Kuwahara H, Shimazaki M, Morikita I, Chanoki Y, Sakurai M
Department of Pathology, Osaka City University Medical School, Japan.
Pathol Res Pract. 1992 Jun;188(4-5):565-9. doi: 10.1016/S0344-0338(11)80057-9.
To gain an objective evaluation of histological sections of giant cell tumors of bone (GCT) and osteosarcomas, microscopic pictures were taken and their grey-tone image measured, using a flying spot scanner and computer. Various values of eight parameters expressing certain characteristical brightness distribution patterns were computed, and comparatively examined among the three groups of benign GCT, malignant GCT and osteosarcoma. As a result, some parameters could facilitate differentiation between the histological images of these bone tumors. Especially, "angular second moment (ASM)", "Contrast" and "Coefficient of variation (COV)" were useful even for discrimination between malignant and benign GCT. After factor analysis of the values of these parameters, scores of each factor for a number of histological scene images were plotted on a 2-dimensional factor plane. On this plane, which was considered to be a histological feature plane, cases of benign GCT were separated from those of osteosarcoma. Cases of malignant GCT were distributed between the two groups. These results suggest that this method could be valuable for computer evaluation of histological images of benign GCT and osteosarcomas.
为了对骨巨细胞瘤（GCT）和骨肉瘤的组织切片进行客观评估，使用飞点扫描仪和计算机拍摄微观图片并测量其灰度图像。计算了表达某些特征亮度分布模式的八个参数的各种值，并在良性GCT、恶性GCT和骨肉瘤三组之间进行了比较研究。结果表明，一些参数有助于区分这些骨肿瘤的组织学图像。特别是，“角二阶矩（ASM）”、“对比度”和“变异系数（COV）”即使对于区分恶性和良性GCT也很有用。对这些参数的值进行因子分析后，将许多组织学场景图像的每个因子得分绘制在二维因子平面上。在这个被认为是组织学特征平面的平面上，良性GCT病例与骨肉瘤病例分开。恶性GCT病例分布在两组之间。这些结果表明，该方法对于良性GCT和骨肉瘤组织学图像的计算机评估可能具有重要价值。
