Evidence map›Paper›PMID 41545581›Full record

ArticleScientific reports2026

Preliminary quantitative assessment of liver and spleen MR imaging and elastography in clinically significant portal hypertension.

Constance de Margerie-Mellon, Florian Joly, Arthur Tenenhaus, Riccardo Sartoris, Valérie Paradis, Maxime Ronot, Pierre-Emmanuel Rautou, Philippe Garteiser, Bernard E Van Beers

Abstract read
In one paragraph

Article in Scientific reports, 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

9 authors.

Constance de Margerie-Mellon *Inserm, Imaging Biomarkers Laboratory, Inflammation Research Center, UMR 1149, Université Paris Cité, Paris, France. constance.de-margerie@aphp.fr.
Florian Joly *Inserm, Imaging Biomarkers Laboratory, Inflammation Research Center, UMR 1149, Université Paris Cité, Paris, France.
Arthur TenenhausSignals and Systems Laboratory, Université Paris-Saclay, Centrale Supélec, Gif-sur-Yvette, France.
Riccardo SartorisInserm, Imaging Biomarkers Laboratory, Inflammation Research Center, UMR 1149, Université Paris Cité, Paris, France.
Valérie ParadisInserm, Inflammation to Cancer Team, Inflammation Research Center, UMR 1149, Université Paris Cité, Paris, France.
Maxime RonotInserm, Imaging Biomarkers Laboratory, Inflammation Research Center, UMR 1149, Université Paris Cité, Paris, France.
Pierre-Emmanuel RautouInserm, Inflammation Research Center, UMR 1149, Université Paris Cité, Paris, France.
Philippe GarteiserInserm, Imaging Biomarkers Laboratory, Inflammation Research Center, UMR 1149, Université Paris Cité, Paris, France.
Bernard E Van BeersInserm, Imaging Biomarkers Laboratory, Inflammation Research Center, UMR 1149, Université Paris Cité, Paris, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Patients with clinically significant portal hypertension (CSPH) are at high risk of developing severe complications of portal hypertension. The aim of our preliminary study was to assess multiparametric liver and spleen MRI and MR elastography for the estimation of CSPH. Seventy-eight patients with advanced chronic liver disease and hepatic venous pressure gradient measurements, who had liver and spleen MRI and MR elastography were assessed. Liver and spleen elasticity and viscosity maps with texture features were derived from the MR elastography acquisitions. Liver surface nodularity (LSN) and texture features were obtained from the T2-weighted MR images. Features were analyzed with regularized generalized canonical correlation analysis for dimensionality reduction. Models based on the combination of MRI and MR elastography features were trained and evaluated, using a support vector machine classifier. Forty-eight patients (62%) had CSPH. Most models based on hepatic and/or splenic MR elastography features, T2 texture features or LSN had fair performance (AUCs 0.7–0.79) for CSPH diagnosis. Multiparametric models that included MR elastography features and LSN had good diagnostic performance (AUCs 0.8–0.89), without improvement with the addition of T2 texture features. Our results suggest that combining liver and spleen MR elastography features with LSN may produce efficient models for diagnosing CSPH.

Indexed as

Elasticity Imaging TechniquesHypertension, PortalLiverMagnetic Resonance ImagingSpleenAdultAgedFemaleHumansMaleMiddle AgedChronic liver diseaseMagnetic resonance elastographyMagnetic resonance imagingPortal hypertensionRadiomics

Identifiers

PMID41545581
PMCPMC12886834

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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.