Time-domain combination of MR spectroscopy data acquired using phased-array coils

A birdcage transmit, 24-channel conformal receive array coil for sensitive 31P magnetic resonance spectroscopic imaging of the human brain at 7 T

Phosphorus (31P) magnetic resonance spectroscopic imaging (MRSI) can serve as a critical tool for more direct quantification of brain energy metabolism, tissue pH, and cell membrane turnover. However, the low concentration of 31P metabolites in biological tissue may result in low signal-to-noise ratio (SNR) in 31P MRS images. In this work, we present an innovative design and construction of a 31P radiofrequency coil for whole-brain MRSI at 7 T. Our coil builds on current literature in ultra-high field 31P coil design and offers complete coverage of the brain, including the cerebellum and brainstem. The coil consists of an actively detunable volume transmit (Tx) resonator and a custom 24-channel receive (Rx) array. The volume Tx resonator is a 16-rung high-pass birdcage coil. The Rx coil consists of a 24-element phased array composed of catered loop shapes and sizes built onto a custom, close-fitting, head-shaped housing. The Rx array was designed to provide complete coverage of the head, while minimizing mutual coupling. The Rx configuration had a meanS 11 $$ {S}_{11} $$ reflection coefficient better than -20 decibels (dB) when the coil was loaded with a human head. The mean mutual coupling (S 21 $$ {S}_{21} $$ ) among Rx elements, when loaded with a human head, was -16 dB. In phantom imaging, the phased array produced a central SNR that was 4.4-fold higher than the corresponding central SNR when operating the 31P birdcage as a transceiver. The peripheral SNR was 12-fold higher when applying the optimized phased array. In vivo 3D 31P MRSI experiments produced high-quality spectra in the cerebrum gray and white matter, as well as in the cerebellum. Characteristic phosphorus metabolites related to adenosine triphosphate metabolism and cell membrane turnover were distinguishable across all brain regions. In summary, our results demonstrate the potential of our novel coil for accurate, whole-brain 31P metabolite quantification.

Optimization of 1H MR spectroscopy methods for large volume acquisition of low concentration downfield resonances at 3T and 7T

Purpose

This goal of this study was to optimize spectrally selective 1H MRS methods for large volume acquisition of low concentration metabolites with downfield resonances at 7T and 3T, with particular attention paid to detection of nicotinamide adenine dinucleotide (NAD+) and tryptophan.

Methods

Spectrally selective excitation was used to avoid magnetization transfer effects with water, and various sinc pulses were compared to a pure-phase E-BURP pulse. Localization using a single slice selective pulse was compared to voxel-based localization that used three orthogonal refocusing pulses, and low bandwidth refocusing pulses were used to take advantage of the chemical shift displacement of water. A technique for water sideband removal was added, and a method of coil channel combination for large volumes was introduced.

Results

Proposed methods were compared qualitatively to previously-reported techniques at 7T. Sinc pulses resulted in reduced water signal excitation and improved spectral quality, with a symmetric, low bandwidth-time product pulse performing best. Single slice localization allowed shorter TEs with large volumes, enhancing signal, while low bandwidth slice selective localization greatly reduced the observed water signal. Gradient cycling helped remove water sidebands, and frequency aligning and pruning individual channels narrowed spectral linewidths. High quality brain spectra of NAD+ and tryptophan are shown in four subjects at 3T.

Conclusion

Improved spectral quality with higher downfield signal, shorter TE, lower nuisance signal, reduced artifacts, and narrower peaks was realized at 7T. These methodological improvements allowed for previously unachievable detection of NAD+ and tryptophan in human brain at 3T in under five minutes.

Multi-channel magnetic resonance spectroscopy graphical user interface (McMRSGUI)

This work introduces an open-sourced graphical user interface (GUI) software enabling the combination of multi-channel magnetic resonance spectroscopy data with different literature-based methods for the improvement of the quality and reliability of combined spectra. The multi-channel magnetic resonance spectroscopy graphical user interface (McMRSGUI) is a MATLAB-based spectroscopy processing GUI equipped to load multi-channel MRS data, pre-process, combine, and export combined data for evaluation with open-source quantification software (jMRUI). A literature-based, decision-tree process was incorporated into the combination type selection to serve as a guide to minimize spectral distortion in selecting between weighting methods. Multi-channel, simulated spectra were combined with the different combination techniques and evaluated for spectral distortion to validate the code. The incorporation of the combination methods into a single processing software enables multi-channel magnetic resonance spectroscopy (MRS) data to be combined and compared for improved spectral quality with little user knowledge of combination techniques. Through the spectral peak distortion simulation of the combination methods, combined signal-to-noise ratio (SNR) values from the literature were verified. The spectral peak distortion simulation provides a secondary tool for researchers to estimate the spectral SNR levels when spectral distortion could occur and use this knowledge to further guide the selection of their combination technique. The McMRSGUI provides a software toolkit for evaluating multi-channel MRS data and their combination. Simulations evaluating spectral distortion at different noise levels were performed for each combination method to validate the GUI and demonstrate a method for researchers to assess the combined SNR levels at which they could be introducing spectral distortion.

Deuterium echo-planar spectroscopic imaging (EPSI) in the human liver in vivo at 7 T

PURPOSE

To demonstrate the feasibility of deuterium echo-planar spectroscopic imaging (EPSI) to accelerate 3D deuterium metabolic imaging in the human liver at 7 T.

METHODS

A deuterium EPSI sequence, featuring a Hamming-weighted k-space acquisition pattern for the phase-encoding directions, was implemented. Three-dimensional deuterium EPSI and conventional MRSI were performed on a water/acetone phantom and in vivo in the human liver at natural abundance. Moreover, in vivo deuterium EPSI measurements were acquired after oral administration of deuterated glucose. The effect of acquisition time on SNR was evaluated by retrospectively reducing the number of averages.

RESULTS

The SNR of natural abundance deuterated water signal in deuterium EPSI was 6.5% and 5.9% lower than that of MRSI in the phantom and in vivo experiments, respectively. In return, the acquisition time of in vivo EPSI data could be reduced retrospectively to 2 min, beyond the minimal acquisition time of conventional MRSI (of 20 min in this case), while still leaving sufficient SNR. Three-dimensional deuterium EPSI, after administration of deuterated glucose, enabled monitoring of hepatic glucose dynamics with full liver coverage, a spatial resolution of 20 mm isotropic, and a temporal resolution of 9 min 50 s, which could retrospectively be shortened to 2 min.

CONCLUSION

In this work, we demonstrate the feasibility of accelerated 3D deuterium metabolic imaging of the human liver using deuterium EPSI. The acceleration obtained with EPSI can be used to increase temporal and/or spatial resolution, which will be valuable to study tissue metabolism of deuterated compounds over time.

Post-acquisition water-signal removal in 3D water-unsuppressed 1 H-MR spectroscopic imaging of the prostate

PURPOSE

To develop a robust processing procedure of raw signals from water-unsuppressed MRSI of the prostate for the mapping of absolute tissue concentrations of metabolites.

METHODS

Water-unsuppressed 3D MRSI data were acquired from a phantom, from healthy volunteers, and a patient with prostate cancer. Signal processing included sequential computation of the modulus of the FID to remove water sidebands, a Hilbert transformation, and k-space Hamming filtering. For the removal of the water signal, we compared Löwner tensor-based blind source separation (BSS) and Hankel Lanczos singular value decomposition techniques. Absolute metabolite levels were quantified with LCModel and the results were statistically analyzed to compare the water removal methods and conventional water-suppressed MRSI.

RESULTS

The post-processing algorithms successfully removed the water signal and its sidebands without affecting metabolite signals. The best water removal performance was achieved by Löwner tensor-based BSS. Absolute tissue concentrations of citrate in the peripheral zone derived from water-suppressed and unsuppressed ¹ H MRSI were the same and as expected from the known physiology of the healthy prostate. Maps for citrate and choline from water-unsuppressed 3D ¹ H-MRSI of the prostate showed expected spatial variations in metabolite levels.

CONCLUSION

We developed a robust relatively simple post-processing method of water-unsuppressed MRSI of the prostate to remove the water signal. Absolute quantification using the water signal, originating from the same location as the metabolite signals, avoids the acquisition of additional reference data.

tDCS induced GABA change is associated with the simulated electric field in M1, an effect mediated by grey matter volume in the MRS voxel

BACKGROUND AND OBJECTIVE

Transcranial direct current stimulation (tDCS) has wide ranging applications in neuro-behavioural and physiological research, and in neurological rehabilitation. However, it is currently limited by substantial inter-subject variability in responses, which may be explained, at least in part, by anatomical differences that lead to variability in the electric field (E-field) induced in the cortex. Here, we tested whether the variability in the E-field in the stimulated cortex during anodal tDCS, estimated using computational simulations, explains the variability in tDCS induced changes in GABA, a neurophysiological marker of stimulation effect.

