Optimal Spectral Combination of a Hyperspectral Camera for Intraoperative Hemodynamic and Metabolic Brain Mapping

Intraoperative optical imaging is a localization technique for the functional areas of the human brain cortex during neurosurgical procedures. These areas are assessed by monitoring the oxygenated (HbO${}_2$) and deoxygenated hemoglobin (Hb) concentration changes occurring in the brain. Sometimes, the functional status of the brain is assessed using metabolic biomarkers: the oxidative state of cytochrome-c-oxidase (oxCCO). A setup composed of a white light source and a hyperspectral or a standard RGB camera could be used to identify the functional areas. The choice of the best spectral configuration is still based on an empirical approach. We propose in this study a method to define the optimal spectral combinations of a commercial hyperspectral camera for the computation of hemodynamic and metabolic brain maps. The method is based on a Monte Carlo framework that simulates the acquisition of the intrinsic optical signal following a neuronal activation. The results indicate that the optimal spectral combination of a hyperspectral camera aims to accurately quantify the HbO${}_2$ ($0.5\%$ error), Hb ($4.4\%$ error), and oxCCO ($15\%$ error) responses in the brain following neuronal activation. We also show that RGB imaging is a low cost and accurate solution to compute Hb maps ($4\%$ error), but not accurate to compute HbO${}_2$ ($48\%$ error) or oxCCO ($1036\%$ error) maps. View Full-Text