Keywords: Spectroscopy, Spectroscopy, Machine Learning/Artificial Intelligence, Artifacts, Data Processing, Software Tools, Simulations, Brain, Pediatric

Motivation: GABA-edited MRS suffers from data quality challenges due to its low signal to noise ratio (SNR). 

Goal(s): We propose an automated labeling algorithm for transient quality and a dual-domain deep learning model for filtering spectra transients based on quality.  

Approach: We trained our model with simulated data containing commonly occurring artifacts labelled with our continuous automated labelling algorithm which ranges from –1 (poor quality) to +1 (good quality). We subsequently evaluated our model’s performance by removing (filtering) poor quality transients corresponding to quality values less than 0. 

Results: Our model outperformed qualitatively simple averaging using all collected transients for 70-80% of scans.

Impact: Our model can successfully assign a continuous quality score between –1 (poor) and +1 (good) to GABA-edited MRS difference data (i.e., a single ON-OFF edit pair) which when used for filtering, improves MRS quality metrics compared to simple transient averaging.   

Keywords: Spectroscopy, Spectroscopy, MRSI, Acquisition Delay, FID-MRSI, Ultra-high field, Preclinical, Rat

Motivation: ¹H Free-Induction Decay (FID) MRSI is limited by the acquisition delay (AD) between the RF excitation pulse and the FID signal. N initial data points are thus lost.

Goal(s): Our goal was to evaluate the consistency of the Backward Linear Prediction (BLP) auto-regressive reconstruction method to recover the lost FID data points.

Approach: In-vivo rat data were used to investigate the impact of the BLP methodology in a cut-and-recover approach; further Monte-Carlo simulations were used to identify the method validity limit.

Results: In-vivo and Monte-Carlo results highlighted the consistency of the BLP methodology for realistic FID reconstruction ranges.

Impact: Focusing on metabolites of interest, no significant variations of brain map concentrations have been detected between original FID acquisitions and BLP reconstruction outcomes between AD=1.3ms and AD=0.708ms. Moreover, Monte Carlo simulations showed good quantification reliability until AD=2.7 ms.

Keywords: Spectroscopy, Spectroscopy, MRSI, UHF, Compressed Sensing

Motivation: Preclinical Magnetic Resonance Spectroscopic Imaging offers valuable spatial information about metabolite content in the rodent brain, but is subjected to low signal-to-noise ratio and long acquisition time.

Goal(s): Our goal was to accelerate preclinical ¹H-MRSI by implementing and validating compressed sensing acceleration schemes to enable accurate acquisitions under 10 minutes.

Approach: Free Induction Decay MRSI sets were acquired on the rodent brain using compressed sensing with different acceleration factors and k-space center acquired volumes.

Results: Metabolic maps and regional differences were preserved with higher acceleration factors, going from 13 minutes to 6.5 minutes acquisition and lower.

Impact: 1H-MRSI using compressed sensing, with its achieved 6.5 minutes acquisition, could be used for effective and reliable transversal metabolic studies of neurodegenerative diseases within preclinical models, such as the bile duct ligation rat model for hepatic encephalopathy. 

Keywords: Spectroscopy, Metabolism, GABA, Spectral editing, MRSI

Motivation: Developed initially for 7T scanners, the widespread inaccessibility of such MRI systems underscores the urgent need to adapt SLOW-editing for more commonly available 3T field strengths.

Goal(s): Our primary goal is to detect metabolites like 2HG, GABA, and Glx using SLOW-editing at 3T, effectively addressing water/lipid suppression challenge.

Approach: We utilized symmetric and asymmetric CHEmical-shifted selective Adiabatic Pulses (CHEAP) in conjunction with a 3D Echo-Planar Spectroscopic Imaging (EPSI) readout sequence.

Results: Our investigations confirm the feasibility of employing SLOW-editing in conjunction with the EPSI sequence for spectral editing of GABA+ and Glx, validated through in vitro and in vivo experiments.

Impact: This work demonstrates that SLOW-EPSI can be employed for spectral editing of low concentration metabolites, including 2HG, GABA and Glx, on a 3T MR scanner for 3D/whole-brain MRSI.

Keywords: High-Field MRI, Spectroscopy, Downfield, Human brain

Motivation: Downfield (DF) MR spectroscopic imaging (MRSI) is a promising new metabolic imaging technique that has previously been demonstrated in the human brain at 3T. This abstract describes initial results of 3D DF-MRSI at 7T.

Goal(s): To implement and test 3D DF-MRSI at 7T.

Approach: The 3D DF-MRSI pulse sequence was adapted for 7T and tested on 4 healthy volunteers.

Results: High-field DF-MRSI with 0.7 mm³ nominal voxel resolution is feasible. Concentration and uncertainty estimates for the 9 downfield peaks and combined amide resonances from selected voxels were not significantly different, except for DF6.83 which was significantly lower in the CSO than DLPFC (p=0.007).

Impact: High-field DF-MRSI should now be able to spatially map the exchangeable protons in human brain within clinically acceptable times and accuracy to be used in future studies of brain tumors or other neuropathological disorders.

