Experimental results using a three-layer skin model for diffuse reflectance spectroscopy

Abstract

We have previously presented an inverse Monte Carlo algorithm based on a three-layer semi-infinite skin model for analyzing diffuse reflectance spectroscopy (DRS) data. The algorithm includes pre-simulated Monte Carlo data for a range of physiologically relevant epidermal thicknesses and tissue scattering levels. The simulated photon pathlength distributions in each layer are stored and the absorption effect from tissue chromophores added in the post-processing. Recorded DRS spectra at source-detector distances of 0.4 and 1.2 mm were calibrated for the relative intensity between the two distances and matched to simulated spectra in a non-linear optimization algorithm. This study evaluates the DRS spectral fitting accuracy and presents data on the main output parameters; the tissue fraction of red blood cells and local oxygenation (SO2). As a reference, the microcirculatory perfusion (Perf) was measured simultaneously in the same probe using laser Doppler Flowmetry. Data were recorded on the volar forearm of three healthy subjects in a protocol involving a 5 min systolic occlusion. The DRS spectra were modeled with an rms-error 7 times compared to baseline. In the third subject the SO2 decreased less during occlusion and increased to baseline values at hyperemia with only a 2-fold increase in Perf. The observed difference could be due to different microvascular beds being probed. It is concluded that integrating DRS and LDF enables new possibilities to deduce microcirculation status.