PathAI Announces Launch of AI-based Measurement of Metabolic Dysfunction-Associated Steatohepatitis ("AIM-MASH") on the AISight Image Management System

Boston, MA – August 13, 2024PathAI, a global leader in artificial intelligence (AI) and digital pathology solutions, is proud to announce the launch of its AIM-MASH1 product on the AISight1 Image Management System (IMS). This product provides advanced AI-based measurement (AIM) to support the analysis of MASH Clinical Research Network (CRN) Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) Activity Score (MAS) component grades and fibrosis staging. The launch of AIM-MASH on AISight aims to increase the reproducibility and scalability of pathologists' assessments and management of MASH cases, which are projected to reach 27 million in the US alone by 20302.

PathAI's AIM-MASH AI-based measurement tools have been utilized in over 20 presentations and publications, demonstrating their effectiveness in assisting pathologists with MASH CRN scoring in clinical trials; bringing them to the AISight IMS enables a seamless connection between trial and laboratory settings. These tools have been rigorously evaluated via a comprehensive multi-site analytical validation study using diverse datasets from four different trials3. They have proven to be reliable and effective in helping pathologists make MASH assessments with:

       Highly Sensitive and Specific Review: AIM-MASH's model overlays have been validated by multiple pathologists for their high specificity and sensitivity in guiding reviews of MASH biopsies and accurately highlight key areas such as artifact, steatosis, hepatocellular ballooning, lobular inflammation, and fibrosis3.

       Repeatable and Reproducible Assessments: AIM-MASH algorithm outputs have shown higher repeatability and reproducibility compared to intra- and inter-pathologist agreement for manual reads, confirming its precision in measuring the CRN scoring system components in liver biopsies from MASH patients3.

       Increased Scoring Confidence: Validation studies have shown that AIM-MASH algorithm outputs are comparable to pathologist assessments, providing accurate first reads equivalent to those of expert pathologists to aid pathologists in their final assessment.3

       Global Collaboration: The AISight digital IMS allows expert GI Liver pathologists to review cases regardless of their location. This eliminates the need for time-consuming and costly shipping of glass slides and provides opportunities to utilize the MASH experts.

The practical application of AI in MASH assessments was highlighted in a recent case study conducted by PathAI Diagnostics (now Ameripath, at its Memphis, TN-based laboratory)4. This study demonstrated the synergy between traditional pathology and AI, showcasing how AI-assisted pathology can enable more precise evaluation of histologic features relevant to MASH, including steatosis, lobular inflammation, and fibrosis.

"We are thrilled to introduce AIM-MASH on the AISight IMS platform," said Andy Beck, MD, PhD, CEO of PathAI. "This product is a game-changer for drug development, as it supports pathologists in making high-quality, reproducible MASH assessments. With AIM-MASH on AISight, pathologists can increase their confidence in pathology reads and decision-making, as if they have the world's expert liver pathologists assisting with every slide, helping with simplifying the complex task of scoring and evaluation."

Dr. Arun J Sanyal, Professor and Interim-Chief of the Division of Gastroenterology, Hepatology, and Nutrition at Virginia Commonwealth University and co-investigator of the AIM-MASH analytical and clinical validation study, adds: "The data supports the use of AIM-MASH by pathologists in clinical trials as a method to resolve the accuracy and precision gaps in MASH assessment while guiding pathologists in an efficient evaluation to result in a standardized and reproducible score."

The addition of AIM-MASH broadens the set of tools available through AISight to assist pathologists in making reproducible and efficient assessments of MASH. This announcement addresses a crucial gap in pathology labs — the lack of a standardized system that ensures consistent, accurate, and reproducible assessments, particularly for challenging conditions like MASH. With AIM-MASH on AISight IMS, PathAI aims to provide digital and AI tools to assist pathologists in making precise and reproducible assessments at scale, along with workflow optimization features, empowering pathology labs worldwide.

About PathAI:

PathAI is a leading provider of integrated AI and digital pathology solutions, dedicated to transforming diagnostic accuracy and operational efficiency in pathology labs worldwide. Through innovative technologies and strategic partnerships, PathAI aims to enhance patient outcomes and drive the future of medical diagnostics.

References:

1:AIM-MASH and AISight are for Research Use Only. Not for use in diagnostic procedures.

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 Jan;67(1):123-133.  https://doi.org/10.1002/hep.29466. Epub 2017 Dec 1. PMID: 28802062; PMCID: PMC5767767.

3: Pulaski, Hanna, et al. “Analytical and Clinical Validation of AIM-NASH: A Digital Pathology Tool for Artificial Intelligence-Based Measurement of Nonalcoholic Steatohepatitis Histology.” MedRxiv (Cold Spring Harbor Laboratory), 29 May 2024, https://doi.org/10.1101/2024.05.29.24308109. Accessed 22 July 2024.

4: Kinsey, S., Reed, M., Parsell, T. “Practical Clinical Application of Artificial Intelligence in Metabolic Dysfunction Associated Steatohepatitis (MASH) – A Case Study Highlighting the Synergy between Traditional Pathology and AI.” PathAI, 2024.