Evidence map›Paper›PMID 37985560›Full record

ReviewEuropean radiology experimental2023

CT-based methods for assessment of metabolic dysfunction associated with fatty liver disease.

Na Hu, Gang Yan, Maowen Tang, Yuhui Wu, Fasong Song, Xing Xia, Lawrence Wing-Chi Chan, Pinggui Lei

Abstract readReview
In one paragraph

Review in European radiology experimental, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

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

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Review
  6. Article
  7. Observational
  8. Review
  9. Review
  10. Article
  11. Review
  12. Antioxidants (Basel, Switzerland) · 2024
    Article
  13. Article
  14. 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

8 authors.

Na Hu *Department of Radiology, The Affiliated Hospital of Guizhou Medical University, Guiyang, China.
Gang Yan *Department of Nuclear Medicine, The Affiliated Hospital of Guizhou Medical University, Guiyang, China.
Maowen Tang *Department of Radiology, The Affiliated Hospital of Guizhou Medical University, Guiyang, China.
Yuhui WuDepartment of Radiology, The Affiliated Hospital of Guizhou Medical University, Guiyang, China.
Fasong SongDepartment of Radiology, The Affiliated Hospital of Guizhou Medical University, Guiyang, China.
Xing XiaDepartment of Radiology, The Affiliated Hospital of Guizhou Medical University, Guiyang, China.
Lawrence Wing-Chi ChanDepartment of Health Technology and Informatics, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, China. wing.chi.chan@polyu.edu.hk.
Pinggui LeiDepartment of Radiology, The Affiliated Hospital of Guizhou Medical University, Guiyang, China. pingguilei@foxmail.com.ORCID 0000-0001-7610-0292

Funding

Funding for the Excellent Reserve Talents in the Discipline of Affiliated Hospital of Guizhou Medical University gyfyxkyc-2023-13National Natural Science Foundation of China 81960338Science and Technology Projects of Guizhou Province Qiankehejichu-ZK[2022]422Science and Technology Projects of Guizhou Province Qiankehejichu-ZK[2023]353
6 · The paper itself

Abstract

Metabolic dysfunction-associated fatty liver disease (MAFLD), previously called metabolic nonalcoholic fatty liver disease, is the most prevalent chronic liver disease worldwide. The multi-factorial nature of MAFLD severity is delineated through an intricate composite analysis of the grade of activity in concert with the stage of fibrosis. Despite the preeminence of liver biopsy as the diagnostic and staging reference standard, its invasive nature, pronounced interobserver variability, and potential for deleterious effects (encompassing pain, infection, and even fatality) underscore the need for viable alternatives. We reviewed computed tomography (CT)-based methods for hepatic steatosis quantification (liver-to-spleen ratio; single-energy "quantitative" CT; dual-energy CT; deep learning-based methods; photon-counting CT) and hepatic fibrosis staging (morphology-based CT methods; contrast-enhanced CT biomarkers; dedicated postprocessing methods including liver surface nodularity, liver segmental volume ratio, texture analysis, deep learning methods, and radiomics). For dual-energy and photon-counting CT, the role of virtual non-contrast images and material decomposition is illustrated. For contrast-enhanced CT, normalized iodine concentration and extracellular volume fraction are explained. The applicability and salience of these approaches for clinical diagnosis and quantification of MAFLD are discussed.Relevance statementCT offers a variety of methods for the assessment of metabolic dysfunction-associated fatty liver disease by quantifying steatosis and staging fibrosis.Key points• MAFLD is the most prevalent chronic liver disease worldwide and is rapidly increasing.• Both hardware and software CT advances with high potential for MAFLD assessment have been observed in the last two decades.• Effective estimate of liver steatosis and staging of liver fibrosis can be possible through CT.

Indexed as

IodineNon-alcoholic Fatty Liver DiseaseHumansLiver CirrhosisTomography, X-Ray ComputedIodineBiomarkersFatty liverLiver cirrhosisLiver diseasesTomography (x-ray computed)

Identifiers

PMID37985560
PMCPMC10661153

What Socratic 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 Socratic graph.