As one of the most fundamental features of light, polarization can be used to develop imaging techniques which can provide insight into the optical and structural properties of tissues. Especially, the Mueller matrix polarimetry is suitable to detect the changes in collagen and elastic fibres, which are the main compositions of skin tissue. Here we demonstrate a novel quantitative, non-contact and in situ technique to monitor the microstructural variations of skin tissue during ultraviolet radiation (UVR) induced photoaging based on Mueller matrix polarimetry. Specifically, we measure the twodimensional (2D) backscattering Mueller matrices of nude mouse skin samples, then calculate and analyze the Mueller matrix derived parameters during the skin photoaging and self-repairing processes. To induce three-day skin photoaging, the back skin of each mouse is irradiated with UVR (0.05J/cm2) for five minutes per day. After UVR, the microstructures of the nude mouse skin are damaged. During the process of UV damage, we measure the backscattering Mueller matrices of the mouse skin samples and examine the relationship between the Mueller matrix parameters and the microstructural variations of skin tissue quantitatively. The comparisons between the UVR damaged groups with and without sunscreens show that the Mueller matrix derived parameters are potential indicators for fibrous microstructure variation in skin tissue. The pathological examinations and Monte Carlo simulations confirm the relationship between the values of Mueller matrix parameters and the changes of fibrous structures. Combined with smart phones or wearable devices, this technique may have a good application prospect in the fields of cosmetics and dermatological health.
Wei Sheng, Honghui He, Dong Yang, and Hui Ma, "Quantitatively characterizing microstructural variations of skin tissues during ultraviolet radiation damaging process based on Mueller matrix polarimetry," Proc. SPIE 10467, Photonics in Dermatology and Plastic Surgery 2018, 104670Y (Presented at SPIE BiOS: January 29, 2018; Published: 14 February 2018); https://doi.org/10.1117/12.2288692.
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