The assessment of dermal alterations is necessary to monitor skin aging, cancer, and other skin diseases and alterations. The gold standard of morphologic diagnostics is still histopathology. Here, we proposed parameters to distinguish morphologically different collagen I structures in the extracellular matrix and to characterize varying collagen I structures in the skin with similar SAAID (SHG-to-AF Aging Index of Dermis, SHG—second-harmonic generation; AF—autofluorescence) values. Test datasets for the papillary and reticular extracellular matrix from images in 24 female subjects, 36 to 50 years of age, were generated. Parameters for SAAID, edge detection, and fast Fourier transformation directionality were determined. Additionally, textural analyses based on the grey level co-occurrence matrix (GLCM) were conducted. At first, changes in the GLCM parameters were determined in the native greyscale images and, furthermore, in the Hilbert-transformed images. Our results demonstrate a robust set of parameters for noninvasive in vivo classification for morphologically different collagen I structures in the skin, with similar and different SAAID values. We anticipate our method to enable an automated prevention and monitoring system with an age- and gender-specific algorithm.
Characterization of collagen fibers by means of texture analysis of second harmonic generation images using orientation-dependent gray level co-occurrence matrix method