Evidence map›Paper›PMID 27648165›Full record

ArticleWorld journal of radiology2016

Peripheral nerve imaging: Not only cross-sectional area.

Alberto Stefano Tagliafico

Abstract readEditorial
In one paragraph

Article in World journal of radiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Clinical Application of Ultra-High-Frequency Ultrasound.Journal of personalized medicine · 2022
    Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. 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.

Alberto Stefano TagliaficoAlberto Stefano Tagliafico, Department of Experimental Medicine, DIMES, Institute of Anatomy, University of Genova, 16132 Genova, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Peripheral nerve imaging is recognized as a complement to clinical and neurophysiological assessment in the evaluation of peripheral nerves with the ability to impact patient management, even for small and difficult nerves. The European Society of Musculoskeletal Radiology, suggest to use ultrasound (US) for nerve evaluation due to the fact that, in sever anatomical area, magnetic resonance imaging is not able to give additional informations. US could be considered the first-choice approach for the assessment of peripheral nerves. The relative drawback of peripheral nerve US is the long learning curve and the deep anatomic competence to evaluate even small nerves. In the recent years, the role of US in peripheral nerve evaluation has been widened. In the past, nerve US was mainly used to assess nerve-cross sectional area, but now more advanced measurements and considerations are desirable and can boost the role of peripheral nerve US. Nerve echotexture evaluation was defined in 2010: The ratio between the hypoechoic and hyperechoic areas of peripheral nerves on US was called "nerve density". For evaluation of patients who have peripheral neuropathies, the role of peripheral nerve is US wider than simple cross-sectional area evaluation. Quantitative measurements describing the internal fascicular echotexture of peripheral nerves introduce the concept of considering US as a possible quantitative imaging biomarker technique. The potential of nerve US has started to be uncovered. It seems clear that only cross-sectional area measurement is no more sufficient for a comprehensive US evaluation of peripheral nerves.

Indexed as

Fascicular ratioImagingMagnetic resonance imagingNerve densityUltrasound

Identifiers

PMID27648165
PMCPMC5002502

What OpenQuestion holds

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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.