Abstract
.Significance: Near-infrared spectroscopy (NIRS) combined with diffuse correlation spectroscopy (DCS) provides a noninvasive approach for monitoring cerebral blood flow (CBF), oxygenation, and oxygen metabolism. However, these methods are vulnerable to signal contamination from the scalp. Our work evaluated methods of reducing the impact of this contamination using time-resolved (TR) NIRS and multidistance (MD) DCS.Aim: The magnitude of scalp contamination was evaluated by measuring the flow, oxygenation, and metabolic responses to a global hemodynamic challenge. Contamination was assessed by collecting data with and without impeding scalp blood flow.Approach: Experiments involved healthy participants. A pneumatic tourniquet was used to cause scalp ischemia, as confirmed by contrast-enhanced NIRS, and a computerized gas system to generate a hypercapnic challenge.Results: Comparing responses acquired with and without the tourniquet demonstrated that the TR-NIRS technique could reduce scalp contributions in hemodynamic signals up to 4 times () and 6 times (). Similarly, blood flow responses from the scalp and brain could be separated by analyzing MD DCS data with a multilayer model. Using these techniques, there was no change in metabolism during hypercapnia, as expected, despite large increases in CBF and oxygenation.Conclusion: NIRS/DCS can accurately monitor CBF and metabolism with the appropriate enhancement to depth sensitivity, highlighting the potential of these techniques for neuromonitoring.
Highlights
There was no change in metabolism during hypercapnia, as expected, despite large increases in cerebral blood flow (CBF) and oxygenation
This study focused on evaluating methods of reducing extracerebral layer (ECL) signal contamination on Near-infrared spectroscopy (NIRS) and diffuse correlation spectroscopy (DCS) measurements of StO2 and CBF, which were combined to determine CMRO2
TR-NIRS data collected with and without temporary scalp ischemia demonstrated how moment analysis could substantially reduce the effects of ECL contamination on cerebral oxygenation measurements
Summary
Near-infrared spectroscopy (NIRS) has long been considered ideal for brain monitoring of critical-care patients given its intrinsic sensitivity to tissue oxygenation, portability, safety, and low cost.[1,2] the overwhelming focus of clinical applications of commercial, continuous-wave (CW) NIRS systems has been on tissue oxygen saturation (StO2), the increasing interest in diffuse correlation spectroscopy (DCS) has opened the possibility to monitor cerebral blood flow (CBF) in conjunction with StO2.3 This combination can be used to determine the cerebral metabolic rate of oxygen (CMRO2), which has been applied to both neonatal and adult NeurophotonicsDownloaded From: https://www.spiedigitallibrary.org/journals/Neurophotonics on 08 Nov 2021 Terms of Use: https://www.spiedigitallibrary.org/terms-of-useOct–Dec 2020 Vol 7(4)Milej et al.: Direct assessment of extracerebral signal contamination on optical measurements. . .critical-care patients.[4,5] incorporating dynamic contrast-enhanced (DCE) NIRS, which uses the light-absorbing dye indocyanine green (ICG) as an intravascular contrast agent, enables the blood flow index (BFI) from DCS to be converted into perfusion units,[6,7,8] which can be used to quantify CMRO2 as well.[9,10]One of the main and well-known challenges with adapting these optical neuromonitoring techniques to adult patients is dealing with limited depth sensitivity, which is caused by substantially greater light interactions in superficial tissues (i.e., scalp and skull) compared with the brain. Fluctuations in scalp hemodynamics can overshadow brain-related signals,[11] and quantification of cerebral hemodynamics and metabolism requires accounting for signal contributions from the extracerebral layer (ECL) Ignoring these contributions can result in substantial errors in StO212,13 and CBF.[14,15,16] To reduce the influence of ECL contamination, most commercial CW-NIRS devices subtract signals measured at two source–detector distances. This approach relies on the assumption that scalp contributions will be similar at the two distances; this can be altered by factors such as local variations in scalp hemodynamics and skin-probe contact.[17] A number of approaches, such as principal component analysis and independent component analysis,[18] and modeling, such as Monte Carlo simulations,[19] have been proposed to eliminate ECL artifacts, but a standardized method remains an active research area. An alternative approach for addressing this issue is to use NIRS techniques that can enhance depth sensitivity, such as frequency-domain or time-resolved (TR) methods.[20,21,22,23,24] Of the two, TR-
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