An expanded cervical cell classification system validated by automated measurements

Abstract

The commonly used nomenclature for classifying cervical cells was expanded to include more classes, reflecting finer gradations of disease-related morphologic changes. Using a set of subjective visual criteria developed for this purpose, we visually classified 7,000 randomly selected cells and then subjected them to morphologic measurement by digital image analysis. Several of the measurements showed statistically significant differences among all the cell classes, indicating that it is possible to distinguish the finer morphologic gradations incorporated in the new system of cell classes. These same measurements showed a continuous trend of change from class to class along the scale from borderline dysplasia to carcinoma. This is consistent with the notion of a continuous progression of disease development. Finally, we found that those measurements that reflect the visual criteria used in the manual classification were significantly different between classes, indicating that the computer system can successfully quantify many of the important visual criteria.