Evidence map›Paper›PMID 42298258›Full record

ReviewHormones (Athens, Greece)2026

Non-invasive imaging diagnostic techniques in metabolic dysfunction-associated steatotic liver disease: a roadmap for clinicians.

Ioannis Lamprinakos, Myrsini Orfanidou, Vasileios Rafailidis, Stergios A Polyzos

Abstract readReview
PubMed Publisher
In one paragraph

Review in Hormones (Athens, Greece), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

4 authors.

Ioannis Lamprinakos *Department of Medical Physics, University Hospitals Dorset NHS Foundation Trust, Poole, UK.
Myrsini Orfanidou *Laboratory of Pharmacology, School of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece. myrsinio@auth.gr.ORCID http://orcid.org/0000-0002-1379-9195
Vasileios RafailidisDepartment of Clinical Radiology, AHEPA University Hospital, Aristotle University of Thessaloniki, Thessaloniki, Greece.
Stergios A PolyzosLaboratory of Pharmacology, School of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece. spolyzos@auth.gr.ORCID http://orcid.org/0000-0001-9232-4042

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Metabolic dysfunction-associated steatotic liver disease (MASLD), previously termed nonalcoholic fatty liver disease (NAFLD), is the most prevalent chronic liver disorder globally and is strongly associated with obesity, type 2 diabetes mellitus, and the metabolic syndrome. Accurate and timely assessment of hepatic steatosis and fibrosis is critical for risk stratification and therapeutic monitoring. However, liver biopsy, the current reference standard, is invasive, subject to sampling variability, and unsuitable for repeated assessments of a large population. Non-invasive imaging modalities have emerged as potential alternatives, offering reproducibility and possibility for quantitative evaluation. Ultrasound-based techniques are focused on qualitative and sometimes quantitative assessment of liver fat, while elastography techniques are focused on liver stiffness, which is associated with fibrosis stage. Magnetic resonance techniques offer highly reproducible evaluation of steatosis, metabolic alterations, and fibrosis, with magnetic resonance imaging-proton density fat fraction regarded as the reference standard for fat quantification and magnetic resonance elastography providing the highest accuracy for fibrosis staging. Computed tomography also enables liver fat quantification; however, its use is limited mainly because of exposure to ionizing radiation. Recent artificial intelligence (AI) applications are oriented towards enhancing diagnostic accuracy and automate quantitative assessment while supporting longitudinal monitoring. Despite these advancements, further research is required to validate emerging techniques, standardize acquisition protocols, and ensure widespread clinical implementation. This review summarizes and synthesizes current evidence on non-invasive imaging diagnostic techniques for MASLD, highlighting their strengths, limitations, and potential integration into routine clinical practice in order to reduce dependence on invasive liver biopsy.

Indexed as

Artificial intelligenceMetabolic dysfunction-associated steatotic liver diseaseNonalcoholic fatty liver diseaseNon-invasive diagnosisNon-invasive imaging

Identifiers

What Socratic 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 Socratic graph.