Clinical validation of an AI-based pathology tool for scoring of metabolic dysfunction-associated steatohepatitis.

Journal: Nature medicine
PMID: 39496972

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.

Authors

  • Hanna Pulaski
    PathAI, Inc., Boston, MA, USA.
  • Stephen A Harrison
    Pinnacle Clinical Research, San Antonio, TX.
  • Shraddha S Mehta
    PathAI, Inc., Boston, MA, USA.
  • Arun J Sanyal
    Stravitz-Sanyal Institute for Liver Disease and Metabolic Health, Virginia Commonwealth University School of Medicine, Richmond, VA, USA.
  • Marlena C Vitali
    PathAI, Inc., Boston, MA, USA.
  • Laryssa C Manigat
    PathAI, Inc., Boston, MA, USA.
  • Hypatia Hou
    PathAI, Inc., Boston, MA, USA.
  • Susan P Madasu Christudoss
    PathAI, Inc., Boston, MA, USA.
  • Sara M Hoffman
    Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
  • Adam Stanford-Moore
    PathAI, Inc., Boston, MA, USA.
  • Robert Egger
    PathAI, Boston, Massachusetts.
  • Jonathan Glickman
    PathAI, Inc., Boston, MA, USA.
  • Murray Resnick
    PathAI, Boston, MA.
  • Neel Patel
    Department of Diagnostic Radiology, Oregon Health and Science University, Portland, Oregon.
  • Cristin E Taylor
    PathAI, Inc., Boston, MA, USA.
  • Robert P Myers
    Gilead Sciences, Inc., Foster City, CA.
  • Chuhan Chung
    Gilead Sciences, Inc., Foster City, CA.
  • Scott D Patterson
    Gilead Sciences, Inc., Foster City, CA, USA.
  • Anne-Sophie Sejling
    Novo Nordisk A/S, Søborg, Denmark.
  • Anne Minnich
    Bristol Myers Squibb, Princeton, NJ, USA.
  • Vipul Baxi
    Bristol Myers Squibb, Princeton, NJ, USA. Vipul.baxi@bms.com.
  • G Mani Subramaniam
    OrsoBio, Inc., Palo Alto, CA, USA.
  • Quentin M Anstee
    Translational & Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK.
  • Rohit Loomba
    From the Bioacoustics Research Laboratory, Department of Electrical and Computer Engineering (A.H., W.D.O.), and Department of Food Science and Human Nutrition (J.W.E.), University of Illinois at Urbana-Champaign, 306 N Wright St, Urbana, IL 61801; Department of Radiology (M.B., M.P.A.), Liver Imaging Group, Department of Radiology (E.H., C.B.S.), and NAFLD Research Center, Division of Gastroenterology, Department of Medicine (R.L.), University of California, San Diego, La Jolla, Calif; and Department of Ultrasound, Institute of Fundamental Technological Research, Polish Academy of Sciences, Warsaw, Poland (M.B.).
  • Vlad Ratziu
    Sorbonne Université, Assistance Publique-Hôpitaux de Paris, Hôpital Pitié Salpêtrière, Institute of Cardiometabolism and Nutrition (ICAN), Paris, France.
  • Michael C Montalto
    PathAI, Boston, MA.
  • Nick P Anderson
    PathAI, Inc., Boston, MA, USA.
  • Andrew H Beck
  • Katy E Wack
    PathAI, Inc., Boston, MA, USA. katy.wack@pathai.com.

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