Gerger Armin, Smolle Josef
Department of Dermatology, University of Graz, Austria.
J Cutan Pathol. 2003 Apr;30(4):247-52. doi: 10.1046/j.0303-6987.2003.044.x.
In tissue counter analysis, digital images are dissected into subregions (elements), and the digital information in each element is used for statistical analysis. The aim of this study was to test the applicability of tissue counter analysis and CART (Classification and Regression Tree) to the diagnostic discrimination of benign common nevi and malignant melanoma in dermatopathology.
Two hundred cases each of benign nevi and malignant melanoma were consecutively sampled. CART analyses of background versus tissue elements, cellular versus 'other' tissue elements and benign versus malignant cellular elements were performed. For diagnostic assessment, only the percentage of cellular elements suggestive for malignancy in each case was used.
CART analysis led to a correct classification of 99% of background versus tissue elements, 96% of cellular versus 'other' tissue elements and 79.1% of benign versus malignant cellular elements. When the percentage of cellular elements suggestive for malignancy in each case was evaluated, 29.5 +/- 14% (range 4.1-62.4) 'malignant' elements were found in benign nevi (n = 200), in contrast to 75.9 +/- 13.9% (range 32.8-97.3) in melanoma (n = 200; z =-16.72, p < 0.001). It turned out that a threshold level of 52.51% provides a correct classification of 192 nevi and 186 melanoma out of 200 each (specificity 96%, sensitivity 93%, positive predictive value 95.9%).
Tissue counter analysis combined with CART may be a useful method for diagnostic purposes in histopathology.
在组织计数分析中，数字图像被分割成子区域（元素），每个元素中的数字信息用于统计分析。本研究的目的是测试组织计数分析和分类与回归树（CART）在皮肤病理学中对良性普通痣和恶性黑色素瘤进行诊断鉴别的适用性。
连续抽取200例良性痣和200例恶性黑色素瘤病例。对背景与组织元素、细胞与“其他”组织元素以及良性与恶性细胞元素进行CART分析。为了进行诊断评估仅使用了每个病例中提示恶性的细胞元素百分比。
CART分析对背景与组织元素的正确分类率为99%，细胞与“其他”组织元素的正确分类率为96%，良性与恶性细胞元素的正确分类率为79.1%。当评估每个病例中提示恶性的细胞元素百分比时，在200例良性痣中发现29.5±14%（范围4.1 - 62.4）的“恶性”元素，相比之下，在200例黑色素瘤中为75.9±13.9%（范围32.8 - 97.3）（z = -16.72，p < 0.001）。结果表明，阈值水平为52.51%时，对200例痣和200例黑色素瘤分别有192例和186例分类正确（特异性96%，敏感性93%，阳性预测值95.9%）。
组织计数分析结合CART可能是组织病理学中用于诊断目的的一种有用方法。