Keywords: Spectroscopy, Brain, MRSI

Motivation: To provide a metabolic reference atlas for brain metabolite concentrations. 

Goal(s): Derive regional metabolite concentration estimates from the human brain. 

Approach: Brain 1H MRSI data were acquired from 10 healthy controls and quantitative metabolite maps were combined via transformation into MNI space to derive median metabolite maps. Regional metabolite concentration estimates were derived. 

Results: Brain metabolite maps and regional concentrations for 12 human brain metabolites have been derived. 

Impact: A reference standard for metabolic brain MRI was established. 

Keywords: Spectroscopy, Spectroscopy

Motivation: The study addresses a gap in literature concerning the impact of spectral linewidth and lineshape differences on GABA+ estimates.

Goal(s): To assess the degree to which differences in linewidth/lineshape may confound GABA+ estimates.

Approach: In-vivo GABA+-edited spectra (N=222) were quantified with six modelling algorithms after applying varying degrees of Lorentzian and Gaussian linebroadening.

Results: Most algorithms showed strong negative associations between amount of Lorentzian linebroadening and GABA+ estimate (2-5% per Hz LB), consistently across datasets. Gaussian linebroadening showed contrasting, substantially weaker associations.
In functional applications and cases of differing T2 relaxation between regions or subject groups, these results indicate a potentially significant confound.

Impact: Comparing metabolite concentration estimates across different anatomical regions, subject groups or experimental conditions requires appropriate handling of differences in linewidth and linebroadening mechanisms. We demonstrate that several modelling algorithms have linebroadening biases, differing by lineshape, that may confound findings.

Keywords: Spectroscopy, Spectroscopy

Motivation: Preprocessing of MRS data is important in order to improve the spectral quality.

Goal(s): Here we propose a novel approach to simultaneously correct for frequency and phase drifts using cross-correlation technique.

Approach: Random frequency and phase offsets were added to a previously acquired STEAM human data at 7T at two different noise levels.

Results: Results show that the proposed technique can accurately correct for both small and large frequency (<50 Hz) and phase drifts (±40 deg) even at low SNR levels. The technique was successfully demonstrated in a noisy MRS dataset acquired from a small volume-of-interest in the mouse brain.

Impact: A fast and robust technique which accurately correct for both small and large frequency and phase shifts in MRS data.

Keywords: Spectroscopy, New Signal Preparation Schemes, Magnetic Resonance Spectroscopy, Macromolecules

Motivation: A new water suppression module optimized for both macromolecule detection and short repetition time sequences such as magnetic resonance spectroscopic imaging.

Goal(s): To have an efficient, flexible, water suppression algorithm where macromolecules can be measured.

Approach: Single voxel localization by adiabatic selective refocusing (semi-LASER) measurement of macromolecules were conducted in the prefrontal cortex, posterior frontal (PFL) and occipital lobes. Both VAPOR and the customizable water suppression (COWS) algorithm were performed for each experiment.

Results: Both WS methods performed well with residual water signals below the 2.01-ppm NAA singlet signals. COWS demonstrated better water suppression than VAPOR overall, especially in the PFL.

Impact: A new customizable water suppression algorithm, COWS, was tested in vivo for improved efficiency and speed when compared to the gold standard (VAPOR).

Keywords: Spectroscopy, Brain, 7T, Neuro, MRSI, Reproducibility

Motivation: 1H FID-CRT-MRSI at 7T is a promising approach for non-invasive quantification of metabolic processes in the brain. Its medium-term reproducibility has never been investigated even though it is a requirement for many potential study setups.

Goal(s): To evaluate the intersession reproducibility of 1H FID-CRT-MRSI at 7T.

Approach: We calculated metabolite concentration estimates in 55 brain regions for two measurement sessions one week apart, and determined coefficients of variations between them.

Results: We found good overall reproducibility, with CVs ranging from 7.5% to 12% for different brain regions, and concentration estimates matching our previous work.

Impact: We established good reproducibility of FID-CRT-MRSI at 7T, enabling longitudinal study setups e.g. for disease monitoring. Another potential follow-up of this work may be tracking the intra-day metabolite level variations in the brain in a non-invasive way.

Keywords: Spectroscopy, Spectroscopy

Motivation: NAD⁺ and tryptophan are important in energy metabolism, DNA repair, mitochondrial function, and aging. Both have recently been observed in brain at 7T, but observation at 3T is more challenging and has not been shown previously.

Goal(s): To detect NAD⁺ and tryptophan at 3T in brain in a clinically feasible scan time less than 5 minutes.

Approach: A single slice spectroscopy sequence with spectrally selective excitation was developed and optimized, allowing high sensitivity acquisition.

Results: The H2 (9.3 ppm) and H6 (9.1 ppm) peaks of NAD⁺ and the indole (10.1 ppm) peak of tryptophan are both unambiguously observed in four healthy subjects.

