Motion correction in magnetic resonance spectroscopy

Frequency and phase correction of GABA-edited magnetic resonance spectroscopy using complex-valued convolutional neural networks

PURPOSE

To determine the significance of complex-valued inputs and complex-valued convolutions compared to real-valued inputs and real-valued convolutions in convolutional neural networks (CNNs) for frequency and phase correction (FPC) of GABA-edited magnetic resonance spectroscopy (MRS) data.

METHODS

An ablation study using simulated data was performed to determine the most effective input (real or complex) and convolution type (real or complex) to predict frequency and phase shifts in GABA-edited MEGA-PRESS data using CNNs. The best CNN model was subsequently compared using both simulated and in vivo data to two recently proposed deep learning (DL) methods for FPC of GABA-edited MRS. All methods were trained using the same experimental setup and evaluated using the signal-to-noise ratio (SNR) and linewidth of the GABA peak, choline artifact, and by visually assessing the reconstructed final difference spectrum. Statistical significance was assessed using the Wilcoxon signed rank test.

RESULTS

The ablation study showed that using complex values for the input represented by real and imaginary channels in our model input tensor, with complex convolutions was most effective for FPC. Overall, in the comparative study using simulated data, our CC-CNN model (that received complex-valued inputs with complex convolutions) outperformed the other models as evaluated by the mean absolute error.

CONCLUSION

Our results indicate that the optimal CNN configuration for GABA-edited MRS FPC uses a complex-valued input and complex convolutions. Overall, this model outperformed existing DL models.

The developmental trajectory of 1H-MRS brain metabolites from childhood to adulthood

Human brain development is ongoing throughout childhood, with for example, myelination of nerve fibers and refinement of synaptic connections continuing until early adulthood. 1H-Magnetic Resonance Spectroscopy (1H-MRS) can be used to quantify the concentrations of endogenous metabolites (e.g. glutamate and γ -aminobutyric acid (GABA)) in the human brain in vivo and so can provide valuable, tractable insight into the biochemical processes that support postnatal neurodevelopment. This can feasibly provide new insight into and aid the management of neurodevelopmental disorders by providing chemical markers of atypical development. This study aims to characterize the normative developmental trajectory of various brain metabolites, as measured by 1H-MRS from a midline posterior parietal voxel. We find significant non-linear trajectories for GABA+ (GABA plus macromolecules), Glx (glutamate + glutamine), total choline (tCho) and total creatine (tCr) concentrations. Glx and GABA+ concentrations steeply decrease across childhood, with more stable trajectories across early adulthood. tCr and tCho concentrations increase from childhood to early adulthood. Total N-acetyl aspartate (tNAA) and Myo-Inositol (mI) concentrations are relatively stable across development. Trajectories likely reflect fundamental neurodevelopmental processes (including local circuit refinement) which occur from childhood to early adulthood and can be associated with cognitive development; we find GABA+ concentrations significantly positively correlate with recognition memory scores.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSION

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

Practical considerations of diffusion-weighted MRS with ultra-strong diffusion gradients

Introduction

Diffusion-weighted magnetic resonance spectroscopy (DW-MRS) offers improved cellular specificity to microstructure-compared to water-based methods alone-but spatial resolution and SNR is severely reduced and slow-diffusing metabolites necessitate higher b-values to accurately characterize their diffusion properties. Ultra-strong gradients allow access to higher b-values per-unit time, higher SNR for a given b-value, and shorter diffusion times, but introduce additional challenges such as eddy-current artefacts, gradient non-uniformity, and mechanical vibrations.

Methods

In this work, we present initial DW-MRS data acquired on a 3T Siemens Connectom scanner equipped with ultra-strong (300 mT/m) gradients. We explore the practical issues associated with this manner of acquisition, the steps that may be taken to mitigate their impact on the data, and the potential benefits of ultra-strong gradients for DW-MRS. An in-house DW-PRESS sequence and data processing pipeline were developed to mitigate the impact of these confounds. The interaction of TE, b-value, and maximum gradient amplitude was investigated using simulations and pilot data, whereby maximum gradient amplitude was restricted. Furthermore, two DW-MRS voxels in grey and white matter were acquired using ultra-strong gradients and high b-values.

Results

Simulations suggest T2-based SNR gains that are experimentally confirmed. Ultra-strong gradient acquisitions exhibit similar artefact profiles to those of lower gradient amplitude, suggesting adequate performance of artefact mitigation strategies. Gradient field non-uniformity influenced ADC estimates by up to 4% when left uncorrected. ADC and Kurtosis estimates for tNAA, tCho, and tCr align with previously published literature.

