Sensitivity of near-infrared spectroscopy and diffuse correlation spectroscopy to brain hemodynamics: simulations and experimental findings during hypercapnia

A Cost-Effective Method for the Spectral Calibration of Photoplethysmography Pulses: The Optimal Wavelengths for Heart Rate Monitoring

A photoplethysmography (PPG) pulse in reflection mode represents the change in diffuse reflectance at the skin surface during a cardiac cycle and is commonly used in wearable devices to monitor heart rate. Commercial PPG sensors often rely on the reflectance signal from light sources at two different wavelength regions, green, such as λ = 523 nm, and near infrared (NIR), such as λ = 945 nm. Early in vivo studies of wearable sensors showed that green light is more beneficial than NIR light in optimizing PPG sensitivity. This contradicts the common trends in the standard near infrared spectroscopy techniques, which rely on the long optical pathlengths at NIR wavelengths to achieve optimal depth sensitivity. To quantitatively analyze the spectral characteristics of PPG across the wavelength region of 500-900 nm in a controlled environment, this study performs the spectral measurement of PPG signals using a simple and cost-effective optical phantom model with two distinct layers and a customized diffuse reflectance spectroscopy system. In addition, Monte Carlo simulations are used to elaborate the underlying phenomena at the green and NIR wavelengths when considering different epithelial thicknesses and source-detector distances (SDD).

Finite Element Modeling of Abdominal Near-Infrared Spectroscopy for Infant Splanchnic Oximetry

Abdominal near-infrared spectroscopy (NIRS) holds promise for early detection of necrotizing enterocolitis and other infant pathologies prior to irreversible injury, but the optimal NIRS sensor design is not well defined. In this study, we develop and demonstrate a computational method to evaluate NIRS sensor designs for infant splanchnic oximetry. We used a finite element (FE) approach to simulate near-infrared light transport through a 3D model of the infant abdomen constructed from computed tomography (CT) images. The simulations enable the measurement of the contrast-to-noise ratio (CNR) for splanchnic oximetry, given a specific NIRS sensor design. A key design criterion is the sensor's source-detector distance (SDD). We calculated the CNR as a function of SDD for two sensor positions near the umbilicus. Contrast-to-noise was maximal at SDDs between 4 and 5 cm, and comparable between sensor positions. Sensitivity to intestinal tissue also exceeded sensitivity to superficial adipose tissue in the 4-5 cm range. FE modeling of abdominal NIRS signals provides a means for rapid and thorough evaluation of sensor designs for infant splanchnic oximetry. By informing optimal NIRS sensor design, the computational methods presented here can improve the reliability and applicability of infant splanchnic oximetry.

Beneath the surface: revealing deep-tissue blood flow in human subjects with massively parallelized diffuse correlation spectroscopy

Significance

Diffuse correlation spectroscopy (DCS) allows label-free, non-invasive investigation of microvascular dynamics deep within tissue, such as cerebral blood flow (CBF). However, the signal-to-noise ratio (SNR) in DCS limits its effective cerebral sensitivity in adults, in which the depth to the brain, through the scalp and skull, is substantially larger than in infants.

Aim

Therefore, we aim to increase its SNR and, ultimately, its sensitivity to CBF through new DCS techniques.

Approach

We present an in vivo demonstration of parallelized DCS (PDCS) to measure cerebral and muscular blood flow in healthy adults. Our setup employs an innovative array with hundreds of thousands single photon avalanche diodes (SPAD) in a 500 × 500 grid to boost SNR by averaging all independent pixel measurements. We tested this device on different total pixel counts and frame rates. A secondary, smaller array was used for reference measurements from shallower tissue at lower source-detector-separation (SDS).

Results

The new system can measure pulsatile blood flow in cerebral and muscular tissue, at up to 4 cm SDS, while maintaining a similar measurement noise as compared with a previously published 32 × 32 PDCS system at 1.5 cm SDS. Data from a cohort of 15 adults provide strong experimental evidence for functional CBF activity during a cognitive memory task and allowed analysis of pulse markers. Additional control experiments on muscular blood flow in the forearm with a different technical configuration provide converging evidence for the efficacy of this technique.

Conclusions

Our results outline successful PDCS measurements with large SPAD arrays to enable detect CBF in human adults. The ongoing development of SPAD camera technology is expected to result in larger and faster detectors in the future. In combination with new data processing techniques, tailored for the sparse signal of binary photon detection events in SPADs, this could lead to even greater SNR increase and ultimately greater depth sensitivity of PDCS.

