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高级别恶性淋巴瘤和反应性滤泡增生中细胞图像的自动识别

Automated recognition of cell images in high grade malignant lymphoma and reactive follicular hyperplasia.

作者信息

Bergmann M, Heyn H, Müller-Hermelink H K, Harms H, Aus H M

机构信息

Institute of Pathology, University of Würzburg, FRG.

出版信息

Anal Cell Pathol. 1990 Feb;2(2):83-95.

PMID:2278863
Abstract

In the past, the comparison of results of studies on malignant lymphomas has been biased by the use of different classifications of the diseases and to an even greater extent by subjective interpretation in the classification of the tumour cells. To overcome these short-comings, we have developed cytometric features specifically for automated recognition of cell images from high grade malignant non-Hodgkin's lymphomas (NHL) and reactive lymphoid lesions. This study used a colour TV-microscope system, high resolution scanning (13.3 pixel/microns), and image processing to study a total of 3600 lymphoid cells from 15 high grade malignant NHL and three tonsils. Sixteen out of 64 features, especially developed for image analysis in cytological preparations, have been evaluated. Because of a considerable overlap of all the single features, no feature on its own allows reliable discrimination. But, multivariant analysis of suitable feature combinations resulted in reliable identification and discrimination of the most frequently occurring cell types. We show that the lymphocytes, centrocytes, centroblasts, immunoblasts and lymphoblasts, as they are defined by subjective morphological criteria in the Kiel-classification of malignant NHL, also form distinctive subpopulations on the basis of their objective mathematical cell features. Furthermore, we have shown that there are distinctive differences between the lymphoma cells and their benign counterparts derived from reactive lymphoid lesions.

摘要

过去,恶性淋巴瘤研究结果的比较因疾病分类方法不同而存在偏差,在肿瘤细胞分类中主观解读的影响甚至更大。为克服这些不足,我们专门开发了细胞计量学特征,用于自动识别高级别恶性非霍奇金淋巴瘤(NHL)和反应性淋巴样病变的细胞图像。本研究使用彩色电视显微镜系统、高分辨率扫描(13.3像素/微米)和图像处理技术,对来自15例高级别恶性NHL和3个扁桃体的共3600个淋巴样细胞进行了研究。对专门为细胞学涂片图像分析开发的64个特征中的16个进行了评估。由于所有单个特征之间存在相当大的重叠,没有一个特征能单独可靠地区分。但是,对合适特征组合进行多变量分析,可对最常见的细胞类型进行可靠识别和区分。我们发现,在恶性NHL的基尔分类中,根据主观形态学标准定义的淋巴细胞、中心细胞、中心母细胞、免疫母细胞和淋巴母细胞,基于其客观的数学细胞特征也形成了独特的亚群。此外,我们还表明,淋巴瘤细胞与其反应性淋巴样病变来源的良性对应细胞之间存在明显差异。

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Anal Cell Pathol. 1990 Feb;2(2):83-95.
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