AI.Dx MASH

A Lab Developed Test (LDT) using AI-Assisted Scoring for MASLD/MASH staging

Introducing AI.Dx MASH: A World’s First Lab Developed Test (LDT) using AI-Assisted Scoring for MASLD/MASH staging

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Instances of Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) are Growing

A growing number of people are being impacted by Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD, formerly Non-Alcoholic Fatty Liver Disease, or NAFLD), and potentially progressing to Metabolic Dysfunction-Associated Steatohepatitis (MASH, formerly Non-Alcoholic Steatohepatitis or NASH).^1-3

8% of the global adult population is estimated to have Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD)¹
5-6% of the U.S. adult population is estimated to have Metabolic Dysfunction-Associated Steatohepatitis (MASH)^2,3
8 Million people are estimated to be living with significant fibrosis without cirrhosis²

Significant Variability Exists in Inter- and Intra-observer Scores

While biopsy is the gold standard for histologic scoring and staging of MASH,^4,5 there is significant variability in inter- and intra-observer scores of each histologic feature that contributes to the overall Clinical Research Network (CRN) Score to assess whether a patient has MASH and how far the disease has progressed:^6,7

31% Discordance between pathologists on MASH diagnosis⁷
59% Intra-reader agreement on MASLD Activity Score when reviewing the same case⁷

An inaccurate assessment of disease progression can mean that the patient is unaware of the severity of their disease,^8,9 with each change in fibrosis stage resulting in a two-fold increase in liver-related mortality⁹

Utilizing AI to Reduce Scoring Variability

A world’s first, AI.Dx MASH utilizes AI, generated from over 100,000 annotations across over 5,900 biopsies to significantly reduce scoring variability in CRN Scoring for MASH histologic scoring.^6,10,11

Additional Features

Image overlay showing the extent of steatosis, lobular inflammation, hepatocellular ballooning and fibrosis^10,11*
Area quantification of histologic features^10,11*

Steatosis
(Yellow)

Hepatocellular Ballooning
(Blue)

Lobular Inflammation
(Green)

Fibrosis
(Orange)

Interested in learning more?

Contact our Client Services Team if you would like to talk to a sales representative [email protected].

Download the AI.Dx MASH Brochure

References

1. Riazi K, Azhari H, Charette JH, Underwood FE, King JA, Afshar EE, et al. The prevalence and incidence of NAFLD worldwide: a systematic review and meta-analysis. The Lancet. 2022;7(9):851-861.

2. Estes C, Razavi H, Loomba R, Younossi Z, Sanyal AJ. Modeling the epidemic of nonalcoholic fatty liver disease demonstrates an exponential increase in burden of disease. Hepatology. 2018;67(1):123-133.

3. Diehl AM, Day C. Cause, pathogenesis, and treatment of nonalcoholic steatohepatitis. N Engl J Med. 2017;377(21):2063-2072.

4. Berger d, Desai V, Janardhan S. 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.

5. Arab JP, Barrera F, Arrese M. The evolving role of liver biopsy in non-alcoholic fatty liver disease. Annals of Hepatology (2018); 17(6):899-902.

6. Kleiner DE, Brunt EM, Van Natta M, et al. Design and validation of a histological scoring system for nonalcoholic fatty liver disease. Hepatology 2005;41:1313–21.

7. Davison B, et al. Suboptimal reliability of liver biopsy evaluation has implications for randomized clinical trials. J Hepatol (2020);73(6):1322-1332.

8. Taylor 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.

9. Pokkala 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.

10. Carrasco-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.

11. Harrison 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.

*The clinical relevance and impact of image heat maps and area quantitation has not been determined.

Laboratory Developed Test (LDT). This test was developed and its performance characteristics determined by Poplar Healthcare (dba PathAI Diagnostics) in a manner consistent with CLIA requirements. This test has not been cleared or approved by the U.S. Food and Drug Administration. This test is intended to be used as an adjunct to existing clinical and pathologic information currently used for diagnosis of Non-alcoholic steatohepatitis (NASH) by liver biopsy.