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管状腺瘤分支分类的多变量判别分析。

Multivariate discriminant analysis for branching classification of colonic tubular adenoma glands.

机构信息

Department of Pathology, College of Medicine, Eulji University, Daejeon, South Korea.

Department of Pathology, Daejeon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, South Korea.

出版信息

Cytometry B Clin Cytom. 2020 Sep;98(5):429-440. doi: 10.1002/cyto.b.21871. Epub 2020 Feb 6.

Abstract

BACKGROUND

Many morphologic findings of histology can be translated into mathematically computerized data, and identifying important parameters is primarily pathologists' task as users. Shape-specific parameters based on computational geometry properties of glands can be used in the field of pathology. We evaluated the diagnostic utility of three shape-specific parameters: the chord intersection ratio, convexity ratio, and maximum concave area ratio for branching classification of glands.

METHODS

Seven cases of tubular adenoma were studied. After image analysis, segmented neoplastic glands were classified into nonbranching, mild branching, and moderate branching. Using image analysis formulae for the three shape-specific parameters, we compared the values of the parameters with the branching classification results for colonic tubular adenoma.

RESULTS

Multivariate discriminant analysis was used to classify the branching groups. Classification accuracies of nonbranching, mild branching, and moderate branching group based on the three shape-specific parameters were 98, 94, and 95%, respectively. More branching growth exhibited a higher chord intersection ratio and maximum concave area ratio but lower convexity ratio. We found a statistically significant difference in chord intersection ratio, maximum concave area ratio, and convexity ratio between mild, moderate, and nonbranching groups. Among the three features, the chord intersection ratio was the most significant parameter.

CONCLUSIONS

Shape-based parameters of chord intersection ratio, convexity ratio, and maximum concave area ratio are valid assessment parameters for irregular branching structures. For the understanding of spatial relationships of histology, the holistic geometric approach using shape-based parameters can be useful.

摘要

背景

许多组织学的形态学发现可以转化为数学计算机数据,识别重要参数主要是病理学家作为用户的任务。基于腺体计算几何特性的特定形状参数可用于病理学领域。我们评估了三个特定形状参数的诊断效用:弦交点比、凸度比和最大凹面积比,用于分支分类的腺体。

方法

研究了 7 例管状腺瘤病例。图像分析后,将肿瘤腺体分为非分支型、轻度分支型和中度分支型。使用三种特定形状参数的图像分析公式,我们比较了参数值与结肠管状腺瘤的分支分类结果。

结果

使用多元判别分析对分支组进行分类。基于三个特定形状参数的非分支、轻度分支和中度分支组的分类准确率分别为 98%、94%和 95%。分支生长越多,弦交点比和最大凹面积比越高,凸度比越低。我们发现,在轻度、中度和非分支组之间,弦交点比、最大凹面积比和凸度比存在统计学显著差异。在这三个特征中,弦交点比是最重要的参数。

结论

基于弦交点比、凸度比和最大凹面积比的形状参数是不规则分支结构的有效评估参数。对于组织学空间关系的理解,使用基于形状的参数的整体几何方法可能是有用的。

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