Fast blood flow index reconstruction of diffuse correlation spectroscopy using a back-propagation-free data-driven algorithm

This study introduces a fast and accurate online training method for blood flow index (BFI) and relative BFI (rBFI) reconstruction in diffuse correlation spectroscopy (DCS). We implement rigorous mathematical models to simulate the auto-correlation functions (g 2) for semi-infinite homogeneous and three-layer human brain models. We implemented a fast online training algorithm known as random vector functional link (RVFL) to reconstruct BFI from noisy g 2. We extensively evaluated RVFL regarding both speed and accuracy for training and inference. Moreover, we compared RVFL with extreme learning machine (ELM) architecture, a conventional convolutional neural network (CNN), and three fitting algorithms. Results from semi-infinite and three-layer models indicate that RVFL achieves higher accuracy than the other algorithms, as evidenced by comprehensive metrics. While RVFL offers comparable accuracy to CNNs, it boosts training speeds that are 3900-fold faster and inference speeds that are 19.8-fold faster, enhancing its generalizability across different experimental settings. We also used g 2 from one- and three-layer Monte Carlo (MC)-based in-silico simulations, as well as from analytical models, to compare the accuracy and consistency of the results obtained from RVFL and ELM. Furthermore, we discuss how RVFL is more suitable for embedded hardware due to its lower computational complexity than ELM and CNN for training and inference.

Proof of concept validation of bioresorbable optical fibers for diffuse correlation spectroscopy

Optical quality bioresorbable materials have been gaining interest in recent years for various interstitial biomedical/medical application. An example of this is when the implant gradually dissolves in the body, providing physiological information over extended periods of time, hence reducing the need for revision surgeries. This study reports for the first time the in-house fabrication of single mode (at 785 nm) calcium phosphate glass (CPG) based bioresorbable optical fibers and investigates their suitability for microvascular blood flow monitoring using diffuse correlation spectroscopy (DCS). Ex vivo experiments in liquid phantom and non-invasive in vivo experiments on the human forearm muscle were conducted using multimode and single mode CPG bioresorbable optical fibers. The retrieved flow index from the correlation curves acquired using CPG fibers was in good agreement with that obtained using standard silica (Si) fibers, both ex vivo and in vivo. The results demonstrate the potential of CPG optical fibers for further exploration.

Microvascular reperfusion during endovascular therapy: the balance of supply and demand

BACKGROUND

Endovascular therapy (EVT) has revolutionized the treatment of acute stroke, but large vessel recanalization does not always result in tissue-level reperfusion. Cerebral blood flow (CBF) is not routinely monitored during EVT. We aimed to leverage diffuse correlation spectroscopy (DCS), a novel transcranial optical imaging technique, to assess the relationship between microvascular CBF and post-EVT outcomes.

METHODS

Frontal lobe CBF was monitored by DCS in 40 patients undergoing EVT. Baseline CBF deficit was calculated as the percentage of CBF impairment on pre-EVT CT perfusion. Microvascular reperfusion was calculated as the percentage increase in DCS-derived CBF that occurred with recanalization. The adequacy of reperfusion was defined by persistent CBF deficit, calculated as: baseline CBF deficit - microvascular reperfusion. A good functional outcome was defined as 90-day modified Rankin Scale score ≤2.

RESULTS

Thirty-six of 40 patients achieved successful recanalization, in whom microvascular reperfusion in itself was not associated with infarct volume or functional outcome. However, patients with good functional outcomes had a smaller persistent CBF deficit (median 1% (IQR -11%-16%)) than patients with poor outcomes (median 28% (IQR 2-50%)) (p=0.02). Smaller persistent CBF deficit was also associated with smaller infarct volume (p=0.004). Multivariate models confirmed that persistent CBF deficit was independently associated with infarct volume and functional outcome.

CONCLUSIONS

CBF augmentation alone does not predict post-EVT outcomes, but when microvascular reperfusion closely matches the baseline CBF deficit, patients experience favorable clinical and radiographic outcomes. By recognizing inadequate reperfusion, bedside CBF monitoring may provide opportunities to personalize post-EVT care aimed at CBF optimization.

