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Updated: Oct 16, 2025
A Standardized Method for the Analysis of Liver Sinusoidal Endothelial Cells and Their Fenestrations by Scanning Electron Microscopy
Published on: April 30, 2015
SOFTWARE-ASSISTED IMAGE ANALYSIS FOR IDENTIFICATION AND QUANTIFICATION OF HEPATIC SINUSOIDAL DILATATION AND
Douglas Mesadri Gewehr1,2,3, Allan Fernando Giovanini1, Sofia Inez Munhoz1,2
1Mackenzie Evangelical Faculty of Paraná, Curitiba, Paraná, Brazil.
Insights
A new semi-automatic protocol quantifies centrilobular fibrosis (CF) and sinusoidal lumen (SL) in liver Masson
Area of Science:
- Digital pathology
- Histopathology
- Medical image analysis
Background:
- Heart dysfunction and liver disease frequently coexist due to systemic conditions.
- Right ventricular failure can lead to hepatic congestion and fibrosis.
- Quantitative assessment of liver biopsy sections is crucial for diagnosing and grading chronic liver disease.
Purpose of the Study:
- Develop a semi-automatic computerized protocol for quantifying centrilobular fibrosis (CF) and sinusoidal dilatation (SL).
- Utilize Masson's Trichrome-stained liver specimens for analysis.
Main Methods:
- Liver samples were processed, stained with Masson's Trichrome, and scanned into whole-slide images.
- Regions of interest (ROIs) were selected for software-assisted image analysis using ImageJ®.
- An in-house Macro was developed to automatically process measurements and calculate CF and SL ratios.
Main Results:
- Empirical determination of optimal settings for identifying CF and SL across 250 ROIs.
- Establishment of color threshold settings for accurate quantification.
- Successful automatic batch processing for calculating fractional area and total area ratios.
Conclusions:
- A detailed method was successfully created to identify and quantify fibrous tissue and sinusoidal lumen.
- This protocol enhances the objective assessment of liver pathology in Masson's Trichrome-stained specimens.
Background:
Heart dysfunction and liver disease often coexist because of systemic disorders. Any cause of right ventricular failure may precipitate hepatic congestion and fibrosis. Digital image technologies have been introduced to pathology diagnosis, allowing an objective quantitative assessment. The quantification of fibrous tissue in liver biopsy sections is extremely important in the classification, diagnosis and grading of chronic liver disease.
Aim:
To create a semi-automatic computerized protocol to quantify any amount of centrilobular fibrosis and sinusoidal dilatation in liver Masson's Trichrome-stained specimen.
Method:
Once fibrosis had been established, liver samples were collected, histologically processed, stained with Masson's trichrome, and whole-slide images were captured with an appropriated digital pathology slide scanner. After, a random selection of the regions of interest (ROI's) was conducted. The data were subjected to software-assisted image analysis (ImageJ®).
Results:
The analysis of 250 ROI's allowed to empirically obtain the best application settings to identify the centrilobular fibrosis (CF) and sinusoidal lumen (SL). After the establishment of the colour threshold application settings, an in-house Macro was recorded to set the measurements (fraction area and total area) and calculate the CF and SL ratios by an automatic batch processing.
Conclusion:
Was possible to create a more detailed method that identifies and quantifies the area occupied by fibrous tissue and sinusoidal lumen in Masson's trichrome-stained livers specimens.
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