METHODS

Data from five previously conducted MRS studies were combined. The anode was placed over the left primary motor cortex (M1, 3 studies, N = 24) or right temporal cortex (2 studies, N = 32), with the cathode over the contralateral supraorbital ridge. Single voxel spectroscopy was performed in a 2x2x2cm voxel under the anode in all cases. MRS data were acquired before and either during or after 1 mA tDCS using either a sLASER sequence (7T) or a MEGA-PRESS sequence (3T). sLASER MRS data were analysed using LCModel, and MEGA-PRESS using FID-A and Gannet. E-fields were simulated in a finite element model of the head, based on individual structural MR images, using SimNIBS. Separate linear mixed effects models were run for each E-field variable (mean and 95th percentile; magnitude, and components normal and tangential to grey matter surface, within the MRS voxel). The model included effects of time (pre or post tDCS), E-field, grey matter volume in the MRS voxel, and a 3-way interaction between time, E-field and grey matter volume. Additionally, we ran a permutation analysis using PALM to determine whether E-field anywhere in the brain, not just in the MRS voxel, correlated with GABA change.

RESULTS

In M1, higher mean E-field magnitude was associated with greater anodal tDCS-induced decreases in GABA (t(24) = 3.24, p = 0.003). Further, the association between mean E-field magnitude and GABA change was moderated by the grey matter volume in the MRS voxel (t(24) = -3.55, p = 0.002). These relationships were consistent across all E-field variables except the mean of the normal component. No significant relationship was found between tDCS-induced GABA decrease and E-field in the temporal voxel. No significant clusters were found in the whole brain analysis.

CONCLUSIONS

Our data suggest that the electric field induced by tDCS within the brain is variable, and is significantly related to anodal tDCS-induced decrease in GABA, a key neurophysiological marker of stimulation. These findings strongly support individualised dosing of tDCS, at least in M1. Further studies examining E-fields in relation to other outcome measures, including behaviour, will help determine the optimal E-fields required for any desired effects.

Fourier-based decomposition for simultaneous 2-voxel MRS acquisition with 2SPECIAL

PURPOSE

To simultaneously acquire spectroscopic signals from two MRS voxels using a multi-banded 2 spin-echo, full-intensity acquired localized (2SPECIAL) sequence, and to decompose the signal to their respective regions by a novel voxel-GRAPPA (vGRAPPA) decomposition approach for in vivo brain applications at 7 T.

METHODS

A wideband, uniform rate, smooth truncation (WURST) multi-banded pulse was incorporated into SPECIAL to implement 2SPECIAL for simultaneous multi-voxel spectroscopy (sMVS). To decompose the acquired data, the voxel-GRAPPA decomposition algorithm is introduced, and its performance is compared to the SENSE-based decomposition. Furthermore, the limitations of two-voxel excitation concerning the multi-banded adiabatic inversion pulse, as well as of the combined B₀ shim and B₁ ⁺ adjustments, are evaluated.

RESULTS

It was successfully shown that the 2SPECIAL sequence enables sMVS without a significant loss in SNR while reducing the total scan time by 21.6% compared to two consecutive acquisitions. The proposed voxel-GRAPPA algorithm properly reassigns the signal components to their respective origin region and shows no significant differences to the well-established SENSE-based algorithm in terms of leakage (both <10%) or Cramér-Rao lower bounds (CRLB) for in vivo applications, while not requiring the acquisition of additional sensitivity maps and thus decreasing motion sensitivity.

CONCLUSION

The use of 2SPECIAL in combination with the novel voxel-GRAPPA decomposition technique allows a substantial reduction of measurement time compared to the consecutive acquisition of two single voxels without a significant decrease in spectral quality or metabolite quantification accuracy and thus provides a new option for multiple-voxel applications.

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.

Coil Combination of Multichannel Single Voxel Magnetic Resonance Spectroscopy with Repeatedly Sampled In Vivo Data

Magnetic resonance spectroscopy (MRS), as a noninvasive method for molecular structure determination and metabolite detection, has grown into a significant tool in clinical applications. However, the relatively low signal-to-noise ratio (SNR) limits its further development. Although the multichannel coil and repeated sampling are commonly used to alleviate this problem, there is still potential room for promotion. One possible improvement way is combining these two acquisition methods so that the complementary of them can be well utilized. In this paper, a novel coil-combination method, average smoothing singular value decomposition, is proposed to further improve the SNR by introducing repeatedly sampled signals into multichannel coil combination. Specifically, the sensitivity matrix of each sampling was pretreated by whitened singular value decomposition (WSVD), then the smoothing was performed along the repeated samplings’ dimension. By comparing with three existing popular methods, Brown, WSVD, and generalized least squares, the proposed method showed better performance in one phantom and 20 in vivo spectra.

k-Space-based coil combination via geometric deep learning for reconstruction of non-Cartesian MRSI data

PURPOSE

State-of-the-art whole-brain MRSI with spatial-spectral encoding and multichannel acquisition generates huge amounts of data, which must be efficiently processed to stay within reasonable reconstruction times. Although coil combination significantly reduces the amount of data, currently it is performed in image space at the end of the reconstruction. This prolongs reconstruction times and increases RAM requirements. We propose an alternative k-space-based coil combination that uses geometric deep learning to combine MRSI data already in native non-Cartesian k-space.

METHODS

Twelve volunteers were scanned at a 3T MR scanner with a 20-channel head coil at 10 different positions with water-unsuppressed MRSI. At the eleventh position, water-suppressed MRSI data were acquired. Data of 7 volunteers were used to estimate sensitivity maps and form a base for simulating training data. A neural network was designed and trained to remove the effect of sensitivity profiles of the coil elements from the MRSI data. The water-suppressed MRSI data of the remaining volunteers were used to evaluate the performance of the new k-space-based coil combination relative to that of a conventional image-based alternative.

RESULTS

For both approaches, the resulting metabolic ratio maps were similar. The SNR of the k-space-based approach was comparable to the conventional approach in low SNR regions, but underperformed for high SNR. The Cramér-Rao lower bounds show the same trend. The analysis of the FWHM showed no difference between the two methods.

CONCLUSION

k-Space-based coil combination of MRSI data is feasible and reduces the amount of raw data immediately after their sampling.

Advanced magnetic resonance spectroscopic neuroimaging: Experts' consensus recommendations

Magnetic resonance spectroscopic imaging (MRSI) offers considerable promise for monitoring metabolic alterations associated with disease or injury; however, to date, these methods have not had a significant impact on clinical care, and their use remains largely confined to the research community and a limited number of clinical sites. The MRSI methods currently implemented on clinical MRI instruments have remained essentially unchanged for two decades, with only incremental improvements in sequence implementation. During this time, a number of technological developments have taken place that have already greatly benefited the quality of MRSI measurements within the research community and which promise to bring advanced MRSI studies to the point where the technique becomes a true imaging modality, while making the traditional review of individual spectra a secondary requirement. Furthermore, the increasing use of biomedical MR spectroscopy studies has indicated clinical areas where advanced MRSI methods can provide valuable information for clinical care. In light of this rapidly changing technological environment and growing understanding of the value of MRSI studies for biomedical studies, this article presents a consensus from a group of experts in the field that reviews the state-of-the-art for clinical proton MRSI studies of the human brain, recommends minimal standards for further development of vendor-provided MRSI implementations, and identifies areas which need further technical development.