How the heterogeneity of the severely injured brain affects hybrid diffuse optical signals: case examples and guidelines

Significance

A shortcoming of the routine clinical use of diffuse optics (DO) in the injured head has been that the results from commercial near-infrared spectroscopy-based devices are not reproducible, often give physiologically invalid values, and differ among systems. Besides the limitations due to the physics of continuous-wave light sources, one culprit is the head heterogeneity and the underlying morphological and functional abnormalities of the probed tissue.

Aim

The aim is to investigate the effect that different tissue alterations in the damaged head have on DO signals and provide guidelines to avoid data misinterpretation.

Approach

DO measurements and computed tomography scans were acquired on brain-injured patients. The relationship between the signals and the underlying tissue types was classified on a case-by-case basis.

Results

Examples and suggestions to establish quality control routines were provided. The findings suggested guidelines for carrying out DO measurements and speculations toward improved devices.

Conclusions

We advocate for the standardization of the DO measurements to secure a role for DO in neurocritical care. We suggest that blind measurements are unacceptably problematic due to confounding effects and care using a priori and a posteriori quality control routines that go beyond an assessment of the signal-to-noise ratio that is typically utilized.

Modified Beer-Lambert algorithm to measure pulsatile blood flow, critical closing pressure, and intracranial hypertension

We introduce a frequency-domain modified Beer-Lambert algorithm for diffuse correlation spectroscopy to non-invasively measure flow pulsatility and thus critical closing pressure (CrCP). Using the same optical measurements, CrCP was obtained with the new algorithm and with traditional nonlinear diffusion fitting. Results were compared to invasive determination of intracranial pressure (ICP) in piglets (n = 18). The new algorithm better predicted ICP elevations; the area under curve (AUC) from logistic regression analysis was 0.85 for ICP ≥ 20 mmHg. The corresponding AUC for traditional analysis was 0.60. Improved diagnostic performance likely results from better filtering of extra-cerebral tissue contamination and measurement noise.

Non-invasive optical and laboratory hematologic biomarkers correlate in patients with sickle cell disease

The goal of this study is to identify non-invasive optical hemodynamic biomarkers that can index laboratory hematology measurements in sickle cell disease (SCD). We acquired frequency-domain NIRS (FD-NIRS) and diffuse correlation spectroscopy (DCS) data from the forearms and foreheads of 17 participants in a randomized, double-blind, placebo-controlled trial evaluating effects of isoquercetin (IQ) on thromboinflammation in SCD. We observed multiple, significant correlations between optical and hematology biomarkers including cerebral tissue oxygen saturation (StO2) and hematocrit (HCT); oxyhemoglobin ([O2Hb]) recovery rate and intercellular adhesion molecule 1 (ICAM-1); and blood flow index (BFI) reperfusion rate and coagulation index (CI). The potential of these non-invasive optical biomarkers for assessing vascular pathophysiology for the management of SCD warrants further exploration.

Time-domain diffuse correlation spectroscopy at large source detector separation for cerebral blood flow recovery

Time-domain diffuse correlation spectroscopy (td-DCS) enables the depth discrimination in tissue's blood flow recovery, considering the fraction of photons detected with higher time of flight (TOF) and longer pathlength through the tissue. However, the recovery result depends on factors such as the instrument response function (IRF), analyzed TOF gate start time, gate width and the source-detector separation (SDS). In this research we evaluate the performance of the td-DCS technique at three SDSs of 1.5, 2 and 2.5 cm to recover cerebral blood flow (CBF). To do that we presented comprehensive characterization of the td-DCS system through a series of phantom experiments. First by quality metrices such as coefficient of variation and contrast-to-noise ratios, we identified optimal time gate(s) of the TOF to extract dynamics of particles. Then using sensitivity metrices, each SDS ability to detect dynamics of particles in superficial and deeper layer was evaluated. Finally, td-DCS at each SDS was tested on healthy volunteers during cuff occlusion test and breathing tasks. According to phantom measurements, the sensitivity to estimate perfusion within the deep layer located at depth of 1.5 cm from the surface can be increased more than two times when the SDS increases from 1.5 cm to 2.5 cm.

Detectability of hemodynamic oscillations in cerebral cortex through functional near-infrared spectroscopy: a simulation study

Significance

We explore the feasibility of using time-domain (TD) and continuous-wave (CW) functional near-infrared spectroscopy (fNIRS) to monitor brain hemodynamic oscillations during resting-state activity in humans, a phenomenon that is of increasing interest in the scientific and medical community and appears to be crucial to advancing the understanding of both healthy and pathological brain functioning.

