Joint zonated quantification of multiple parameters in hepatic lobules

Area of Science:

• Hepatology
• Medical Image Analysis
• Biochemistry

Background:

• Liver diseases and metabolic functions exhibit distinct spatial zonation within the hepatic lobule.
• Understanding the interplay between disease zonation and metabolic zonation is crucial for liver disease research.

Purpose of the Study:

• To develop and validate an image analysis workflow for the joint quantification of disease and metabolic parameters in zonated liver tissue.
• To enable visualization and analysis of how liver conditions impact metabolic zonation.

Main Methods:

• Utilized whole-slide images of serially sectioned mouse livers stained for histology (HE, GS) and cytochrome P450 (CYP) enzymes.
• Employed image registration to align serial sections, identifying lobules and dividing them into twelve intralobular zones.
• Quantified and visualized zonal distributions of multiple parameters from different stained sections.

Main Results:

• Successfully identified and analyzed the same lobules and zones across consecutive serial sections.
• Visualized heterogeneous expression patterns of marker proteins in normal and steatotic livers.
• Demonstrated the workflow's capability to map zonal distributions of various quantified parameters.

Conclusions:

• The developed image analysis workflow allows for the joint quantification of zonated liver diseases and metabolic functions.
• This approach provides a powerful tool for investigating the impact of liver pathologies on metabolic zonation and function.
• Future applications include quantifying the effects of steatosis severity on CYP enzyme expression and metabolic function.