Abstract

Brain tissue oxygen saturation, StO₂, measured with near-infrared spectroscopy (NIRS) is of great clinical interest as it quantifies the balance between cerebral oxygen supply and demand. Some brain oximeters are based on spatially resolved spectroscopy (SRS), where NIRS data is collected at multiple distances from the light source to estimate a slope of light attenuation against distance. Other use a broadband approach which utilizes derivatives of the absorption spectra to estimate StO₂, such as broadband fitting (BF). We describe a novel algorithm, broadband spatially resolved spectroscopy (BB-SRS), for estimating StO₂. It is based on comparing the measured slope to a model of the attenuation slope, which depends on the optical properties of tissue. Fitting this model with a least squares fitting procedure recovers parameters describing absorption and scattering; the concentrations of oxy- and deoxy-haemoglobin and hence StO₂ and the scattering parameters β and α describing the exponential dependence of scattering on wavelength. To demonstrate BB-SRS, a broadband spectrum (700 -1000 nm, step size 2 nm) was simulated in NIRFAST and was analysed with BB-SRS, SRS and BF. The developed BB-SRS algorithm recovered StO₂ with a relative error of -9%; the concentration of deoxyhaemoglobin with a relative error of +4%, oxyhaemoglobin −10%. The scattering parameters β and α were recovered with a relative error of -30% and -2%, respectively. Among the three algorithms, BB-SRS performed with the best relative error.

© 2019 SPIE/OSA