Large Source-detector Separation Research Articles

Enhancing diffuse correlation spectroscopy pulsatile cerebral blood flow signal with near-infrared spectroscopy photoplethysmography.

Combining near-infrared spectroscopy (NIRS) and diffuse correlation spectroscopy (DCS) allows for quantifying cerebral blood volume, flow, and oxygenation changes continuously and non-invasively. As recently shown, the DCS pulsatile cerebral blood flow index () can be used to quantify critical closing pressure (CrCP) and cerebrovascular resistance (). Although current DCS technology allows for reliable monitoring of the slow hemodynamic changes, resolving pulsatile blood flow at large source-detector separations, which is needed to ensure cerebral sensitivity, is challenging because of its low signal-to-noise ratio (SNR). Cardiac-gated averaging of several arterial pulse cycles is required to obtain a meaningful waveform. Taking advantage of the high SNR of NIRS, we demonstrate a method that uses the NIRS photoplethysmography (NIRS-PPG) pulsatile signal to model DCS , reducing the coefficient of variation of the recovered pulsatile waveform () and allowing for an unprecedented temporal resolution (266Hz) at a large source-detector separation (). In 10 healthy subjects, we verified the quality of the NIRS-PPG during common tasks, showing high fidelity against ( ). We recovered CrCP and at 0.25Hz, times faster than previously achieved with DCS. NIRS-PPG improves DCS SNR, reducing the number of gate-averaged heartbeats required to recover CrCP and .

Superconducting nanowire single-photon sensing of cerebral blood flow

.Significance: The ability of diffuse correlation spectroscopy (DCS) to measure cerebral blood flow (CBF) in humans is hindered by the low signal-to-noise ratio (SNR) of the method. This limits the high acquisition rates needed to resolve dynamic flow changes and to optimally filter out large pulsatile oscillations and prevents the use of large source-detector separations (), which are needed to achieve adequate brain sensitivity in most adult subjects.Aim: To substantially improve SNR, we have built a DCS device that operates at 1064 nm and uses superconducting nanowire single-photon detectors (SNSPD).Approach: We compared the performances of the SNSPD-DCS in humans with respect to a typical DCS system operating at 850 nm and using silicon single-photon avalanche diode detectors.Results: At a 25-mm separation, we detected times more photons and achieved an SNR gain of on the forehead of 11 subjects using the SNSPD-DCS as compared to typical DCS. At this separation, the SNSPD-DCS is able to detect a clean pulsatile flow signal at 20 Hz in all subjects. With the SNSPD-DCS, we also performed measurements at 35 mm, showing a lower scalp sensitivity of with respect to the scalp sensitivity at 25 mm for both the 850 and 1064 nm systems. Furthermore, we demonstrated blood flow responses to breath holding and hyperventilation tasks.Conclusions: While current commercial SNSPDs are expensive, bulky, and loud, they may allow for more robust measures of non-invasive cerebral perfusion in an intensive care setting.

Diffuse correlation spectroscopy measurements of blood flow using 1064nm light.

.Significance: Diffuse correlation spectroscopy (DCS) is an established optical modality that enables noninvasive measurements of blood flow in deep tissue by quantifying the temporal light intensity fluctuations generated by dynamic scattering of moving red blood cells. Compared with near-infrared spectroscopy, DCS is hampered by a limited signal-to-noise ratio (SNR) due to the need to use small detection apertures to preserve speckle contrast. However, DCS is a dynamic light scattering technique and does not rely on hemoglobin contrast; thus, there are significant SNR advantages to using longer wavelengths () for the DCS measurement due to a variety of biophysical and regulatory factors.Aim: We offer a quantitative assessment of the benefits and challenges of operating DCS at 1064 nm versus the typical 765 to 850 nm wavelength through simulations and experimental demonstrations.Approach: We evaluate the photon budget, depth sensitivity, and SNR for detecting blood flow changes using numerical simulations. We discuss continuous wave (CW) and time-domain (TD) DCS hardware considerations for 1064 nm operation. We report proof-of-concept measurements in tissue-like phantoms and healthy adult volunteers.Results: DCS at 1064 nm offers higher intrinsic sensitivity to deep tissue compared with DCS measurements at the typically used wavelength range (765 to 850 nm) due to increased photon counts and a slower autocorrelation decay. These advantages are explored using simulations and are demonstrated using phantom and in vivo measurements. We show the first high-speed (cardiac pulsation-resolved), high-SNR measurements at large source–detector separation (3 cm) for CW-DCS and late temporal gates (1 ns) for TD-DCS.Conclusions: DCS at 1064 nm offers a leap forward in the ability to monitor deep tissue blood flow and could be especially useful in increasing the reliability of cerebral blood flow monitoring in adults.

