Diagnostic Algorithm to Reflect Regressive Changes of Human Papilloma Virus in Tissue Biopsies

다국어 초록 (Multilingual Abstract)

Purpose: Landmark indicators have not yet to be developed to detect the regressionof cervical intraepithelial neoplasia (CIN). We propose that quantitative viral load and indicative histological criteria can be used to differentiate between atypicalsquamous cells of undetermined significance (ASCUS) and a CIN of grade 1. Materials and Methods: We collected 115 tissue biopsies from women who testedpositive for the human papilloma virus (HPV). Nine morphological parameters including nuclear size, perinuclear halo, hyperchromasia, typical koilocyte (TK), abortive koilocyte (AK), bi-/multi-nucleation, keratohyaline granules, inflammation,and dyskeratosis were examined for each case. Correlation analyses, cumulativelogistic regression, and binary logistic regression were used to determine optimalcut-off values of HPV copy numbers. The parameters TK, perinuclear halo, multi-nucleation, and nuclear size were significantly correlated quantitatively to HPV copy number. Results: An HPV loading number of 58.9 and AK number of 20 were optimal to discriminate between negative and subtle findings in biopsies. An HPV loading number of 271.49 and AK of 20 were optimal for discriminating between equivocal changes and obvious koilocytosis. Conclusion: We propose that a squamous epithelial lesion with AK of >20 and quantitative HPV copy numberbetween 58.9-271.49 represents a new spectrum of subtle pathological findings,characterized by AK in ASCUS. This can be described as a distinct entity and called “regressing koilocytosis”.

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