Discussion

In conclusion, we successfully implemented acquisition and data processing strategies for ultra-strong gradient DW-MRS and results indicate that confounding effects of the strong gradient system can be ameliorated, while achieving shorter diffusion times and improved metabolite SNR.

Deuterium body array for the simultaneous measurement of hepatic and renal glucose metabolism and gastric emptying with dynamic 3D deuterium metabolic imaging at 7 T

Deuterium metabolic imaging (DMI) is a novel noninvasive method to assess tissue metabolism and organ (patho)physiology in vivo using deuterated substrates, such as [6,6'-² H₂ ]-glucose. The liver and kidneys play a central role in whole-body glucose homeostasis, and in type 2 diabetes, both hepatic and renal glucose metabolism are dysregulated. Diabetes is also associated with gastric emptying abnormalities. In this study, we developed a four-channel ² H transmit/receive body array coil for DMI in the human abdomen at 7 T and assessed its performance. In addition, the feasibility of simultaneously measuring gastric emptying, and hepatic and renal glucose uptake and metabolism with dynamic 3D DMI upon administration of deuterated glucose, was investigated. Simulated and measured B₁ ⁺ patterns were in good agreement. The intrasession variability of the natural abundance deuterated water signal in the liver and right kidney, measured in nine healthy volunteers, was 5.6% ± 0.9% and 4.9% ± 0.7%, respectively. Dynamic 3D DMI scans with oral administration of [6,6'-² H₂ ]-glucose showed similar kinetics of deuterated glucose appearance and disappearance in the liver and kidney. The measured gastric emptying half time was 80 ± 10 min, which is in good agreement with scintigraphy measurements. In conclusion, DMI with oral administration of [6,6'-² H₂ ]-glucose enables simultaneous assessment of gastric emptying and liver and kidney glucose uptake and metabolism. When applied in patients with diabetes, this approach may advance our understanding of the interplay between disturbances in liver and kidney glucose uptake and metabolism and gastric emptying, at a detail that cannot be achieved by any other method.

Magnetic resonance imaging of cardiac metabolism in heart failure: how far have we come?

As one of the highest energy consumer organs in the body, the heart requires tremendous amount of adenosine triphosphate (ATP) to maintain its continuous mechanical work. Fatty acids, glucose, and ketone bodies are the primary fuel source of the heart to generate ATP with perturbations in ATP generation possibly leading to contractile dysfunction. Cardiac metabolic imaging with magnetic resonance imaging (MRI) plays a crucial role in understanding the dynamic metabolic changes occurring in the failing heart, where the cardiac metabolism is deranged. Also, targeting and quantifying metabolic changes in vivo noninvasively is a promising approach to facilitate diagnosis, determine prognosis, and evaluate therapeutic response. Here, we summarize novel MRI techniques used for detailed investigation of cardiac metabolism in heart failure including magnetic resonance spectroscopy (MRS), hyperpolarized MRS, and chemical exchange saturation transfer based on evidence from preclinical and clinical studies and to discuss the potential clinical application in heart failure.

Does the change in glutamate to GABA ratio correlate with change in depression severity? A randomized, double-blind clinical trial

Previous proton magnetic resonance spectroscopy (¹H-MRS) studies suggest a perturbation in glutamate and/or GABA in Major Depressive Disorder (MDD). However, no studies examine the ratio of glutamate and glutamine (Glx) to GABA (Glx/GABA) as it relates to depressive symptoms, which may be more sensitive than either single metabolite. Using a within-subject design, we hypothesized that reduction in depressive symptoms correlates with reduction in Glx/GABA in the anterior cingulate cortex (ACC). The present trial is a randomized clinical trial that utilized ¹H-MRS to examine Glx/GABA before and after 8 weeks of escitalopram or placebo. Participants completed the 17-item Hamilton Depression Rating Scale (HDRS₁₇) and underwent magnetic resonance spectroscopy before and after treatment. Two GABA-edited MEGA-PRESS acquisitions were interleaved with a water unsuppressed reference scan. GABA and Glx were quantified from the average difference spectrum, with preprocessing using Gannet and spectral fitting using TARQUIN. Linear mixed models were utilized to evaluate relationships between change in HDRS₁₇ and change in Glx/GABA using a univariate linear regression model, multiple linear regression incorporating treatment type as a covariate, and Bayes Factor (BF) hypothesis testing to examine strength of evidence. No significant relationship was detected between percent change in Glx, GABA, or Glx/GABA and percent change in HDRS₁₇, regardless of treatment type. Further, MDD severity before/after treatment did not correlate with ACC Glx/GABA. In light of variable findings in the literature and lack of association in our investigation, future directions should include evaluating glutamate and glutamine individually to shed light on the underpinnings of MDD severity. Advancing Personalized Antidepressant Treatment Using PET/MRI, ClinicalTrials.gov, NCT02623205.

