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通过图像处理对胃上皮肿瘤的异型程度进行客观量化。

Objective quantification of grade of atypia in epithelial tumors of the stomach by image processing.

作者信息

Ishido T, Nakamura K

机构信息

Division of Pathology, Tsuchiura Kyohdoh Hospital.

出版信息

Jpn J Cancer Res. 1991 Feb;82(2):199-205. doi: 10.1111/j.1349-7006.1991.tb01829.x.

Abstract

An image processing technique to extract tubular and nuclear areas from histological specimens stained with hematoxylin was established. Two indices representing tubular density and nucleus-to-cytoplasm ratio of glands were examined in intestinal-type tumor of the stomach. In specimens clearly stained with hematoxylin, significant differences of brightness among nuclei, cytoplasm and stroma can be obtained. Image processing by computer enabled us to identify nuclei, cytoplasm and stroma by utilizing the differences of brightness among them. Both indices tended to increase with severity of histological atypia and their values in the tubular adenoma group were significantly different from those in the tubular adenocarcinoma group (P less than 0.05). Therefore, these two indices could be regarded as valid and objective measures of the grade of histological atypia. Eighty-four percent of tubular adenoma and tubular adenocarcinoma cases were classified correctly with the discriminant formula and critical value calculated from the two indices on the basis of measurement of the images magnified by 40 times. There is, however, still a non-negligible overlap of discriminant scores between the tubular adenoma group and tubular adenocarcinoma group. More indices representing histological atypia will be required to allow objective differential diagnosis between malignant and benign lesions.

摘要

建立了一种从苏木精染色的组织学标本中提取管状和核区域的图像处理技术。在胃的肠型肿瘤中检测了代表腺体管状密度和核质比的两个指标。在苏木精染色清晰的标本中,可获得细胞核、细胞质和基质之间明显的亮度差异。通过计算机进行图像处理,使我们能够利用它们之间的亮度差异来识别细胞核、细胞质和基质。这两个指标都倾向于随着组织学异型性的严重程度而增加,并且它们在管状腺瘤组中的值与管状腺癌组中的值有显著差异(P小于0.05)。因此,这两个指标可被视为组织学异型性分级的有效和客观指标。根据放大40倍的图像测量结果,用从这两个指标计算出的判别公式和临界值,84%的管状腺瘤和管状腺癌病例被正确分类。然而,管状腺瘤组和管状腺癌组之间的判别分数仍有不可忽略的重叠。需要更多代表组织学异型性的指标来实现恶性和良性病变之间的客观鉴别诊断。

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