Evidence map›Paper›PMID 41493547›Full record

ArticleEuropean radiology2026

A multicenter multinational retrospective study of the 1-year natural history of LI-RADS 3 observations in patients with cirrhosis.

Luigi Asmundo, Nathaniel Mercaldo, Felipe Furtado, Alexander Herold, Amirkasra Mojtahed, Mark Anderson, William Bradley, Mina Hesami, Valeria Peña-Trujillo, Antonino Andrea Blandino and 16 more

Abstract readMulticenter Study
PubMed Publisher
In one paragraph

Article in European radiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

26 authors.

Luigi Asmundo *Department of Radiology, ASST Grande Ospedale Metropolitano Niguarda, Milan, Italy.
Nathaniel Mercaldo *Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Felipe FurtadoStephen M. Ross School of Business, University of Michigan, Ann Arbor, MI, USA.
Alexander HeroldDepartment of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Amirkasra MojtahedDepartment of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Mark AndersonDepartment of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
William BradleyDepartment of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Mina HesamiDepartment of Emergency Medicine, Yale University, New Haven, CT, USA.
Valeria Peña-TrujilloDepartment of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Antonino Andrea BlandinoDepartment of Biomedicine, Neuroscience and Advanced Diagnostics, University of Palermo, Palermo, Italy.
Roberto CannellaDepartment of Biomedicine, Neuroscience and Advanced Diagnostics, University of Palermo, Palermo, Italy.
Federica VernuccioDepartment of Biomedicine, Neuroscience and Advanced Diagnostics, University of Palermo, Palermo, Italy.
Saubhagya SrivastavaDepartment of Radiology, University of Washington, Seattle, WA, USA.
Manjiri DigheDepartment of Radiology, University of Washington, Seattle, WA, USA.
Manish DhyaniDepartment of Radiology, University of Washington, Seattle, WA, USA.
Dushyant SahaniDepartment of Radiology, University of Washington, Seattle, WA, USA.
Cristiano SgrazzuttiDepartment of Radiology, ASST Grande Ospedale Metropolitano Niguarda, Milan, Italy.
Nicolò BrandiDepartment of Radiology, Ospedale per gli Infermi di Faenza, AUSL Romagna, Faenza, Italy.
Matteo RenzulliDepartment of Radiology, Morgagni-Pierantoni Hospital, AUSL Romagna, Forlì, Italy.
Stefano FantiDepartment of Nuclear Medicine, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy.
Bhan IrunDepartment of Gastroenterology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Giuseppe BrancatelliDepartment of Biomedicine, Neuroscience and Advanced Diagnostics, University of Palermo, Palermo, Italy.
Angelo VanzulliDepartment of Radiology, ASST Grande Ospedale Metropolitano Niguarda, Milan, Italy.
Claude SirlinDepartment of Radiology, University of California San Diego, San Diego, CA, USA.
Avinash R KambadakoneDepartment of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Onofrio A CatalanoDepartment of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA. onofriocatalano@yahoo.it.ORCID http://orcid.org/0000-0001-7733-4138

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo assess the 1-year natural history of liver imaging reporting and data system (LI-RADS) 3 observations on contrast-enhanced MRI in cirrhotic patients across multiple international centers, and to identify clinical and imaging predictors of progression using multivariable and machine learning models. MATERIALS AND

methodsThis retrospective study included 347 cirrhotic patients with 540 LI-RADS 3 observations from six centers across three countries, each with 12 (±3) months of follow-up MRI. Observations were reassessed using LI-RADS v2018 criteria. Generalized linear mixed-effects models and machine learning (LASSO, random forest) evaluated predictors of progression. Area under the curve (AUC) analysis assessed the predictive performance of clinical and imaging variables.

resultsWithin one year, 28% of LI-RADS 3 observations progressed: 14% to LI-RADS 4 and 14% to LI-RADS 5. Independent predictors of progression included lesion size, with an odds ratio (OR: 1.12, 95% CI: 1.01-1.24), Child-Pugh Class C (OR: 8.36, 95% CI: 1.01-69.27), and alcohol-related liver disease (OR: 0.24, 95% CI: 0.06-0.94). Enhancing capsule and untreated hepatitis C virus were significant in univariable analysis. Imaging features improved predictive accuracy, increasing AUC from 0.65 to 0.72 (p = 0.01). A lesion size cut-off of 9.5 mm was associated with increased progression risk.

conclusionOne in four LI-RADS 3 observations progress within one year. Lesion size, liver function, and etiology are key predictors. Integration of imaging features enhances risk stratification and supports more personalized follow-up strategies for indeterminate liver lesions. KEY POINTS: Question Identifying which LI-RADS 3 liver observations progress to malignancy remains challenging; evidence from large, standardized, multicenter MRI cohorts is lacking. Findings In this large multinational study, 28% of LI-RADS 3 observations progressed within one year; lesion size, liver dysfunction, and disease etiology were key independent predictors. Clinical relevance LI-RADS 3 observations show significant progression risk, with imaging features improving prediction models and guiding surveillance strategies for early HCC detection.

Indexed as

Carcinoma, HepatocellularLiver CirrhosisLiver NeoplasmsMagnetic Resonance ImagingAgedContrast MediaDisease ProgressionFemaleHumansMachine LearningMaleMiddle AgedRetrospective StudiesContrast MediaCirrhosisHepatocellular carcinomaLI-RADS 3Multicenter studyRisk prediction

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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.