Evidence map›Paper›PMID 32902745›Full record

ArticleEuropean radiology2021

Comparison of liver stiffness measurements by a 2D-shear wave technique and transient elastography: results from a European prospective multi-centre study.

Maxime Ronot, Giovanna Ferraioli, Hans-Peter Müller, Mireen Friedrich-Rust, Carlo Filice, Valérie Vilgrain, David Cosgrove, Adrian K Lim

Abstract readMulticenter Study
PubMed Publisher
In one paragraph

Article in European radiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
2.5field-weighted citation impact, top 10% 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

16 citing papers in PubMed, 27 citations in OpenAlex.

  1. Article
  2. Identification of Hepatic Fibrosis and Steatosis via A Point-of-Care Transient Elastography System With Integrated AI.Liver international : official journal of the International Association for the Study of the Liver · 2026
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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

8 authors at 6 institutions in 4 countries.

Maxime RonotDepartment of Radiology, Beaujon University Hospital, APHP.Nord, Clichy, France. maxime.ronot@aphp.fr.ORCID http://orcid.org/0000-0001-7464-3939
Giovanna FerraioliDepartment of Clinical Sciences and Infectious Diseases, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy.
Hans-Peter MüllerDepartment of Hepatology and Imaging, Charité Hospital, University of Berlin, Berlin, Germany.
Mireen Friedrich-RustDepartment of Internal Medicine 1, Division of Gastroenterology and Hepatology, Goethe University Hospital, Frankfurt, Germany.
Carlo FiliceDepartment of Clinical Sciences and Infectious Diseases, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy.
Valérie VilgrainDepartment of Radiology, Beaujon University Hospital, APHP.Nord, Clichy, France.
David CosgroveDepartment of Imaging, Imperial College Healthcare NHS Trust, Charing Cross Hospital, Fulham Palace Road, London, W6 8RF, UK.
Adrian K LimDepartment of Imaging, Imperial College Healthcare NHS Trust, Charing Cross Hospital, Fulham Palace Road, London, W6 8RF, UK.
Imperial College Healthcare NHS Trust · GBUniversity of Pavia · ITCharité - Universitätsmedizin Berlin · DEGoethe University Frankfurt · DEHôpital Beaujon · FRUniversité Paris Cité · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo compare liver stiffness measurement (LSM) provided by Canon 2D-shear wave elastography (2D-SWE) and transient elastography (TE), the latter being the reference method.

methodsProspective study conducted in four European centres from 2015 to 2016 including patients with various chronic liver diseases who had LSMs with both 2D-SWE and TE on the same day. Median of 10 valid measurements (in kPa) was used for comparison using paired t test, Pearson correlation, intraclass correlation coefficient (ICC) and Bland-Altman plot. The ability of 2D-SWE to stratify patient according to recognised LSM-TE thresholds was assessed by ROC curve analysis.

resultsSix hundred forty patients were scanned, where 593 (92.7%), 572 (89.4%) and 537 (83.9%) had reliable LSMs by TE, 2D-SWE and both combined, respectively. In the latter (n = 537, 310 [57.7%] male, mean 55.3 ± 14.8 years), median LSM-TE and LSM-2D-SWE had a mean of 10.1 ± 9.4 kPa (range 2.4-75) and 9.1 ± 6.1 kPa (range 3.6-55.7) (paired t test: p < 0.001), respectively. These were significantly correlated (Pearson r = 0.932, p < 0.001, ICC 0.850 (0.825-0.872), bias 0.99 ± 4.33 kPa [95% limits of agreement - 9.48 to + 7.49] with proportional error towards higher LSM values). LSM-2D-SWE values significantly increased with TE categories (ANOVA: p < 0.001). AUROCs ranged from 0.935 ± 0.010 (95% CI 0.910-0.954) to 0.973 ± 0.009 (95% CI 0.955-0.985), resulting in correct classification of 390/537 (73%) patients. Three 2D-SWE measurements were sufficient for reliable LSMs.

conclusionLSM using 2D-SWE correlates well with TE. It tends to underestimate higher stages of liver fibrosis but correctly classifies the majority of patients. It may be used in TE-derived algorithms to manage patients. KEY POINTS: • Liver stiffness measurement (LSM) by 2D-shear wave elastography (2D-SWE) and transient elastography (TE) are strongly correlated. • 2D-SWE shows proportionately lower LSM values compared to TE, particularly with the higher LSM range. • Three individual measurements by 2D-SWE are sufficient to assess LSM reliably.

Indexed as

Elasticity Imaging TechniquesHumansLiverLiver CirrhosisMaleProspective StudiesReproducibility of ResultsElasticity imaging techniqueFibrosisLiver diseasesPortal hypertensionProspective studies

Identifiers

PMID32902745
OpenAlexW3086233915

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.