OBJECTIVE: To present a computerized system for cell counting in histopathologic slides of meningioma and oligodendroglioma stained immunohistochemically against Ki-67 antigen and discuss the variability of tumor cell numbers in the field of view of analyzed neoplasms to standardize tumor cellularity. STUDY DESIGN: A computer program using an algorithm based on mathematical morphology was developed to perform quantitative evaluation of slides. That solution was combined with the Support Vector Machine used for classification of cell immunoreactivity. RESULTS: The mean number of cells in the analyzed field of view from patients with meningioma was 623. Of these, 95% were in the 386-781 cells range. In oligodendrogliomas the mean was 474 cells and all results were in the 204-736 range. The mean relative discrepancy between results of our system and human expert score was 8%. CONCLUSION: The proposed system appeared to be an efficient tool for supporting histopathologic diagnosis. The applied sequential thresholding simulated well the human process of cell recognition. Cellularity of the analyzed tumors did not show stability within the specimens from different patients. The results were also highly variable in different fields of view obtained from the same patient.
OBJECTIVE: To present a computerized system for cell counting in histopathologic slides of meningioma and oligodendroglioma stained immunohistochemically against Ki-67 antigen and discuss the variability of tumor cell numbers in the field of view of analyzed neoplasms to standardize tumor cellularity. STUDY DESIGN: A computer program using an algorithm based on mathematical morphology was developed to perform quantitative evaluation of slides. That solution was combined with the Support Vector Machine used for classification of cell immunoreactivity. RESULTS: The mean number of cells in the analyzed field of view from patients with meningioma was 623. Of these, 95% were in the 386-781 cells range. In oligodendrogliomas the mean was 474 cells and all results were in the 204-736 range. The mean relative discrepancy between results of our system and human expert score was 8%. CONCLUSION: The proposed system appeared to be an efficient tool for supporting histopathologic diagnosis. The applied sequential thresholding simulated well the human process of cell recognition. Cellularity of the analyzed tumors did not show stability within the specimens from different patients. The results were also highly variable in different fields of view obtained from the same patient.