3D 31 P MR spectroscopic imaging of the human brain at 3 T with a 31 P receive array: An assessment of 1 H decoupling, T1 relaxation times, 1 H-31 P nuclear Overhauser effects and NAD. NMR IN BIOMEDICINE 2021;34:e4169. [PMID: 31518036 PMCID: PMC8244063 DOI: 10.1002/nbm.4169]

³¹ P MR spectroscopic imaging (MRSI) is a versatile technique to study phospholipid precursors and energy metabolism in the healthy and diseased human brain. However, mainly due to its low sensitivity, ³¹ P MRSI is currently limited to research purposes. To obtain 3D ³¹ P MRSI spectra with improved signal-to-noise ratio on clinical 3 T MR systems, we used a coil combination consisting of a dual-tuned birdcage transmit coil and a ³¹ P eight-channel phased-array receive insert. To further increase resolution and sensitivity we applied WALTZ4 ¹ H decoupling and continuous wave nuclear Overhauser effect (NOE) enhancement and acquired high-quality MRSI spectra with nominal voxel volumes of ~ 17.6 cm³ (effective voxel volume ~ 51 cm³ ) in a clinically relevant measurement time of ~ 13 minutes, without exceeding SAR limits. Steady-state NOE enhancements ranged from 15 ± 9% (γ-ATP) and 33 ± 3% (phosphocreatine) to 48 ± 11% (phosphoethanolamine). Because of these improvements, we resolved and detected all ³¹ P signals of metabolites that have also been reported for ultrahigh field strengths, including resonances for NAD⁺ , NADH and extracellular inorganic phosphate. T₁ times of extracellular inorganic phosphate were longer than for intracellular inorganic phosphate (3.8 ± 1.4s vs 1.8 ± 0.65 seconds). A comparison of measured T₁ relaxation times and NOE enhancements at 3 T with published values between 1.5 and 9.4 T indicates that T₁ relaxation of ³¹ P metabolite spins in the human brain is dominated by dipolar relaxation for this field strength range. Even although intrinsic sensitivity is higher at ultrahigh fields, we demonstrate that at a clinical field strength of 3 T, similar ³¹ P MRSI information content can be obtained using a sophisticated coil design combined with ¹ H decoupling and NOE enhancement.

Measuring transverse relaxation rates of the major brain metabolites from single-voxel PRESS acquisitions at a single TE

PURPOSE

To compare transverse relaxation rates of brain metabolites estimated from single-TE PRESS acquisitions with more conventionally derived rates estimated from multiple-TE PRESS acquisitions.

METHODS

Single-voxel (8 mL) PRESS data within white matter from 6 subjects were acquired at five different TEs. Transverse relaxation rates R₂ of N-acetylaspartate, creatine, and choline were estimated from a single TE using full versus right-side-only sampling of the echo. These R₂ values were compared with R_2Hahn values obtained from the multiple-TE PRESS acquisitions.

RESULTS

Following baseline subtraction and RMS weighting, interindividual mean R₂ values from TE = 288 ms magnitude spectra for choline, creatine, and N-acetylaspartate were highly correlated with respective R_2Hahn values (r² = 0.99). Paired individual measurements at this TE showed less correlation (r² = 0.48), primarily due to the N-acetylaspartate resonance. Using TE = 360 ms data for N-acetylaspartate and 288 ms for choline and creatine resulted in an improved correlation coefficient (r² = 0.80). The average absolute intra-individual differences in the estimated R₂ s between single-TE and Hahn method was 9.6 ± 7.7%.

CONCLUSION

For the major brain metabolite singlets, R_2Hahn values showed correlations with more fragile measurements of R₂ from a single TE that are worthy of interest. Because the left side of long-TE spin echoes is available "for free" from an acquisition perspective, and although the single-TE method for estimating R₂ values is associated with lower precision, the reduction in scan time may be clinically helpful.

Optimized truncation to integrate multi-channel MRS data using rank-R singular value decomposition

Multi-channel phased receive arrays have been widely adopted for magnetic resonance imaging (MRI) and spectroscopy (MRS). An important step in the use of receive arrays for MRS is the combination of spectra collected from individual coil channels. The goal of this work was to implement an improved strategy termed OpTIMUS (i.e., optimized truncation to integrate multi-channel MRS data using rank-R singular value decomposition) for combining data from individual channels. OpTIMUS relies on spectral windowing coupled with a rank-R decomposition to calculate the optimal coil channel weights. MRS data acquired from a brain spectroscopy phantom and 11 healthy volunteers were first processed using a whitening transformation to remove correlated noise. Whitened spectra were then iteratively windowed or truncated, followed by a rank-R singular value decomposition (SVD) to empirically determine the coil channel weights. Spectra combined using the vendor-supplied method, signal/noise² weighting, previously reported whitened SVD (rank-1), and OpTIMUS were evaluated using the signal-to-noise ratio (SNR). Significant increases in SNR ranging from 6% to 33% (P ≤ 0.05) were observed for brain MRS data combined with OpTIMUS compared with the three other combination algorithms. The assumption that a rank-1 SVD maximizes SNR was tested empirically, and a higher rank-R decomposition, combined with spectral windowing prior to SVD, resulted in increased SNR.

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.

Whole brain 31 P MRSI at 7T with a dual-tuned receive array

PURPOSE

The design and performance of a novel head coil setup for 31 P spectroscopy at ultra-high field strengths (7T) is presented. The described system supports measurements at both the 1 H and 31 P resonance frequencies.

METHODS

The novel coil consists of 2, actively detunable, coaxial birdcage coils to give homogeneous transmit, combined with a double resonant 30 channel receive array. This allows for anatomical imaging combined with 31 P acquisitions over the whole head, without changing coils or disturbing the subject. A phosphate buffer phantom and 3 healthy volunteers were scanned with a pulse acquire CSI sequence using both the novel array coil and a conventional transceiver birdcage. Four different methods of combining the array channels were compared at 3 different levels of SNR.

RESULTS

The novel coil setup delivers significantly increased 31 P SNR in the peripheral regions of the brain, reaching up to factor 8, while maintaining comparable performance relative to the birdcage in the center.

CONCLUSIONS

The new system offers the potential to acquire whole brain 31 P MRSI with superior signal relative to the standard options.

Non-Cartesian GRAPPA and coil combination using interleaved calibration data - application to concentric-ring MRSI of the human brain at 7T

PURPOSE

Proton MR spectroscopic imaging (MRSI) benefits from B₀ ≥ 7T and multichannel receive coils, promising substantial resolution improvements. However, MRSI acquisition with high spatial resolution requires efficient acceleration and coil combination. To speed up the already-fast sampling via concentric rings, we implemented additional, non-Cartesian, hybrid through-time/through-k-space (tt/tk)-generalized autocalibrating partially parallel acquisition (GRAPPA). A new multipurpose interleaved calibration scan (interleaved MUSICAL) acquires reference data for both coil combination and PI. This renders the reconstruction process (especially PI) less sensitive to instabilities.

METHODS

Six healthy volunteers were scanned at 7T. Three calibration datasets for coil combination and PI were recorded: a) iMUSICAL, b) static MUSICAL as prescan, c) moved MUSICAL as prescan with misaligned head position. The coil combination performance, including motion sensitivity, of iMUSICAL was compared to MUSICAL for single-slice free induction decay (FID)-MRSI. Through-time/through-k-space-GRAPPA with constant/variable-density undersampling was evaluated on the same data, comparing the three calibration datasets. Additionally, the proposed method was successfully applied to 3D whole-brain FID-MRSI.

RESULTS

Using iMUSICAL for coil combination yielded the highest signal-to-noise ratio (SNR) (+9%) and lowest Cramer-Rao lower bounds (CRLBs) (-6%) compared to both MUSICAL approaches, with similar metabolic map quality. Also, excellent mean g-factors of 1.07 and low residual lipid aliasing were obtained when using iMUSICAL as calibration data for two-fold, variable-density undersampling, while significantly degraded metabolic maps were obtained using the misaligned MUSICAL calibration data.

CONCLUSION

Through-time/through-k-space-GRAPPA can accelerate already time-efficient non-Cartesian spatial-spectral 2D/3D-MRSI encoding even further. Particularly promising results have been achieved using iMUSICAL as a robust, interleaved multipurpose calibration for MRSI reconstruction, without extra calibration prescan.

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.

Brain iron and metabolic abnormalities in C19orf12 mutation carriers: A 7.0 tesla MRI study in mitochondrial membrane protein-associated neurodegeneration

BACKGROUND

Mitochondrial membrane protein-associated neurodegeneration is an autosomal-recessive disorder caused by C19orf12 mutations and characterized by iron deposits in the basal ganglia.

OBJECTIVES

The aim of this study was to quantify iron concentrations in deep gray matter structures using quantitative susceptibility mapping MRI and to characterize metabolic abnormalities in the pyramidal pathway using ¹ H MR spectroscopy in clinically manifesting membrane protein-associated neurodegeneration patients and asymptomatic C19orf12 gene mutation heterozygous carriers.

METHODS

We present data of 4 clinically affected membrane protein-associated neurodegeneration patients (mean age: 21.0 ± 2.9 years) and 9 heterozygous gene mutation carriers (mean age: 50.4 ± 9.8 years), compared to age-matched healthy controls. MRI assessments were performed on a 7.0 Tesla whole-body system, consisting of whole-brain gradient-echo scans and short echo time, single-volume MR spectroscopy in the white matter of the precentral/postcentral gyrus. Quantitative susceptibility mapping, a surrogate marker for iron concentration, was performed using a state-of-the-art multiscale dipole inversion approach with focus on the globus pallidus, thalamus, putamen, caudate nucleus, and SN.

