Evidence map›Paper›PMID 38265152›Full record

ArticleMagnetic resonance in medicine2024

Universal dynamic fitting of magnetic resonance spectroscopy.

William T Clarke, Clémence Ligneul, Michiel Cottaar, I Betina Ip, Saad Jbabdi

Abstract read
In one paragraph

Article in Magnetic resonance in medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Review
  2. Article
  3. Age dependency of neurometabolite TMagnetic resonance in medicine · 2025
    Article
  4. Article
  5. Metabolite TMagnetic resonance in medicine · 2025
    Article
  6. Simultaneous Concentration and TNMR in biomedicine · 2025
    Article
  7. Article
  8. Article
  9. Model-based frequency-and-phase correction ofMagnetic resonance in medicine · 2024
    Article
  10. Article
  11. Metabolite TbioRxiv : the preprint server for biology · 2024
    Article
  12. Article
  13. Model-based frequency-and-phase correction ofbioRxiv : the preprint server for biology · 2024
    Article
  14. 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

5 authors.

William T ClarkeWellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.ORCID 0000-0001-7159-7025
Clémence LigneulWellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.ORCID 0000-0001-5673-3009
Michiel CottaarWellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.ORCID 0000-0003-4679-7724
I Betina IpWellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.ORCID 0000-0003-3544-0711
Saad JbabdiWellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.ORCID 0000-0003-3234-5639

Funding

Medical Research Council MR/V034723/1Royal Society Dorothy Hodgkin Fellowship DHF∖R1∖201141Wellcome Trust 203139Wellcome Trust 203139/A/16/ZWellcome Trust 203139/Z/16/ZWellcome Trust 215573Wellcome Trust 215573/Z/19/ZWellcome Trust 221933Wellcome Trust 221933/Z/20/ZWellcome Trust 225924Wellcome Trust 225924/Z/22/Z
6 · The paper itself

Abstract

purposeDynamic (2D) MRS is a collection of techniques where acquisitions of spectra are repeated under varying experimental or physiological conditions. Dynamic MRS comprises a rich set of contrasts, including diffusion-weighted, relaxation-weighted, functional, edited, or hyperpolarized spectroscopy, leading to quantitative insights into multiple physiological or microstructural processes. Conventional approaches to dynamic MRS analysis ignore the shared information between spectra, and instead proceed by independently fitting noisy individual spectra before modeling temporal changes in the parameters. Here, we propose a universal dynamic MRS toolbox which allows simultaneous fitting of dynamic spectra of arbitrary type.

methodsA simple user-interface allows information to be shared and precisely modeled across spectra to make inferences on both spectral and dynamic processes. We demonstrate and thoroughly evaluate our approach in three types of dynamic MRS techniques. Simulations of functional and edited MRS are used to demonstrate the advantages of dynamic fitting.

resultsAnalysis of synthetic functional

conclusionA toolbox for generalized and universal fitting of dynamic, interrelated MR spectra has been released and validated. The toolbox is shared as a fully open-source software with comprehensive documentation, example data, and tutorials.

Indexed as

Contrast MediaSoftwareDiffusionMagnetic Resonance SpectroscopyUncertaintyContrast MediadMRSedited‐MRSfMRSMRSspectroscopy

Identifiers

PMID38265152
PMCPMC7616727

What OpenQuestion holds

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LicenceCC BY
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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.