Tsybrovskyy O, Vassilenko I, Mannweiler S, Klimpfinger M
Department of Anatomic Pathology, State Medical University of Donetsk, Ukraine.
Virchows Arch. 1998 Aug;433(2):135-43. doi: 10.1007/s004280050228.
A retrospective analysis of 19 follicular adenomas, 12 minimally invasive follicular carcinomas and 3 widely invasive follicular carcinomas of the thyroid was performed on 5-microm-thick Feulgen-stained paraffin sections by means of a semiautomatic system for picture analysis. The major aim was to assess the potential of multiparameter karyometry for separation of the first two tumour types. Sixteen planimetric and densitometric features were defined in each case on 200-300 randomly selected nuclei and processed by a number of uni- and multivariate statistical methods. Despite predominantly significant ANOVA results a substantial overlap between tumour groups limited the practical usefulness of any karyometric feature alone. Factor and cluster analyses indicated independence of planimetric and densitometric parameters from each other, which was of crucial importance in finding an optimal subset of variables for discriminant analysis. The classification rule derived from the latter procedure was checked by the "jack-knife" method, by classification of 3 widely invasive cancers and by hierarchical tumour clustering. Sensitivity and specificity of the model for detection of malignancy were 100% and 94.7%, respectively. A multivariate karyometric approach, when applied correctly, can be a useful tool for differentiation between follicular adenomas and minimally invasive follicular carcinomas of the thyroid.
对19例甲状腺滤泡性腺瘤、12例微侵袭性滤泡癌和3例广泛侵袭性滤泡癌进行回顾性分析，采用半自动图像分析系统，在5微米厚的福尔根染色石蜡切片上进行分析。主要目的是评估多参数核测量法区分前两种肿瘤类型的潜力。在每种情况下，对200 - 300个随机选择的细胞核定义了16个平面测量和密度测量特征，并通过多种单变量和多变量统计方法进行处理。尽管方差分析结果大多具有显著性，但肿瘤组之间存在大量重叠，限制了任何单独核测量特征的实际应用价值。因子分析和聚类分析表明平面测量参数和密度测量参数相互独立，这对于找到判别分析的最佳变量子集至关重要。通过“留一法”、对3例广泛侵袭性癌症进行分类以及进行肿瘤层次聚类，对从后一程序得出的分类规则进行了检验。该模型检测恶性肿瘤的敏感性和特异性分别为100%和94.7%。正确应用多变量核测量方法可成为区分甲状腺滤泡性腺瘤和微侵袭性滤泡癌的有用工具。
