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AI-assisted fibrosis scoring in MASH: Exploring pathologist decision-making with an SHG-based AI digital pathology

Desiree Abdurrachim¹, Aileen Wee², Gwyneth Soon²

¹Quantitative Biosciences, MSD, Singapore.

JHEP Reports : Innovation in Hepatology

|March 13, 2026

Summary

Second harmonic generation-based AI-powered digital pathology (AI-DP) shows promise in improving pathologist concordance for metabolic dysfunction-associated steatohepatitis (MASH) fibrosis scoring. While helpful, AI tools subtly influence decisions and can both reduce and increase scoring discrepancies, highlighting the need for careful integration.

Keywords:

AI MASH case study digital pathology fibrosis staging inter-reader variability pathologist assistance pathologist scoring second harmonic generation

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Area of Science:

Histopathology
Artificial Intelligence
Medical Imaging

Background:

Liver biopsy scoring for metabolic dysfunction-associated steatohepatitis (MASH) faces challenges due to intra- and inter-reader variability.
AI-powered digital pathology (AI-DP) offers a potential solution to enhance pathologist concordance.

Purpose of the Study:

To evaluate the impact of second harmonic generation (SHG)-based AI-DP on pathologist decision-making for MASH fibrosis scoring.
To provide guidance for integrating SHG-based AI assistance into pathology workflows.

Main Methods:

Four pathologists reviewed 120 MASH cases with and without an AI assistance tool.
Concordance, scoring changes, and pathologist perceptions were assessed via surveys and case reviews.
Qualitative analysis of 22 cases explored discrepancies and AI-pathologist interactions.

Main Results:

Pathologists found the AI tool helpful in 57% of cases and consciously changed scores in 12% more.
The tool reduced discrepancies in 65% of previously discordant cases but increased them in 27% of initially concordant cases.
Score shifts occurred even when the tool was deemed unhelpful, indicating subtle influence.

Conclusions:

SHG-based AI-DP tools are promising adjuncts for MASH fibrosis scoring, aiding pathologist concordance.
Practical insights for AI integration are provided, emphasizing collaborative human-AI approaches for precision histopathology.
Future AI development should address areas highlighted by pathologist-AI discrepancies to advance clinical trial outcomes.