Evidence map›Paper›PMID 36121336›Full record

ArticleMagnetic resonance in medicine2023

The future is 2D: spectral-temporal fitting of dynamic MRS data provides exponential gains in precision over conventional approaches.

Assaf Tal

Abstract read
In one paragraph

Article in Magnetic resonance in medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Review
  2. Age dependency of neurometabolite TMagnetic resonance in medicine · 2025
    Article
  3. Stability of single-subject estimation of glutamate and GABA dynamics in concurrent fMRI-fMRS at 7 T.Proceedings of the International Society for Magnetic Resonance in Medicine ... Scientific Meeting and Exhibition. International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition · 2025
    Article
  4. Metabolite TMagnetic resonance in medicine · 2025
    Article
  5. Simultaneous Concentration and TNMR in biomedicine · 2025
    Article
  6. Article
  7. Article
  8. Model-based frequency-and-phase correction ofMagnetic resonance in medicine · 2024
    Article
  9. Article
  10. Metabolite TbioRxiv : the preprint server for biology · 2024
    Article
  11. Article
  12. Model-based frequency-and-phase correction ofbioRxiv : the preprint server for biology · 2024
    Article
  13. Article
  14. Article
  15. 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

1 author.

Assaf TalDepartment of Chemical and Biological Physics, Weizmann Institute of Science, Rehovot, Israel.ORCID 0000-0001-6718-6522

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeMany MRS paradigms produce 2D spectral-temporal datasets, including diffusion-weighted, functional, and hyperpolarized and enriched (carbon-13, deuterium) experiments. Conventionally, temporal parameters-such as T

methodsWe derived a Cramer Rao lower bound for the temporal parameters for both 1D and 2D approaches for 2 experiments: a multi-echo experiment designed to estimate metabolite T

resultsWhen peaks were spectrally distant, 2D fitting improved precision by approximately 20% relative to 1D fitting, regardless of the experiment and other parameter values. These gains increased exponentially as peaks drew closer. Dependence on temporal model parameters was weak to negligible.

conclusionOur results strongly support a 2D approach to MRS fitting where applicable, and particularly in nuclei such as hydrogen and deuterium, which exhibit substantial spectral overlap.

Indexed as

Magnetic Resonance SpectroscopyDeuteriumDiffusionDeuteriumdynamic fittingdynamic MRSmagnetic resonance spectroscopy (MRS)quantification

Identifiers

PMID36121336
PMCPMC10087547

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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.