Aim

Our general object is to maximize fNIRS sensitivity to brain resting-state oscillations. More specifically, we aim to define comprehensive guidelines for optimizing main operational parameters in fNIRS measurements [average photon count rate, measurement length, sampling frequency, and source-detector distance (SSD)]. In addition, we compare TD and CW fNIRS performance for the detection and localization of oscillations.

Approach

A series of synthetic TD and CW fNIRS signals were generated by exploiting the solution of the diffusion equation for two different geometries of the probed medium: a homogeneous medium and a bilayer medium. Known and periodical perturbations of the concentrations of oxy- and deoxy-hemoglobin were imposed in the medium, determining changes in its optical properties. The homogeneous slab model was used to determine the effect of multiple measurement parameters on fNIRS sensitivity to oscillatory phenomena, and the bilayer model was used to evaluate and compare the abilities of TD and CW fNIRS in detecting and isolating oscillations occurring at different depths. For TD fNIRS, two approaches to enhance depth-selectivity were evaluated: first, a time-windowing of the photon distribution of time-of-flight was performed, and then, the time-dependent mean partial pathlength (TMPP) method was used to retrieve the hemoglobin concentrations in the medium.

Results

In the homogeneous medium case, the sensitivity of TD and CW fNIRS to periodical perturbations of the optical properties increases proportionally with the average photon count rate, the measurement length, and the sampling frequency and approximatively with the square of the SSD. In the bilayer medium case, the time-windowing method can detect and correctly localize the presence of oscillatory components in the TD fNIRS signal, even in the presence of very low photon count rates. The TMPP method demonstrates how to correctly retrieve the periodical variation of hemoglobin at different depths from the TD fNIRS signal acquired at a single SSD. For CW fNIRS, measurements taken at typical SSDs used for short-separation channel regression show notable sensitivity to oscillations occurring in the deep layer, challenging the assumptions underlying this correction method when the focus is on analyzing oscillatory phenomena.

Conclusions

We demonstrated that the TD fNIRS technique allows for the detection and depth-localization of periodical fluctuations of the hemoglobin concentrations within the probed medium using an acquisition at a single SSD, offering an alternative to multi-distance CW fNIRS setups. Moreover, we offered some valuable guidelines that can assist researchers in defining optimal experimental protocols for fNIRS studies.

Lawrence K, Chui J, Diop M. Assessing changes in regional cerebral hemodynamics in adults with a high-density full-head coverage time-resolved near-infrared spectroscopy device

Significance

Cerebral oximeters have the potential to detect abnormal cerebral blood oxygenation to allow for early intervention. However, current commercial systems have two major limitations: (1) spatial coverage of only the frontal region, assuming that surgery-related hemodynamic effects are global and (2) susceptibility to extracerebral signal contamination inherent to continuous-wave near-infrared spectroscopy (NIRS).

Aim

This work aimed to assess the feasibility of a high-density, time-resolved (tr) NIRS device (Kernel Flow) to monitor regional oxygenation changes across the cerebral cortex during surgery.

Approach

The Flow system was assessed using two protocols. First, digital carotid compression was applied to healthy volunteers to cause a rapid oxygenation decrease across the ipsilateral hemisphere without affecting the contralateral side. Next, the system was used on patients undergoing shoulder surgery to provide continuous monitoring of cerebral oxygenation. In both protocols, the improved depth sensitivity of trNIRS was investigated by applying moment analysis. A dynamic wavelet filtering approach was also developed to remove observed temperature-induced signal drifts.

Results

In the first protocol (28 ± 5 years; five females, five males), hair significantly impacted regional sensitivity; however, the enhanced depth sensitivity of trNIRS was able to separate brain and scalp responses in the frontal region. Regional sensitivity was improved in the clinical study given the age-related reduction in hair density of the patients (65 ± 15 years; 14 females, 13 males). In five patients who received phenylephrine to treat hypotension, different scalp and brain oxygenation responses were apparent, although no regional differences were observed.

Conclusions

The Kernel Flow has promise as an intraoperative neuromonitoring device. Although regional sensitivity was affected by hair color and density, enhanced depth sensitivity of trNIRS was able to resolve differences in scalp and brain oxygenation responses in both protocols.

