HistoIndex to Showcase Groundbreaking AI-powered Stain-free Digital Pathology Advances with 8 Accepted Abstracts at EASL Congress 2024

  • Company to deliver two oral and six poster presentations, including one TOP poster and one selected for poster tour, further reinforcing its leadership position in MASH digital pathology.
  • HistoIndex’s AI-driven solutions provide unprecedented insights into the direct prediction of patient clinical outcomes such as fibrosis progression, hepatic decompensation, and all-cause mortality.
  • Company will host a breakfast meeting on June 5th to explore the transformative potential of stain-free digital pathology and AI in current MASH clinical trials and its prospective role in the clinical/treatment management of MASH patients post drug approval.

SINGAPORE, June 3, 2024 /PRNewswire/ — HistoIndex, a global leader in stain-free AI-powered digital pathology solutions, today announced its strong presence at the upcoming European Association for the Study of the Liver (EASL) Congress 2024. The annual EASL Congress is Europe’s largest event in this domain where cutting-edge research and innovations in liver diseases are presented. The Company’s stain-free Second Harmonic Generation/Two-Photon Excitation (SHG/TPE) imaging and AI solutions will be featured in a total of 8 accepted abstracts, including two oral presentations, one TOP poster, and one poster presented during a poster tour at the conference. These accomplishments underscore HistoIndex’s pioneering role in advancing Metabolic dysfunction-associated steatohepatitis (MASH) and Metabolic dysfunction-associated steatotic liver disease (MASLD) digital pathology through innovative AI-based technologies.

The oral presentations will provide first-hand evidence that assessments using fibrotic features identified by qFibrosis outperform ordinal scoring in predicting fibrosis progression, all-cause mortality, and hepatic decompensation. qFibrosis is a quantitative fibrosis tool that provides measures of specific collagen parameters for reproducible and accurate assessments of fibrosis changes, surpassing the limitations of the current gold standard of manual observational assessment.

Accepted as a late-breaker, the oral presentation by Dr. Jörn M Schattenberg, Professor of Medicine and Director of the Department of Medicine II at the University Medical Center Homburg and the University of the Saarland Germany, compares the specific fibrotic features identified by qFibrosis with ordinal scoring and NITs in their correlation to fibrosis progression. Commenting on the significance of this work, Dr. Schattenberg stated, “There is a need to improve the methods we are currently using, such as the ordinal scoring and NITs, to capture dynamic fibrotic changes happening in MASH. AI-based assessments are tools we can adopt to help us identify more specific features that correlate to fibrosis progression, capturing the fibrosis heterogeneity we see in MASH.”

In the second oral presentation, Dr. Timothy Kendall will share the improved performance of predictive indices of all-cause mortality and hepatic decompensation derived from quantified fibrosis parameters provided by qFibrosis that are unapparent to human observers.

As part of the poster tour, Dr. Dean Tai, Chief Scientific Officer and co-founder of HistoIndex will demonstrate the Company’s innovative approach to detecting and quantifying ballooned hepatocytes, a critical feature in MASH assessment, as well as in MASH resolution for trial endpoints. Based on a consensus group of 9 internationally recognized expert liver pathologists who worked together with HistoIndex over the past four years, this tool builds consensus among pathologists in identifying ballooned cells, increasing reproducibility in assessments, specifically in the patient inclusion and efficacy evaluation phases in MASH drug trials.

“Our growing presence at EASL 2024 reflects HistoIndex’s unwavering commitment to advancing liver digital pathology through our proprietary stain-free imaging and AI-driven solutions,” said Dr. Gideon Ho, CEO of HistoIndex. “We are excited to share our latest findings and discuss how our tools can complement and assist pathologists in assessing, predicting, and treating MASH.”

Further information on key abstracts featuring HistoIndex technology that will be presented at EASL 2024 can be found below:

Oral Presentation (Friday, June 7th, 5:15 – 5:30 PM, Gold Room)
Title: Identification and validation of pre-identified morphological baseline features for prediction of fibrosis progression in MAESTRO-NASH
Presenter: Dr. Jörn M Schattenberg
Presentation ID: OS-124

Oral Presentation (Friday, June 7th, 5:45 – 6:300 PM, Space 1+2)
Title: Stain-free digital pathology imaging provides microarchitecturally-resolved insights into scar evolution, allowing direct clinical outcome prediction in MASLD
Presenter: Dr. Timothy Kendall
Presentation ID: OS-087

Poster Tour (Saturday, June 8th, 12:15 AM12:22 PM, Track Hub: Metabolism, Alcohol & Toxicity)
Title: qBallooning: AI-based ballooned hepatocyte detection and quantification by second harmonic generation/two-photon excitation microscopy
Presenter: Dr. Dean Tai
Poster Number: FRI-208

Poster Presentations
Title: Assessment of fibrosis change rates in placebo arm of metabolic dysfunction-associated steatohepatitis drug trials based on pathologist readouts and qFibrosis continuous values
Time and Location: Wednesday, June 5th, Poster Area
Presenter: Dr. Kutbuddin Akbary
Poster Number: WED-213

Title: AI digital pathology unmasked the “No Change” in conventional pathological assessment of MASLD patients with one year lifestyle intervention in a prospective cohort study
Time and Location: Wednesday, June 5th, Poster Area
Presenter: Dr. Xiaoxue Zhu
Poster Number: WED-319

Title: Validation of optimal liver biopsy size for reliable quantitation of fibrosis severity in different areas and structures of liver lobule using second harmonic generation microscopy with artificial intelligence analyses
Time and Location: Friday, June 7th, Poster Area
Presenter: Prof. Nikolai V Naoumov
Poster Number: FRI-203

Title: Regional fibrosis progression analysed by digital pathology with artificial intelligence is associated with renal dysfunction
Time and Location: Friday, June 7th, Poster Area
Presenter: Prof. Minghua Zheng
Poster Number: FRI-267

Title: Genetic determinants of disease progression in metabolic dysfunction-associated liver disease patients unresponsive to lifestyle intervention: implications for personalized medicine
Time and Location: Friday, June 7th, Poster Area
Presenter: Mr. Aruhan Yang
Poster Number: TOP-310

About MASLD and MASH

Metabolic dysfunction-associated steatotic liver disease (MASLD), previously known as non-alcoholic fatty liver disease (NAFLD), is a condition characterized by the buildup of fat in the liver, which is not caused by alcohol consumption. MASLD is closely associated with obesity, type 2 diabetes, and other metabolic disorders. It is a spectrum of liver disorders ranging from simple steatosis (fatty liver) to a more severe form called metabolic dysfunction-associated steatohepatitis (MASH), formerly referred to as non-alcoholic steatohepatitis (NASH).

MASH is a progressive form of MASLD characterized by liver inflammation and damage, 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. Currently, liver biopsy is the gold standard for diagnosing and assessing the severity of MASH. However, in MASH drug trials, surrogate endpoints such as histological categorial scoring systems are often used to evaluate drug efficacy. These endpoints have limitations 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 accelerate the development of effective therapies for MASH.

About qFibrosis

qFibrosis® is an automated, quantitative technique to evaluate liver fibrosis in patients with MAFLD and MASH. Using artificial intelligence (AI) to analyze liver biopsy images, it provides quantitative measures of specific collagen features relative to the spatial zones of a liver lobule. This multi-parametric quantitative assessment provides a continuous measure of fibrosis to lend greater sensitivity in treatment response evaluations, compared to current categorial scoring systems.

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. The Company’s breakthrough digital pathology solutions are accelerating research, expediting pharmaceutical drug development, and transforming medical standards,

 

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