Evidence map›Paper›PMID 29261786›Full record

ArticlePloS one2017

RESUME: Turning an SWI acquisition into a fast qMRI protocol.

Serena Monti, Pasquale Borrelli, Enrico Tedeschi, Sirio Cocozza, Giuseppe Palma

Abstract read
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Precision Medicine in Radiomics and Radiogenomics.Journal of personalized medicine · 2022
    Article
  3. Article
  4. Observational
  5. Article
  6. Review
  7. 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.

Serena MontiIRCCS SDN, Naples, Italy.
Pasquale BorrelliIRCCS SDN, Naples, Italy.
Enrico TedeschiDepartment of Advanced Biomedical Sciences, University "Federico II", Naples, Italy.
Sirio CocozzaDepartment of Advanced Biomedical Sciences, University "Federico II", Naples, Italy.
Giuseppe PalmaInstitute of Biostructures and Bioimaging, National Research Council, Naples, Italy.ORCID http://orcid.org/0000-0002-0210-268X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Susceptibility Weighted Imaging (SWI) is a common MRI technique that exploits the magnetic susceptibility differences between the tissues to provide valuable image contrasts, both in research and clinical contexts. However, despite its increased clinical use, SWI is not intrinsically suitable for quantitation purposes. Conversely, quantitative Magnetic Resonance Imaging (qMRI) provides a way to disentangle the sources of common MR image contrasts (e.g. proton density, T1, etc.) and to measure physical parameters intrinsically related to tissue microstructure. Unfortunately, the poor signal-to-noise ratio and resolution, coupled with the long imaging time of most qMRI strategies, have hindered the integration of quantitative imaging into clinical protocols. Here we present the RElaxometry and SUsceptibility Mapping Expedient (RESUME) to show that the standard acquisition leading to a clinical SWI dataset can be easily turned into a thorough qMRI protocol at the cost of a further 50% of the SWI scan time. The R1, [Formula: see text], proton density and magnetic susceptibility maps provided by the RESUME scheme alongside the SWI reconstruction exhibit high reproducibility and accuracy, and a submillimeter resolution is proven to be compatible with a total scan time of 7 minutes.

Indexed as

AlgorithmsBrainHumansImage Processing, Computer-AssistedMagnetic Resonance ImagingNumerical Analysis, Computer-AssistedReproducibility of ResultsSignal-To-Noise Ratio

Identifiers

PMID29261786
PMCPMC5738122

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.