SINGAPORE, Dec. 9, 2024 /PRNewswire/ — A newly published collaborative
Figure 1. Read without AI-assistance vs. read with AI-assistance [2]
“I am excited about the findings of this study, which highlight how AI-assisted SHG/TPEF imaging and quantitative fibrosis scoring have improved inter-pathologist agreement, especially for early-stage fibrosis (F0-F2).” said Dr. Arun Sanyal, M.D., Professor of Medicine, Physiology and Molecular Pathology at Virginia Commonwealth University School of Medicine, and Principal Investigator of the study. “This increased accuracy not only enhances confidence in staging but also has the potential to streamline clinical trial processes and reduce the need for third-pathologist adjudication.”
“Witnessing the journey of this study from concept to fruition has been incredibly rewarding, made possible by the collaboration across global teams.” said Dr. Gideon Ho, CEO of HistoIndex, “The findings, especially the improvement in inter-pathologist agreement with AI-assistance, are set to transform both clinical trial assessments that transcend into precise and personalized care for MASH patients.”
This study marks a significant step forward in leveraging AI to aid pathologists in both MASH clinical trials and routine patient care, offering a promising pathway for improving consistency and accuracy in diagnosing and managing MASH as a global health challenge.
About MASH
Metabolic dysfunction-associated steatohepatitis (MASH) is a progressive form of Metabolic dysfunction-associated steatotic liver disease (MASLD) characterized by steatosis and inflammation, which can lead to fibrosis (scarring), cirrhosis, liver failure, and an increased risk of liver cancer. The presence of ballooned hepatocytes (enlarged and damaged liver cells) is a key feature distinguishing MASH from simple steatosis. Pathologist assessments of liver biopsy remain the gold standard for diagnosing and assessing the severity of MASH. Histological categorial scoring systems are often used as surrogate endpoints to evaluate drug efficacy in clinical trials. These endpoints are limited in capturing the complex and heterogeneous nature of the disease. As a result, there is a growing need for more accurate and reliable tools, such as AI-based digital pathology solutions, to improve the assessment of treatment response and disease severity in MASH.
About HistoIndex
Founded in 2010, HistoIndex pioneers in stain-free, fully automated imaging solutions for visualizing and quantifying fibrosis in biological tissues. By combining cutting-edge biophotonic technology with AI-based analysis, HistoIndex provides innovative tools to improve the assessment of fibrosis changes and drug efficacy. HistoIndex’s breakthrough digital pathology solutions are currently used in accelerating clinical research, expediting pharmaceutical drug development, and transforming medical standards.
References:
[1] “Utility of AI digital pathology as an aid for pathologists scoring fibrosis in MASH” DOI: 10.1016/j.jhep.2024.11.032 |
[2] Adapted from Graphical Abstract in “Utility of AI digital pathology as an aid for pathologists scoring fibrosis in MASH” by Desiree Abdurrachim et al. |
