Abstract
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.
Highlights
An overarching observation in our evaluation was that the 24 algorithms can be ranked by the relative magnitude of their diameter output values (Table 2)
T4 and T8 frequently failed to segment images; we recommend against using them for automatic fibrin clot analysis
Having identified the algorithms whose diameter outputs best correlated with manually measured diameter values, we evaluated if these algorithms can be used to distinguish differences in fiber diameters between healthy control and patient samples
Summary
Biomolecules 2021, 11, 1536 density, and network pore size or porosity [1,2,3,4,5,6,7,8,9]. These microscopic characteristics are related to macroscopic clot properties, such as permeability, lytic resistance, or viscoelasticity, which, in turn, have been shown to associate with disease. Clots with thinner, more densely packed fibers, and smaller pores and more branch points result in a stiffer network, reduced permeability, and increased resistance to fibrinolysis [10,11,12]. Clot structure and stability may be used to assess prevalence and treatment of bleeding disorders, such as hemophilia
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