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Keywords: Spectroscopy, fMRI (task based), functional MRS

We present multimodal functional MRS-fMRI-Behavioral data, which demonstrates how the E/I balance changes in the dACC during a reinforcement learning paradigm. The E/I balance decreases during rest periods between tasks, supporting a consolidation phase that is invisible to BOLD-fMRI. Additionally, we find a significant negative correlation between both GABA and glutamate, and the mean z-score of the BOLD signal from the spectroscopic voxel, during the decision-making game. We suggests that the elevation in Glu is related to cellular activity rather than neuronal activity, indicating a GABAergic activation during the task.

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Rudy Rizzo^1,2, Angeliki Stamatelatou³, Arend Heerschap³, Tom Scheenen³, and Roland Kreis^1,2
1Magnetic Resonance Methodology, Institute of Diagnostic and Interventional Neuroradiology, University of Bern, Bern, Switzerland, ²Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland, ³Department of Medical Imaging, Radboud University Medical Center, Nijmegen, Netherlands

Keywords: Spectroscopy, Data Acquisition, T2-mapping

A multi-parametric MR Spectroscopic Imaging (MRSI) experiment (Multi-Echo Single-Shot MRSI, MESS-MRSI) deploys partially sampled multi-echo trains from single readouts combined with simultaneous multi-parametric model fitting to produce metabolite-specific T₂ and concentration maps in 7min. It was tested in-vivo on a cohort of 5 subjects. Cramer-Rao Lower-Bounds (CRLBs) are used as measure of performance. The novel scheme was compared with the (i) traditional Multi-Echo Multi-Shot (MEMS) method and (ii) a truncated version of MEMS, which mimics the MESS acquisition (MESS-mocked). Results extended former findings for single voxel measurements with improvements in CRLB ranging from 17-45% for concentrations and 10-23% for T₂s.

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Steve C.N. Hui^1,2, Tao Gong^3,4, Helge J. Zöllner^1,2, Kathleen Hupfeld^1,2, Aaron Gudmundson^1,2, Yulu Song^1,2, Saipavitra Murali-Manohar^1,2, Christopher Davies-Jenkins^1,2, Georg Oeltzschner^1,2, Guangbin Wang^3,4, and Richard A. E. Edden^1,2
1Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States, ²F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States, ³Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China, ⁴Department of Radiology, Shandong University, Jinan, China

Keywords: Spectroscopy, Data Analysis, magnetic resonance spectroscopy, sLASER, PRESS, localization, aging

Recent MRS community consensus recommended sLASER over PRESS for reduced chemical-shift displacement. There is very little evidence supporting this consensus in terms of ability to reveal in vivo biochemistry. sLASER- and PRESS-localized spectra were collected in gray- and white-matter regions in 102 adult subjects (aged 20-69). sLASER showed slightly higher SNR than PRESS (by 4% on average), but improved SNR and localization did not convert into reduced variance or improved detection of metabolite-age correlations. Between-subject CVs of 13 modeled metabolites were remarkably consistent, and the pattern of metabolite-age correlations was also similar.

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Isaac M Adanyeguh¹, Pierre-Gilles Henry¹, and Dinesh K Deelchand^1
1Center for Magnetic Resonance Imaging, University of Minnesota, Minneapolis, MN, United States

Keywords: Spectroscopy, Spinal Cord

Proton magnetic resonance spectroscopy in the spinal cord is particularly challenging and motion remains one of biggest obstacles. Although several prospective motion correction techniques currently exist in the human brain, none have yet been reported in the spinal cord. Here we report prospective motion correction in the spinal cord using reduced-field-of-view 2DRF excitation. Results show than spectral quality were similar with and without motion. This study demonstrates the feasibility of prospective motion correction for spinal cord MRS.

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Keywords: Spectroscopy, High-Field MRI, Paralel Transmit and B1 shimming

We demonstrated that applying a fast implementation of an RF phase shimming method enabled the acquisition of localized MR spectra in different regions of the human brain including B1 challenging areas, such as the hippocampus and prefrontal cortex, using a commercially available pTx coil on a clinical platform at 7T.  RF efficiency was increased by ~100% cerebellum and PFC while ~50-75% for pons and hippocampus. The most favorable flip angle distributions were obtained for the cerebellum and the prefrontal cortex. Fast B1 shimming with advanced MRS methodology enables high-quality single voxel spectra at 7T using a commercially available setup. 