RESULTS AND CONCLUSION

In membrane protein-associated neurodegeneration patients, magnetic susceptibilities were 2 to 3 times higher in the globus pallidus (P = 0.02) and SN (P = 0.02) compared to controls. In addition, significantly higher magnetic susceptibility was observed in the caudate nucleus (P = 0.02). Non-manifesting heterozygous mutation carriers exhibited significantly increased magnetic susceptibility (relative to controls) in the putamen (P = 0.003) and caudate nucleus (P = 0.001), which may be an endophenotypic marker of genetic heterozygosity. MR spectroscopy revealed significantly increased levels of glutamate, taurine, and the combined concentration of glutamate and glutamine in membrane protein-associated neurodegeneration, which may be a correlate of corticospinal pathway dysfunction frequently observed in membrane protein-associated neurodegeneration patients. © 2019 International Parkinson and Movement Disorder Society.

Methodological consensus on clinical proton MRS of the brain: Review and recommendations

Proton MRS (1 H MRS) provides noninvasive, quantitative metabolite profiles of tissue and has been shown to aid the clinical management of several brain diseases. Although most modern clinical MR scanners support MRS capabilities, routine use is largely restricted to specialized centers with good access to MR research support. Widespread adoption has been slow for several reasons, and technical challenges toward obtaining reliable good-quality results have been identified as a contributing factor. Considerable progress has been made by the research community to address many of these challenges, and in this paper a consensus is presented on deficiencies in widely available MRS methodology and validated improvements that are currently in routine use at several clinical research institutions. In particular, the localization error for the PRESS localization sequence was found to be unacceptably high at 3 T, and use of the semi-adiabatic localization by adiabatic selective refocusing sequence is a recommended solution. Incorporation of simulated metabolite basis sets into analysis routines is recommended for reliably capturing the full spectral detail available from short TE acquisitions. In addition, the importance of achieving a highly homogenous static magnetic field (B0 ) in the acquisition region is emphasized, and the limitations of current methods and hardware are discussed. Most recommendations require only software improvements, greatly enhancing the capabilities of clinical MRS on existing hardware. Implementation of these recommendations should strengthen current clinical applications and advance progress toward developing and validating new MRS biomarkers for clinical use.

Effect of linewidth on estimation of metabolic concentration when using water lineshape spectral model fitting for single voxel proton spectroscopy at 7 T

Good B₀ field homogeneity is considered an essential requirement to obtain high-quality MRS data. Many commonly used spectral fitting methods assume that all metabolite signals have Lorentzian or Gaussian shapes. However, B₀ inhomogeneity can both broaden the linewidth and modify the lineshape. In this study, it is hypothesized that a realistic metabolite fitting model, which accounts for B₀ homogeneity on the basis of the water lineshape, will improve the accuracy of estimation of metabolite concentrations. In-vivo water suppressed/unsuppressed single voxel spectroscopy signals were acquired under three different B₀ field homogeneity regimes. Individual realistic basis sets were created for each acquisition. Frequency-domain spectral fitting with LCModel was used to quantify the metabolite concentrations with fitting uncertainties given in terms of the Cramer-Rao lower bound. The quantification results obtained using the water lineshape basis set yielded similar concentrations independent of linewidth and showed a larger fitting error as the linewidth increased. The conventional approach, however quantifies metabolite concentrations with greater variations despite showing a supposedly improved fitting quality. The water lineshape basis set achieved single voxel spectroscopy accuracy that is less sensitive to the linewidth compared to the conventional spectral fitting method for the range of linewidths used in this study, but the precision deteriorated with worsening B₀ field inhomogeneity. The beneficial effect was ascribed to a reduction in the number of degrees of freedom when using the water lineshape to generate the basis set.

Optimal Phased-Array Signal Combination For Polyunsaturated Fatty Acids Measurement In Breast Cancer Using Multiple Quantum Coherence MR Spectroscopy At 3T

Polyunsaturated fatty acid (PUFA), a key marker in breast cancer, is non-invasively quantifiable using multiple quantum coherence (MQC) magnetic resonance spectroscopy (MRS) at the expense of losing half of the signal. Signal combination for phased array coils provides potential pathways to enhance the signal to noise ratio (SNR), with current algorithms developed for conventional brain MRS. Since PUFA spectra and the biochemical environment in the breast deviate significantly from those in the brain, we set out to identify the optimal algorithm for PUFA in breast cancer. Combination algorithms were compared using PUFA spectra from 17 human breast tumour specimens, 15 healthy female volunteers, and 5 patients with breast cancer on a clinical 3 T MRI scanner. Adaptively Optimised Combination (AOC) yielded the maximum SNR improvement in specimens (median, 39.5%; interquartile range: 35.5-53.2%, p < 0.05), volunteers (82.4 ± 37.4%, p < 0.001), and patients (median, 61%; range: 34-105%, p < 0.05), while independent from voxel volume (rho = 0.125, p = 0.632), PUFA content (rho = 0.256, p = 0.320) or water/fat ratio (rho = 0.353, p = 0.165). Using AOC, acquisition in patients is 1.5 times faster compared to non-noise decorrelated algorithms. Therefore, AOC is the most suitable current algorithm to improve SNR or accelerate the acquisition of PUFA MRS from breast in a clinical setting.

A comparison of coil combination strategies in 3D multi-channel MRSI reconstruction for patients with brain tumors

The goal of this study was to find the most robust algorithm for a phase-sensitive coil combination of 3D single-cycle and lactate-edited, multi-channel H-1 point-resolved spectroscopy (PRESS) localized echo planar spectroscopic imaging (EPSI) data for clinical applications in the brain. Data were acquired over 5-10 minutes at 3T using 8- or 32-channel array coils. Peak referencing with residual water and N-acetyl-aspartate, first-point phasing, generalized least squared (GLS) and whitened singular-value decomposition (WSVD) combination algorithms were evaluated relative to unsuppressed water with data from a phantom, six volunteers and 55 patients with brain tumors. Comparison metrics were signal-to-noise ratio, coefficient of variance and percent signal increase. Where residual water was present, using it as a reference peak for phasing and weighting factors from an imaging calibration scan gave the best overall performance. Greater improvement was seen for large selected volumes (>720 cm³ ) and for the 32-channel array (25%) compared with the 8-channel array (19%). Applying voxel-by-voxel phase corrections produced a larger increase in performance for the 32- versus 8-channel coil. We conclude that, for clinically relevant 3D H-1 PRESS localized EPSI studies, the most robust technique employed individual phase maps generated from high residual water and individual amplitude maps generated from calibration scans.

Variance components associated with long-echo-time MR spectroscopic imaging in human brain at 1.5T and 3T

OBJECT

Magnetic resonance spectroscopic imaging (MRSI) is increasingly used in medicine and clinical research. Previous reliability studies have used small samples and focussed on limited aspects of variability; information regarding 1.5T versus 3T performance is lacking. The aim of the present work was to measure the inter-session, intra-session, inter-subject, within-brain and residual variance components using both 1.5T and 3T MR scanners.

MATERIALS AND METHODS

Eleven healthy volunteers were invited for MRSI scanning on three occasions at both 1.5T and 3T, with four scans acquired at each visit. We measured variance components, correcting for grey matter and white matter content of voxels, of metabolite peak areas and peak area ratios.

RESULTS

Residual variance was in general the largest component at 1.5T (8.6-24.6%), while within-brain variation was the largest component at 3T (12.0-24.7%). Inter-subject variation was around 5%, while inter- and intra-session variance were both generally small.

CONCLUSION

Multiple variance contributions associated with MRSI measurements were quantified and the performance of 1.5T and 3T MRI scanners compared using data from the same group of subjects. Residual error is much lower at 3T, but other variance components remain important.

