Evidence map›Paper›PMID 41491129›Full record

ArticleEuropean radiology experimental2026

Impact of hepatic vessels on whole liver proton density fat fraction and R2* quantification.

Ana Jimenez-Pastor, David Marti-Aguado, Bernardo Pereira, Clara Alfaro-Cervello, Alexandre Perez-Girbes, Angel Alberich-Bayarri, Luis Marti-Bonmati

Abstract readMulticenter Study
In one paragraph

Article in European radiology experimental, 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. Article
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

7 authors.

Ana Jimenez-Pastor *Quantitative Imaging Biomarkers in Medicine, Quibim SL, Valencia, Spain. anajimenez@quibim.com.ORCID http://orcid.org/0000-0002-0978-9429
David Marti-Aguado *Digestive Disease Department, Clinic University Hospital of Valencia, INCLIVA Biomedical Research Institute, Valencia, Spain.
Bernardo PereiraQuantitative Imaging Biomarkers in Medicine, Quibim SL, Valencia, Spain.
Clara Alfaro-CervelloFaculty of Medicine and Dentistry, University of Valencia, Valencia, Spain.
Alexandre Perez-GirbesBiomedical Imaging Research Group (GIBI230), La Fe Health Research Institute and Imaging La Fe node at Distributed Network for Biomedical Imaging (ReDIB) Unique Scientific and Technical Infrastructures (ICTS), Valencia, Spain.
Angel Alberich-BayarriQuantitative Imaging Biomarkers in Medicine, Quibim SL, Valencia, Spain.
Luis Marti-BonmatiBiomedical Imaging Research Group (GIBI230), La Fe Health Research Institute and Imaging La Fe node at Distributed Network for Biomedical Imaging (ReDIB) Unique Scientific and Technical Infrastructures (ICTS), Valencia, Spain.

Funding

Conselleria de Cultura, Educación y Ciencia, Generalitat Valenciana CIGE/2022/37Joan Rodés JR22/00002
6 · The paper itself

Abstract

objectivesThis study investigated the influence of hepatic vessels on the quantification of magnetic resonance imaging (MRI) proton density fat fraction (PDFF) and R2* using automated whole-liver segmentation. MATERIALS AND

methodsThis prospective multicenter study included patients with chronic liver disease having paired liver biopsy and MR exams with a standardized multiecho chemical-shift gradient echo sequence. Automated whole-liver segmentation was performed, generating two masks per patient, one including and the other excluding the major hepatic vessels. PDFF and R2* were quantified and graded for both masks. Histological grading of hepatic steatosis and iron overload severity was used as a reference standard.

resultsA total of 377 patients were evaluated, of whom 54% had hepatic steatosis and 20% had iron overload on biopsy readings. Stratified by histological grades, there were no statistically significant differences in the distribution of PDFF or R2* between the two segmentation masks. Overall, PDFF and R2* values were minimally lower when vessels were included, with a bias of -0.06% for PDFF and -0.25 s

conclusionExcluding hepatic vessels entails nonsignificant differences in PDFF and R2* quantification. Although with limited impact, vessel exclusion improves biomarker precision in research settings demanding high accuracy and increases clinicians' confidence when using automatic tools in clinical practice. RELEVANCE STATEMENT: Fat and iron quantification on MRI are key imaging biomarkers for the accurate non-invasive assessment of patients with chronic liver disease. Proton density, fat fraction, and R2* quantification show minimal differences if hepatic vessels are included or excluded from the liver segmentation mask. KEY POINTS: The effect of hepatic vessels on proton density, fat fraction, and R2* quantification was evaluated. No significant differences were found, excluding hepatic vessels, although their inclusion showed a small negative bias. Vessel exclusion may improve clinicians' confidence and precision in high-sensitivity applications.

Indexed as

Fatty LiverLiverMagnetic Resonance ImagingAdultAgedBiopsyFemaleHumansMaleMiddle AgedProspective StudiesProtonsProtonsArtificial intelligenceBlood vesselsFatty liverIron overloadMagnetic resonance imaging

Identifiers

PMID41491129
PMCPMC12770010

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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.