Measuring pulsatile cortical blood flow and volume during carotid endarterectomy

Carotid endarterectomy (CEA) involves removal of plaque in the carotid artery to reduce the risk of stroke and improve cerebral perfusion. This study aimed to investigate the utility of assessing pulsatile blood volume and flow during CEA. Using a combined near-infrared spectroscopy/diffuse correlation spectroscopy instrument, pulsatile hemodynamics were assessed in 12 patients undergoing CEA. Alterations to pulsatile amplitude, pulse transit time, and beat morphology were observed in measurements ipsilateral to the surgical side. The additional information provided through analysis of pulsatile hemodynamic signals has the potential to enable the discovery of non-invasive biomarkers related to cortical perfusion.

Improving heart rate monitoring in the obese with time-of-flight photoplethysmography (TOF-PPG): a quantitative analysis of source-detector-distance effect

Commercial photoplethysmography (PPG) sensors rely on the measurement of continuous-wave diffuse reflection signals (CW-DRS) to monitor heart rate. Using Monte Carlo modeling of light propagation in skin, we quantitatively evaluate the dependence of continuous-wave photoplethysmography (CW-PPG) in commercial wearables on source-detector distance (SDD). Specifically, when SDD increases from 0.5 mm to 3.3 mm, CW-PPG signal increases by roughly 846% for non-obese (NOB) skin and roughly 683% for morbidly obese (MOB) skin. Ultimately, we introduce the concept of time-of-flight PPG (TOF-PPG) which can significantly improve heart rate signals. Our model shows that the optimized TOF-PPG improves heart rate monitoring experiences by roughly 47.9% in NOB and 93.2% in MOB when SDD = 3.3 mm is at green light. Moving forward, these results will provide a valuable source for hypothesis generation in the scientific community to improve heart rate monitoring.

Validation of the Openwater wearable optical system: cerebral hemodynamic monitoring during a breath-hold maneuver

Significance

Bedside cerebral blood flow (CBF) monitoring has the potential to inform and improve care for acute neurologic diseases, but technical challenges limit the use of existing techniques in clinical practice.

Aim

Here, we validate the Openwater optical system, a novel wearable headset that uses laser speckle contrast to monitor microvascular hemodynamics.

Approach

We monitored 25 healthy adults with the Openwater system and concurrent transcranial Doppler (TCD) while performing a breath-hold maneuver to increase CBF. Relative blood flow (rBF) was derived from changes in speckle contrast, and relative blood volume (rBV) was derived from changes in speckle average intensity.

Results

A strong correlation was observed between beat-to-beat optical rBF and TCD-measured cerebral blood flow velocity (CBFv), R = 0.79 ; the slope of the linear fit indicates good agreement, 0.87 (95% CI: 0.83 - 0.92 ). Beat-to-beat rBV and CBFv were also strongly correlated, R = 0.72 , but as expected the two variables were not proportional; changes in rBV were smaller than CBFv changes, with linear fit slope of 0.18 (95% CI: 0.17 to 0.19). Further, strong agreement was found between rBF and CBFv waveform morphology and related metrics.

Conclusions

This first in vivo validation of the Openwater optical system highlights its potential as a cerebral hemodynamic monitor, but additional validation is needed in disease states.

Comparing the performance potential of speckle contrast optical spectroscopy and diffuse correlation spectroscopy for cerebral blood flow monitoring using Monte Carlo simulations in realistic head geometries

Significance

The non-invasive measurement of cerebral blood flow based on diffuse optical techniques has seen increased interest as a research tool for cerebral perfusion monitoring in critical care and functional brain imaging. Diffuse correlation spectroscopy (DCS) and speckle contrast optical spectroscopy (SCOS) are two such techniques that measure complementary aspects of the fluctuating intensity signal, with DCS quantifying the temporal fluctuations of the signal and SCOS quantifying the spatial blurring of a speckle pattern. With the increasing interest in the use of these techniques, a thorough comparison would inform new adopters of the benefits of each technique.

Aim

We systematically evaluate the performance of DCS and SCOS for the measurement of cerebral blood flow.

Approach

Monte Carlo simulations of dynamic light scattering in an MRI-derived head model were performed. For both DCS and SCOS, estimates of sensitivity to cerebral blood flow changes, coefficient of variation of the measured blood flow, and the contrast-to-noise ratio of the measurement to the cerebral perfusion signal were calculated. By varying complementary aspects of data collection between the two methods, we investigated the performance benefits of different measurement strategies, including altering the number of modes per optical detector, the integration time/fitting time of the speckle measurement, and the laser source delivery strategy.

