular pattern. Age-associated pattern and content differences may provide information about the aging process.

Comparison of direct 13C and indirect 1H-[13C] MR detection methods for the study of dynamic metabolic turnover in the human brain

A wide range of direct ¹³C and indirect ¹H-[¹³C] MR detection methods exist to probe dynamic metabolic pathways in the human brain. Choosing an optimal detection method is difficult as sequence-specific features regarding spatial localization, broadband decoupling, spectral resolution, power requirements and sensitivity complicate a straightforward comparison. Here we combine density matrix simulations with experimentally determined values for intrinsic ¹H and ¹³C sensitivity, T₁ and T₂ relaxation and transmit efficiency to allow selection of an optimal ¹³C MR detection method for a given application and magnetic field. The indirect proton-observed, carbon-edited (POCE) detection method provides the highest accuracy at reasonable RF power deposition both at 4T and 7T. The various polarization transfer methods all have comparable performances, but may become infeasible at 7T due to the high RF power deposition. 2D MR methods have limited value for the metabolites considered (primarily glutamate, glutamine and γ-amino butyric acid (GABA)), but may prove valuable when additional information can be extracted, such as isotopomers or lipid composition. While providing the lowest accuracy, the detection of non-protonated carbons is the simplest to implement with the lowest RF power deposition. The magnetic field homogeneity is one of the most important parameters affecting the detection accuracy for all metabolites and all acquisition methods.