Evidence map›Paper›PMID 34268821›Full record

ArticleMagnetic resonance in medicine2021

In vivo macromolecule signals in rat brain

Dunja Simicic, Veronika Rackayova, Lijing Xin, Ivan Tkáč, Tamas Borbath, Zenon Starcuk, Jana Starcukova, Bernard Lanz, Cristina Cudalbu

Abstract read
In one paragraph

Article in Magnetic resonance in medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Article
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  6. Model-based frequency-and-phase correction ofMagnetic resonance in medicine · 2024
    Article
  7. High-resolutionNMR in biomedicine · 2024
    Article
  8. Article
  9. Model-based frequency-and-phase correction ofbioRxiv : the preprint server for biology · 2024
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. In vivo macromolecule signals in rat brainMagnetic resonance in medicine · 2021
    Article
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

9 authors.

Dunja SimicicCIBM Center for Biomedical Imaging, Switzerland.ORCID 0000-0002-6600-2696
Veronika RackayovaCIBM Center for Biomedical Imaging, Switzerland.
Lijing XinCIBM Center for Biomedical Imaging, Switzerland.ORCID 0000-0002-5450-6109
Ivan TkáčCenter for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, Minnesota, USA.ORCID 0000-0001-5054-0150
Tamas BorbathHigh-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tübingen, Germany.ORCID 0000-0003-3679-2380
Zenon StarcukInstitute of Scientific Instruments, Czech Academy of Sciences, Brno, Czech Republic.ORCID 0000-0002-1218-0585
Jana StarcukovaInstitute of Scientific Instruments, Czech Academy of Sciences, Brno, Czech Republic.ORCID 0000-0003-0337-7893
Bernard LanzLaboratory for functional and metabolic imaging (LIFMET), EPFL, Lausanne, Switzerland.
Cristina CudalbuCIBM Center for Biomedical Imaging, Switzerland.

Funding

TRD4 - Ultrahigh Field Engineering and SafetyP41EB027061 · NIBIB · UNIVERSITY OF MINNESOTA · PI Gregory John Metzger · 2019 to 2026
$11.7M
Institutional Center Cores for Advanced NeuroimagingP30NS076408 · NINDS · UNIVERSITY OF MINNESOTA · PI UGURBIL, KAMIL · 2012 to 2020
$4.2M
NIBIB NIH HHS P41 EB027061NINDS NIH HHS P30 NS076408
6 · The paper itself

Abstract

purposeReliable detection and fitting of macromolecules (MM) are crucial for accurate quantification of brain short-echo time (TE)

methodsA single inversion recovery sequence combined with advanced AMARES prior knowledge was used to eliminate the metabolite residuals, fit, and parametrize 10 MM components directly from 9.4T rat brain in vivo

resultsA very stiff baseline (DKNTMN ≥ 1 ppm) in combination with a single MM spectrum led to deviations in metabolite concentrations. For some metabolites the parametrized MM showed deviations from the ground truth for all DKNTMN values. Adding prior knowledge on parametrized MM improved MM and metabolite quantification. The apparent T

conclusionModerate flexibility in the spline baseline was required for reliable quantification of real/experimental spectra based on in vivo and Monte Carlo data. Prior knowledge on parametrized MM improved MM and metabolite quantification.

Indexed as

BrainBrain ChemistryAnimalsMacromolecular SubstancesRatsMacromolecular Substances1H-MRSbaselinefittingmacromoleculesparametrizationrat brainrelaxation timesUHF

Identifiers

PMID34268821
PMCPMC8596437

What OpenQuestion holds

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Registered trials

None linked

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.