Department of Physics, Wake Forest University, Winston-Salem, NC 27109, USA.
Center of Excellence for Nutrition (CEN), Potchefstroom Campus, North-West University, Potchefstroom 2520, South Africa.
Biomolecules. 2021 Oct 18;11(10):1536. doi: 10.3390/biom11101536.
Scanning Electron Microscopy (SEM) is a powerful, high-resolution imaging technique widely used to analyze the structure of fibrin networks. Currently, structural features, such as fiber diameter, length, density, and porosity, are mostly analyzed manually, which is tedious and may introduce user bias. A reliable, automated structural image analysis method would mitigate these drawbacks. We evaluated the performance of DiameterJ (an ImageJ plug-in) for analyzing fibrin fiber diameter by comparing automated DiameterJ outputs with manual diameter measurements in four SEM data sets with different imaging parameters. We also investigated correlations between biophysical fibrin clot properties and diameter, and between clot permeability and DiameterJ-determined clot porosity. Several of the 24 DiameterJ algorithms returned diameter values that highly correlated with and closely matched the values of the manual measurements. However, optimal performance was dependent on the pixel size of the images-best results were obtained for images with a pixel size of 8-10 nm (13-16 pixels/fiber). Larger or smaller pixels resulted in an over- or underestimation of diameter values, respectively. The correlation between clot permeability and DiameterJ-determined clot porosity was modest, likely because it is difficult to establish the correct image depth of field in this analysis. In conclusion, several DiameterJ algorithms (M6, M5, T3) perform well for diameter determination from SEM images, given the appropriate imaging conditions (13-16 pixels/fiber). Determining fibrin clot porosity via DiameterJ is challenging.
扫描电子显微镜(SEM)是一种强大的高分辨率成像技术,广泛用于分析纤维蛋白网络的结构。目前,纤维直径、长度、密度和孔隙率等结构特征主要通过手动分析,这既繁琐又可能引入用户偏差。一种可靠的自动化结构图像分析方法将减轻这些缺点。我们通过将 DiameterJ(一个 ImageJ 插件)的自动纤维直径输出与四个具有不同成像参数的 SEM 数据集的手动直径测量进行比较,评估了 DiameterJ 分析纤维蛋白纤维直径的性能。我们还研究了纤维蛋白凝块的生物物理性质与直径之间的相关性,以及凝块渗透性与 DiameterJ 确定的凝块孔隙率之间的相关性。24 个 DiameterJ 算法中的几个返回的直径值与手动测量值高度相关且匹配紧密。然而,最佳性能取决于图像的像素大小-最佳结果是在像素大小为 8-10nm(13-16 个像素/纤维)的图像中获得的。较大或较小的像素分别导致直径值的高估或低估。凝块渗透性与 DiameterJ 确定的凝块孔隙率之间的相关性适中,这可能是因为在这种分析中很难建立正确的图像景深。总之,在适当的成像条件下(13-16 个像素/纤维),几种 DiameterJ 算法(M6、M5、T3)可很好地用于从 SEM 图像中确定直径。通过 DiameterJ 确定纤维蛋白凝块的孔隙率具有挑战性。