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Hanna Bugler^1,2,3,4, Rodrigo Berto^1,2,3,4, Roberto Souza^1,3,5, and Ashley D. Harris^2,3,4
1Biomedical Engineering Department, University of Calgary, Calgary, AB, Canada, ²Department of Radiology, University of Calgary, Calgary, AB, Canada, ³Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada, ⁴Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada, ⁵Electrical and Software Engineering Department, University of Calgary, Calgary, AB, Canada

Keywords: Spectroscopy, Machine Learning/Artificial Intelligence, Brain

Edited Magnetic Resonance Spectroscopy (Edited-MRS) is important for the quantification of ɣ-amino butyric acid (GABA) in vivo. However, during acquisition, data may suffer phase and frequency shifts, which affects the quality of the output spectrum. Frequency and phase correction (FPC) is necessary to account for these shifts, and deep learning models have obtained recent success in this task. Still, current methods do not take into consideration that MRS data is complex-valued. We propose a complex-valued convolutional neural network model for FPC. Our results showed that our model compares favorably against two recently proposed deep learning methods.

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Guodong Weng^1,2, Piotr Radojewski^1,2, and Johannes Slotboom^1,2
1Support Center for Advanced Neuroimaging (SCAN), University of Bern, Bern, Switzerland, ²Translational Imaging Center, sitem-insel, Bern, Switzerland

Keywords: Pulse Sequence Design, Spectroscopy, Spectral Editing

Changes in brain glucose occur in many neurological disorders as well as during aging. Most studies on the uptake of glucose in the brain use positron emission tomography, which requires injection of a radioactive tracer. Our study shows that ultra-high-field 1H-MRS single-shot SLOW-editing can be used to measure α-D-glucose at 5.22 ppm in vivo, and thus that α-D-glucose might have the potential to be used as a an economic radiation free tracer in the human brain.

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Chao Ma^1,2, Thibault Marin^1,2, Paul K. Han^1,2, and Georges El Fakhri^1,2
1Radiology, Massachusetts General Hospital, Boston, MA, United States, ²Radiology, Harvard Medical School, Boston, MA, United States

Keywords: Spectroscopy, Image Reconstruction, MRSI quantification

Conventional MRSI methods perform MRSI image reconstruction and spectral quantification in two separate steps. This work presents a novel direct estimation method for MRSI that reconstructs high-resolution metabolite concentration maps from undersampled k-space data, leveraging a linear tangent space alignment (LTSA) model for spectral quantification and a low-rank (LR) model for denoising. Furthermore, the proposed framework allows estimating the temporal basis functions of the LR model from the undersampled, noise-corrupted k-space data, thus eliminating the need for experiment-dependent or pre-acquired spectral training data. The performance of the proposed method was validated using numerical simulation phantom and in vivo MRSI data.

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Yudu Li^1,2, Chao Ma^3,4, Shirui Luo², Wen Jin^1,5, Ruihao Liu¹, Georges El Fakhri^3,4, Yao Li⁶, Maria Jaromin², Volodymyr Kindratenko^2,5, Brad Sutton^1,2,7,8, and Zhi-Pei Liang^1,2,5
1Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, United States, ²National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana, IL, United States, ³Radiology, Harvard Medical School, Boston, MA, United States, ⁴Radiology, Massachusetts General Hospital, Boston, MA, United States, ⁵Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, United States, ⁶School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China, ⁷Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL, United States, ⁸Carle Illinois College of Medicine, University of Illinois at Urbana-Champaign, Urbana, IL, United States

Keywords: Spectroscopy, Image Reconstruction

High-resolution MR spectroscopic imaging (MRSI) suffers from very low signal-to-noise ratio, which is often addressed using a priori information/constraints. Existing constrained reconstruction methods utilize spectral constraints in the form of spectral subspaces/manifolds, while impose spatial constraints though spatial regularization. This paper presents a novel kernel-based partial separability model for reconstruction of high-resolution of metabolite maps from noisy MRSI data. The proposed model uses spectral basis functions to absorb spectral prior and a learned kernel function to absorb spatial prior. Experimental results demonstrated very encouraging reconstruction performance.

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Keywords: Data Acquisition, Spectroscopy, MRS, GABA, 7 Tesla

Two-step editing techniques have been widely used to detect the GABA H4 signal at 3.01 ppm with the dominant creatine methyl proton signal cancelled by subtraction. However, subtraction is inherently sensitive to patient movements and system instability. In this work, a single-shot spectral editing technique is developed to detect the GABA H2 resonances at 2.28 ppm in the human brain at 7 Tesla. Although GABA H2 is partially overlapped by glutamate H4, we demonstrate that GABA-glutamate correlation originating from spectral overlap can be reduced to practically zero, therefore suppressing the overlapping effect of glutamate H4 on GABA H2 without subtraction.