In vivo spectral editing of phosphorylethanolamine

PURPOSE

To demonstrate J-difference editing of phosphorylethanolamine (PE) with chemical shifts at 3.22 (PE3.22 ) and 3.98 (PE3.98 ) ppm, and compare the merits of two editing strategies.

METHODS

Density-matrix simulations of MEGA-PRESS (Mescher-Garwood PRESS) for PE were performed at TEs ranging from 80 to 200 ms in steps of 2 ms, applying 20-ms editing pulses (ON/OFF) at (1) 3.98/7.5 ppm to detect PE3.22 and (2) 3.22/7.5 ppm to detect PE3.98 . Phantom experiments were performed using a PE phantom to validate simulation results. Ten subjects were scanned using a Philips 3T MRI scanner at TEs of 90 ms and 110 ms to edit PE3.22 and PE3.98 . Osprey was used for data processing, modeling, and quantification.

RESULTS

Simulations show substantial TE modulation of the intensity and shape of the edited signals due to coupling evolution. Simulated and phantom integrals suggest that TEs of 110 ms and 90 ms were optimal for the edited detection of PE3.22 and PE3.98 , respectively. Phantom results indicated strong agreement with the simulated spectra and integrals. In vivo quantification of the PE3.22 /total creatine and PE3.98 /total creatine concentration ratio yielded values of 0.26 ± 0.04 (between-subject coefficient of variation [CV]: 15.4%) and 0.18 ± 0.04 (CV: 22.8%), respectively, at TE = 90 ms, and 0.24 ± 0.02 (CV: 8.2%) and 0.23 ± 0.04 (CV: 18.0%), respectively, at TE = 110 ms.

CONCLUSION

Simulations and in vivo MEGA-PRESS of PE demonstrate that both PE3.22 and PE3.98 are potential candidates for editing, but PE3.22 at TE = 110 ms yields lower variation across TEs.

Medial Prefrontal Cortex Glutamate Is Reduced in Schizophrenia and Moderated by Measurement Quality: A Meta-analysis of Proton Magnetic Resonance Spectroscopy Studies

BACKGROUND

Magnetic resonance spectroscopy studies measuring brain glutamate separately from glutamine are helping elucidate schizophrenia pathophysiology. An expanded literature and improved methodologies motivate an updated meta-analysis examining effects of measurement quality and other moderating factors in characterizing abnormal glutamate levels in schizophrenia.

METHODS

Searching previous meta-analyses and the MEDLINE database identified 83 proton magnetic resonance spectroscopy datasets published through March 25, 2020. Three quality metrics were extracted-Cramér-Rao lower bound (CRLB), line width, and coefficient of variation. Pooled effect sizes (Hedges' g) were calculated with random-effects, inverse variance-weighted models. Moderator analyses were conducted using quality metrics, field strength, echo time, medication, age, and stage of illness.

RESULTS

Across 36 datasets (2086 participants), medial prefrontal cortex glutamate was significantly reduced in patients (g = -0.19, confidence interval [CI] = -0.07 to -0.32). CRLB and coefficient of variation quality subgroups significantly moderated this effect. Glutamate was significantly more reduced in studies with lower CRLB or coefficient of variation (g = -0.44, CI = -0.29 to -0.60, and g = -0.43, CI = -0.29 to -0.57, respectively). Studies using echo time ≤20 ms also showed significantly greater reduction in glutamate (g = -0.41, CI = -0.26 to -0.55). Across 11 hippocampal datasets, group differences and moderator effects were nonsignificant. Group effects in thalamus and dorsolateral prefrontal cortex were also nonsignificant.

CONCLUSIONS

High-quality measurements reveal consistently reduced medial prefrontal cortex glutamate in schizophrenia. Stricter CRLB criteria and reduced nuisance variance may increase the sensitivity of future studies examining additional regions and the pathophysiological significance of abnormal glutamate levels in schizophrenia.

