Evidence map›Paper›PMID 34983091›Full record

ReviewKorean journal of radiology2022

Quantitative Evaluation of Hepatic Steatosis Using Advanced Imaging Techniques: Focusing on New Quantitative Ultrasound Techniques.

Junghoan Park, Jeong Min Lee, Gunwoo Lee, Sun Kyung Jeon, Ijin Joo

Abstract readReview
In one paragraph

Review in Korean journal of radiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed, 1 pooled it
–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

44 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  7. Article
  8. Imaging Evaluation for Steatotic Liver Disease.Korean journal of radiology · 2026
    Review
  9. Observational
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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.

Junghoan ParkDepartment of Radiology, Seoul National University Hospital, Seoul, Korea.ORCID 0000-0002-0636-3756
Jeong Min LeeDepartment of Radiology, Seoul National University Hospital, Seoul, Korea.ORCID 0000-0003-0561-8777
Gunwoo LeeUltrasound R&D 2 Group, Health & Medical Equipment Business, Samsung Electronics Co., Ltd., Seoul, Korea.ORCID 0000-0002-7826-0035
Sun Kyung JeonDepartment of Radiology, Seoul National University Hospital, Seoul, Korea.ORCID 0000-0002-8991-3986
Ijin JooDepartment of Radiology, Seoul National University Hospital, Seoul, Korea.ORCID 0000-0002-1341-4072

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nonalcoholic fatty liver disease, characterized by excessive accumulation of fat in the liver, is the most common chronic liver disease worldwide. The current standard for the detection of hepatic steatosis is liver biopsy; however, it is limited by invasiveness and sampling errors. Accordingly, MR spectroscopy and proton density fat fraction obtained with MRI have been accepted as non-invasive modalities for quantifying hepatic steatosis. Recently, various quantitative ultrasonography techniques have been developed and validated for the quantification of hepatic steatosis. These techniques measure various acoustic parameters, including attenuation coefficient, backscatter coefficient and speckle statistics, speed of sound, and shear wave elastography metrics. In this article, we introduce several representative quantitative ultrasonography techniques and their diagnostic value for the detection of hepatic steatosis.

Indexed as

Elasticity Imaging TechniquesNon-alcoholic Fatty Liver DiseaseHumansLiverMagnetic Resonance ImagingUltrasonographyLiverLiver steatosisQuantitative evaluationQuantitative ultrasoundUltrasound imaging

Identifiers

PMID34983091
PMCPMC8743150

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.