Non-invasive skin oxygenation imaging using a multi-spectral camera system: effectiveness of various concentration algorithms applied on human skin

Abstract

This study describes noninvasive noncontact methods to acquire and analyze functional information from the skin. Multispectral images at several selected wavelengths in the visible and near infrared region are collected and used in mathematical methods to calculate concentrations of different chromophores in the epidermis and dermis of the skin. This is based on the continuous wave Near Infrared Spectroscopy method, which is a well known non-invasive technique for measuring oxygenation changes in the brain and in muscle tissue. Concentration changes of hemoglobin (dO₂Hb, dHHb and dtHb) can be calculated from light attenuations using the modified Lambert Beer equation. We applied this technique on multi-spectral images taken from the skin surface using different algorithms for calculating changes in O₂Hb, HHb and tHb. In clinical settings, the imaging of local oxygenation variations and/or blood perfusion in the skin can be useful for e.g. detection of skin cancer, detection of early inflammation, checking the level of peripheral nerve block anesthesia, study of wound healing and tissue viability by skin flap transplantations. Images from the skin are obtained with a multi-spectral imaging system consisting of a 12-bit CCD camera in combination with a Liquid Crystal Tunable Filter. The skin is illuminated with either a broad band light source or a tunable multi wavelength LED light source. A polarization filter is used to block the direct reflected light. The collected multi-spectral imaging data are images of the skin surface radiance; each pixel contains either the full spectrum (420 - 730 nm) or a set of selected wavelengths. These images were converted to reflectance spectra. The algorithms were validated during skin oxygen saturation changes induced by temporary arm clamping and applied to some clinical examples. The initial results with the multi-spectral skin imaging system show good results for detecting dynamic changes in oxygen concentration. However, the optimal algorithm needs to be determined. Multi-spectral skin imaging shows to be a promising technique for various clinical applications were the local distribution of oxygenation is of major importance.