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Morphometry and digital AgNOR analysis in cytological imprints of benign, borderline and malignant serous ovarian tumours.

机译:形态学和数字AgNOR分析在良性,交界性和恶性浆液性卵巢肿瘤的细胞学印记中。

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AIM: The aim of the study was to determine values of a quantitative morphometry analysis of nuclear characteristics and argyrophilic nucleolar organizer regions (AgNORs) in differential cytodiagnosis of benign, atypically proliferating (borderline) and malignant serous ovarian tumours. METHODS: Cytological imprints of benign (n = 20), borderline (n = 19) and malignant (n = 20) ovarian serous tumours were analysed. A computerized, digital analysis was used to determine morphometric nuclear features, the number and characteristics of single AgNORs, cluster AgNORs, total AgNOR and AgNOR areaucleus (relative area) ratio. According to their size AgNORs were classified in three categories. A one-way variance analysis and post hoc test (Scheffe) were used for statistical analysis. RESULTS: The morphometric nuclear analysis showed that benign, borderline and malignant serous ovarian tumours are statistically different (P < 0.001) according to the area and outline, the values being highest in malignant tumours and lowest in the borderline group. Digital analysis of AgNORs in benign, borderline and malignant groups showed that the total AgNOR number increases with progression of the lesion (meaning tumour malignancy) significantly (P < 0.001) between benign and malignant as well as between borderline and malignant serous ovarian tumours (P < 0.001). The progression of the lesion malignancy was accompanied by a significant (P < 0.001) progressive increase of the total and relative AgNOR area per nucleus. The AgNOR size increases from benign to malignant tumours and a statistically significant difference (P < 0.001) was observed in all three groups regarding small and large AgNORs. CONCLUSION: Combining different markers of morphometric nuclear characteristics and AgNOR values could improve differential cytodiagnosis of benign, borderline and malignant serous ovarian tumours.
机译:目的:该研究的目的是确定核形态学特征和嗜银核仁组织区(AgNORs)定量形态分析在鉴别良性,非典型性增生(边界)和恶性浆液性卵巢肿瘤的细胞学诊断中的价值。方法:分析良性(n = 20),交界性(n = 19)和恶性(n = 20)卵巢浆液性肿瘤的细胞学印记。使用计算机化的数字分析来确定形态核特征,单个AgNOR的数量和特征,AgNOR簇,总AgNOR和AgNOR面积/核(相对面积)之比。根据其大小,AgNOR分为三类。使用单向方差分析和事后检验(Scheffe)进行统计分析。结果:形态核学分析显示,根据区域和轮廓,良性,交界性和恶性浆液性卵巢肿瘤在统计学上有差异(P <0.001),其值在恶性肿瘤中最高,在交界性组中最低。良性,边缘性和恶性组中AgNORs的数字分析表明,良性和恶性之间以及边缘性和恶性浆液性卵巢肿瘤之间(P <0.001)。病变恶性程度的进展伴随着每个核的总和相对AgNOR面积的显着(P <0.001)逐渐增加。从良性肿瘤到恶性肿瘤,AgNOR的大小均增加,并且在大小AgNOR的所有三个组中,均观察到统计学显着性差异(P <0.001)。结论:结合形态学核特征和AgNOR值的不同标志物可以改善对良性,交界性和恶性浆液性卵巢肿瘤的鉴别诊断。

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