Evidence map›Paper›PMID 42995264›Full record

ArticleVirchows Archiv : an international journal of pathology2026

Trichrome-based deep learning for quantitative assessment of steatosis, hepatocellular ballooning, and fibrosis in metabolic dysfunction-associated steatohepatitis.

Byoung Uk Park, Bashar Hassan, Saadiya Nazli, Lindsey Smith, Abdelrahman Shabaan, Ameya Patil, Lucas Stetzik, Rofyda Elhalaby, Adilson DaCosta, Priya Sivasubramaniam and 10 more

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Article in Virchows Archiv : an international journal of pathology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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5 · Who and what money

Authors and funding

20 authors.

Byoung Uk ParkDepartment of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, Minnesota, USA. park3145@umn.edu.ORCID http://orcid.org/0000-0002-8797-2026
Bashar HassanDepartment of Preventive, Occupational, and Aerospace Medicine, Mayo Clinic, Rochester, Minnesota, USA.
Saadiya NazliDepartment of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA.
Lindsey SmithMySME, Birmingham, Alabama, USA.
Abdelrahman ShabaanDepartment of Pathology, University of Virginia, Charlottesville, Virginia, USA.
Ameya PatilDepartment of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA.
Lucas StetzikAiforia Technologies, Rochester, Minnesota, USA.
Rofyda ElhalabyDepartment of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA.
Adilson DaCostaDepartment of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA.
Priya SivasubramaniamDepartment of Pathology, Medical College of Wisconsin, Milwaukee, Wisconsin, USA.
Tracy Loh JiezhenDepartment of Anatomical Pathology, Singapore General Hospital, Singapore, Singapore.
Gyanendra PuriDepartment of Internal Medicine, St. Francis Medical Center, Monroe, Louisiana, USA.
Harmeet MalhiDivision of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota, USA.
Gregory GoresDivision of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota, USA.
Zachary D GoodmanCenter for Liver Diseases, Inova Fairfax Hospital, Falls Church, Virginia, USA.
Marcela SalomaoDepartment of Laboratory Medicine and Pathology, Mayo Clinic, Scottsdale, Arizona, USA.
Rish PaiDepartment of Laboratory Medicine and Pathology, University of Toronto, Toronto, Ontario, Canada.
Christopher P HartleyDepartment of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA.
Rondell P GrahamDepartment of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA.
Roger K MoreiraDepartment of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimsThis study aimed to develop and evaluate Tri-MASH, a trichrome-based deep learning model for quantitative assessment of steatosis, classic hepatocellular ballooning, and fibrosis, and to explore their spatial relationships. Inflammatory-cell density was evaluated as an exploratory measure. METHODS AND

resultsTri-MASH was trained using 161 training specimens and internally evaluated on 30 randomly selected, nonoverlapping specimens. External evaluation comprised 39 biopsies independently scored by four pathologists and 524 baseline and week-72 biopsies from 262 clinical-trial participants. Internal-validation F1 scores ranged from 78.9% for inflammatory-cell detection to 99.2% for sinusoidal fibrosis. In cohort 1, associations with median pathologist assessments were very strong for steatosis (Rs = 0.85) and fibrosis (Rs = 0.87-0.88) and moderate for ballooning (Rs = 0.55). In cohort 2, exploratory pooled analyses showed moderate associations for steatosis (Rs = 0.52), ballooning (Rs = 0.54), and total and portal-septal fibrosis (Rs = 0.50); confidence intervals and p values were unadjusted for repeated observations within participants. Inflammatory-cell density correlated poorly with lobular inflammation grade (Rs=-0.01 to 0.14). Continuous measurements characterized within-arm longitudinal variation, including variation despite unchanged fibrosis stage. In a selected 50-biopsy subset enriched for NAS ballooning grade 2, case-specific median distances to sinusoidal fibrosis were shorter for ballooned hepatocytes than for lipid droplets (p < 0.0001).

conclusionsTri-MASH enables integrated quantitative and spatial analysis of steatosis, classic hepatocellular ballooning, and fibrosis on a single trichrome section. The current data support its use as an adjunctive quantitative research platform rather than a replacement for conventional H&E-based assessment or standalone clinical grading; inflammatory-cell output did not reproduce conventional lobular inflammation grading.

Indexed as

Artificial intelligenceDeep learningDigital pathologyLiver fibrosisMetabolic dysfunction-associated steatohepatitisTrichrome

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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.