Estimating adult cerebral oxygen saturation from time-resolved near-infrared spectroscopy measurements with few discrete wavelengths at a single source-detector distance

Time-resolved Near-Infrared Spectroscopy (trNIRS) methods typically use multiple wavelengths and source-detector distances in conjunction with a solution of the diffusion approximation to quantify tissue blood content and oxygenation. This approach can be both computationally intensive and costly, as multiple detectors are required. We propose a novel two-layer fitting approach for multi-wavelength trNIRS, which uses a single detector while providing accurate estimates of cerebral oxygen saturation (ScO2) and hemoglobin content. The method uses a multi-step fitting algorithm to establish rough estimates of the absorption and scattering coefficients in the extracerebral layer and the brain, and subsequently refine those estimates, to improve accuracy while reducing crosstalk and complexity. Validation was conducted using Monte Carlo simulations in a realistic adult head model with appropriate optical properties at 680nm, 750nm, 800nm, and 830nm. The detector was located 30 mm anteriorly from the source, which was placed 50 mm above the right temple. Scalp oxygen saturation (SO2) (50%, 60%, and 70%) and ScO2 (40%-80%, 2% increments) were varied independently. The recovered ScO2 had a difference (mean±standard deviation) of 2.31±2.93% from inputted values, and cerebral total hemoglobin was recovered with a difference of 2.94±3.47%. Such high accuracy demonstrates the robustness of this computationally efficient two-layer fitting approach for analyzing multi-wavelength trNIRS measurements acquired with a single detector. Future work will involve validating the technique in tissue mimicking phantoms and animal studies.