AI-Based Pathology Tool Validated for MASH Scoring in Clinical Trials
A multisite clinical validation study demonstrated that AIM-MASH, an AI-based digital pathology system, significantly reduces reader variability in metabolic dysfunction-associated steatohepatitis histology scoring. AI-assisted reads by expert pathologists were superior to unassisted reads for inflammation, ballooning, and MASH resolution assessment, while maintaining non-inferiority for steatosis and fibrosis. The system addresses a critical bottleneck in MASH drug development where subjective biopsy scoring has long hindered reliable therapeutic endpoint assessment.
The original study
Clinical validation of an AI-based pathology tool for scoring of metabolic dysfunction-associated steatohepatitis.
- Authors
- Pulaski H, Harrison SA, Mehta SS, Sanyal AJ, Vitali MC, Manigat LC, et al.
- Journal
- Nature medicine
- Type
- Journal Article, Validation Study
- PMID
- 39496972
Original abstract
Metabolic dysfunction-associated steatohepatitis (MASH) is a major cause of liver-related morbidity and mortality, yet treatment options are limited. Manual scoring of liver biopsies, currently the gold standard for clinical trial enrollment and endpoint assessment, suffers from high reader variability. This study represents the most comprehensive multisite analytical and clinical validation of an artificial intelligence (AI)-based pathology system, AI-based measurement of metabolic dysfunction-associated steatohepatitis (AIM-MASH), to assist pathologists in MASH trial histology scoring. AIM-MASH demonstrated high repeatability and reproducibility compared to manual scoring. AIM-MASH-assisted reads by expert MASH pathologists were superior to unassisted reads in accurately assessing inflammation, ballooning, MAS ≥ 4 with ≥1 in each score category and MASH resolution, while maintaining non-inferiority in steatosis and fibrosis assessment. These findings suggest that AIM-MASH could mitigate reader variability, providing a more reliable assessment of therapeutics in MASH clinical trials.