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Abstract: Near-infrared neuromonitoring (NIN) is based on near-infrared spectroscopy (NIRS) measurements performed through the intact scalp and skull. Despite the important effects of overlying tissue layers on the measurement of brain hemodynamics, the influence of scalp and skull on NIN sensitivity are not well characterized. Using 3555 Monte Carlo simulations, we estimated the sensitivity of individual continuous-wave NIRS measurements to brain activity over the entire adult human head by introducing a small absorption perturbation to brain gray matter and quantifying the influence of scalp and skull thickness on this sensitivity. After segmenting the Colin27 template into five tissue types (scalp, skull, cerebrospinal fluid, gray matter and white matter), the average scalp thickness was 6.9±3.6mm (range: 3.6–11.2mm), while the average skull thickness was 6.0±1.9mm (range: 2.5–10.5mm). Mean NIN sensitivity – defined as the partial path length through gray matter divided by the total photon path length – ranged from 0.06 (i.e., 6% of total path length) at a 20mm source–detector separation, to over 0.19 at 50mm separations. NIN sensitivity varied substantially around the head, with occipital pole exhibiting the highest NIRS sensitivity to gray matter, whereas inferior frontal regions had the lowest sensitivity. Increased scalp and skull thickness were strongly associated with decreased sensitivity to brain tissue. Scalp thickness always exhibited a slightly larger effect on sensitivity than skull thickness, but the effect of both varied with SD separation. We quantitatively characterize sensitivity around the head as well as the effects of scalp and skull, which can be used to interpret NIN brain activation studies as well as guide the design, development and optimization of NIRS devices and sensors. [Copyright &y& Elsevier]

Abstract: In previous work we introduced a novel method for reducing global interference, based on adaptive filtering, to improve the contrast to noise ratio (CNR) of evoked hemodynamic responses measured non-invasively with near infrared spectroscopy (NIRS). Here, we address the issue of how to generally apply the proposed adaptive filtering method. A total of 156 evoked visual response measurements, collected from 15 individuals, were analyzed. The similarity (correlation) between measurements with far and near source–detector separations collected during the rest period before visual stimulation was used as indicator of global interference dominance. A detailed analysis of CNR improvement in oxy-hemoglobin (O2Hb) and deoxy-hemoglobin (HHb), as a function of the rest period correlation coefficient, is presented. Results show that for O2Hb measurements, 66% exhibited substantial global interference. For this dataset, dominated by global interference, 71% of the measurements revealed CNR improvements after adaptive filtering, with a mean CNR improvement of 60%. No CNR improvement was observed for HHb. This study corroborates our previous finding that adaptive filtering provides an effective method to increase CNR when there is strong global interference, and also provides a practical way for determining when and where to apply this technique. [Copyright &y& Elsevier]