False-Positive Atypical Endocervical Cells in Conventional Pap Smears: Cyto-Histological Correlation and Analysis

Abstract

Introduction: Endocervical glandular atypia is relatively rarely diagnosed by Pap smears. A significant proportion of follow-up histological samples show no premalignant or malignant lesions. The observed cytomorphological findings in premalignant glandular lesions overlap with histologically proven reactive lesions. Methods: A total of 45 conventional Pap smears diagnosed as atypical endocervical cells, not otherwise specified (AEC, NOS) with human papillomavirus (HPV) status available were blindly evaluated in a search for 38 cytomorphological features representing background, architectural, cellular and nuclear features. Of the cases, 30 represented histologically proven benign changes, and 15 represented histologically proven adenocarcinoma in situ (AIS) or endocervical adenocarcinoma (EAC) cases. The benign biopsies were re-evaluated, and the associations of the cytomorphological features or combinations of them with specific histological features and entities were statistically examined. Results: The most frequent histological findings in the benign group were squamous metaplasia, inflammation, tubal metaplasia and microglandular hyperplasia. The statistical analysis revealed cytological features associated with squamous metaplastic changes, inflammation and microglandular hyperplasia. Unfortunately, no cytomorphological feature was sufficiently specific to confidently leave the lesion without follow-up and histological correlation. Degeneration and nuclear crowding were the most salient features that distinguished the instances of glandular atypia with benign follow-up histology from those with histologically proven AIS or EAC (26.7% vs. 60.0%, P= 0.030 and 50.0% vs 86.7%, P = 0.017). Conclusion: Additional methods besides cytomorphology are required to reliably distinguish smears with AEC, NOS harbouring only benign histological changes from those exhibiting endocervical glandular malignancy.

Comparison of Segmentation Analysis in Nucleus Detection with GLCM Features using Otsu and Polynomial Methods

“…These images can provide insights into the condition of each cell [7], but they tend to be challenging and susceptible to errors [8]. The primary source of error is the relatively small cell sizes and overlapping cell nuclei [9], making them challenging to identify [10], [11]. Therefore, image analysis is required in the image processing to assist in inspections and achieve more accurate results.…”