Results

Through comparison across these metrics with simulated detectors having realistic noise properties, we determine several guiding principles for the optimization of these techniques and report the performance comparison between the two over a range of measurement properties and tissue geometries. We find that SCOS outperforms DCS in terms of contrast-to-noise ratio for the cerebral blood flow signal in the ideal case simulated here but note that SCOS requires careful experimental calibrations to ensure accurate measurements of cerebral blood flow.

Conclusion

We provide design principles by which to evaluate the development of DCS and SCOS systems for their use in the measurement of cerebral blood flow.

Quantification of blood flow index in diffuse correlation spectroscopy using a robust deep learning method

Significance

Diffuse correlation spectroscopy (DCS) is a powerful, noninvasive optical technique for measuring blood flow. Traditionally the blood flow index (BFi) is derived through nonlinear least-square fitting the measured intensity autocorrelation function (ACF). However, the fitting process is computationally intensive, susceptible to measurement noise, and easily influenced by optical properties (absorption coefficient μ a and reduced scattering coefficient μ s ' ) and scalp and skull thicknesses.

Aim

We aim to develop a data-driven method that enables rapid and robust analysis of multiple-scattered light's temporal ACFs. Moreover, the proposed method can be applied to a range of source-detector distances instead of being limited to a specific source-detector distance.

Approach

We present a deep learning architecture with one-dimensional convolution neural networks, called DCS neural network (DCS-NET), for BFi and coherent factor (β ) estimation. This DCS-NET was performed using simulated DCS data based on a three-layer brain model. We quantified the impact from physiologically relevant optical property variations, layer thicknesses, realistic noise levels, and multiple source-detector distances (5, 10, 15, 20, 25, and 30 mm) on BFi and β estimations among DCS-NET, semi-infinite, and three-layer fitting models.

Results

DCS-NET shows a much faster analysis speed, around 17,000-fold and 32-fold faster than the traditional three-layer and semi-infinite models, respectively. It offers higher intrinsic sensitivity to deep tissues compared with fitting methods. DCS-NET shows excellent anti-noise features and is less sensitive to variations of μ a and μ s ' at a source-detector separation of 30 mm. Also, we have demonstrated that relative BFi (rBFi) can be extracted by DCS-NET with a much lower error of 8.35%. By contrast, the semi-infinite and three-layer fitting models result in significant errors in rBFi of 43.76% and 19.66%, respectively.

Conclusions

DCS-NET can robustly quantify blood flow measurements at considerable source-detector distances, corresponding to much deeper biological tissues. It has excellent potential for hardware implementation, promising continuous real-time blood flow measurements.

Decoding diffuse light scattering dynamics in layered tissues: path length versus fluctuation time scale

Dynamic multiple light scattering (DMLS) has found numerous applications, including soft matter physics and biomedical optics. Yet biological tissues may have complex internal geometries, presenting a challenge for noninvasive measurements. Deciphering laminar dynamics is crucial to accurately interpret tissue or organ physiology. Seminal DMLS work noted that one can probe deeper layers indirectly by analyzing light fluctuations on shorter time scales. Recent technologies have enabled probing deeper layers directly by analyzing fluctuations at longer path lengths. The following question arises: are the indirect and direct approaches synergistic or redundant? Here, by adding an optical switch to path-length-filtered interferometric diffusing wave spectroscopy, we experimentally address this question in the context of a forearm occlusion study. We find that both approaches afford better distinction of light scattering dynamics in layered tissues than either approach alone. This motivates further development of methods that integrate both decorrelation time scale and light path length to probe layered tissues.

Impaired cerebrovascular reactivity in pediatric sickle cell disease using diffuse correlation spectroscopy

Cerebrovascular reactivity (CVR), defined as the ability of cerebral vasculature to dilate in response to a vasodilatory stimulus, is an integral mechanism in brain homeostasis that is thought to be impaired in sickle cell disease (SCD). This study used diffuse correlation spectroscopy and a simple breath-hold stimulus to quantify CVR non-invasively in a cohort of 12 children with SCD and 14 controls. Median [interquartile range] CVR was significantly decreased in SCD compared to controls (2.03 [1.31, 2.44] versus 3.49 [3.00, 4.11] %/mmHg, p = 0.028). These results suggest DCS may provide a feasible means to routinely monitor CVR impairments in pediatric SCD.

