PathAI Diagnostics Unveils World’s First AI-Assisted Laboratory Developed Test for MASLD and MASH

PathAI: The test allows for the histologic scoring and staging of metabolic dysfunction-associated steatotic liver disease (MASLD) and metabolic dysfunction-associated steatohepatitis (MASH). It will be announced at the American College of Gastroenterology 2023 Meeting October 20-25 in Vancouver, Canada.

Boston, MA – October 19, 2023 – PathAI Diagnostics, a leading laboratory services company, today announced the world’s first AI-Assisted Laboratory Developed Test (LDT) for the histologic scoring and staging of metabolic dysfunction-associated steatotic liver disease (MASLD) and metabolic dysfunction-associated steatohepatitis (MASH). This pioneering advancement will be introduced at the American College of Gastroenterology 2023 (ACG2023) Meeting in Vancouver, Canada, from October 20-25.

MASLD and MASH are posing an escalating healthcare challenge, affecting millions of individuals worldwide. Recent estimates suggest that approximately 37.8% of the global adult population suffers from some form of MASLD, with 5-6% of the U.S. adult population at risk of progressing to MASH—a potential precursor to severe conditions such as cirrhosis and liver cancer.^1-3

While the gold standard for MASLD/MASH scoring is liver biopsy, the scoring provided by pathologists can exhibit variability.^4-5 In fact, there can be as much as a 30% disagreement in MASH diagnosis between pathologists, and intra-observer variability can reach up to 41% for the same case.⁶ Accurate scoring and staging are paramount, as each fibrosis stage corresponds to approximately a two-fold increase in liver-related mortality.⁷

In order to better tackle this growing issue, PathAI Diagnostics developed AI.Dx MASH, a laboratory developed test, which provides AI-assisted histologic scoring that supports expert pathologists with enhanced insights for liver biopsy reporting. “We are excited to bring the world’s first AI-assisted Laboratory Developed Test for MASH to market,” said Jim Sweeney, President of PathAI Diagnostics. “The tool uses our deep expertise in AI-powered pathology coupled with our world-class diagnostics laboratory to improve patient outcomes through AI-assisted histologic scoring for MASH.”

This groundbreaking tool utilizes an AI algorithm that has been proven to significantly reduce inter- and intra-operator variability in CRN scoring. Moreover, AI.Dx MASH reports include image overlays and quantitation, offering a comprehensive view of steatosis, lobular inflammation, hepatocyte ballooning, and fibrosis, thus facilitating more accurate diagnosis and staging.^8-11

“AI.Dx MASH provides a powerful tool for histologic MASH scoring by offering visual image overlays of key features to show how a score was reached,” said R. Shawn Kinsey, MD, gastrointestinal and hepatobiliary pathologist at PathAI Diagnostics. “This addresses one of the key challenges that leads to variability when assessing progression of the disease for a more accurate summary of a patient’s condition to inform future treatment and intervention.”

Learn more about AI.Dx MASH and PathAI Diagnostics at Booth 613 at the 2023 American College of Gastroenterologists Meeting in Vancouver, Canada, October 20-25. Alternatively, explore PathAI Diagnostic’s full range of anatomic and molecular pathology services, spanning gastroenterology, dermatology, urology, and women’s health, at www.pathaidx.com.

¹Riazi K, et al. The prevalence and incidence of NAFLD worldwide: a systematic review and meta-analysis. The Lancet. 2022;7(9):851-861.
²Estes C, et al. Modeling the epidemic of nonalcoholic fatty liver disease demonstrates an exponential increase in the burden of disease. Hepatology. 2018;67(1):123-133.
³Diehl AM, Day C. Cause, pathogenesis, and treatment of nonalcoholic steatohepatitis. N Engl J Med. 2017;377(21):2063-2072.
⁴Berger D, et al. Con: Liver Biopsy Remains the Gold Standard to Evaluate Fibrosis in Patients With Nonalcoholic Fatty Liver Disease. Clin Liver Dis (Hoboken). 2019 Apr;13(4):114–116.
⁵Arab JP, et al. The evolving role of liver biopsy in non-alcoholic fatty liver disease. Annals of Hepatology (2018);17(6):899-902.
⁶Davison B, et al. Suboptimal reliability of liver biopsy evaluation has implications for randomized clinical trials. J Hepatol (2020);73(6):1322-1332.
⁷Taylor RS, et al. Association Between Fibrosis Stage and Outcomes of Patients With Nonalcoholic Fatty Liver Disease: A Systematic Review and Meta-Analysis. Gastroenterology. 2020;158:1611-1625.
⁸Pokkala H, et al. Machine Learning Models Identify Novel Histologic Features Predictive of Clinical Disease Progression in Patients With Advanced Fibrosis Due to Nonalcoholic Steatohepatitis. EASL ILC 2020 Poster 2497.
⁹Carrasco-Zevallos O, et al. AI-based histologic measurement of NASH (AIM-NASH): A drug development tool for assessing clinical trial endpoints, EASL 2021 Abstract 1611.
¹⁰Harrison SA, et al. Analytical and Clinical Validation of AIM-NASH a Digital Pathology Tool for Artificial Intelligence-based Measurement of Nonalcoholic Steatohepatitis Histology. EASL 2023.
¹¹Loomba R, et al. Comparison of the effects of semaglutide on liver histology in patients with non-alcoholic steatohepatitis cirrhosis between machine learning model assessment and pathologist evaluation. Poster AASID 2022.

SOURCE: PathAI