Evidence map›Paper›PMID 42093729›Full record

ArticleJournal of pathology informatics2026

Detection of macrovesicular steatosis in hematoxylin and eosin-stained histological images of human livers: A feature-based method.

E Malamutmann, M Platte, S Theurer, M Jalc, J Rashidi-Alavijeh, K Willuweit, J-W Treckmann, A Oezcelik, F Nensa, J Haubold and 2 more

Abstract read
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In one paragraph

Article in Journal of pathology informatics, 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
–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

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

12 authors.

E MalamutmannGeneral, Visceral & Transplantation Surgery, University Hospital Essen, Hufelandstr. 55, 45147 Essen, Germany.
M PlatteClinic for Gastroenterology and Hepatology, University Hospital Essen, Hufelandstr. 55, 45147 Essen, Germany.
S TheurerInstitute of Pathology, University Hospital Essen, Hufelandstr. 55, 45147 Essen, Germany.
M JalcGeneral, Visceral & Transplantation Surgery, University Hospital Essen, Hufelandstr. 55, 45147 Essen, Germany.
J Rashidi-AlavijehClinic for Gastroenterology and Hepatology, University Hospital Essen, Hufelandstr. 55, 45147 Essen, Germany.
K WilluweitClinic for Gastroenterology and Hepatology, University Hospital Essen, Hufelandstr. 55, 45147 Essen, Germany.
J-W TreckmannGeneral, Visceral & Transplantation Surgery, University Hospital Essen, Hufelandstr. 55, 45147 Essen, Germany.
A OezcelikGeneral, Visceral & Transplantation Surgery, University Hospital Essen, Hufelandstr. 55, 45147 Essen, Germany.
F NensaInstitute of Artificial Intelligence, University Hospital Essen, Hufelandstr. 55, 45147 Essen, Germany.
J HauboldInstitute of Artificial Intelligence, University Hospital Essen, Hufelandstr. 55, 45147 Essen, Germany.
U NeumannGeneral, Visceral & Transplantation Surgery, University Hospital Essen, Hufelandstr. 55, 45147 Essen, Germany.
D P HoyerGeneral, Visceral & Transplantation Surgery, University Hospital Essen, Hufelandstr. 55, 45147 Essen, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Macrovesicular steatosis (MaS) affects liver transplant outcomes. Traditional visual biopsy assessment is subjective and shows inter-observer variability (weighted κ = 0.595 in our cohort), which complicates allocation and prognostication. Methods: We developed a semi-automated image analysis method using HALCON Progress (evaluation license, 2019-2023) to quantify MaS in H&E whole-slide images (WSIs). The pipeline processes native SVS files at full resolution (average runtime 1.26 ± 0.53 min/WSI) without tiling, downsampling, or format conversion. Four shape features (area, roundness, circularity, and compactness) guide classification. Results were compared with three specialized pathologists using Pearson and Spearman correlations. Results: Across 129 WSIs (≈52,000 lipid droplets), artificial intelligence-pathologist correlations were statistically significant (Pearson Conclusions: The method provides a rapid, objective readout of MaS and performs on par with inter-pathologist agreement (R

Indexed as

Automated image analysisDigital pathologyDonor liver evaluationImage processing techniquesLiver histologyLiver steatosis quantificationLiver transplantationMacrovesicular steatosis (MaS)Whole-slide imaging (WSI)

Identifiers

PMID42093729
PMCPMC13141805

What Socratic holds

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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 Socratic graph.