Comparison of numerical-integration-based methods for blood flow estimation in diffuse correlation spectroscopy

BACKGROUND AND OBJECTIVE

Diffuse correlation spectroscopy (DCS) is an optical blood flow monitoring technology that has been utilized in various biomedical applications. In signal processing of DCS, nonlinear fitting of the experimental data and the theoretical model can be a hindrance in real-time blood flow monitoring. As one of the approaches to resolve the issue, INISg1, the inverse of numerical integration of squared g1 (a normalized electric field autocorrelation function), that could surpass the state-of-the-art technique at the time in terms of signal processing speed, has been introduced. While it is possible to implement INISg1 using various numerical integration methods, no relevant studies have been performed. Meanwhile, INISg1 was only tested within limited experimental conditions, which cannot guarantee the robustness of INISg1 in various experimental conditions. Thus, this study aims to introduce variants of INISg1 and perform a thorough comparison of the original INISg1 and its variants.

METHODS

In this study, based on the right Riemann sum (RR) and trapezoid rule (TR) of numerical integration, INISg1_RR and INISg1_TR are suggested. They are thoroughly compared with the original INISg1 using model-based simulations that offer us control of most of the experimental conditions, including integration time, β, and photon count rate.

RESULTS

Except for some extreme cases, INISg1 performed more robustly than INISg1_RR and INISg1_TR. However, in extreme conditions, variants of INISg1 performed better than INISg1. With the same condition, the signal processing speed of INISg1 was 1.63 and 1.98 times faster than INISg1_RR and INISg1_TR, respectively.

CONCLUSION

This study shows that INISg1 is robust in most cases and the study can be a guide for researchers using INISg1 and its variants in different types of DCS applications.

Differences in time-frequency characteristics between healthy controls and TBI patients during hypercapnia assessed via fNIRS

Damage to the cerebrovascular network is a universal feature of traumatic brain injury (TBI). This damage is present during different phases of the injury and can be non-invasively assessed using functional near infrared spectroscopy (fNIRS). fNIRS signals are influenced by partial arterial carbon dioxide (PaCO2), neurogenic, Mayer waves, respiratory and cardiac oscillations, whose characteristics vary in time and frequency and may differ in the presence of TBI. Therefore, this study aims to investigate differences in time-frequency characteristics of these fNIRS signal components between healthy controls and TBI patients and characterize the changes in their characteristics across phases of the injury. Data from 11 healthy controls and 21 TBI patients were collected during the hypercapnic protocol. Results demonstrated significant differences in low-frequency oscillations between healthy controls and TBI patients, with the largest differences observed in Mayer wave band (0.06 to 0.15 Hz), followed by the PaCO2 band (0.012 to 0.02 Hz). The effects within these bands were opposite, with (i) Mayer wave activity being lower in TBI patients during acute phase of the injury (d = 0.37 [0.16, 0.57]) and decreasing further during subacute (d = 0.66 [0.44, 0.87]) and postacute (d = 0.75 [0.50, 0.99]) phases; (ii) PaCO2 activity being lower in TBI patients only during acute phase of the injury (d = 0.36 [0.15, 0.56]) and stabilizing to healthy levels by the subacute phase. These findings demonstrate that TBI patients have impairments in low frequency oscillations related to different mechanisms and that these impairments evolve differently over the course of injury.

Anatomical Modeling and Optimization of Speckle Contrast Optical Tomography

Traditional methods for mapping cerebral blood flow (CBF), such as positron emission tomography and magnetic resonance imaging, offer only isolated snapshots of CBF due to scanner logistics. Speckle contrast optical tomography (SCOT) is a promising optical technique for mapping CBF. However, while SCOT has been established in mice, the method has not yet been demonstrated in humans - partly due to a lack of anatomical reconstruction methods and uncertainty over the optimal design parameters. Herein we develop SCOT reconstruction methods that leverage MRI-based anatomical head models and finite-element modeling of the SCOT forward problem (NIRFASTer). We then simulate SCOT for CBF perturbations to evaluate sensitivity of imaging performance to exposure time and SD-distances. We find image resolution comparable to intensity-based diffuse optical tomography at superficial cortical tissue depth (~1.5 cm). Localization errors can be reduced by including longer SD-measurements. With longer exposure times speckle contrast decreases, however, noise decreases faster, resulting in a net increase in SNR. Specifically, extending exposure time from 10μs to 10ms increased SCOT SNR by 1000X. Overall, our modeling methods provide anatomically-based image reconstructions that can be used to evaluate a broad range of tissue conditions, measurement parameters, and noise sources and inform SCOT system design.

