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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.
Insights
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.
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:
- 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.
Abstract:
A methodological approach by computerized image analysis to quantify immunostained objects in histological sections is described. We have investigated antibodies against CD4, CD8, CD20, CD23 and CD25 in frozen sections of human nasal mucosa; however, the methodology of standardization is of general validity. The study was designed particularly to investigate the following points: 1) light intensity, 2) the grey level for counter staining intensity, 3) the grey level threshold value for positive objects, 4) the minimal acceptable size of a positive object, 5) the influence of the brightness of the light on both the number and the area of objects. Furthermore, random sampling and determination of 6) the area per section, and 7) the number of histological sections to be measured per biopsy. Finally, a study of reproducibility of immunostaining intensity was performed. The influence of the different parameters mentioned above was studied and the values (eg. threshold value) for our particular setting of microscope, image analysis equipment, computer software etc, were defined. The method was then tested for intra- and interindividual variation which was found to be less than 5%. Correlation analysis of the reproducibility gave coefficients of correlation of 0.99, both concerning number of immunopositive objects and immunopositive area. We emphasize the importance of a highly standardized methodology if the numeric data obtained from computer assisted image analysis are to be more accurate than semiquantitative assessments by experienced observers. With a thorough standardization as described in this method it is possible to obtain numeric values, and data with low deviations, which are two obvious and important advantages.