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尿路上皮乳头状病变中进行性核异常的定量评估。

Quantitative evaluation of the progressive nuclear abnormalities in urothelial papillary lesions.

作者信息

Montironi R, Scarpelli M, Ansuini G, Pisani E, Del Fiasco S, Mariuzzi G M

出版信息

Appl Pathol. 1986;4(1-2):65-73.

PMID:3580195
Abstract

The natural history of noninvasive urothelial papillary carcinomas is characterized by structural and nuclear abnormalities of the epithelial lining in the three grades. Morphometry is applied to measure nuclear-related quantitative parameters from the lower (L) and upper (U) halves of urothelial thickness, i.e. perimeter, area and roundness factor. Their mean and SD as well as the derived parameters have values steadily higher from normal-looking urothelium to G3, whereas the relative frequency distribution shows over-lapping among the grades. The multivariate analysis is then applied. First of all the smallest number of least correlated and most discriminant features is selected: SD of nuclear area log (L), percentage of round nuclei (L), mean of the 10 largest values of nuclear area (L) and mean nuclear perimeter (L). The results of the pattern recognition analysis based on these features show the following percentages of agreement between histopathological and computer classifications: 94% in the training set and 80% in the test set. The calculation of the classification probability and the adoption of a threshold approach of 0.25 less than P less than 0.75 are helpful in identifying the 'in-between' cases, i.e., those in the 'intermediate' position between G1 and G2 and between G2 and G3. Morphometry and multivariate analysis allow us to quantify the nuclear abnormalities of urothelial papillary carcinomas and show a progressive and continuous spectrum of modifications.

摘要

非侵袭性尿路上皮乳头状癌的自然病史以三个级别的上皮衬里的结构和核异常为特征。形态计量学用于测量尿路上皮厚度下半部(L)和上半部(U)与核相关的定量参数,即周长、面积和圆度因子。从外观正常的尿路上皮到G3,它们的平均值、标准差以及导出参数的值稳步升高,而相对频率分布显示各级之间存在重叠。然后应用多变量分析。首先选择数量最少、相关性最小且最具判别力的特征:核面积对数(L)的标准差、圆形核百分比(L)、核面积10个最大值的平均值(L)和平均核周长(L)。基于这些特征的模式识别分析结果显示,组织病理学分类与计算机分类之间的一致性百分比为:训练集中为94%,测试集中为80%。分类概率的计算以及采用小于P小于0.75且差值为0.25的阈值方法有助于识别“中间”病例,即在G1和G2之间以及G2和G3之间处于“中间”位置的病例。形态计量学和多变量分析使我们能够量化尿路上皮乳头状癌的核异常,并显示出渐进性和连续性的改变谱。

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