The Temporal Confounding Effects of Extra-cerebral Contamination Factors on the Hemodynamic Signal Measured by Functional Near-Infrared Spectroscopy.

Introduction: Functional near-infrared spectroscopy (fNIRS) has been broadly applied for optical brain imaging. This method is hemodynamic-based functional brain imaging relying on the measurement of the neurovascular coupling to detect changes in cerebral neuronal activities. The extra-cerebral hemodynamic changes are important contaminating factors in fNIRS measurements. This error signal can be misinterpreted as cerebral activities during fNIRS studies. Recently, it was assumed that temporal changes in deoxygenated hemoglobin concentration [HHb] was hardly affected by superficial blood flow, and it was proposed that the activation maps could be determined from [HHb] at large source-detector separation. Methods: In the current study, we measured the temporal changes in [HHb] using a continueswave fNIRS device at large source-detector separation, while superficial blood flow was stimulated by infrared lasers. A mesh-based Monte Carlo code was applied to estimate fNIRS sensitivity to superficial hemodynamic changes in a realistic 3D MRI-based brain phantom. Results: First, we simulated photon migration in a four-layered human-head slab model to calculate PPLs and fNIRS sensitivity. Then, the localization of the infrared laser inside a realistic brain model was studied using the Monte Carlo method. Finally, the changes in [HHb] over the prefrontal cortex of six adult males were measured by fNIRS at a source-detector separation of 3 cm. The results demonstrated that the relation between fNIRS sensitivity and an increase in S-D separation was nonlinear and a correlation between shallow and deep signals was observed. Conclusion: The presented results demonstrated that the temporal changes in the superficial blood flow could strongly affect HHb measurement at large source-detector separation. Hence, the cerebral activity map extracted from the [HHb] signal was mainly contaminated by superficial blood flow.

Study on the cross-polarization method for extracting internal information of objects

In noninvasive near-infrared (NIR) noncontact measurement, a cross-polarization method is employed to eliminate undesired surface reflection and extract useful internal information. Experiments on various samples (both in vitro and in vivo) at different source-detector separations (SDSs) were conducted to investigate the effectiveness of this method. In conclusion, the cross-polarization method is proved to be effective in eliminating surface reflection as well as conducive to the measurement of objects’ internal information and this method is more suitable for scattering objects with smooth surfaces and complex interiors. Furthermore, a larger SDS can lead to a better measurement effect. This study can be a reference for tissue constituent sensing.

Depth dependence of coherent hemodynamics in the human head.

We report a near-infrared spectroscopy (NIRS) study of coherent hemodynamic oscillations measured on the human forehead at multiple source-detector distances (1 to 4cm). The physiological source of the coherent hemodynamics is arterial blood pressure oscillations at a frequency of 0.1Hz, induced by cyclic inflation (to a pressure of 200mmHg) and deflation of two thigh cuffs wrapped around the subject's thighs. To interpret our results, we use a recently developed hemodynamic model and a phasor representation of the oscillations of oxyhemoglobin, deoxyhemoglobin, and total hemoglobin concentrations in the tissue (phasors O, D, and T, respectively). The increase in the phase angle between D and O at larger source-detector separations is assigned to greater flow versus volume contributions and to a stronger blood flow autoregulation in deeper tissue (brain cortex) with respect to superficial tissue (scalp and skull). The relatively constant phase lag of T versus arterial blood pressure oscillations at all source-detector distances was assigned to competing effects from stronger autoregulation and smaller arterial-to-venous contributions in deeper tissue with respect to superficial tissue. We demonstrate the application of a hemodynamic model to interpret coherent hemodynamics measured with NIRS and to assess the different nature of shallow (extracerebral) versus deep (cerebral) tissue hemodynamics.

