Evidence map›Paper›PMID 30159792›Full record

ReviewCurrent gastroenterology reports2018

Imaging of Hepatic Fibrosis.

Rishi Philip Mathew, Sudhakar Kundapur Venkatesh

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current gastroenterology reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
3.6field-weighted citation impact, top 7% of its field
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

12 citing papers in PubMed, 36 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Article
  6. Article
  7. Using MR elastography to assess portal hypertension and response to beta-blockers in patients with cirrhosis.Liver international : official journal of the International Association for the Study of the Liver · 2021
    Article
  8. Article
  9. Review
  10. Review
  11. Updates on Imaging of Liver Tumors.Current oncology reports · 2020
    Review
  12. 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

2 authors at 1 institution in 1 country.

Rishi Philip MathewDepartment of Radiology, Mayo Clinic, Mayo Clinic College of Medicine, 200, First Street SW, Rochester, MN, 55905, USA.
Sudhakar Kundapur VenkateshDepartment of Radiology, Mayo Clinic, Mayo Clinic College of Medicine, 200, First Street SW, Rochester, MN, 55905, USA. venkatesh.sudhakar@mayo.edu.
Mayo Clinic · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purpose of reviewThe purpose of this review is to discuss the current imaging techniques for non-invasive assessment of liver fibrosis (LF). RECENT

findingsElastography-based techniques are the most widely used imaging methods for the evaluation of LF. Currently, MR elastography (MRE) is the most accurate non-invasive method for detection and staging of LF. Ultrasound-based vibration-controlled transient elastography (VCTE) is the most widely used as it can be easily performed at the point of care but has technical limitations especially in the obese. Innovations and technical improvements continue to evolve in elastography for improving accuracy and avoiding misinterpretation from confounding factors. Other imaging methods including diffusion-weighted imaging (DWI), hepatocellular contrast-enhanced (HCE) MRI, T1 relaxometry, T1ρ imaging, textural analysis, liver surface nodularity, susceptibility-weighted imaging, and perfusion imaging are promising but need further evaluation and clinical validation. MRE is the most accurate imaging technique for assessment of LF.

Indexed as

Elasticity Imaging TechniquesHumansLiver CirrhosisMagnetic Resonance ImagingFunctional imagingLiver fibrosisMagnetic resonance elastography

Identifiers

PMID30159792
OpenAlexW2889524820

What OpenQuestion holds

Textmetadata
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.