Effects of proximity and noise level of phased array coil elements on overall signal-to-noise in parallel MR spectroscopy

Parallel imaging using phased array coils facilitates accelerated magnetic resonance imaging (MRI) and spectroscopy (MRS). Parallel data reconstruction requires the combination of data from individual coil elements, but limited combination algorithms currently exist for higher-order phased arrays and MRS data. Here, we present a systematic framework for identifying coil proximity-related signal inhomogeneities and noise levels in phased array coils that may affect sensitivity of parallel MRS. Single-voxel MRS was acquired in nine voxel positions in a brain spectroscopy phantom on a 3T whole-body MR scanner using commercially available 64-, 32-, and 20-channel phased array coils. Spectra produced by individual coil elements were combined using both a signal-to-noise ratio (SNR) threshold and based on the position of individual coil elements. SNR and metabolite Cramer-Rao lower bounds (CRLBs) from the final combined spectra were used as metrics to compare combination strategies and the effects of the phased array geometry and individual coil proximity. Comparisons were performed using one-way repeated measures ANOVA and post-hoc Tukey's range test (p<0.05). The 32-channel phased array coil produced the highest overall SNR compared to the 64-channel (p=0.0009) or 20-channel coils (p=0.003). Low SNR spectra from individual coil elements in the 64-channel coil can reduce the overall SNR when simply combining spectra from all elements. SNR varied significantly as a function of voxel position (F=58.3, p<0.0001) and SNR threshold for all phased arrays (p<0.05 for 64-, 32-, and 20-channel coils). Metabolite CRLBs were dependent on the combination strategy. We demonstrate the importance of the sampling voxel position and coil proximity on overall SNR in parallel MRS data acquisition, with significant SNR improvements after selectively filtering individual spectra based on pre-determined SNR thresholds which must be optimized for each phased array coil element and volume of interest.

Non-uniformly weighted sampling for faster localized two-dimensional correlated spectroscopy of the brain in vivo

Two-dimensional localized correlated spectroscopy (2D L-COSY) offers greater spectral dispersion than conventional one-dimensional (1D) MRS techniques, yet long acquisition times and limited post-processing support have slowed its clinical adoption. Improving acquisition efficiency and developing versatile post-processing techniques can bolster the clinical viability of 2D MRS. The purpose of this study was to implement a non-uniformly weighted sampling (NUWS) scheme for faster acquisition of 2D-MRS. A NUWS 2D L-COSY sequence was developed for 7T whole-body MRI. A phantom containing metabolites commonly observed in the brain at physiological concentrations was scanned ten times with both the NUWS scheme of 12:48 duration and a 17:04 constant eight-average sequence using a 32-channel head coil. 2D L-COSY spectra were also acquired from the occipital lobe of four healthy volunteers using both the proposed NUWS and the conventional uniformly-averaged L-COSY sequence. The NUWS 2D L-COSY sequence facilitated 25% shorter acquisition time while maintaining comparable SNR in humans (+0.3%) and phantom studies (+6.0%) compared to uniform averaging. NUWS schemes successfully demonstrated improved efficiency of L-COSY, by facilitating a reduction in scan time without affecting signal quality.

Detection of metabolite changes in response to a varying visual stimulation paradigm using short-TE 1 H MRS at 7 T

The two-fold benefit of ¹ H magnetic resonance spectroscopy (MRS) at high B₀ fields - enhanced sensitivity and increased spectral dispersion - has been used previously to study dynamic changes in metabolite concentrations in the human brain in response to visual stimulation. In these studies, a strong visual on/off stimulus was combined with MRS data acquisition in a voxel location in the occipital cortex determined by an initial functional magnetic resonance imaging experiment. However, 1) to exclude the possibility of systemic effects (heartbeat, blood flow, etc.), which tend to be different for on/off conditions, a modified stimulation condition not affecting the target voxel needs to be employed, and 2) to assess important neurotransmitters of low concentration, in particular γ-aminobutyric acid (GABA), it may be advantageous to analyze steady-state, rather than dynamic, conditions. Thus, the aim of this study was to use short-TE ¹ H MRS methodology at 7 T to detect differences in steady-state metabolite levels in response to a varying stimulation paradigm in the human visual cortex. The two different stimulation conditions were termed voxel and control activation. Localized MR spectra were acquired using the SPECIAL (spin-echo full-intensity acquired localized) sequence. Data were analyzed using LCModel. Fifteen individual metabolites were reliably quantified. On comparison of steady-state concentrations for voxel versus control activation, a decrease in GABA of 0.05 mmol/L (5%) and an increase in lactate of 0.04 mmol/L (7%) were found to be the only significant effects. The observed reduction in GABA can be interpreted as reduced neuronal inhibition during voxel activation, whereas the increase in lactate hints at an intensification of anaerobic glycolysis. Differences from previous studies, notably the absence of any changes in glutamate, are attributed to the modified experimental conditions. This study demonstrates that the use of advanced ¹ H MRS methodology at 7 T allows the detection of subtle changes in metabolite concentrations involved in neuronal activation and inhibition.

Neurometabolic abnormalities in schizophrenia and depression observed with magnetic resonance spectroscopy at 7 T

BACKGROUND

Examining neurometabolic abnormalities in critical brain areas in schizophrenia and major depressive disorder (MDD) may help guide future pharmacological interventions including glutamate-modulating treatments.

AIMS

To measure metabolite concentrations within the anterior cingulate cortex (ACC) and thalamus of people with schizophrenia and people with MDD.

METHODS

Spectra were acquired from 16 volunteers with schizophrenia, 17 with MDD and 18 healthy controls using magnetic resonance spectroscopy on a 7 Tesla scanner.

RESULTS

In the thalamus, there were lower glycine concentrations in the schizophrenia group relative to control (P=0.017) and MDD groups (P=0.012), and higher glutamine concentrations relative to healthy controls (P=0.009). In the thalamus and the ACC, the MDD group had lower myo-inositol concentrations than the control (P=0.014, P=0.009, respectively) and schizophrenia (P=0.004, P=0.002, respectively) groups.

CONCLUSION

These results support the glutamatergic theory of schizophrenia and indicate a potential glycine deficiency in the thalamus. In addition, reduced myo-inositol concentrations in MDD suggest its involvement in the disorder.

DECLARATION OF INTEREST

None.

COPYRIGHT AND USAGE

© The Royal College of Psychiatrists 2017. This is an open access article distributed under the terms of the Creative Commons Non-Commercial, No Derivatives (CC BY-NC-ND) license.

Adaptively Optimized Combination (AOC) of Phased-Array MR Spectroscopy Data in the Presence of Correlated Noise: Compared with Noise-Decorrelated or Whitened Methods

PURPOSE

A method for adaptively optimized combination (AOC) of MR spectroscopic data from a coil array was recently introduced. The superior performance of the AOC method is evident when compared with the methods that assume uncorrelated noise between coil elements. However, it is unclear whether the AOC method represents the most optimal combination in the presence of correlated noise, when compared with the noise-decorrelated or whitened methods that specifically tackle the correlated noise between coil elements.

METHODS

A new, unified theoretical framework was developed to illustrate the relationship between the AOC method and three noise-decorrelated or whitened methods, namely, noise-decorrelated combination (nd-comb), whitened singular value decomposition (WSVD), and improved WSVD (WSVD+Apod). Simulation-based comparisons and in vivo human brain experiments on a 3 Tesla (T) MRI scanner were performed using an 8-channel phased-array head coil.

RESULTS

Compared with the noise-decorrelated or whitened methods, the AOC method consistently yielded the best combination in terms of the robustness against noise and maintaining the combined spectrum from distortion, and the superior performance was most evident at a low signal-to-noise ratio (SNR).

CONCLUSION

The AOC method represents the theoretical optimal combination in the presence of correlated noise between coil elements, whereas the three noise-decorrelated or whitened methods are asymptotically optimal. Magn Reson Med 78:848-859, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Brain γ-aminobutyric acid (GABA) detection in vivo with the J-editing (1) H MRS technique: a comprehensive methodological evaluation of sensitivity enhancement, macromolecule contamination and test-retest reliability

Abnormalities in brain γ-aminobutyric acid (GABA) have been implicated in various neuropsychiatric and neurological disorders. However, in vivo GABA detection by (1) H MRS presents significant challenges arising from the low brain concentration, overlap by much stronger resonances and contamination by mobile macromolecule (MM) signals. This study addresses these impediments to reliable brain GABA detection with the J-editing difference technique on a 3-T MR system in healthy human subjects by: (i) assessing the sensitivity gains attainable with an eight-channel phased-array head coil; (ii) determining the magnitude and anatomic variation of the contamination of GABA by MM; and (iii) estimating the test-retest reliability of the measurement of GABA with this method. Sensitivity gains and test-retest reliability were examined in the dorsolateral prefrontal cortex (DLPFC), whereas MM levels were compared across three cortical regions: DLPFC, the medial prefrontal cortex (MPFC) and the occipital cortex (OCC). A three-fold higher GABA detection sensitivity was attained with the eight-channel head coil compared with the standard single-channel head coil in DLPFC. Despite significant anatomical variation in GABA + MM and MM across the three brain regions (p < 0.05), the contribution of MM to GABA + MM was relatively stable across the three voxels, ranging from 41% to 49%, a non-significant regional variation (p = 0.58). The test-retest reliability of GABA measurement, expressed as either the ratio to voxel tissue water (W) or to total creatine, was found to be very high for both the single-channel coil and the eight-channel phased-array coil. For the eight-channel coil, for example, Pearson's correlation coefficient of test vs. retest for GABA/W was 0.98 (R(2)  = 0.96, p = 0.0007), the percentage coefficient of variation (CV) was 1.25% and the intraclass correlation coefficient (ICC) was 0.98. Similar reliability was also found for the co-edited resonance of combined glutamate and glutamine (Glx) for both coils. Copyright © 2016 John Wiley & Sons, Ltd.

