Share:
Peer-Reviewed Publication
Eur Radiol2026;36(8):6523-6534.August 1, 2026Journal Article

Combination of quantitative MRI and laboratory markers for the detection and staging of metabolic dysfunction-associated steatotic liver disease.

Nienke P M Wassenaar1, Koen C van Son2,3,4, Bas Voermans2, Kirsi M A van Eekhout2, Marian A Troelstra5, Stan Driessen2,3, Anne Line Mak2,3, Julia J Witjes2,3, Anne-Marieke van Dijk2,3, Veera Houttu2,3, Diona Zwirs2, Elizabeth Shumbayawonda6, Max Nieuwdorp2,3, Michail Doukas7, Joanne Verheij3,8, Aart J Nederveen5, Oliver J Gurney-Champion5, Adriaan G Holleboom2,3
1Radiology and Nuclear Medicine, Amsterdam UMC location University of Amsterdam, Amsterdam, The Netherlands. n.p.wassenaar@amsterdamumc.nl.
2Vascular Medicine, Amsterdam UMC location University of Amsterdam, Amsterdam, The Netherlands.
3Amsterdam Gastroenterology Endocrinology Metabolism (AGEM) Institute, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.
4Gastroenterology and Hepatology, Amsterdam UMC location University of Amsterdam, Amsterdam, The Netherlands.
5Radiology and Nuclear Medicine, Amsterdam UMC location University of Amsterdam, Amsterdam, The Netherlands.
6Perspectum Ltd., Oxford, United Kingdom.
7Department of Pathology, Erasmus University Medical Center, Rotterdam, The Netherlands.
8Pathology, Amsterdam UMC location University of Amsterdam, Amsterdam, The Netherlands.

Abstract

OBJECTIVES: Metabolic dysfunction-associated steatotic liver disease (MASLD) is increasing both in numbers and severity worldwide. Non-invasive alternatives to liver biopsy, particularly for the detection of metabolic dysfunction-associated steatohepatitis (MASH), have proven difficult to establish. We aimed to assess whether quantitative MRI (qMRI) alone and in combination with laboratory and ant…

Create a free account to keep reading

Free members get 10 full research views every month across publications, clinical trials, FDA clearances, adverse events, and NIH grants. No credit card required.

Want unlimited research access? See Pro plans

Data Accuracy Notice: Research intelligence on Health AI Central is aggregated from public sources (PubMed, ClinicalTrials.gov, FDA, NIH, CMS, and others) and refreshed nightly. Classifications and derived metrics are produced by automated methods described in our Methodology. We recommend verifying critical data points against the primary sources before making decisions.