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

Abstract

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.

Multiparametric Quantitative Analysis of Photodamage to Skin Using Optical Coherence Tomography

“…The two intensity peaks in Figure 2 c correspond to the location of the bright band in Figure 2 b, which represents the upper and lower surfaces of the AS. We can calculate the thickness from the number of pixels N between two intensity peaks to obtain the overall AS thickness distribution [ 31 ]. The surface roughness is determined by the upper surface profile of the skin.…”

“…As shown in Figure 2 f, D (x,y) is the AS thickness at position (x,y). D (x,y) = N ∗ , where N is the number of pixels between the two intensity peaks of the A-scan [ 31 ]. is the pixel size in the z direction.…”

“…Many studies have reported OCT signal process techniques to evaluate or quantify the parameters of a sample, as OCT data reveal more information about the sample than merely its 3D structure [ 13 , 30 , 31 , 32 , 33 ]. Schmitt et al obtained internals of the upper surface of the skin based on B-scan images and characterized the morphological features of the skin tissue [ 13 ].…”

“…The reliability of the roughness measurements was demonstrated by comparing the results with those from the PRIMOS skin measurement device. Zhao et al utilized OCT A-scan signal analysis and an adaptive algorithm to realize the quantification of the roughness of AS samples for a quality check [ 31 ]. In addition, tissue optical characterization is widely used in OCT biological tissue image pathology.…”

Methods and applications of full-filed optical coherence tomography: a review

“…Compared with FF-OCT, OCT has a larger imaging FOV and imaging depth and has been widely used in materials science, in situ process monitoring, and tissue engineering. 80 – 83 , 93 – 95 But FF-OCT has isotropic micrometric resolution and has the ability of producing a histology-like image from a thick sample within a few milliseconds without physical slicing. Therefore, this technology is also known as optical biopsy.…”