Direct assessment of extracerebral signal contamination on optical measurements of cerebral blood flow, oxygenation, and metabolism

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 ( $r_{\mathrm{SD}}=3\mathrm{cm}$ ) and 6 times ( $r_{\mathrm{SD}}=4\mathrm{cm}$ ). 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.

Keywords: brain imaging; diffuse correlation spectroscopy; diffuse reflectance; dynamic contrast-enhanced measurements; indocyanine green; near-infrared spectroscopy; time-resolved measurements.

Fig. 1

(a) Illustration of optical probes placement and (b) experimental paradigms used in the study.

Fig. 2

(a) Illustration of the experimental setup. The subject is wearing a sealed mask connected to the RespirAct™ system. An articulating arm stabilized the optical probes located on the forehead. (b) Time-varying changes in ${{\mathrm{P}}_{\mathrm{ET}}\mathrm{CO}}_2$ recorded before and after the tourniquet was inflated.

Fig. 3

Change in the (a) number of photons, (b) mean time-of-flight, and (c) variance plotted as a function of time following an intravenous bolus injection of ICG. Time courses are shown before (black) and after (red) inflating the tourniquet and for three source–detector distances. Shading surrounding each line represents the standard error of the mean.

Fig. 4

Average time courses of the change in oxyhemoglobin concentration ($\mathrm{\Delta }{C}_{\mathrm{HbO}}$) in response to hypercapnia, which is indicated by the gray region between 2 and 7 min. Time courses are shown for data acquired before and after tourniquet inflation and determined from the (a) number of photons, (b) mean time-of-flight, and (c) variance. Shading surrounding each line represents the standard error of the mean.

Fig. 5

Average time courses of the change in deoxyhemoglobin concentration ($\mathrm{\Delta }{C}_{\mathrm{Hb}}$) in response to hypercapnia (gray region). Time courses are shown for data acquired before and after tourniquet inflation and determined from the (a) number of photons, (b) mean time-of-flight, and (c) variance. Shading surrounding each line represents the standard error of the mean.

Fig. 6

(a) Changes in the blood flow index (rBFI) in response to step increases in tourniquet pressure recorded at $r_{\mathrm{SD}}=1$ and 3 cm. Shading surrounding each line represents the standard error of the mean. (b) BFI values for brain and scalp were derived using the multilayer model. Error bars represent the standard error of the mean. For reference, the shading represents the individual time courses [from (a)] recorded at $r_{\mathrm{SD}}=1$ and 3 cm.

Fig. 7

Changes in blood flow index ($\mathrm{\Delta }\mathrm{BFI}$) plotted as a function of time during the hypercapnic challenge with and without tourniquet inflation. Time courses are presented for (a) $r_{\mathrm{SD}}=1\mathrm{cm}$ and (b) $r_{\mathrm{SD}}=3\mathrm{cm}$. (c) For illustration purposes, the $\mathrm{\Delta }\mathrm{BFI}$ time courses for the two distances when the tourniquet was inflated are repeated. The shadowing represents the standard error of the mean.

Fig. 8

Tissue saturation (${\mathrm{StO}}_2$), rBFI, and ${\mathrm{rCMRO}}_2$ during the hypercapnic challenge (a) without and (b) with the tourniquet inflated. All data were acquired at $r_{\mathrm{SD}}=3\mathrm{cm}$, and ${\mathrm{StO}}_2$ was derived from the variance. Shadowing represents the standard error of the mean. (c) Final graph presents relative CBF changes obtained from the multilayer model and the corresponding ${\mathrm{rCMRO}}_2$. Error bars represent the standard error of the mean, and the shading represents rBFI and ${\mathrm{rCMRO}}_2$ time series with the tourniquet not inflated.