Digital Pathology and AI for Liver Outcomes in MASLD

NCT ID: NCT06344364

Last Updated: 2025-08-05

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

NOT_YET_RECRUITING

Total Enrollment

1800 participants

Study Classification

OBSERVATIONAL

Study Start Date

2025-09-01

Study Completion Date

2026-03-15

Brief Summary

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The aim of this multi-center, retrospective epidemiologic study is to confirm the prognostic performance of the Digital Pathology (DP) FibroNest Phenotypic Fibrosis Composite Score (Ph-FCS), derived from standard digital pathology liver biopsy images, in predicting clinical hepatic decompensation events in patients with metabolic dysfunction-associated steatohepatitis (MASH).

Detailed Description

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MASH, or metabolic dysfunction-associated steatohepatitis, presents histological liver changes resembling those caused by alcohol abuse, but in the absence of alcohol intake. Common among adults with conditions like obesity and type-2 diabetes, MASH, especially its severe form, is anticipated to become a leading cause of end-stage liver disease.

Currently lacking approved treatments, MASH poses a significant burden on liver health and transplantation. Diagnosis and assessment rely on subjective histological review, prone to variability and limitations in detecting subtle changes. Consequently, there's an urgent need for accurate, continuous histological biomarkers.

The FibroNest Ph-FCS offers a promising solution, utilizing high resolution digital pathology and sophisticated algorithmic methods for sensitive and reproducible fibrosis severity assessment and prediction of clinical events. In a 2003 proof of concept retrospective study on 400 patients, its prognostic performance was excellent.

In this proposed multi-center retrospective study, we aim to confirm the Ph-FCS's prognostic value on a large cohort of 1,700 MASLD patients. We will also compare the prognostic performance of the Ph-FCS with the prognostic performance of the NASH-CR Fibrosis stages, and with non-invasive biomarkers like Fib-4 and elastography/Fibroscan, also collected retrospectively from the point of initial diagnosis.

This study seeks to:

(i) Confirm Ph-FCS's prognostic utility on a large scale.

(ii) Compare biopsy-based Ph-FCS with NASH-CRN F Stages

(iii) Compare biopsy-based Ph-FCS with non-invasive biomarkers.

Conditions

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Metabolic Dysfunction-associated Steatotic Liver Disease

Study Design

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Observational Model Type

COHORT

Study Time Perspective

RETROSPECTIVE

Study Groups

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Non-Liver Related Event

Absence of any of the liver events described in the second group in the patient clinical follow-up.

Digital Pathology FibroNest Phenotypic Fibrosis Composite Score (Ph-FCS)

Intervention Type DIAGNOSTIC_TEST

Biomarker name: FibroNest Phenotypic Fibrosis Composite Score Acronym: FibroNest Ph-FCS Type of Biomarker: Histologic based, Digital, Quantitative Image Analysis, Imaging modality Definition: A quantitative, normalized (no unit) and continuous composite score that aggregates quantitative histological features of fibrosis severity measured by high resolution quantitative image analysis.

Liver Related Event

Liver-related events include liver-related death, hepatic decompensation events (variceal hemorrhage, ascites, hepatic encephalopathy), and hepatocellular carcinoma.

Digital Pathology FibroNest Phenotypic Fibrosis Composite Score (Ph-FCS)

Intervention Type DIAGNOSTIC_TEST

Biomarker name: FibroNest Phenotypic Fibrosis Composite Score Acronym: FibroNest Ph-FCS Type of Biomarker: Histologic based, Digital, Quantitative Image Analysis, Imaging modality Definition: A quantitative, normalized (no unit) and continuous composite score that aggregates quantitative histological features of fibrosis severity measured by high resolution quantitative image analysis.

Interventions

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Digital Pathology FibroNest Phenotypic Fibrosis Composite Score (Ph-FCS)

Biomarker name: FibroNest Phenotypic Fibrosis Composite Score Acronym: FibroNest Ph-FCS Type of Biomarker: Histologic based, Digital, Quantitative Image Analysis, Imaging modality Definition: A quantitative, normalized (no unit) and continuous composite score that aggregates quantitative histological features of fibrosis severity measured by high resolution quantitative image analysis.

Intervention Type DIAGNOSTIC_TEST

Eligibility Criteria

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Inclusion Criteria

* Adult pts ( \>=18 years old) with MASLD defined histologically.
* Liver biopsy with fibrosis stains available for digitization or already digitized.
* Clinical follow-up \>1 year available recording liver-related outcomes either through hospitalization ICD-10 codes or through clinical observation

Exclusion Criteria

* Liver diseases other than MASLD Note: no exclusion based on bariatric surgery, significant weight loss or enrollment in NASH clinical studies, but data is collected for data analysis / competing effects (see data analysis plan)
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Chinese University of Hong Kong

OTHER

Sponsor Role collaborator

University of Seville

OTHER

Sponsor Role collaborator

Fundacio Clinic Barcelona

OTHER

Sponsor Role collaborator

Sorbonne University

OTHER

Sponsor Role collaborator

PharmaNest, Inc

INDUSTRY

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Vlad Ratziu, MD, PhD

Role: PRINCIPAL_INVESTIGATOR

Sorbonne University

Locations

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The Chinese University of Hong Kong

Shatin, , Hong Kong

Site Status

Fundació de Recerca Clinic Barcelona

Barcelona, , Spain

Site Status

University of Seville

Seville, , Spain

Site Status

Countries

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Hong Kong Spain

Central Contacts

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Li Chen, PhD

Role: CONTACT

+1 609 375 2003

Louis Petitjean

Role: CONTACT

+1 609 375 2003

Facility Contacts

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Vincent Wong, PhD

Role: primary

Isabel Graupera, PhD

Role: primary

Manuel R Gómez, PhD

Role: primary

References

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Sanyal AJ, Van Natta ML, Clark J, Neuschwander-Tetri BA, Diehl A, Dasarathy S, Loomba R, Chalasani N, Kowdley K, Hameed B, Wilson LA, Yates KP, Belt P, Lazo M, Kleiner DE, Behling C, Tonascia J; NASH Clinical Research Network (CRN). Prospective Study of Outcomes in Adults with Nonalcoholic Fatty Liver Disease. N Engl J Med. 2021 Oct 21;385(17):1559-1569. doi: 10.1056/NEJMoa2029349.

Reference Type BACKGROUND
PMID: 34670043 (View on PubMed)

Kendall TJ, Jimenez-Ramos M, Turner F, Ramachandran P, Minnier J, McColgan MD, Alam M, Ellis H, Dunbar DR, Kohnen G, Konanahalli P, Oien KA, Bandiera L, Menolascina F, Juncker-Jensen A, Alexander D, Mayor C, Guha IN, Fallowfield JA. An integrated gene-to-outcome multimodal database for metabolic dysfunction-associated steatotic liver disease. Nat Med. 2023 Nov;29(11):2939-2953. doi: 10.1038/s41591-023-02602-2. Epub 2023 Oct 30.

Reference Type BACKGROUND
PMID: 37903863 (View on PubMed)

Ratziu V, Chen L, Petitjean L. et al. Novel Artificial Intelligence-Assisted Digital Pathology Quantitative Image Analysis Predicts the occurrence of Liver-related Clinical Events in the Multicentric, European, Hepatic Outcomes and Survival Fatty Liver Registry (HITSURFR) Study. Hepatology. 78(S1) S1-S2154 2084-A

Reference Type BACKGROUND

Other Identifiers

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PHN 1-080-23

Identifier Type: -

Identifier Source: org_study_id

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