Automatic quantitative analysis of structure parameters in the growth cycle of artificial skin using optical coherence tomography.

Significance: Artificial skin (AS) is widely used in dermatology, pharmacology, and toxicology, and has great potential in transplant medicine, burn wound care, and chronic wound treatment. There is a great demand for high-quality AS product and a non-invasive detection method is highly desirable. Aim: To quantify the constructure parameters (i.e., thickness and surface roughness) of AS samples in the culture cycle and explore the growth regularities using optical coherent tomography (OCT). Approach: An adaptive interface detection algorithm is developed to recognize surface points in each A-scan, offering a rapid method to calculate parameters without constructing OCT B-scan pictures and further achieving realizing real-time quantification of AS thickness and surface roughness. Experiments on standard roughness plates and H&E-staining microscopy were performed as a verification. Results: As applied on the whole cycle of AS culture, our method’s results show that during the air–liquid culture, the surface roughness of the skin first decreases and then exhibits an increase, which implies coincidence with the degree of keratinization under a microscope. And normal and typical abnormal samples can be differentiated by thickness and roughness parameters during the culture cycle. Conclusions: The adaptive interface detection algorithm is suitable for high-sensitivity, fast detection, and quantification of the interface with layered characteristic tissues, and can be used for non-destructive detection of the growth regularity of AS sample thickness and roughness during the culture cycle.