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淋巴结阴性乳腺癌的细胞核形态测量学

Nuclear morphometry in node-negative breast carcinoma.

作者信息

Giardina C, Renzulli G, Serio G, Caniglia D M, Lettini T, Ferri C, D'Eredità G, Ricco R, Delfino V P

机构信息

Institute of Pathological Anatomy and the Surgical Clinic, University of Bari, Italy.

出版信息

Anal Quant Cytol Histol. 1996 Oct;18(5):374-82.

PMID:8908309
Abstract

OBJECTIVE

To determine whether nuclear morphometry can confirm or add useful information to classic clinicopathological prognosticators to identify the subpopulation of breast carcinoma patients with node-negative (N-) disease, at high risk of disease relapse.

STUDY DESIGN

On the basis of results obtained by clinicopathologic evaluation of a group of patients with N- breast cancer, on a test group of 56 cases (32 patients disease free and 24 with relapse), we performed a morphometric analytical study of nuclei using the Shape Analytical Morphometry (SAM) software system; 20 nuclei for each case and 17 morphometric parameters for each nucleus were analyzed.

RESULTS

The SAM system allowed us to quantify shape differences in nuclei in terms of contour irregularities and asymmetries along with evaluation of nuclear dimensions. Dimensional and analytic parameters were subjected to univariate (Student's t test) and multivariate (Hotelling's test) analysis. Multivariate discriminant analysis showed that an exact forecast of disease relapse could be made in 77% of patients with N- breast cancer by using a set of six both analytic and dimensional parameters.

CONCLUSION

These results confirm that nuclear pleomorphism is the result of both contour irregularities and shape asymmetries and that even though they should be considered preliminary results, they stress the importance of quantitative shape evaluation.

摘要

目的

确定核形态测量法能否证实经典临床病理预后指标或为其增添有用信息,以识别疾病复发风险高的淋巴结阴性(N-)乳腺癌患者亚群。

研究设计

基于一组N-乳腺癌患者临床病理评估结果,在一个由56例患者组成的测试组(32例无病患者和24例复发患者)中,我们使用形状分析形态测量法(SAM)软件系统对细胞核进行了形态测量分析研究;对每个病例的20个细胞核以及每个细胞核的17个形态测量参数进行了分析。

结果

SAM系统使我们能够根据轮廓不规则性和不对称性以及核尺寸评估来量化细胞核的形状差异。对尺寸和分析参数进行了单变量(学生t检验)和多变量(霍特林检验)分析。多变量判别分析表明,通过使用一组六个分析和尺寸参数,可对77%的N-乳腺癌患者的疾病复发做出准确预测。

结论

这些结果证实核多形性是轮廓不规则性和形状不对称性共同作用的结果,并且尽管这些应被视为初步结果,但它们强调了定量形状评估的重要性。

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