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 (rSD = 3 cm) and 6 times (rSD = 4 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.
Optical methods are attractive tools for neuromonitoring given their safety and sensitivity to key markers of brain health: tissue oxygenation can be assessed by near-infrared spectroscopy (NIRS) and cerebral blood flow by diffuse correlation spectroscopy (DCS). Although the application of these tools to neonatal patients is fairly straightforward, since it is reasonable to model the head as an optically homogeneous medium, their use with adult patients is more complicated due to substantial signal contamination caused by hemodynamic fluctuations in the extracerebral (EC) tissue. The purpose of this study was to assess the magnitude of this contamination by acquiring NIRS and DCS data in response to a hypercapnic challenge with and without scalp contributions. Scalp blood flow was impeded by a pneumatic tourniquet, which was confirmed by dynamic contrast-enhanced (DCE) NIRS. The results showed that EC contamination for intensity measurements could be as high as 75%; however, using time-resolved detection can reduce this value to 30%.
There is a growing interest in the possibility of using functional neuroimaging techniques to aid in detecting covert awareness in patients who are thought to be suffering from a disorder of consciousness. Immerging optical techniques such as time-resolved functional near-infrared spectroscopy (TR-fNIRS) are ideal for such applications due to their low-cost, portability, and enhanced sensitivity to brain activity. The aim of this case study was to investigate for the first time the ability of TR-fNIRS to detect command driven motor imagery (MI) activity in a functionally locked-in patient suffering from Guillain–Barré syndrome. In addition, the utility of using TR-fNIRS as a brain–computer interface (BCI) was also assessed by instructing the patient to perform an MI task as affirmation to three questions: (1) confirming his last name, (2) if he was in pain, and (3) if he felt safe. At the time of this study, the patient had regained limited eye movement, which provided an opportunity to accurately validate a BCI after the fNIRS study was completed. Comparing the two sets of responses showed that fNIRS provided the correct answers to all of the questions. These promising results demonstrate for the first time the potential of using an MI paradigm in combination with fNIRS to communicate with functionally locked-in patients without the need for prior training.
The analysis of statistical moments of time-resolved (TR) diffuse optical signals can be used to evaluate the absorption and scattering coefficients of turbid media; however, this method requires careful measurement of the instrument response function. We propose an alternative approach that avoids this step by estimating the optical properties from the difference of TR measurements acquired at different source-detector separations. The efficiency of this method was validated using simulated data (from analytical model and Monte-Carlo simulations) and tissue-mimicking phantoms. Results for a homogenous and layered medium showed that the subtraction technique can accurately estimate the optical properties. Specifically, our preliminary results show that the method can estimate the optical properties of a homogeneous medium (simulated using μa = 0.1 mm-1, μs’ = 10 mm-1) with an error less than 10 %. Accurate results were obtained at source-detector separations large enough (5 mm or greater) to resolve differences in the moments. Moreover, we also observed that the subtraction method has improved depth sensitivity compared to the classic method of moments. These results suggests that time-resolved subtraction is a simple but effective means of quantifying optical properties of turbid media, in addition to offering a new approach for obtaining spatially sensitive measurements, although additional studies are required to confirm the latter.
Functional near-infrared spectroscopy (fNIRS) is a non-invasive optical technique for detecting brain activity, which has
been previously used during motor and motor executive tasks. There is an increasing interest in using fNIRS as a brain
computer interface (BCI) for patients who lack the physical, but not the mental, ability to respond to commands. The
goal of this study is to assess the feasibility of time-resolved fNIRS to detect brain activity during motor imagery.
Stability tests were conducted to ensure the temporal stability of the signal, and motor imagery data were acquired on
healthy subjects. The NIRS probes were placed on the scalp over the premotor cortex (PMC) and supplementary motor
area (SMA), as these areas are responsible for motion planning. To confirm the fNIRS results, subjects underwent
functional magnetic resonance imaging (fMRI) while performing the same task. Seven subjects have participated to date,
and significant activation in the SMA and/or the PMC during motor imagery was detected by both fMRI and fNIRS in 4
of the 7 subjects. No activation was detected by either technique in the remaining three participants, which was not
unexpected due to the nature of the task. The agreement between the two imaging modalities highlights the potential of
fNIRS as a BCI, which could be adapted for bedside studies of patients with disorders of consciousness.