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啮齿动物睾丸组织的精确定量组织形态计量学-数学图像分析方法及其在男科学和生殖医学中可能的未来研究前景。

Accurate Quantitative Histomorphometric-Mathematical Image Analysis Methodology of Rodent Testicular Tissue and Its Possible Future Research Perspectives in Andrology and Reproductive Medicine.

作者信息

Sziva Réka Eszter, Ács Júlia, Tőkés Anna-Mária, Korsós-Novák Ágnes, Nádasy György L, Ács Nándor, Horváth Péter Gábor, Szabó Anett, Ke Haoran, Horváth Eszter Mária, Kopa Zsolt, Várbíró Szabolcs

机构信息

Department of Obstetrics and Gynecology, Semmelweis University, Üllői Street 78/a, 1082 Budapest, Hungary.

Department of Physiology, Semmelweis University, Tűzoltó Street 37-47, 1094 Budapest, Hungary.

出版信息

Life (Basel). 2022 Jan 27;12(2):189. doi: 10.3390/life12020189.

Abstract

Infertility is increasing worldwide; male factors can be identified in nearly half of all infertile couples. Histopathologic evaluation of testicular tissue can provide valuable information about infertility; however, several different evaluation methods and semi-quantitative score systems exist. Our goal was to describe a new, accurate and easy-to-use quantitative computer-based histomorphometric-mathematical image analysis methodology for the analysis of testicular tissue. On digitized, original hematoxylin-eosin (HE)-stained slides (scanned by slide-scanner), quantitatively describable characteristics such as area, perimeter and diameter of testis cross-sections and of individual tubules were measured with the help of continuous magnification. Immunohistochemically (IHC)-stained slides were digitized with a microscope-coupled camera, and IHC-staining intensity measurements on digitized images were also taken. Suggested methods are presented with mathematical equations, step-by-step detailed characterization and representative images are given. Our novel quantitative histomorphometric-mathematical image analysis method can improve the reproducibility, objectivity, quality and comparability of andrological-reproductive medicine research by recognizing even the mild impairments of the testicular structure expressed numerically, which might not be detected with the present semi-quantitative score systems. The technique is apt to be subjected to further automation with machine learning and artificial intelligence and can be named 'Computer-Assisted or -Aided Testis Histology' (CATHI).

摘要

不孕症在全球范围内呈上升趋势;在几乎所有不孕夫妇中,近一半可查明男性因素。睾丸组织的组织病理学评估可为不孕症提供有价值的信息;然而,存在几种不同的评估方法和半定量评分系统。我们的目标是描述一种新的、准确且易于使用的基于计算机的定量组织形态计量学 - 数学图像分析方法,用于分析睾丸组织。在数字化的原始苏木精 - 伊红(HE)染色玻片(通过玻片扫描仪扫描)上,借助连续放大测量睾丸横截面和单个小管的面积、周长和直径等可定量描述的特征。免疫组织化学(IHC)染色玻片用显微镜耦合相机进行数字化处理,并对数字化图像上的IHC染色强度进行测量。文中通过数学方程展示了建议方法,给出了逐步详细的特征描述和代表性图像。我们新颖的定量组织形态计量学 - 数学图像分析方法可以提高男科学 - 生殖医学研究的可重复性、客观性、质量和可比性,因为它能够识别出睾丸结构即使是轻微的数值表达损伤,而目前的半定量评分系统可能检测不到这些损伤。该技术易于通过机器学习和人工智能实现进一步自动化,可命名为“计算机辅助睾丸组织学”(CATHI)。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc67/8875546/2842947fb7a9/life-12-00189-g001.jpg

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