Time-resolved (TR) near-infrared spectroscopy (NIRS) is a promising technique for neuromonitoring, but there are currently very few TR-NIRS devices with the spectral range and resolution needed for accurate monitoring of cerebral blood oxygenation (S t O 2 ) and metabolism (cytochrome-c-oxidase; oxCCO). Here we present a hyperspectral TR compressive sensing spectrometer with a wide spectral range, high spectral resolution, and no afterpulsing. A homogeneous blood-yeast phantom experiment was performed to evaluate the spectrometer's ability to monitor S t O 2 and oxCCO with and without compression. The effect of using a 90% compression rate on the recovered changes in deoxyhemoglobin (Hb), oxyhemoglobin (HbO), and oxCCO concentrations was investigated. No meaningful differences were found between concentration changes recovered from uncompressed and compressed data, with mean differences of 0.16 ± 0.20 µM , -0.25 ± 0.21 µM , and -0.04 ± 0.10 µM for Hb, HbO, and oxCCO, respectively. The results show that changes in oxCCO and S t O 2 can be reliably monitored with a high compression rate. Future work will compare the performance of the TR spectrometer with that of a continuous-wave spectrometer to assess accuracy and will investigate the sensitivity of the device to oxCCO and S t O 2 changes in the bottom compartment of a 2-layer tissue-mimicking phantom.
Time-resolved (TR) spectroscopy is well-suited to address the challenges of quantifying light absorbers in highly scattering media such as living tissue; however, current TR spectrometers are either based on expensive array detectors or rely on wavelength scanning. Here, we introduce a TR spectrometer architecture based on compressed sensing (CS) and time-correlated single-photon counting. Using both CS and basis scanning, we demonstrate that—in homogeneous and two-layer tissue-mimicking phantoms made of Intralipid and Indocyanine Green—the CS method agrees with or outperforms uncompressed approaches. Further, we illustrate the superior depth sensitivity of TR spectroscopy and highlight the potential of the device to quantify absorption changes in deeper (>1 cm) tissue layers.
Joint hypoxia plays a central role in the progression and perpetuation of rheumatoid arthritis (RA). Thus, optical techniques that can measure surrogate markers of hypoxia such as blood flow, oxyhemoglobin, deoxyhemoglobin, and oxygen saturation are being developed to monitor RA. The purpose of the current study was to compare the sensitivity of these physiological parameters to arthritis. Experiments were conducted in a rabbit model of RA and the results revealed that joint blood flow was the most sensitive to arthritis and could detect a statistically significant difference (p<0.05, power = 0.8) between inflamed and healthy joints with a sample size of only four subjects. Considering that this a quantitative technique, the high sensitivity to arthritis suggests that joint perfusion has the potential to become a potent tool for monitoring disease progression and treatment response in RA.
The dynamics of cerebral blood flow (CBF) at the onset of hypoglycemia may play a key role in hypoglycemia unawareness; however, there is currently a paucity of techniques that can monitor adult CBF with high temporal resolution. Herein, we investigated the use of diffuse correlation spectroscopy (DCS) to monitor the dynamics of CBF during insulin-induced hypoglycemia in adults. Plasma glucose concentrations, cortisol levels, and changes in CBF were measured before and during hypoglycemia in 8 healthy subjects. Cerebral blood flow increased by 42% following insulin injection with a delay of 17 ± 10 min, while the onset of hypoglycemia symptoms was delayed by 24 ± 11 min. The findings suggest that the onset of CBF increments precedes the appearance of hypoglycemia symptoms in nondiabetic subjects with normal awareness to hypoglycemia, and DCS could be a valuable tool for investigating the role of CBF in hypoglycemia unawareness.
Near-infrared spectroscopy (NIRS) can measure tissue blood content and oxygenation; however, its use for adult neuromonitoring is challenging due to significant contamination from their thick extracerebral layers (ECL; primarily scalp and skull). This report presents a fast method for accurate estimation of adult cerebral blood content and oxygenation from hyperspectral time resolved NIRS (trNIRS) data. A two-phase fitting method, based on a two-layer head model (ECL and brain), was developed. Phase 1 uses spectral constraints to accurately estimate the baseline blood content and oxygenation in both layers, which are then used by Phase 2 to correct for the ECL contamination of the late-arriving photons. The method was validated with in silico data from Monte-Carlo simulations of hyperspectral trNIRS in a realistic model of the adult head obtained from a high-resolution MRI. Phase 1 recovered cerebral blood oxygenation and total hemoglobin with an accuracy of 2.7 ± 2.5 and 2.8 ± 1.8%, respectively, with unknown ECL thickness, and 1.5 ± 1.4 and 1.7 ± 1.1% when the ECL thickness was known. Phase 2 recovered these parameters with an accuracy of 1.5 ± 1.5 and 3.1 ± 0.9%, respectively. Future work will include further validation in tissue-mimicking phantoms with various top layer thicknesses and in a pig model of the adult head before human applications.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.