Image analysis for accurately counting CD4+ and CD8+ T cells in human tissue

Area of Science:

• Immunology
• Virology
• Computational Biology

Background:

• In situ detection of immune cells provides insights into host-pathogen interactions.
• Traditional manual cell counting in tissue sections is time-consuming and subjective.
• Automated image analysis offers potential for faster and more accurate quantification.

Purpose of the Study:

• To compare manual cell counting with automated cell counting using CellProfiler.
• To evaluate the accuracy and efficiency of CellProfiler for analyzing immune cells in infected tissues.
• To assess the ability of CellProfiler to detect immune cell clustering.

Main Methods:

• Fluorescently labeled human genital skin biopsies from herpesvirus type 2 (HSV-2) infected subjects were analyzed.
• Manual cell counting was performed on tissue sections.
• Automated cell counting and clustering analysis were conducted using CellProfiler software.

Main Results:

• CellProfiler demonstrated high correlation with manual cell counting for both CD4+ and CD8+ T cells.
• Automated analysis accurately detected immune cell clustering, a key indicator of inflammation.
• CellProfiler provides a rapid and precise method for quantifying immune cells in situ.

Conclusions:

• CellProfiler is an effective and accurate tool for quantifying immune cells in fluorescently labeled biopsies.
• Automated analysis can supplement or replace manual counting in research and diagnostics.
• This approach enhances the study of immune responses in infectious diseases and other conditions.