Coil combination for receive array spectroscopy: Are data-driven methods superior to methods using computed field maps?

PURPOSE

Combining spectra from receive arrays, particularly X-nuclear spectra with low signal-to-noise ratios (SNRs), is challenging. We test whether data-driven combination methods are better than using computed coil sensitivities.

THEORY

Several combination algorithms are recast into the notation of Roemer's classic formula, showing that they differ primarily in their estimation of coil receive sensitivities. This viewpoint reveals two extensions of the whitened singular-value decomposition (WSVD) algorithm, using temporal or temporal + spatial apodization to improve the coil sensitivities, and thus the combined spectral SNR.

METHODS

Radiofrequency fields from an array were simulated and used to make synthetic spectra. These were combined with 10 algorithms. The combined spectra were then assessed in terms of their SNR. Validation used phantoms and cardiac (31) P spectra from five subjects at 3T.

RESULTS

Combined spectral SNRs from simulations, phantoms, and humans showed the same trends. In phantoms, the combined SNR using computed coil sensitivities was lower than with WSVD combination whenever the WSVD SNR was >14 (or >11 with temporal apodization, or >9 with temporal + spatial apodization). These new apodized WSVD methods gave higher SNRs than other data-driven methods.

CONCLUSION

In the human torso, at frequencies ≥49 MHz, data-driven combination is preferable to using computed coil sensitivities. Magn Reson, 2015. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. Magn Reson Med 75:473-487, 2016. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.

Increased glutamate levels observed upon functional activation in the anterior cingulate cortex using the Stroop Task and functional spectroscopy

It has been shown in recent studies that it is possible to detect changes in the main excitatory neurotransmitter, glutamate, upon functional activation with visual and motor paradigms using a 7 T MRI and functional magnetic resonance spectroscopy. A cognitive task would be desirable for this technique because it could then be used to examine psychiatric disorders that have cognitive deficiencies. The aim of the work presented here was to use functional magnetic resonance spectroscopy with a 7 T MRI to show that increases in glutamate can be observed within the anterior cingulate cortex using the Stroop Task as the activation paradigm in healthy controls. Significant glutamate increases (0.24±0.09 µmol/g, P<0.025), comparable with what has been reported in the studies of the occipital cortex and motor cortex, were observed when the participants (n=7) performed the task, followed by a trend toward returning to baseline in the post-task recovery period (−0.23±0.13 µmol/g). This method would be ideal for the study of neuropsychiatric disorders that have been shown to have abnormal resting glutamate levels and cognitive deficiencies in the anterior cingulate cortex, such as schizophrenia. This exploratory study is the first to demonstrate functional magnetic resonance spectroscopy in the anterior cingulate with a cognitive task using a 7 T MRI.

Phased-array combination for MR spectroscopic imaging using a water reference

PURPOSE

To evaluate methods for multichannel combination of three-dimensional MR spectroscopic imaging (MRSI) data with a focus on using information from a water-reference spectroscopic image.

METHODS

Volumetric MRSI data were acquired for a phantom and for human brain using 8- and 32-channel detection. Acquisition included a water-reference dataset that was used to determine the weights for several multichannel combination methods. Results were compared using the signal-to-noise ratio (SNR) of the N-acetylaspartate resonance.

RESULTS

Performance of all methods was very similar for the phantom study, with the whitened singular value decomposition (WSVD) and signal magnitude (S) weighting combination having a small advantage. For in vivo studies, the S weighting, SNR weighting and signal to noise squared (S/N(2) ) weighting were the three best methods and performed similarly. Example spectra and SNR maps indicated that the SVD and WSVD methods tend to fail for voxels at the outer edges of the brain that include strong lipid signal contributions.

CONCLUSION

For data combination of MRSI data using water-reference information, the S/N(2) weighting, SNR and S weighting were the best methods in terms of spectral quality SNR. These methods are also computationally efficient and easy to implement. Magn Reson Med 76:733-741, 2016. © 2015 Wiley Periodicals, Inc.

Functional magnetic resonance spectroscopy of glutamate in schizophrenia and major depressive disorder: anterior cingulate activity during a color-word Stroop task

Background:

Glutamate abnormalities have been suggested to be associated with symptoms of schizophrenia. Using functional magnetic resonance spectroscopy (¹H-fMRS), it is possible to monitor glutamate dynamically in the activated brain areas, which has yet to be reported in schizophrenia. It was hypothesized that subjects with schizophrenia would have weaker glutamatergic responses in the anterior cingulate to a color-word Stroop Task.

AIMS:

The aim of this study was to gain insight into the health of GLU neurotransmission and the GLU-GLN cycle in SZ using a ¹H-fMRS protocol.

Methods:

Spectra were acquired from the anterior cingulate of 16 participants with schizophrenia, 16 healthy controls and 16 participants with major depressive disorder (MDD) while performing the Stroop task in a 7T magnetic resonance imaging scanner. ¹H-fMRS spectra were acquired for 20 min in which there were three 4-min blocks of cross fixation interleaved with two 4-min blocks of the Stroop paradigm.

Results:

A repeated-measures analysis of variance revealed a main effect of time for glutamate concentrations of all groups (P<0.001). The healthy control group increased glutamate concentrations in the first run of the Stroop task (P=0.006) followed by a decrease in the recovery period (P=0.007). Neither the schizophrenia (P=0.107) nor MDD (P=0.081) groups had significant glutamate changes in the first run of the task, while the schizophrenia group had a significant increase in glutamine (P=0.005). The MDD group decreased glutamate concentrations in the second run of the task (P=0.003), as did all the groups combined (P=0.003).

Conclusions:

¹H-fMRS data were successfully acquired from psychiatric subjects with schizophrenia and mood disorder using a cognitive paradigm for the first time. Future study designs should further elucidate the glutamatergic response to functional activation in schizophrenia.

In vivo effects of ketamine on glutamate-glutamine and gamma-aminobutyric acid in obsessive-compulsive disorder: Proof of concept

We previously reported the rapid and robust clinical effects of ketamine versus saline infusions in a proof-of-concept crossover trial in unmedicated adults with obsessive-compulsive disorder (OCD). This study examined the concurrent neurochemical effects of ketamine versus saline infusions using proton magnetic resonance spectroscopy ((1)H MRS) during the clinical proof-of-concept crossover trial. Levels of the inhibitory neurotransmitter gamma-aminobutyric acid (GABA) and the excitatory neurochemicals glutamate+glutamine (Glx) were acquired in the medial prefrontal cortex (MPFC), a region implicated in OCD pathology. Seventeen unmedicated OCD adults received two intravenous infusions at least 1 week apart, one of saline and one of ketamine, while lying supine in a 3.0 T GE MR scanner. The order of each infusion pair was randomized. Levels of GABA and Glx were measured in the MPFC before, during, and after each infusion and normalized to water (W). A mixed effects model found that MPFC GABA/W significantly increased over time in the ketamine compared with the saline infusion. In contrast, there were no significant differences in Glx/W between the ketamine and saline infusions. Together with earlier evidence of low cortical GABA in OCD, our findings suggest that models of OCD pathology should consider the role of GABAergic abnormalities in OCD symptomatology.

In vivo brain rosette spectroscopic imaging (RSI) with LASER excitation, constant gradient strength readout, and automated LCModel quantification for all voxels

PURPOSE

To optimize the Rosette trajectories for high-sensitivity in vivo brain spectroscopic imaging and reduced gradient demands.

METHODS

Using LASER localization, a rosette based sampling scheme for in vivo brain spectroscopic imaging data on a 3 Tesla (T) system is described. The two-dimensional (2D) and 3D rosette spectroscopic imaging (RSI) data were acquired using 20 × 20 in-plane resolution (8 × 8 mm(2) ), and 1 (2D) -18 mm (1.1 cc) or 12 (3D) -8 mm partitions (0.5 cc voxels). The performance of the RSI acquisition was compared with a conventional spectroscopic imaging (SI) sequence using LASER localization and 2D or 3D elliptical phase encoding (ePE). Quantification of the entire RSI data set was performed using an LCModel based pipeline.

