Image analysis of hyperchromatic crowded cell groups in SurePath cervical cytology

Abstract

The discrimination of hyperchromatic crowded cell groups (HCCGs) in cervical cytology is a difficult and error-prone interpretive task. While the classic features of dyskaryosis are of undoubted value, the contribution of size, shape and colour intensity of HCCGs is less certain. This study employed morphometric analysis to determine whether HCCG area, shape and colour intensity are useful in categorising them. Seventy-five digital images from each of six categories of HCCG were subjected to image analysis. Ten variables relating to HCCG size, shape and colour intensity were assessed by discriminant function analysis. A further 28 cases were employed as a test set to determine the classification accuracy of the discriminant model. All samples were SurePath liquid-based cytology preparations. Nine of the 10 variables contributed significantly to the model (P<0.001) but no single variable had sufficient discriminative ability. Classification accuracy was highest for abnormal endocervical HCCGs and lowest for squamous metaplastic cells (64.0 vs. 17.3% correct classification rate). The accuracy of the model for distinguishing normal and abnormal HCCGs was 70.0%, which was significantly higher than chance (P<0.0001), but this reduced to 64.3% for the test cases, which was no better than chance (P>0.05). The area, shape and colour intensity of HCCGs, either alone or in combination, have little discriminative value. Practitioners and trainers should focus on the well-established features of dyskaryosis, such as chromatin pattern, nuclear membrane irregularities and group architecture. In terms of morphometric analysis, DNA ploidy and chromatin texture analysis may be more fruitful avenues of investigation.