Non-Alcoholic Steatohepatitis (NASH)

Non-alcoholic fatty liver disease (NAFLD) has become the most common cause of chronic liver disease in the Western world. NAFLD is a complex spectrum of liver diseases ranging from benign hepatic steatosis to its more aggressive necro-inflammatory manifestation, non-alcoholic steatohepatitis (NASH). Rodent models of NAFLD/NASH are important for understanding the etiology of this disease and are valuable in the development of efficient therapies for this condition. A valuable approach for evaluation of therapeutic response directly within liver tissue from a rodent NASH model is utilization of histology combined with digital image analysis.

Analysis Approach
A customised classifier algorithm is developed to classify liver parenchyma (green analysis mask) and exclude prominent vasculature structures (red analysis mask). A vacuole algorithm is then utilized to developed to detect steatotic vacuoles within the Liver Parenchyma ROI (red analysis mask). Detection of vacuoles within tissue sections can be tailored to Client’s requirements based on size, circularity and pixel colour / intensity.

Example Readouts Include:

  • Area Liver Parenchyma (mm2)
  • Number of Vacuoles per mm2 Parenchyma
  • Area of Vacuoles as % of Parenchyma

Sample 1 (NASH Disease):

Liver NASH Analysis Sample 1 A)Original stained whole slide image. B) Classified regions in whole image showing: liver parenchyma (green analysis mask) and prominent vasculature structures (red analysis mask). C) Vacuole detection across whole tissue section. D) Original stained image at high magnification. E) Classified regions at high magnification. F) Vacuole detection at high magnification.

Liver NASH Analysis Sample 1 A)Original stained whole slide image. B) Classified regions in whole image showing: liver parenchyma (green analysis mask) and prominent vasculature structures (red analysis mask). C) Vacuole detection across whole tissue section. D) Original stained image at high magnification. E) Classified regions at high magnification. F) Vacuole detection at high magnification.

Sample 2 (Control):

Liver NASH Analysis Sample 2 A)Original stained whole slide image. B) Classified regions in whole image showing: liver parenchyma (green analysis mask) and prominent vasculature structures (red analysis mask). C) Vacuole detection across whole tissue section. D) Original stained image at high magnification. E) Classified regions at high magnification. F) Vacuole detection at high magnification.

Liver NASH Analysis Sample 2 A)Original stained whole slide image. B) Classified regions in whole image showing: liver parenchyma (green analysis mask) and prominent vasculature structures (red analysis mask). C) Vacuole detection across whole tissue section. D) Original stained image at high magnification. E) Classified regions at high magnification. F) Vacuole detection at high magnification.

Example Results:

Liver NASH Analysis Data

Liver NASH Analysis Data

Benefits

  • Custom algorithms allow accurate classification of regions of interest (ROI)
  • Accurate segmentation of normal parenchyma and vasculature area within the whole tissue section
  • The ability to quantify and classify the area of vacoules within each ROI
  • Objectively applied analysis across all study slides
  • Whole slide quantitative analysis increases the robustness of the data
  • Whole slide image overlays returned to the Client