An investigation on the use of data-driven scattering profiles in Monte Carlo simulations of ultraviolet light propagation in skin tissues.
Ultraviolet light can affect the appearance and medical condition of the human skin by triggering biophysical processes such as erythema, melanogenesis, photoaging and carcinogenesis. The evolution of these processes is related to the amount of ultraviolet light absorbed by skin pigments. This amount may vary with the wavelength and path length of the radiation that is propagated within the skin tissues. For many years, biomedical researchers have been investigating the propagation of ultraviolet light in skin tissues through Monte Carlo simulations. The scattering of the incident radiation by tissue internal structures, a key component in this process, is usually approximated by functions without a plausible connection with the underlying physical phenomena. In this paper, we examine the origins of such an approach, and question its generalized use with respect to wavelengths and biological materials for which there is no supporting data available. Furthermore, we perform comparisons to demonstrate that the accuracy and predictability of Monte Carlo simulations of ultraviolet propagation in skin tissues can be improved by using a data-driven approach to represent the scattering profile of these tissues.