Evidence map›Paper›PMID 31321823›Full record

ArticleMagnetic resonance in medicine2019

Robust 3D Bloch-Siegert based

Nadège Corbin, Julio Acosta-Cabronero, Shaihan J Malik, Martina F Callaghan

Abstract read
In one paragraph

Article in Magnetic resonance in medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. BMagnetic resonance in medicine · 2023
    Article
  5. Article
  6. Article
  7. Article
  8. Imperfect spoiling in variable flip angle TMagnetic resonance in medicine · 2021
    Article
  9. Robust 3D Bloch-Siegert basedMagnetic resonance in medicine · 2019
    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

4 authors.

Nadège CorbinWellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom.ORCID 0000-0003-3296-4544
Julio Acosta-CabroneroWellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom.ORCID 0000-0003-1174-5983
Shaihan J MalikSchool of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.ORCID 0000-0001-8925-9032
Martina F CallaghanWellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom.ORCID 0000-0003-0374-1659

Funding

Medical Research Council MR/R000050/1
6 · The paper itself

Abstract

purposeQuantitative MRI applications, such as mapping the T THEORY AND

methodsIt is shown here by means of simulation and experiments that the amplitude of the error depends on MR pulse sequence parameters, such as repetition time and radiofrequency spoiling increment, but more problematically, on the intrinsic properties, T

resultsIn line with simulations, phantom and in vivo experiments confirmed that the general linear model-based method removed the dependency on tissue properties and pulse sequence settings.

conclusionThe general linear model-based method is recommended as a more accurate approach to BSS-based

Indexed as

Echo-Planar ImagingMagnetic Resonance ImagingAdultAlgorithmsFemaleHumansImage Interpretation, Computer-AssistedImage Processing, Computer-AssistedImaging, Three-DimensionalLinear ModelsMaleModels, TheoreticalMotionPhantoms, ImagingRadio WavesReproducibility of ResultsBloch-Siegert shiftGLMinterleaved acquisitionmulti-echo readoutRF spoiling

Identifiers

PMID31321823
PMCPMC6771691

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.