Adopting AI-assisted digital pathology imaging analysis in MASH histology assessments

Metabolic Dysfunction Associated Steatotic Liver Disease (MASLD) is the most common chronic liver disease worldwide, associated with considerable clinical and economic burden. Early detection and timely intervention of Metabolic Dysfunction Associated Steatohepatitis (MASH) remains a key cornerstone of management. Traditionally, histopathology assessment is central to the characterization of MASH disease activity and fibrosis, albeit with inherent limitations. The advent of artificial intelligence (AI) has provided transformative tools to augment many aspects of MASH diagnostics, including histology assessment. New technologies enabling digitalization of pathology slides and allowing for further AI assisted model analysis have helped to address some of the previous limitations. In this review, we highlight the key AI assisted digital pathology tools, including utility, performance and clinical impact. Limitations and real-world considerations in adopting these AI tools are also explored.