Comparison of methods for spectral alignment and signal modelling of GABA-edited MR spectroscopy data

Many methods exist for aligning and quantifying magnetic resonance spectroscopy (MRS) data to measure in vivo γ-aminobutyric acid (GABA). Research comparing the performance of these methods is scarce partly due to the lack of ground-truth measurements. The concentration of GABA is approximately two times higher in grey matter than in white matter. Here we use the proportion of grey matter within the MRS voxel as a proxy for ground-truth GABA concentration to compare the performance of four spectral alignment methods (i.e., retrospective frequency and phase drift correction) and six GABA signal modelling methods. We analyse a diverse dataset of 432 MEGA-PRESS scans targeting multiple brain regions and find that alignment to the creatine (Cr) signal produces GABA+ estimates that account for approximately twice as much of the variance in grey matter as the next best performing alignment method. Further, Cr alignment was the most robust, producing the fewest outliers. By contrast, all signal modelling methods, except for the single-Lorentzian model, performed similarly well. Our results suggest that variability in performance is primarily caused by differences in the zero-order phase estimated by each alignment method, rather than frequency, resulting from first-order phase offsets within subspectra. These results provide support for Cr alignment as the optimal method of processing MEGA-PRESS to quantify GABA. However, more broadly, they demonstrate a method of benchmarking quantification of in vivo metabolite concentration from other MRS sequences.

Prospective frequency and motion correction for edited 1H magnetic resonance spectroscopy

The major inhibitory neurotransmitter gamma-aminobutyric acid (GABA) and the dominant antioxidant glutathione (GSH) both play a crucial role in brain functioning and are involved in several neurodegenerative and psychiatric diseases. Magnetic resonance spectroscopy (MRS) is a unique way to measure these neurometabolites non-invasively, but the measurement is highly sensitive to head movements, and especially in specific patient groups, motion stabilization in MRS could be valuable. Conventional MRS is acquired at relatively short echo times (TE), however, for unambiguous detection of GABA and GSH, spectral editing techniques are typically used. These depend on longer TEs and use frequency selective spectral editing pulses to separate the low-intensity peaks of GABA and GSH from overlapping resonances, but results in further increased motion sensitivity. Low-intensity metabolite peaks are usually edited one-by-one, however, simultaneous editing of multiple metabolites can be achieved using a Hadamard scheme, resulting in a substantial reduction in scan time. To investigate and correct for motion sensitivity in both conventional short-TE MRS (PRESS) and edited MRS (HERMES), we implemented a navigator-based prospective motion correction strategy including reacquisition of corrupted data. PRESS and HERMES spectra were acquired without motion, with motion with correction (repeated twice), and with motion without correction. Results indicate that when sufficient retrospective outlier removal is used, no significant differences in concentration and spectral quality were observed between motion conditions, even without prospective correction. HERMES spectral editing data showed to be more sensitive to motion, as significant differences in metabolite estimates and variability of spectral quality measures were observed for tCr, GABA+ and GSH when only retrospective outlier removal was applied. When using both prospective and retrospective correction, spectral quality was improved to almost the level of the no-motion acquisition. No differences in metabolite ratios for GABA and GSH could be observed when using motion correction. In conclusion, edited MRS showed to be more prone to motion artifacts, and prospective motion correction can restore most of the spectral quality in both conventional and edited MRS.

Correcting frequency and phase offsets in MRS data using robust spectral registration

An algorithm for retrospective correction of frequency and phase offsets in MRS data is presented. The algorithm, termed robust spectral registration (rSR), contains a set of subroutines designed to robustly align individual transients in a given dataset even in cases of significant frequency and phase offsets or unstable lipid contamination and residual water signals. Data acquired by complex multiplexed editing approaches with distinct subspectral profiles are also accurately aligned. Automated removal of unstable lipid contamination and residual water signals is applied first, when needed. Frequency and phase offsets are corrected in the time domain by aligning each transient to a weighted average reference in a statistically optimal order using nonlinear least-squares optimization. The alignment of subspectra in edited datasets is performed using an approach that specifically targets subtraction artifacts in the frequency domain. Weighted averaging is then used for signal averaging to down-weight poorer-quality transients. Algorithm performance was assessed on one simulated and 67 in vivo pediatric GABA-/GSH-edited HERMES datasets and compared with the performance of a multistep correction method previously developed for aligning HERMES data. The performance of the novel approach was quantitatively assessed by comparing the estimated frequency/phase offsets against the known values for the simulated dataset or by examining the presence of subtraction artifacts in the in vivo data. Spectral quality was improved following robust alignment, especially in cases of significant spectral distortion. rSR reduced more subtraction artifacts than the multistep method in 64% of the GABA difference spectra and 75% of the GSH difference spectra. rSR overcomes the major challenges of frequency and phase correction.