Presentation + Paper
5 March 2021 Assessing the ability to monitor cerebral blood flow and oxygen consumption by combining time-resolved near-infrared and diffuse correlation spectroscopy
Author Affiliations +
Abstract
Near-infrared spectroscopy (NIRS) combined with diffuse correlation spectroscopy (DCS) provides a non-invasive approach for monitoring oxygenation, cerebral blood flow (CBF) and the cerebral metabolic rate of oxygen (CMRO2); however, these methods are vulnerable to signal contamination from the extracerebral layer (ECL). The aim of this work was to evaluate methods of reducing the impact of this contamination using time-resolved (tr) NIRS and multi-distance (MD) DCS. Experiments involved healthy participants, and oxygenation and CBF changes in response to hypercapnia were measured. A pneumatic tourniquet was used to impede scalp blood flow to assess ECL contamination. Responses acquired with and without the tourniquet demonstrated that trNIRS technique substantially reduced scalp contributions in the oxygenation signals, while blood flow responses from the scalp and brain could be separated by analyzing MD DCS data with a multi-layer model. Finally, no change in CMRO2 during hypercapnia was observed, despite the large increases in CBF and oxygenation. These results indicate that NIRS/DCS techniques can accurately monitor cerebral blood flow and metabolism, highlighting the potential of these techniques for neuromonitoring
Conference Presentation
© (2021) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Daniel Milej, Androu Abdalmalak, Ajay Rajaram, and Keith St. Lawrence "Assessing the ability to monitor cerebral blood flow and oxygen consumption by combining time-resolved near-infrared and diffuse correlation spectroscopy", Proc. SPIE 11639, Optical Tomography and Spectroscopy of Tissue XIV, 1163918 (5 March 2021); https://doi.org/10.1117/12.2577933
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KEYWORDS
Near infrared spectroscopy

Cerebral blood flow

Oxygen

Spectroscopy

Data modeling

Time resolved spectroscopy

Contamination

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