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角膜铺片血管生成和淋巴管生成形态计量学的改良半自动方法。

Improved semiautomatic method for morphometry of angiogenesis and lymphangiogenesis in corneal flatmounts.

作者信息

Bock F, Onderka J, Hos D, Horn F, Martus P, Cursiefen C

机构信息

Department of Ophthalmology, University of Erlangen-Nürnberg, Germany.

出版信息

Exp Eye Res. 2008 Nov;87(5):462-70. doi: 10.1016/j.exer.2008.08.007. Epub 2008 Aug 26.

Abstract

Purpose of the study was to describe a novel semiautomatic, quantitative image analysis method based on threshold analysis for morphometry of corneal (lymph)angiogenesis and to test its validity, reliability and objectivity. Murine corneas were vascularized by using a suture-induced neovascularization assay. For immunohistochemistry, flatmounts of the vascularized corneas were stained with LYVE-1 as a specific lymphatic vascular endothelial marker and with CD31 as panendothelial marker. Morphometry of corneal hem and lymphangiogenesis was performed semi-automatically on digital images using image analysis software. Data were analyzed by a paired t-test, intraclass-correlation and systemic difference analysis compared to a manual method. The semiautomatic method based on threshold analysis was more valid in measuring the area covered by blood or lymphatic vessels. Both methods had a good reproducibility with respect to both vessel types (blood vessels: manual: 0.969, semiautomatic: 0.982; lymphatic vessels: manual: 0.951, semiautomatic: 0.966), whereas the systemic difference was significant for both groups measuring lymphatic vessels (manual: p<0.003; semiautomatic: p<0.035) and for the manual method measuring blood vessels (manual: p<0.0001; semiautomatic: p<0.419). The new semiautomatic morphometry method based on threshold analysis provides higher accuracy, is more valid than and at least as reproducible and objective as the manual outlining method. Therefore the semiautomatic method can be used to detect even small effects on hem and lymphangiogenesis in murine corneal flatmounts with greater precision.

摘要

本研究的目的是描述一种基于阈值分析的新型半自动定量图像分析方法,用于角膜(淋巴管)生成的形态测量,并测试其有效性、可靠性和客观性。通过缝线诱导的新生血管形成试验使小鼠角膜血管化。对于免疫组织化学,将血管化角膜的平铺标本用LYVE-1(作为特异性淋巴管内皮标记物)和CD31(作为全内皮标记物)染色。使用图像分析软件在数字图像上半自动进行角膜血管生成和淋巴管生成的形态测量。与手动方法相比,通过配对t检验、组内相关性和系统差异分析对数据进行分析。基于阈值分析的半自动方法在测量血管或淋巴管覆盖面积方面更有效。两种方法对于两种血管类型(血管:手动:0.969,半自动:0.982;淋巴管:手动:0.951,半自动:0.966)都具有良好的可重复性,而在测量淋巴管时两组的系统差异均显著(手动:p<0.003;半自动:p<0.035),在测量血管时手动方法也有显著差异(手动:p<0.0001;半自动:p<0.419)。基于阈值分析的新型半自动形态测量方法具有更高的准确性,比手动勾勒方法更有效,并且至少具有相同的可重复性和客观性。因此,半自动方法可用于更精确地检测小鼠角膜平铺标本中对血管生成和淋巴管生成的微小影响。

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