Near-Infrared Reflectometry on Human Head at Large Source-Detector Separation: Use of Passive Photodiode and EEG Amplifier

Near-Infrared Reflectometry on Human Head at Large Source-Detector Separation: Use of Passive Photodiode and EEG Amplifier

Joint derivation method for determining optical properties based on steady-state spatially resolved diffuse reflectance measurement at small source-detector separations and large reduced albedo range: theory and simulation

Accurate determination of the optical properties (the absorption coefficient μ(a) and the reduced scattering coefficient μ(s) (')) of tissues is very important in a variety of diagnostic and therapeutic procedures. Optical diffusion theory is frequently used as the forward model for describing the photon transfer in media with large reduced albedos (a(')) and in large source-detector separations (SDS). Several other methods (PN approximation, hybrid diffusion-P3 approximation) have also been published that describe photon transfer in media with low a(') or small SDSs. We studied the theoretical models for the steady-state spatially resolved diffuse reflectance measurement to accurately determine μ(a) and μ(s) (') at large a(') range but small SDSs. Instead of using a single model, a joint derivation method is proposed. The developed method uses one of the best aforementioned theoretical methods separately in five ranges of a(') determined from several forward models. In the region of small SDSs (the range between 0.4 and 8 mm) and large a(') range (between 0.5 and 0.99), the best theoretical derivation model was determined. The results indicate that the joint derivation method can improve the derivation accuracy and that a(') range can be determined by the steady-state spatially resolved diffuse reflectance measurement.

Noncontact diffuse correlation spectroscopy for noninvasive deep tissue blood flow measurement

A noncontact diffuse correlation spectroscopy (DCS) probe has been developed using two separated optical paths for the source and detector. This unique design avoids the interference between the source and detector and allows large source-detector separations for deep tissue blood flow measurements. The noncontact probe has been calibrated against a contact probe in a tissue-like phantom solution and human muscle tissues; flow changes concurrently measured by the two probes are highly correlated in both phantom (R(2)=0.89, p<10(-5)) and real-tissue (R(2)=0.77, p<10(-5), n=9) tests. The noncontact DCS holds promise for measuring blood flow in vulnerable (e.g., pressure ulcer) and soft (e.g., breast) tissues without distorting tissue hemodynamic properties.

Assessment of inflow and washout of indocyanine green in the adult human brain by monitoring of diffuse reflectance at large source-detector separation

Recently, it was shown in measurements carried out on humans that time-resolved near-infrared reflectometry and fluorescence spectroscopy may allow for discrimination of information originating directly from the brain avoiding influence of contaminating signals related to the perfusion of extracerebral tissues. We report on continuation of these studies, showing that the near-infrared light can be detected noninvasively on the surface of the tissue at large interoptode distance. A multichannel time-resolved optical monitoring system was constructed for measurements of diffuse reflectance in optically turbid medium at very large source-detector separation up to 9 cm. The instrument was applied during intravenous injection of indocyanine green and the distributions of times of flight of photons were successfully acquired showing inflow and washout of the dye in the tissue. Time courses of the statistical moments of distributions of times of flight of photons are presented and compared to the results obtained simultaneously at shorter source-detector separations (3, 4, and 5 cm). We show in a series of experiments carried out on physical phantom and healthy volunteers that the time-resolved data acquisition in combination with very large source-detector separation may allow one to improve depth selectivity of perfusion assessment in the brain.

Sequential estimation of optical properties of a two-layered epithelial tissue model from depth-resolved ultraviolet-visible diffuse reflectance spectra

A method for estimating the optical properties of two-layered media (such as squamous epithelial tissue) over a range of wavelengths in the ultraviolet-visible spectrum is proposed and tested with Monte Carlo modeling. The method first used a fiber-optic probe with angled illumination and the collection fibers placed at a small separation (<or=300 microm) to restrict the transport of detected light to the top layer. A Monte Carlo-based inverse model for a homogeneous medium was employed to estimate the top layer optical properties from the measured diffuse reflectance spectrum. Then a flat-tip probe with a large source-detector separation (>or=1000 microm) was used to detect diffuse reflectance preferentially from the bottom layer. A second Monte Carlo-based inverse model for a two-layered medium was applied to estimate the bottom layer optical properties, as well as the top layer thickness, given that the top layer optical properties have been estimated. The results of Monte Carlo validation show that this method works well for an epithelial tissue model with a top layer thickness ranging from 200 to 500 microm. For most thicknesses within this range, the absorption coefficients were estimated to within 15% of the true values, the reduced scattering coefficients were estimated to within 20% and the top layer thicknesses were estimated to within 20%. The application of a variance reduction technique to the Monte Carlo modeling proved to be effective in improving the accuracy with which the optical properties are estimated.