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Related Experiment Videos

Quantitative computerized image analysis of immunostained lymphocytes. A methodological approach

M G Karlsson1, A Davidsson, H B Hellquist

  • 1Department of Pathology, Orebro Medical Center Hospital, Sweden.

Pathology, Research and Practice
|September 1, 1994
PubMed
Summary

This study presents a standardized method for quantifying immunostained cells in tissue using computerized image analysis. This approach ensures accurate, reproducible results for cell counting and area measurement in histological sections.

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Area of Science:

  • Immunohistochemistry
  • Digital Pathology
  • Quantitative Biology

Background:

  • Accurate quantification of immunostained cells in histology is crucial for research and diagnostics.
  • Traditional semiquantitative assessments can be subjective and lack precision.
  • Computerized image analysis offers potential for objective and reproducible cell quantification.

Purpose of the Study:

  • To describe and validate a standardized methodological approach for quantifying immunostained objects in histological sections using computerized image analysis.
  • To investigate key parameters influencing image analysis, including light intensity, grey levels, and object size thresholds.
  • To assess the reproducibility and accuracy of the developed method for cell counting and area measurement.

Main Methods:

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  • Development of a standardized protocol for computerized image analysis of immunostained human nasal mucosa sections (CD4, CD8, CD20, CD23, CD25).
  • Investigation of parameters: light intensity, counterstain grey level, positive object threshold, minimal object size, and brightness influence.
  • Determination of optimal sampling strategies (area per section, number of sections per biopsy) and reproducibility assessment.

    • Main Results:

    • The standardized method achieved high reproducibility, with intra- and inter-individual variations below 5%.
    • Correlation coefficients for reproducibility of both object number and area were 0.99.
    • Defined optimal parameter values (e.g., threshold values) for the specific microscope and image analysis system used.

    Conclusions:

    • A highly standardized methodology is essential for accurate numeric data from computer-assisted image analysis in histology.
    • The described method provides accurate, reproducible, and precise quantitative data, surpassing semiquantitative assessments.
    • This approach enables obtaining reliable numerical values with minimal deviation for research applications.