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AI in steatohepatitis diagnostics: precision beyond the microscope

Year: 2025

Type: article

Abstract: Non-alcoholic steatohepatitis (NASH), the progressive form of nonalcoholic fatty liver disease (NAFLD), is a major global health burden without curative therapy. Conventional histological diagnosis is limited by interobserver variability and insensitivity to subtle changes, necessitating more objective diagnostic tools. Artificial intelligence (AI), integrated with digital pathology techniques such as second harmonic generation/two-photon excitation (SHG/TPE) fluorescence imaging, provides quantitative and reproducible assessment of steatosis, ballooning, and fibrosis. Recent studies have demonstrated strong correlations between AI-derived and pathologist-assigned grades, underscoring AI's potential to enhance diagnostic precision and reproducibility. However, challenges including high operational costs, limited large-scale validation, population heterogeneity, and lack of regulatory frameworks remain barriers to clinical translation. Expanding research, developing standardized protocols, and establishing robust policies are essential for widespread adoption. AI-based pathology could revolutionize the diagnostic paradigm for liver disease, enabling earlier detection, improved patient stratification, and precision care in NASH.

Source: Annals of Medicine and Surgery

DOI: 10.1097/ms9.0000000000003997

Authors: Ayesha Ejaz, Mehreen Mushtaq Ahmed, Maliha Khalid, Muhammad Talha, Aminath Waafira

Institutions: King Edward Medical University, Hayatabad Medical Complex, Jinnah Sindh Medical University, Maldives National University

Language: English

Topic: Liver Disease Diagnosis and Treatment

Subfield: Epidemiology

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $1,850