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Metabolic Continuum Roundtable Contributors Author Journal Article on AI-Assisted Digital Pathology for NASH

February 1, 2024 – The Metabolic Continuum Roundtable announced today the publication of a journal article titled “Artificial Intelligence-Assisted Digital Pathology for Non-Alcoholic Steatohepatitis: Current Status and Future Directions” in the Journal of Hepatology. The article appears in volume 80, issue 2, on pages 335-351, February 2024, and can be accessed via DOI: 10.1016/j.jhep.2023.10.015.

The authors of this article include notable experts in the field: Vlad Ratziu, Marcus Hompesch, Mathieu Petitjean, Cindy Serdjebi, Janani Iyer, Anil Parwani, Dean Tai, Elisabetta Bugianesi, Kenneth Cusi, Scott L Friedman, Eric Lawitz, Manuel Romero-Gómez, Detlef Schuppan, Rohit Loomba, Valérie Paradis, Cynthia Behling, and Arun J Sanyal.

The forum, held during the Metabolic Continuum Roundtable’s annual meeting, brought together these authors to discuss the potential of AI-assisted digital pathology in the evaluation and treatment of non-alcoholic steatohepatitis (NASH). The article highlights the increasing global prevalence of NASH and the significant medical burden it poses. Despite the lack of approved therapeutics, NASH drug development heavily relies on the histological analysis of liver biopsies by expert pathologists for trial enrollment and efficacy assessment. This process faces several challenges, including sample heterogeneity, inter-reader and intra-reader variability, and the limitations of ordinal scoring systems.

To address these challenges, there is a high unmet need for accurate, reproducible, quantitative, and automated methods to assist pathologists. Digital pathology (DP) workflows combined with artificial intelligence (AI) have shown promise in other medical fields and are currently being explored for NASH. These DP/AI models can automatically detect, localize, quantify, and score histological parameters, potentially reducing scoring variability in NASH clinical trials.

The narrative review presented in the article provides a comprehensive overview of the DP/AI tools being developed for NASH, key regulatory considerations, and the potential impact of these advancements on the future of NASH clinical management and drug development. The authors emphasize the importance of prioritizing these developments to improve the creation of safe and effective therapeutics for NASH.

For more details, the abstract of the article can be found at Journal of Hepatology.