Single Source-Detector Separation Approach to Calculate Tissue Oxygen Saturation Using Continuous Wave Near-Infrared Spectroscopy

Currently, common optical techniques to measure tissue oxygen saturation (StO(2)) include time domain (TD), frequency domain (FD), and continuous wave (CW) near-infrared spectroscopy (NIRS). While TD-and FD-NIRS can provide absolute hemoglobin concentration, these systems are often complex and expensive. CW-NIRS, such as diffuse reflectance spectroscopy and spatially resolved spectroscopy (SRS), are simpler and more affordable, but they still require at least two source-detector separations. Here, we propose a single source-detector separation (SSDS) approach to measure StO(2) using reflected intensities from three wavelengths. The accuracy of the SSDS-based StO(2) measurement was verified using an optical simulation and an in-vivo experiment. Simulated spatially dependent reflectance was generated using the Virtual Tissue Simulator on a 1-layer model, which has StO(2) ranging from 0% to 100%. SSDS calculation yielded an equivalent StO(2) to the actual value (average error = 0.3% +/- 0.5%). We then performed StO(2) measurements on seven healthy volunteers in the prefrontal cortex during a simulated hypercapnia test using a CW-NIRS device. This device consists of a light source and two photodetectors, which are 30 mm and 40 mm away from the light source. The cerebral oxygen saturation was calculated using both the SRS approach, which uses the reflected intensities at both separations, and the SSDS approach, which employs the reflected intensities at either 30 mm or 40 mm separation. The SRS-based StO(2) calculation was similar to the value calculated from the SSDS method (average difference = 5.0% +/- 1.1%). This proposed method will help to advance the development of miniaturized technologies to monitor StO(2) continuously.