RESULTS

The RSI acquisitions took 32 s for the 2D scan, and as short as 5 min for the 3D 20 × 20 × 12 scan, using a maximum gradient strength Gmax=5.8 mT/m and slew-rate Smax=45 mT/m/ms. The Bland-Altman agreement between RSI and ePE CSI, characterized by the 95% confidence interval for their difference (RSI-ePE), is within 13% of the mean (RSI+ePE)/2. Compared with the 3D ePE at the same nominal resolution, the effective RSI voxel size was three times smaller while the measured signal-to-noise ratio sensitivity, after normalization for differences in effective size, was 43% greater.

CONCLUSION

3D LASER-RSI is a fast, high-sensitivity spectroscopic imaging sequence, which can acquire medium-to-high resolution SI data in clinically acceptable scan times (5-10 min), with reduced stress on the gradient system. Magn Reson Med 76:380-390, 2016. © 2015 Wiley Periodicals, Inc.

Adaptively optimized combination (AOC) of magnetic resonance spectroscopy data from phased array coils

PURPOSE

MR spectroscopy (MRS) can benefit from multi-element coil arrays with enhanced signal-to-noise ratio (SNR). However, how to combine the MRS data in an optimized way from a multi-element coil array has been studied much less than MRI. A recently published method and routine combination methods have detrimental effects on SNR. We present herein a new method for optimal combination of multi-coil MRS data.

METHODS

Based on an analytical solution for maximizing the SNR of the combined spectrum, a new method called "adaptively optimized combination (AOC)" of MRS data from phased array coils was developed in which the inversion of the full noise correlation matrix was incorporated into the coil weighting coefficients. Simulations were carried out to demonstrate the superior performance of the proposed AOC method in various noise scenarios. Validation experiments on human subjects were performed with different voxel locations and sizes on a 3T MRI scanner using an eight-element phased array head coil.

RESULTS

Compared with a recently published method (i.e., weighting with the ratio of signal to the square of noise) and routine methods, our proposed AOC method adaptively and robustly produced significant SNR improvement in the combined spectra.

CONCLUSION

The simulation and human experiments demonstrate that the proposed AOC method represents the theoretical optimal combination of MR spectroscopic data from multi-element coil arrays. Magn Reson Med 75:2235-2244, 2016. © 2015 Wiley Periodicals, Inc.

MRS: a noninvasive window into cardiac metabolism

A well-functioning heart requires a constant supply of a balanced mixture of nutrients to be used for the production of adequate amounts of adenosine triphosphate, which is the main energy source for most cellular functions. Defects in cardiac energy metabolism are linked to several myocardial disorders. MRS can be used to study in vivo changes in cardiac metabolism noninvasively. MR techniques allow repeated measurements, so that disease progression and the response to treatment or to a lifestyle intervention can be monitored. It has also been shown that MRS can predict clinical heart failure and death. This article focuses on in vivo MRS to assess cardiac metabolism in humans and experimental animals, as experimental animals are often used to investigate the mechanisms underlying the development of metabolic diseases. Various MR techniques, such as cardiac (31) P-MRS, (1) H-MRS, hyperpolarized (13) C-MRS and Dixon MRI, are described. A short overview of current and emerging applications is given. Cardiac MRS is a promising technique for the investigation of the relationship between cardiac metabolism and cardiac disease. However, further optimization of scan time and signal-to-noise ratio is required before broad clinical application. In this respect, the ongoing development of advanced shimming algorithms, radiofrequency pulses, pulse sequences, (multichannel) detection coils, the use of hyperpolarized nuclei and scanning at higher magnetic field strengths offer future perspective for clinical applications of MRS.

Proton MRS and MRSI of the brain without water suppression

Water suppression (WS) techniques have played a vital role in the commencement and development of in vivo proton magnetic resonance spectroscopy (MRS, including spectroscopic imaging - MRSI). WS not only made in vivo proton MRS functionally available but also made its applications conveniently accessible, and it has become an indispensable tool in most of the routine applications of in vivo proton MR spectroscopy. On the other hand, WS brought forth some challenges. Therefore, various techniques of proton MRS without WS have been developed since the pioneering work in the late 1990s. After more than one and a half decades of advances in both hardware and software, non-water-suppressed proton MRS is coming to the stage of maturity and seeing increasing application in biomedical research and clinical diagnosis. In this article, we will review progress in the technical development and applications of proton MRS without WS.

Multivendor implementation and comparison of volumetric whole-brain echo-planar MR spectroscopic imaging

PURPOSE

To assess volumetric proton MR spectroscopic imaging (MRSI) of the human brain on multivendor MRI instruments.

METHODS

Echo-planar spectroscopic imaging was developed on instruments from three manufacturers, with matched specifications and acquisition protocols that accounted for differences in sampling performance, radiofrequency (RF) power, and data formats. Intersite reproducibility was evaluated for signal-normalized maps of N-acetylaspartate (NAA), creatine (Cre), and choline using phantom and human subject measurements. Comparative analyses included metrics for spectral quality, spatial coverage, and mean values in atlas-registered brain regions.

RESULTS

Intersite differences for phantom measurements were less than 1.7% for individual metabolites and less than 0.2% for ratio measurements. Spatial uniformity ranged from 79% to 91%. The human studies found differences of mean values in the temporal lobe, but good agreement in other white matter regions, with maximum differences relative to their mean of under 3.2%. For NAA/Cre, the maximum difference was 1.8%. In gray matter, a significant difference was observed for frontal lobe NAA. Primary causes of intersite differences were attributed to shim quality, B0 drift, and accuracy of RF excitation. Correlation coefficients for measurements at each site were over 0.60, indicating good reliability.

CONCLUSION

A volumetric intensity-normalized MRSI acquisition can be implemented in a comparable manner across multivendor MR instruments.

Semi-LASER 1 H MR spectroscopy at 7 Tesla in human brain: Metabolite quantification incorporating subject-specific macromolecule removal

PURPOSE

To develop an in vivo ¹ H short-echo-time semi-LASER spectroscopy protocol at 7 Tesla (T) incorporating subject-specific macromolecule removal.

METHODS

T₁ constants of the major metabolites were measured with little macromolecule contribution in seven healthy volunteers and used to optimize double inversion metabolite nulling. Spectra were acquired from parietal-occipital cortex of five healthy volunteers. Metabolite-nulled macromolecule spectra were subtracted from the metabolite spectra before fitting in the time domain with prior-knowledge templates. Absolute metabolite concentrations were determined by referencing to the water signal, following partial volume and relaxation corrections.

RESULTS

The average signal to noise ratio, N-acetylaspartate peak height divided by the baseline noise standard deviation, was 48 ± 6. T₁ constants for N-acetylaspartate, glutamate, creatine, and choline were 1.71 ± 0.15 s, 1.68 ± 0.19 s, 1.63 ± 0.10 s, and 1.41 ± 0.09 s, respectively. The optimal double inversion times for metabolite suppression were TI₁  = 2.09 s and TI₂  = 0.52 s. The coefficient of variation was less than 10% for N-acetylaspartate, creatine, choline, and myo-inositol, and less than 20% for glutamate and glutamine.

CONCLUSION

Short echo-time ¹ H semi-LASER spectroscopy at 7T incorporating subject-specific macromolecule removal yielded reproducible brain metabolite concentrations ideal for applications in disease conditions where macromolecule contributions may deviate from the norm. Magn Reson Med 74:4-12, 2015. © 2014 Wiley Periodicals, Inc.

Reliability of MRSI brain temperature mapping at 1.5 and 3 T

MRSI permits the non-invasive mapping of brain temperature in vivo, but information regarding its reliability is lacking. We obtained MRSI data from 31 healthy male volunteers [age range, 22-40 years; mean ± standard deviation (SD), 30.5 ± 5.0 years]. Eleven subjects (age range, 23-40 years; mean ± SD, 30.5 ± 5.2 years) were invited to receive four point-resolved spectroscopy MRSI scans on each of 3 days in both 1.5-T (TR/TE = 1000/144 ms) and 3-T (TR/TE = 1700/144 ms) clinical scanners; a further 20 subjects (age range, 22-40 years; mean ± SD, 30.5 ± 4.9 years) were scanned on a single occasion at 3 T. Data were fitted in the time domain to determine the water-N-acetylaspartate chemical shift difference, from which the temperature was estimated. Temperature data were analysed using a linear mixed effects model to determine variance components and systematic temperature changes during the scanning sessions. To characterise the effects of instrumental drift on apparent MRSI brain temperature, a temperature-controlled phantom was constructed and scanned on multiple occasions. Components of apparent in vivo temperature variability at 1.5 T/3 T caused by inter-subject (0.18/0.17 °C), inter-session (0.18/0.15 °C) and within-session (0.36/0.14 °C) effects, as well as voxel-to-voxel variation (0.59/0.54 °C), were determined. There was a brain cooling effect during in vivo MRSI of 0.10 °C [95% confidence interval (CI): -0.110, -0.094 °C; p < 0.001] and 0.051 °C (95% CI: -0.054, -0.048 °C; p < 0.001) per scan at 1.5 T and 3 T, respectively, whereas phantom measurements revealed minimal drift in apparent MRSI temperature relative to fibre-optic temperature measurements. The mean brain temperature at 3 T was weakly associated with aural (R = 0.55, p = 0.002) and oral (R = 0.62, p < 0.001) measurements of head temperature. In conclusion, the variability associated with MRSI brain temperature mapping was quantified. Repeatability was somewhat higher at 3 T than at 1.5 T, although subtle spatial and temporal variations in apparent temperature were demonstrated at both field strengths. Such data should assist in the efficient design of future clinical studies.

