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基于灰度共生矩阵特征的核染色质分布和粗糙程度判别分析及其在宫颈腺上皮增生中的解释

Discriminant analysis and interpretation of nuclear chromatin distribution and coarseness using gray-level co-occurrence matrix features for lobular endocervical glandular hyperplasia.

机构信息

Department of Biomedical Laboratory Sciences, School of Health Sciences, Shinshu University, Matsumoto, Japan.

Division of Diagnostic Pathology, Okaya City Hospital, Okaya, Japan.

出版信息

Diagn Cytopathol. 2020 Aug;48(8):724-735. doi: 10.1002/dc.24466. Epub 2020 May 6.

DOI:10.1002/dc.24466
PMID:32374944
Abstract

BACKGROUND

Lobular endocervical glandular hyperplasia (LEGH) is a disease considered to be the origin of tumorigenesis of minimal deviation adenocarcinoma, which has characteristic expression in the gastric pyloric mucosa. It is difficult to diagnose by nuclear findings because of lower nuclear atypia. In this study, nuclei of endocervical (EC) and LEGH cells were digitized, and nuclear information was quantified from nuclear images and objectively evaluated using a computer. We examined whether it is possible to distinguish between EC and LEGH cells, which is difficult by human eyes.

METHODS

Signal intensity, morphological features, Otsu thresholding technique and gray-level co-occurrence matrix (GLCM) features were calculated from nuclei of EC and LEGH cells on cytology microscopic images. Then, discriminant analysis was performed using the significant difference test and linear support vector machine (LSVM).

RESULTS

GLCM features in LEGH cells were higher than those in EC cells. The nuclei of LEGH cells had a higher frequency of signal value pairs with a larger signal value difference than that of EC cells. Therefore, LEGH cell nuclei are thought to have more chromatin granules, and the chromatin is coarse and granular. Moreover, in the LSVM discriminant analysis, the accuracy of GLCM calculated using these features was 85.4%.

CONCLUSION

In this study, GLCM accurately demonstrated the nuclear chromatin distribution and coarseness. Discriminant analysis of EC and LEGH cells using GLCM features is useful.

摘要

背景

小叶型宫颈管内腺体增生(LEGH)被认为是微偏腺癌发生的起源,其在胃幽门黏膜中具有特征性表达。由于核异型性较低,通过核发现来诊断具有一定难度。在本研究中,对宫颈管(EC)和 LEGH 细胞的核进行了数字化,并从核图像中定量核信息,使用计算机进行客观评估。我们检查了是否可以区分 EC 和 LEGH 细胞,这是通过肉眼难以区分的。

方法

在细胞学显微镜图像上计算 EC 和 LEGH 细胞的核的信号强度、形态特征、Otsu 阈值技术和灰度共生矩阵(GLCM)特征。然后,使用显著差异检验和线性支持向量机(LSVM)进行判别分析。

结果

LEGH 细胞的 GLCM 特征高于 EC 细胞。LEGH 细胞的核具有更高的信号值对频率,信号值差异更大。因此,LEGH 细胞的核被认为具有更多的染色质颗粒,并且染色质粗糙且呈颗粒状。此外,在 LSVM 判别分析中,使用这些特征计算的 GLCM 的准确率为 85.4%。

结论

在本研究中,GLCM 准确地显示了核染色质的分布和粗糙程度。使用 GLCM 特征对 EC 和 LEGH 细胞进行判别分析是有用的。

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