Evidence map›Paper›PMID 39793640›Full record

ArticleNeuroImage2025

Exploring in vivo human brain metabolism at 10.5 T: Initial insights from MR spectroscopic imaging.

Lukas Hingerl, Bernhard Strasser, Simon Schmidt, Korbinian Eckstein, Guglielmo Genovese, Edward J Auerbach, Andrea Grant, Matt Waks, Andrew Wright, Philipp Lazen and 8 more

Abstract read
In one paragraph

Article in NeuroImage, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. 10.5 T In Vivo Head Imaging With Universal RF Shimming.Magnetic resonance in medicine · 2026
    Article
  2. Article
  3. Aspartate in the Brain: A Review.Neurochemical research · 2025
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

18 authors.

Lukas HingerlHigh-field MR Center HFMR, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria.
Bernhard StrasserHigh-field MR Center HFMR, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria.
Simon SchmidtCenter for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, USA.
Korbinian EcksteinThe University of Queensland, School of Information Technology and Electrical Engineering, St Lucia, Australia.
Guglielmo GenoveseCenter for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, USA.
Edward J AuerbachCenter for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, USA.
Andrea GrantCenter for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, USA.
Matt WaksCenter for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, USA.
Andrew WrightAdvanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, USA.
Philipp LazenHigh-field MR Center HFMR, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria; Department of Neurosurgery, Medical University of Vienna, Vienna, Austria.
Alireza Sadeghi-TarakamehCenter for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, USA.
Gilbert HangelHigh-field MR Center HFMR, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria; Department of Neurosurgery, Medical University of Vienna, Vienna, Austria; Christian Doppler Laboratory for MR Imaging Biomarkers, Vienna, Austria.
Fabian NiessHigh-field MR Center HFMR, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria.
Yigitcan EryamanCenter for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, USA.
Gregor AdrianyCenter for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, USA.
Gregory MetzgerCenter for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, USA.
Wolfgang BognerHigh-field MR Center HFMR, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria; Christian Doppler Laboratory for MR Imaging Biomarkers, Vienna, Austria. Electronic address: wolfgang.bogner@meduniwien.ac.at.
Małgorzata MarjańskaCenter for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, USA. Electronic address: gosia@umn.edu.

Funding

TRD4 - Ultrahigh Field Engineering and SafetyP41EB027061 · NIBIB · UNIVERSITY OF MINNESOTA · PI Mehmet Akcakaya · 2019 to 2026
$11.7M
Institutional Center Cores for Advanced NeuroimagingP30NS076408 · NINDS · UNIVERSITY OF MINNESOTA · PI UGURBIL, KAMIL · 2012 to 2020
$4.2M
Novel 10.5 T deuterium-based MRS/I method to measure brain metabolismR01EB031787 · NIBIB · UNIVERSITY OF MINNESOTA · PI Wolfgang Bogner, Malgorzata Marjanska · 2022 to 2026
$2.2M
NIBIB NIH HHS P41 EB027061NIBIB NIH HHS R01 EB031787NINDS NIH HHS P30 NS076408
6 · The paper itself

Abstract

introductionUltra-high-field magnetic resonance (MR) systems (7 T and 9.4 T) offer the ability to probe human brain metabolism with enhanced precision. Here, we present the preliminary findings from 3D MR spectroscopic imaging (MRSI) of the human brain conducted with the world's first 10.5 T whole-body MR system.

methodsEmploying a custom-built 16-channel transmit and 80-channel receive MR coil at 10.5 T, we conducted MRSI acquisitions in six healthy volunteers to map metabolic compounds in the human cerebrum in vivo. Three MRSI protocols with different matrix sizes and scan times (4.4 × 4.4 × 4.4 mm³: 10 min, 3.4 × 3.4 × 3.4 mm³: 15 min, and 2.75×2.75×2.75 mm³: 25 min) were tested. Concentric ring trajectories were utilized for time-efficient encoding of a spherical 3D k-space with ∼4 kHz spectral bandwidth. B

resultsBy combining the benefits of an ultra-high-field system with the advantages of free-induction-decay (FID-)MRSI, we present the first metabolic maps acquired at 10.5 T in the healthy human brain at both high (voxel size of 4.4³ mm³) and ultra-high (voxel size of 2.75³ mm³) isotropic spatial resolutions. Maps of 13 metabolic compounds (aspartate, choline compounds and creatine + phosphocreatine, γ-aminobutyric acid (GABA), glucose, glutamine, glutamate, glutathione, myo-inositol, scyllo-inositol, N-acetylaspartate (NAA), N-acetylaspartylglutamate (NAAG), taurine) and macromolecules were obtained individually. The spectral quality was outstanding in the parietal and occipital lobes, but lower in other brain regions such as the temporal and frontal lobes. The average total NAA (tNAA = NAA + NAAG) signal-to-noise ratio over the whole volume of interest was 12.1± 8.9 and the full width at half maximum of tNAA was 24.7± 9.6 Hz for the 2.75 × 2.75 × 2.75 mm³ resolution. The need for an increased spectral bandwidth in combination with spatio-spectral encoding imposed significant challenges on the gradient system, but the FID approach proved very robust to field inhomogeneities of ∆B DISCUSSION: These preliminary findings highlight the potential of 10.5 T MRSI as a powerful imaging tool for probing cerebral metabolism. By providing unprecedented spatial and spectral resolution, this technology could offer a unique view into the metabolic intricacies of the human brain, but further technical developments will be necessary to optimize data quality and fully leverage the capabilities of 10.5 T MRSI.

Indexed as

BrainMagnetic Resonance ImagingAdultFemaleHumansImaging, Three-DimensionalMagnetic Resonance SpectroscopyMaleYoung Adult10.5 teslaCerebral metabolismConcentric ring trajectoriesMRSISpatio-spectral encodingUltra-high-field MRI

Identifiers

PMID39793640
PMCPMC11906155

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.