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Philipp Lazen¹, Benjamin Spurny-Dworak², Wolfgang Bogner^3,4, Lukas Hingerl³, Bernhard Strasser³, Rupert Lanzenberger², Karl Rössler¹, Siegfried Trattnig^3,4,5, and Gilbert Hangel^1,3
1Department of Neurosurgery, Medical University of Vienna, Vienna, Austria, ²Division of General Psychiatry, Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria, ³High-field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria, ⁴Christian Doppler Laboratory for MR Imaging Biomarkers, Vienna, Austria, ⁵Institute for Clinical Molecular MRI, Karl Landsteiner Society, St. Pölten, Austria

Keywords: Spectroscopy, Brain

We evaluated the intra-subject stability of CRT-FID-MRSI at 7 T in a cohort of 15 volunteers. Two magnetic resonance spectroscopic imaging acquisitions were performed consecutively and metabolite concentration estimates (CEs) were calculated using internal water referencing. The resulting metabolic maps were segmented in 55 brain regions. For analysis, the CEs of both acquisitions were compared and coefficients of variations (CVs) were calculated. We saw high stability in almost all volunteers, with CVs being well below 5% in the brain regions generally associated with good data quality.

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Jodi J. Weinstein^1,2, Abigail Dalton¹, Jack Kaufman¹, In-Young Choi^3,4, Roland Kreis^5,6, and Christoph Juchem^7,8
1Department of Psychiatry and Behavioral Health, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, United States, ²New York State Psychiatric Institute and Department of Psychiatry, Columbia University Irving Medical Center, New York City, NY, United States, ³Department of Neurology, University of Kansas Medical Center, Kansas City, KS, United States, ⁴Hoglund Biomedical Imaging Center, University of Kansas Medical Center, Kansas City, KS, United States, ⁵Magnetic Resonance Methodology, Institute of Diagnostic and Interventional Neuroradiology, University of Bern, Bern, Switzerland, ⁶Translational Imaging Center, sitem-insel, Bern, Switzerland, ⁷Department of Biomedical Engineering, Columbia University School of Engineering and Applied Science, New York, NY, United States, ⁸Department of Radiology, Columbia University Irving Medical Center, New York, NY, United States

Keywords: Spectroscopy, Translational Studies

The MRS community recently established a set of expert Consensus Recommendations. To date, however, knowledge on their implementation beyond anecdotal reports is largely lacking. Here we report a preliminary assessment of the achieved dissemination and, more importantly, the level of acceptance of the established guidelines and standards by the clinical MRS research community. We compiled feedback from 22 editors-in-chief of major clinical journals, together accounting for more than 100 (>12%) of the in vivo clinical MRS publications from 2021.

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Parker L La¹, Tiffany K Bell¹, William Craig², Quynh Doan³, Miriam H Beauchamp⁴, Roger Zemek⁵, Keith O Yeates⁶, and Ashley D Harris^1
1Radiology, University of Calgary, Calgary, AB, Canada, ²University of Alberta and Stollery Children's Hospital, Edmonton, AB, Canada, ³University of British Columbia, Vancouver, BC, Canada, ⁴University of Montreal and St Justine Hospital, Montreal, QC, Canada, ⁵University of Ottawa and Children's Hospital of Eastern Ontario, Ottawa, ON, Canada, ⁶Psychology, University of Calgary, Calgary, AB, Canada

Keywords: Spectroscopy, Brain, Traumatic Brain Injury

The use of multiple sites and scanners is commonly used to increase sample size; however, this introduces unwanted variance into spectroscopy data. In this work we compare statistical co-variate techniques in combination with ComBat harmonization using data from a concussion study. We show traditional statistical methods of accounting for multi-site variance (using covariates to control for site and vendor) could result in erroneous interpretation of clinical data. Our data supports the use of ComBat harmonization and suggests how to best control for multisite data statistically.

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Keywords: Spectroscopy, Neuro, neuroscience

Investigating the relationships between morphological, functional, and metabolic changes in the brain can help reveal subtle changes caused by disease. To establish an understanding of the relationship between brain glutamate levels with cortical thickness (CT) and cerebral blood flow (CBF) in the healthy brain, magnetic resonance spectroscopy (MRS), arterial spin labeled MRI and anatomical MRI were obtained from 4 sub-divisions of the cingulate cortex. A linear mixed effects model revealed that glutamate was significantly correlated with CT (p=0.05, R²=0.30) but not with CSF (p=0.21, R²=0.17) within healthy participants. These results will help inform studies of disease or therapeutic interventions.

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Keywords: Spectroscopy, Brain

The prefrontal cortex plays a central role in controlling executive functions such as decision-making and emotional-monitoring and has thus been the subject of several ¹H-MRS studies on psychiatric illnesses. This region, however, is sensitive to motion-induced increases in linewidths due to the voxel moving away from the originally shimmed location. Here, we combined metabolite cycling (MC) with continuous prospective frequency correction to better account for frequency instabilities when performing single-voxel brain MRS at 7T. We find that MC sLASER with continuous prospective frequency correction reduces frequency instability, water linewidths, and N-acetylaspartate linewidths relative to semi-LASER acquisitions without prospective frequency correction.