Monitoring angiogenesis using a human compatible calibration for broadband near-infrared spectroscopy

Investigating spectroscopic measurement of sublingual veins and tissue to estimate central venous oxygen saturation

BACKGROUND

Venous oxygen saturation reflects venous oxygenation status and can be used to assess treatment and prognosis in critically ill patients. A novel method that can measure central venous oxygen saturation (ScvO2) non-invasively may be beneficial and has the potential to change the management routine of critically ill patients.

OBJECTIVE

The study aims to evaluate the potential of sublingual venous oxygen saturation (SsvO2) to be used in the estimation of ScvO2.

METHODS

We have developed two different approaches to calculate SsvO2. In the first one, near-infrared spectroscopy (NIRS) measurements were performed directly on the sublingual veins. In the second approach, NIRS spectra were acquired from the sublingual tissue apart from the sublingual veins, and arterial oxygen saturation was measured using a pulse oximeter on the fingertip.

RESULTS

Twenty-six healthy subjects were included in the study. In the first and second approaches, average SsvO2 values were 75.0% ± 1.8 and 75.8% ± 2.1, respectively. The results of the two different approaches were close to each other and similar to ScvO2 of healthy persons (> 70%).

CONCLUSION

Oxygen saturation of sublingual veins has the potential to be used in intensive care units, non-invasively and in real-time, to estimate ScvO2.

Near-infrared measurements of brain oxygenation in stroke

We investigated the feasibility of using frequency-domain near-infrared spectroscopy (fdNIRS) to study brain oxygenation in the first few hours of stroke onset. The OxiplexTS(®) fdNIRS system was used in this study. Using a standard probing protocol based on surface landmarks, we measured brain tHb and [Formula: see text] in healthy volunteers, cadavers, and acute stroke patients within 9 h of stroke onset and 3 days later. We obtained measurements from 11 controls, 5 cadavers, and 5 acute stroke patients. [Formula: see text] values were significantly lower in cadavers compared to the controls and stroke patients. Each stroke patient had at least one area with reduced [Formula: see text] on the stroke side compared to the contralateral side. The evolution of tHb and [Formula: see text] at 3 days differed depending on whether a large infarct occurred. This study shows the proof of principle that quantified measurements of brain oxygenation using NIRS could be used in the hectic environment of acute stroke management. It also highlights the current technical limitations and future challenges in the development of this unique bedside monitoring tool for stroke.

Diffuse reflectance spectroscopy for the measurement of tissue oxygen saturation

Tissue oxygen saturation (StO2) is a useful parameter for medical applications. A spectroscopic method has been developed to detect pathologic tissues, due to a lack of normal blood circulation, by measuring StO2. In this study, human blood samples with different levels of oxygen saturation have been prepared and spectra were acquired using an optical fiber probe to investigate the correlation between the oxygen saturation levels and the spectra. A linear correlation between the oxygen saturation and ratio of the intensities (760 nm to 790 nm) of the spectra acquired from blood samples has been found. In a validation study, oxygen saturations of the blood samples were estimated from the spectroscopic measurements with an error of 2.9%. It has also been shown that the linear dependence between the ratio and the oxygen saturation of the blood samples was valid for the blood samples with different hematocrits. Spectra were acquired from the forearms of 30 healthy volunteers to estimate StO2 prior to, at the beginning of, after 2 min, and at the release of total vascular occlusion. The average StO2 of a forearm before and after the two minutes occlusion was significantly different. The results suggested that optical reflectance spectroscopy is a sensitive method to estimate the StO2 levels of human tissue. The technique developed to measure StO2 has potential to detect ischemia in real time.

Studying cerebral hemodynamics and metabolism using simultaneous near-infrared spectroscopy and transcranial Doppler ultrasound: a hyperventilation and caffeine study

Caffeine is one of the most widely consumed psycho-stimulants in the world, yet little is known about its effects on brain oxygenation and metabolism. Using a double-blind, placebo-controlled, randomized cross-over study design, we combined transcranial Doppler ultrasound (TCD) and near-infrared spectroscopy (NIRS) to study caffeine's effect on middle cerebral artery peak blood flow velocity (Vp), brain tissue oxygenation (S_tO₂), total hemoglobin (tHb), and cerebral oxygen metabolism (CMRO₂) in five subjects. Hyperventilation-induced hypocapnia served as a control to verify the sensitivity of our measurements. During hypocapnia (∼16 mmHg below resting values), Vp decreased by 40.0 ± 2.4% (95% CI, P < 0.001), while S_tO₂ and tHb decreased by 2.9 ± 0.3% and 2.6 ± 0.4%, respectively (P = 0.003 and P = 0.002, respectively). CMRO₂, calculated using the Fick equation, was reduced by 29.3 ± 9% compared to the isocapnic-euoxia baseline (P < 0.001). In the pharmacological experiments, there was a significant decrease in Vp, S_tO₂, and tHb after ingestion of 200 mg of caffeine compared with placebo. There was no significant difference in CMRO₂ between caffeine and placebo. Both showed a CMRO₂ decline compared to baseline showing the importance of a placebo control. In conclusion, this study showed that profound hypocapnia impairs cerebral oxidative metabolism. We provide new insight into the effects of caffeine on cerebral hemodynamics. Moreover, this study showed that multimodal NIRS/TCD is an excellent tool for studying brain hemodynamic responses to pharmacological interventions and physiological challenges.

Combining independent component analysis and Granger causality to investigate brain network dynamics with fNIRS measurements

In this study a new strategy that combines Granger causality mapping (GCM) and independent component analysis (ICA) is proposed to reveal complex neural network dynamics underlying cognitive processes using functional near infrared spectroscopy (fNIRS) measurements. The GCM-ICA algorithm implements the following two procedures: (i) extraction of the region of interests (ROIs) of cortical activations by ICA, and (ii) estimation of the direct causal influences in local brain networks using Granger causality among voxels of ROIs. Our results show that the use of GCM in conjunction with ICA is able to effectively identify the directional brain network dynamics in time-frequency domain based on fNIRS recordings.