Coil combination of multichannel MRSI data at 7 T: MUSICAL

The goal of this study was to evaluate a new method of combining multi-channel (1)H MRSI data by direct use of a matching imaging scan as a reference, rather than computing sensitivity maps. Seven healthy volunteers were measured on a 7-T MR scanner using a head coil with a 32-channel array coil for receive-only and a volume coil for receive/transmit. The accuracy of prediction of the phase of the (1)H MRSI data with a fast imaging pre-scan was investigated with the volume coil. The array coil (1)H MRSI data were combined using matching imaging data as coil combination weights. The signal-to-noise ratio (SNR), spectral quality, metabolic map quality and Cramér-Rao lower bounds were then compared with the data obtained by two standard methods, i.e. using sensitivity maps and the first free induction decay (FID) data point. Additional noise decorrelation was performed to further optimize the SNR gain. The new combination method improved significantly the SNR (+29%), overall spectral quality and visual appearance of metabolic maps, and lowered the Cramér-Rao lower bounds (-34%), compared with the combination method based on the first FID data point. The results were similar to those obtained by the combination method using sensitivity maps, but the new method increased the SNR slightly (+1.7%), decreased the algorithm complexity, required no reference coil and pre-phased all spectra correctly prior to spectral processing. Noise decorrelation further increased the SNR by 13%. The proposed method is a fast, robust and simple way to improve the coil combination in (1)H MRSI of the human brain at 7 T, and could be extended to other (1)H MRSI techniques.

Combination of multichannel single-voxel MRS signals using generalized least squares

PURPOSE

To propose using the generalized least square (GLS) algorithm for combining multichannel single-voxel magnetic resonance spectroscopy (MRS) signals.

MATERIALS AND METHODS

Phantom and in vivo brain MRS experiments on a 7 T scanner equipped with a 32-channel receiver coil, as well as Monte Carlo simulations, were performed to compare the coefficient of variation (CV) of the GLS method with those of two recently reported spectral combination methods.

RESULTS

Compared to the two existing methods, the GLS method significantly reduced CV values for the simulation, phantom, and in vivo experiments.

CONCLUSION

The GLS method can lead to improved precision of peak quantification.

Methodology for improved detection of low concentration metabolites in MRS: optimised combination of signals from multi-element coil arrays

State of the art magnetic resonance imaging (MRI) scanners are generally equipped with multi-element receive coils; 16 or 32 channel coils are common. Their development has been predominant for parallel imaging to enable faster scanning. Less consideration has been given to localized magnetic resonance spectroscopy (MRS). Multinuclear studies, for example (31)P or (13)C MRS, are often conducted with a single element coil located over the region of interest. (1)H MRS studies have generally employed the same multi-element coils used for MRI, but little consideration has been given as to how the spectroscopic data from the different channels are combined. In many cases it is simply co-added with detrimental effect on the signal to noise ratio. In this study, we derive the optimum method for combining multi-coil data, namely weighting with the ratio of signal to the square of the noise. We show that provided that the noise is uncorrelated, this is the theoretical optimal combination. The method is demonstrated for in vivo proton MRS data acquired using a 32 channel receive coil at 7T in four different brain areas; left motor and right motor, occipital cortex and medial frontal cortex.

Impact of reduced k-space acquisition on pathologic detectability for volumetric MR spectroscopic imaging

PURPOSE

To assess the impact of accelerated acquisitions on the spectral quality of volumetric magnetic resonance spectroscopic imaging (MRSI) and to evaluate their ability in detecting metabolic changes with mild injury.

MATERIALS AND METHODS

The implementation of a generalized autocalibrating partially parallel acquisition (GRAPPA) method for a high-resolution whole-brain echo planar SI (3D-EPSI) sequence is first described and the spectral accuracy of the GRAPPA-EPSI method is investigated using lobar and voxel-based analyses for normal subjects and patients with mild traumatic brain injuries (mTBI). The performance of GRAPPA was compared with that of fully encoded EPSI for five datasets collected from normal subjects at the same scanning session, as well as on 45 scans (20 normal subjects and 25 mTBI patients) for which the reduced k-space sampling was simulated. For comparison, a central k-space lower-resolution 3D-EPSI acquisition was also simulated. Differences in individual metabolites and metabolite ratio distributions of the mTBI group relative to those of age-matched control subjects were statistically evaluated using analyses divided into hemispheric brain lobes and tissue types.

RESULTS

GRAPPA-EPSI with 16-minute scan time yielded robust and similar results in terms of MRSI quantitation, spectral fitting, and accuracy with that of fully sampled 3D-EPSI acquisitions and was more accurate than central k-space acquisition. Primary findings included high correlations (accuracy of 92.6%) between the GRAPPA and fully sampled results.

CONCLUSION

Although the reduced encoding method is associated with lower signal-to-noise ratio (SNR) that impacts the quality of spectral analysis, the use of the parallel imaging method can lead to the same diagnostic outcomes as the fully sampled data when using the sensitivity-limited volumetric MRSI.

Quantitative comparison of post-processing methods for reduction of frequency modulation sidebands in non-water suppression 1H MRS

Non-water suppression MRS (NWS MRS) has several advantages. First, the unsuppressed water signal can be used as internal calibration for metabolite quantification and as a reliable frequency/phase reference for retrospective motion correction. Second, it avoids the potential artifacts caused by incomplete water suppression (WS) and extra radiofrequency deposition from WS pulses. However, the frequency modulation (FM) sidebands originating from a large water signal will distort the spectrum. Among the methods proposed to solve the problems caused by FM sidebands, post-acquisition processing methods are superior in flexibility for general use compared with experimental methods. In this study, we propose two algorithms based on advanced matrix decomposition to remove the FM sidebands. These methods, the simultaneous diagonalization (QZ) algorithm and its subsequent variant, the simultaneously generalized Schur decomposition (SGSD) algorithm, were numerically evaluated using computer simulations. In addition, we quantitatively compared the performance of these methods and the modulus method in an in vitro experiment and in vivo NWS MRS against conventional WS data. Our results show that the proposed SGSD algorithm can reduce the FM sidebands to achieve superior estimation of concentration on three major metabolites. This method can be applied directly to spectra pre-acquired under various experimental conditions without modifying the acquisition sequences.

Prostate 3T-MR spectroscopic imaging without an endorectal surface coil using the MLEV-PRESS sequence

PURPOSE

The aim of this study was to determine to what extent we could identify the metabolism product peak using 3-T proton magnetic resonance spectroscopic imaging (MRSI) of the prostate gland in healthy volunteers by combining an external array coil with Malcolm Levitt composite-pulse decoupling sequence (MLEV)-point-resolved spatially localized spectroscopy (PRESS).

MATERIALS AND METHODS

MRSI data were obtained from the entire prostate gland in six healthy volunteers. The heights of the choline, citrate peaks and the standard deviation (SD) of the noise in each voxel were calculated. When the choline and/or citrate peak in a voxel exceeded 3 SD, the peak was clearly identified.

RESULTS

The clear citrate peak rate in the peripheral zone (PZ) and the central gland (CG) were 78.8 and 70.3 %, respectively. The clear choline peak rate in the PZ and the CG were 55.4 and 44.9 %, respectively. In addition, the clear peak rates for both citrate and choline in the PZ and the CG were 51.8 and 38.6 %. Therefore, in the entire prostate gland, 75.2 % had a clear citrate peak, 51.1 % had a clear choline peak, and 46.3 % had both citrate and choline peaks.

CONCLUSION

The citrate peak was clearly detected in 75.2 % of the voxels by this technique.