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Image correlation spectroscopy (ICS) is known to be a useful tool for the evaluation of fiber width in the extracellular matrix. Here we evaluate a more general from of ICS fit parameters for fiber networks and arrive at a means of quantifying the fiber density, pore size and length which facilitates the characterization of the extracellular matrix. A simulation package was made to create images with different structural properties of fiber networks such as fiber orientation, width, fiber density and length. A pore finding algorithm was developed which determines the distribution of circular voids in the image. Collagen I hydrogels were prepared under different polymerization conditions for validation of our pore size algorithm with microscopy data. ICS parameters included amplitude, standard deviation and ellipticity and are shown to predict the structural properties of fiber networks in a quantitative manner. While the fiber width is related to the ICS sigma; the fiber density relates to the pore size distribution which correlates with the ICS amplitude in thresholded images. Fiber length is related to ICS ellipticity if the fibers have a preferred orientation. Findings from ICS and pore distribution algorithms were verified for both simulated and microscopy data. Based on these findings, we conclude that ICS can be used in the assessment of the extracellular matrix and the prediction of fiber orientation, width, density, length and matrix pore size.

The efficacy of image correlation spectroscopy for characterization of the extracellular matrix