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计算机辅助图像分析中反映出的良性色素性皮肤病变已知细胞组成的差异。

Differences in the known cellular composition of benign pigmented skin lesions reflected in computer-aided image analysis.

作者信息

Choi Jae Woo, Ryu Hyeong Ho, Byun Sang Young, Youn Sang Woong

机构信息

Department of Dermatology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea.

出版信息

Ann Dermatol. 2014 Jun;26(3):314-20. doi: 10.5021/ad.2014.26.3.314. Epub 2014 Jun 12.

Abstract

BACKGROUND

Computer-aided image analysis (CAIA) has been suggested as an effective diagnostic tool for pigmented skin lesions (PSLs), especially melanoma. However, few studies on benign PSLs have been reported.

OBJECTIVE

The purpose of this study was to evaluate benign PSLs with our CAIA software and analyze the differences between the parameters of those lesions.

METHODS

By using homegrown CAIA software, we analyzed 3 kinds of PSLs-nevus, lentigo, and seborrheic keratosis. The group of seborrheic keratosis was divided into pigmented seborrheic keratosis, sebolentigine, and hyperkeratotic seborrheic keratosis. The CAIA was used to extract the color, as well as the morphological, textural, and topological features from each image.

RESULTS

In line with clinical observations, the objective parameters indicated that nevus was dark and round, lentigo was small and bright, and seborrheic keratosis was large and spiky. The surface of nevus showed the highest contrast and correlation. In topological analysis, the concentricity clearly separated melanocytic lesions from seborrheic keratosis. The parameters of pigmented seborrheic keratosis were between those of typical nevus and seborrheic keratosis.

CONCLUSION

We confirmed that definite correlations exist between the subjective differentiation by experts' examination and the objective evaluation by using CAIA. We also found that the morphological differences observed in CAIA were greatly influenced by the composition ratios of keratinocytes and melanocytes, which are already known histopathological characteristics of each PSL.

摘要

背景

计算机辅助图像分析(CAIA)已被认为是一种用于色素沉着性皮肤病变(PSL),尤其是黑色素瘤的有效诊断工具。然而,关于良性PSL的研究报道较少。

目的

本研究旨在使用我们的CAIA软件评估良性PSL,并分析这些病变参数之间的差异。

方法

通过使用自主研发的CAIA软件,我们分析了3种PSL——痣、雀斑样痣和脂溢性角化病。脂溢性角化病组又分为色素性脂溢性角化病、脂溢性雀斑样痣和角化过度性脂溢性角化病。CAIA用于从每个图像中提取颜色以及形态、纹理和拓扑特征。

结果

与临床观察结果一致,客观参数表明痣颜色深且呈圆形,雀斑样痣小且明亮,脂溢性角化病大且呈尖状。痣的表面显示出最高的对比度和相关性。在拓扑分析中,同心度清楚地将黑素细胞性病变与脂溢性角化病区分开来。色素性脂溢性角化病的参数介于典型痣和脂溢性角化病之间。

结论

我们证实专家检查的主观鉴别与使用CAIA的客观评估之间存在明确的相关性。我们还发现,CAIA中观察到的形态学差异受角质形成细胞和黑素细胞组成比例的极大影响,而这是每种PSL已知的组织病理学特征。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a115/4069641/938e38700898/ad-26-314-g001.jpg

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