Evidence map›Paper›PMID 40132140›Full record

ArticleHepatology (Baltimore, Md.)2026

Proton density fat fraction for diagnosis of metabolic dysfunction-associated steatotic liver disease.

Nikolaos Panagiotopoulos, Tanya Wolfson, David T Harris, Danielle Batakis, Rashmi Agni, Lael Ceriani, Yesenia Covarrubias, Gavin Hamilton, Michael S Middleton, Vitor F Martins and 12 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Hepatology (Baltimore, Md.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
–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

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Automated Deep Learning Detection of Hepatic Steatosis on Noncontrast Computed Tomography Scans and Discrepancy With Scan Reports.Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association · 2026
    Article
  4. Article
  5. Article
  6. Review
  7. Review
  8. Observational
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

22 authors.

Nikolaos PanagiotopoulosDepartment of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA.ORCID 0009-0006-6237-0586
Tanya WolfsonComputational and Applied Statistical Laboratory (CASL), San Diego Supercomputer Center, University of California San Diego, San Diego, California, USA.
David T HarrisDepartment of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA.ORCID 0000-0002-1150-8702
Danielle BatakisDepartment of Radiology, University of California San Diego, San Diego, California, USA.
Rashmi AgniDepartment of Pathology and Laboratory Medicine, University of Wisconsin-Madison, Madison, Wisconsin, USA.ORCID 0000-0001-7803-4647
Lael CerianiDepartment of Radiology, University of California San Diego, San Diego, California, USA.ORCID 0000-0003-4427-4161
Yesenia CovarrubiasDepartment of Radiology, University of California San Diego, San Diego, California, USA.
Gavin HamiltonDepartment of Radiology, University of California San Diego, San Diego, California, USA.
Michael S MiddletonDepartment of Radiology, University of California San Diego, San Diego, California, USA.ORCID 0000-0002-4247-1287
Vitor F MartinsDepartment of Radiology, University of California San Diego, San Diego, California, USA.ORCID 0000-0002-9060-1314
Anthony C GamstComputational and Applied Statistical Laboratory (CASL), San Diego Supercomputer Center, University of California San Diego, San Diego, California, USA.
Thekla H OechteringDepartment of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA.ORCID 0000-0002-1931-1912
Ryan SappenfieldDepartment of Pathology and Laboratory Medicine, University of Wisconsin-Madison, Madison, Wisconsin, USA.ORCID 0000-0001-7397-4330
Santiago HorganDepartment of Surgery, University of California San Diego, San Diego, California, USA.
Eduardo GrunvaldDepartment of Medicine, University of California San Diego, San Diego, California, USA.ORCID 0000-0001-9332-7069
Luke M FunkDepartment of Surgery, University of Wisconsin-Madison, Madison, Wisconsin, USA.ORCID 0000-0003-4475-304
Garth R JacobsenDepartment of Surgery, University of California San Diego, San Diego, California, USA.
Anne O LidorDepartment of Surgery, University of Wisconsin-Madison, Madison, Wisconsin, USA.
James A GoodmanTranslational Clinical Sciences, Pfizer Research & Development, Cambridge, Massachusetts, USA.ORCID 0000-0002-6055-7885
Sami B KhouryDepartment of Radiology, University of California San Diego, San Diego, California, USA.
Claude B SirlinDepartment of Radiology, University of California San Diego, San Diego, California, USA.ORCID 0000-0002-6639-9072
Scott B ReederDepartment of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA.ORCID 0000-0003-4728-8171

Funding

UC San Diego Clinical and Translational Research InstituteUL1TR001442 · NCATS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI FIRESTEIN, GARY S, HOGARTH, MICHAEL · 2015 to 2024
$88.3M
Technical Validation of MRI Biomarkers of Liver FatR01DK088925 · NIDDK · UNIVERSITY OF WISCONSIN-MADISON · PI REEDER, SCOTT B., SIRLIN, CLAUDE B · 2010 to 2021
$7.1M
Traning Clinical Scientists in Radiological ImagingT32EB005970 · NIBIB · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Eric Y Chang, Rebecca Ann Rakow-Penner · 2007 to 2026
$3.2M
Fully Automated High-Throughput Quantitative MRI of the LiverR01EB031886 · NIBIB · UNIVERSITY OF WISCONSIN-MADISON · PI HERNANDO, DIEGO, REEDER, SCOTT B. · 2022 to 2025
$2.4M
Technical Development of Quantitative Biomarkers of Fatty Liver Disease with MRIR01DK083380 · NIDDK · UNIVERSITY OF WISCONSIN-MADISON · PI REEDER, SCOTT B. · 2010 to 2013
$1.2M
NCATS NIH HHS UL1 TR001442NIBIB NIH HHS R01 EB031886NIBIB NIH HHS T32 EB005970NIDDK NIH HHS R01 DK083380NIDDK NIH HHS R01 DK088925
6 · The paper itself

Abstract

BACKGROUND AND

aimsPrior work has shown that MRI-derived proton density fat fraction (PDFF) can diagnose metabolic dysfunction-associated steatotic liver disease (MASLD) noninvasively, but there is a paucity of data on the performance of PDFF to classify more advanced forms of the MASLD spectrum. The purpose of this study was to assess the diagnostic performance of PDFF for the diagnoses of MASLD, metabolic dysfunction-associated steatohepatitis (MASH), and fibrotic MASH in adults with obesity undergoing bariatric surgery, using contemporaneous intraoperative liver biopsy as a reference. APPROACH AND

resultsPDFF was evaluated alone and with other potential classifiers (imaging, serum and anthropometric), using Bayesian Information Criterion-based stepwise logistic regression models. Areas under the receiver operating characteristic (ROC) curves (AUC) were computed for all models and single classifiers. Cross-validated sensitivity and specificity were calculated at Youden-based PDFF classification thresholds. Data analysis from 140 patients demonstrated that PDFF was the most accurate single classifier, with high AUC for MASLD (0.95), MASH (0.85), and fibrotic MASH (0.82) (all p <0.001). Multivariable models, including PDFF, outperformed those without PDFF. The Youden-based threshold for PDFF was 4.4% for MASLD (sensitivity: 87%, specificity: 86%), 6.9% for MASH (sensitivity: 77%, specificity: 66%), and 13.5% for fibrotic MASH (sensitivity: 67%, specificity: 85%).

conclusionsPDFF was the most accurate single classifier for diagnosing MASLD, MASH, and fibrotic MASH. The most accurate multivariable classification models for MASLD, MASH, and fibrotic MASH included PDFF, demonstrating the central importance of PDFF for noninvasive assessment of the MASLD spectrum.

Indexed as

Fatty LiverMagnetic Resonance ImagingObesityAdultBariatric SurgeryBiopsyFemaleHumansLiverLiver CirrhosisMaleMiddle AgedNon-alcoholic Fatty Liver DiseaseROC CurveSensitivity and Specificitymagnetic resonance imaging (MRI)MASLDmetabolic dysfunction–associated steatohepatitis (MASH)PDFFquantitative imaging biomarker

Identifiers

PMID40132140
PMCPMC12353623

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Registered trials

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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.