AI Models vs Non-Invasive Fibrosis Scores in MAFLD Diagnosis

NCT07305636 | Completed

• 1 other identifier: TANTAU-MAFLD-AI-2025-01
• Study Type: observational
• Target: 522
• Locations: 1 country
• Sites: 1

Brief Summary

This study evaluates the accuracy of artificial intelligence (AI) models using FibroScan and clinical data to predict hepatic fibrosis in Egyptian patients with metabolic-associated fatty liver disease (MAFLD). The performance of the AI models will be compared with conventional noninvasive fibrosis scores (FIB-4, APRI, NAFLD fibrosis score, and FAST). The goal is to improve early, noninvasive diagnosis of fibrosis and reduce reliance on liver biopsy.

Conditions

MAFLD; AI (Artificial Intelligence)

Outcome Measures

Primary Outcomes (1)

• Measure diagnostic accuracy of AI models in predicting hepatic fibrosis stage (F0-F4)

  At enrollment (single cross-sectional assessment).

Eligibility Criteria

• Age: 18 Days+
• Sex: all
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Adult Egyptian patients (≥18 years) diagnosed with metabolic associated fatty liver disease (MAFLD) according to international criteria, recruited from the outpatient clinic and FibroScan unit of the Tropical Medicine Department, Faculty of Medicine, Tanta University.

You may qualify if:

• \- Adults ≥18 years.
• Diagnosed with MAFLD according to international criteria (hepatic steatosis with metabolic dysfunction).
• Valid FibroScan evaluation with available LSM and CAP values.

You may not qualify if:

• Excessive alcohol intake (\>30 g/day for men, \>20 g/day for women).
• Chronic viral hepatitis (HBV or HCV).
• Autoimmune hepatitis.
• Known malignancy.
• Pregnancy.
• Refusal to participate.

Sponsors & Collaborators

• Tanta University: lead

Study Sites (1)

Faculty of Medicine

Tanta, Egypt

Location

Study Design

• Study Type: observational
• Observational Model: OTHER
• Time Perspective: CROSS SECTIONAL
• Target Duration: 1 Day
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Lecturer of Tropical Medicine and Infectious diseases

Study Record Dates

• First Submitted: December 12, 2025
• First Posted: December 26, 2025
• Study Start: May 13, 2025
• Primary Completion: August 30, 2025
• Study Completion: November 30, 2025
• Last Updated: December 26, 2025

Record last verified: 2025-12

Locations

EG (1)