Impact: The ability to identify NAD+ and tryptophan at 3T in less than 5 minutes has the potential to significantly enhance the adoption of this method as part of existing neuroimaging protocols.

Keywords: Spectroscopy, High-Field MRI

Motivation: Hepatic choline-containing compounds (CCC) are an important biomarker of metabolic health.

Goal(s): The aim of this work is to measure the concentration of fat and choline-containing compounds in the liver using water-suppression cycled (WSC) and water suppressed (WS) spectroscopy at 7T.

Approach: Livers of seven healthy volunteers were scanned using water-suppression cycling and the results were compared with standard water-suppressed acquisitions.

Results: Similar concentrations of CCC were reported for both techniques, with WSC providing somewhat narrower line widths. Hepatic fat fractions were also very close using each method validating WSC as a method for use at 7T.

Impact: Frequency-aligned spectra from water-suppression cycled acquisitions enable the quantification of low-concentration metabolites in vivo at 7T.

Keywords: Spectroscopy, High-Field MRI, Metabolism, Neuro

Motivation: 7T MRI is adversely affected by inhomogeneity in the B₁ transmit field. In MRSI applications, this can manifest as spatial variability in water-suppression and signal excitation, which may adversely affect quantification. 

Goal(s): To use B₁⁺ shimming to decrease the inhomogeneity of the transmit field and improve water suppression and metabolite quantification in RS-COKE MRSI. 

Approach: B₁⁺ shim weights for all RF pulses were optimised using magnitude least-squares and data compared with a circularly polarised mode acquisition. 

Results: Metabolite quantification showed greater consistency, lower error estimates and improved water-suppression efficiency, in some subjects, when B₁⁺ shimming was applied to the RS-COKE MRSI sequence.

Impact: The use of B₁⁺ shimming in RS-COKE MRSI improves the quantification of metabolite concentrations in some subjects. This increased robustness will allow for its application to patient populations in future clinical research.

Keywords: Spectroscopy, Spectroscopy

Motivation: Nuisance signal contamination and challenges associated with implementation involving advanced RF pulses and sequence hinder clinical adoption. Simplified sequence implementation and dissemination are crucial for community-driven advancement and vendor support.

Goal(s): Our goal is to integrate CHEmical-shift selective Adiabatic refocusing Pulses(CHEAP) on the Philips platform via Pulseq open-source platform, creating advanced MRSI sequences that refine metabolite analysis by minimizing unwanted signals.

Approach: Integrating chemically selective adiabatic 2𝜋-refocus pulses in Pulseq achieved optimal spectrum coverage, reducing interference from residual water and lipid signals.

Results: Implementing the CHEAP sequence significantly mitigated interference from residual water and lipid signals, demonstrating its potential for advancing MRSI.

Impact: The implementation of CHEAP sequence via Pulseq promises a standardized, shareable method, fostering collaboration and enabling precise metabolic studies. This advancement in MRS techniques may significantly improve reproducibility across sites and enhance capacity for metabolic profiling in health and disease.

Keywords: Spectroscopy, Brain, chemical shift displacement error

Motivation: Chemical shift displacement error (CSDE) and within-voxel saturation (WVS) lead to significant spatial displacement of the MRS voxel from the prescribed region and to overestimation of metabolite concentrations. 

Goal(s): To compare prospective and retrospective corrections for severe CSDE+WVS observed in standard 3T GE PRESS data. 

Approach: Prospective corrections utilize (a) removal of OVS saturation bands and (b) over-prescription of the shifted water voxel at data acquisition. Retrospective correction relies on Gasparovic’s equation and re-scaling of metabolite concentrations by the water vs. metabolite volume ratio. 

Results: Corrected concentrations agree with literature. Both corrections are applicable in multi-centre studies and laboratories with limited technical support. 

Impact: Chemical shift displacement error (CSDE) and within-voxel saturation (WVS) observed in standard 3T GE PRESS data can be corrected prospectively and retrospectively relative to data acquisition. These solutions are relevant to multi-centre studies and laboratories with limited pulse-sequence technical support.

Keywords: Spectroscopy, Spectroscopy, 3D-FID-CRT-MRSI, 3T and 7T, Longitudinal Reproducibility, High-Field MRI, Ultrahigh-Field MRI, Magnetic Resonance Spectroscopy Imaging

Motivation: A direct comparison of the longitudinal reproducibility of 3D FID-CRT-MRSI across 3T and 7T has not been performed.

Goal(s): The aim was to determine the consistency of MRSI across these two field strengths in different brain regions.

Approach: The same subjects were scanned twice within a week at both fields and intra-subject and inter-subject Coefficients of Variation (CV%) for three metabolite ratios in different brain regions were calculated.

Results: The study found high reproducibility (CVs for most ROIs <10%) for both fields. 3T can provide sufficiently reproducible results by using larger voxel sizes and shorter measurement times.

Impact: The results will impact researchers and clinicians using MRSI, providing them with a reproducible technique at a clinical field strength of 3Tand7T and can be a method for those focusing on larger brain regions or longitudinal monitoring of metabolite changes.