How does obstructive sleep apnea alter cerebral hemodynamics?

STUDY OBJECTIVES

We aimed to characterize the cerebral hemodynamic response to obstructive sleep apnea/hypopnea events, and evaluate their association to polysomnographic parameters. The characterization of the cerebral hemodynamics in obstructive sleep apnea (OSA) may add complementary information to further the understanding of the severity of the syndrome beyond the conventional polysomnography.

METHODS

Severe OSA patients were studied during night sleep while monitored by polysomnography. Transcranial, bed-side diffuse correlation spectroscopy (DCS) and frequency-domain near-infrared diffuse correlation spectroscopy (NIRS-DOS) were used to follow microvascular cerebral hemodynamics in the frontal lobes of the cerebral cortex. Changes in cerebral blood flow (CBF), total hemoglobin concentration (THC), and cerebral blood oxygen saturation (StO2) were analyzed.

RESULTS

We considered 3283 obstructive apnea/hypopnea events from sixteen OSA patients (Age (median, interquartile range) 57 (52-64.5); females 25%; AHI (apnea-hypopnea index) 84.4 (76.1-93.7)). A biphasic response (maximum/minimum followed by a minimum/maximum) was observed for each cerebral hemodynamic variable (CBF, THC, StO2), heart rate and peripheral arterial oxygen saturation (SpO2). Changes of the StO2 followed the dynamics of the SpO2, and were out of phase from the THC and CBF. Longer events were associated with larger CBF changes, faster responses and slower recoveries. Moreover, the extrema of the response to obstructive hypopneas were lower compared to apneas (p < .001).

CONCLUSIONS

Obstructive apneas/hypopneas cause profound, periodic changes in cerebral hemodynamics, including periods of hyper- and hypo-perfusion and intermittent cerebral hypoxia. The duration of the events is a strong determinant of the cerebral hemodynamic response, which is more pronounced in apnea than hypopnea events.

Measuring human cerebral blood flow and brain function with fiber-based speckle contrast optical spectroscopy system

Cerebral blood flow (CBF) is crucial for brain health. Speckle contrast optical spectroscopy (SCOS) is a technique that has been recently developed to measure CBF, but the use of SCOS to measure human brain function at large source-detector separations with comparable or greater sensitivity to cerebral rather than extracerebral blood flow has not been demonstrated. We describe a fiber-based SCOS system capable of measuring human brain activation induced CBF changes at 33 mm source detector separations using CMOS detectors. The system implements a pulsing strategy to improve the photon flux and uses a data processing pipeline to improve measurement accuracy. We show that SCOS outperforms the current leading optical modality for measuring CBF, i.e. diffuse correlation spectroscopy (DCS), achieving more than 10x SNR improvement at a similar financial cost. Fiber-based SCOS provides an alternative approach to functional neuroimaging for cognitive neuroscience and health science applications.

Fast time-domain diffuse correlation spectroscopy with superconducting nanowire single-photon detector: system validation and in vivo results

Time-domain diffuse correlation spectroscopy (TD-DCS) has been introduced as an advancement of the "classical" continuous wave DCS (CW-DCS) allowing one to not only to measure depth-resolved blood flow index (BFI) but also to extract optical properties of the measured medium without using any additional diffuse optics technique. However, this method is a photon-starved technique, specially when considering only the late photons that are of primary interest which has limited its in vivo application. In this work, we present a TD-DCS system based on a superconducting nanowire single-photon detector (SNSPD) with a high quantum efficiency, a narrow timing response, and a negligibly low dark count noise. We compared it to the typically used single-photon avalanche diode (SPAD) detector. In addition, this system allowed us to conduct fast in vivo measurements and obtain gated pulsatile BFI on the adult human forehead.

Normative cerebral microvascular blood flow waveform morphology assessed with diffuse correlation spectroscopy

Microvascular cerebral blood flow exhibits pulsatility at the cardiac frequency that carries valuable information about cerebrovascular health. This study used diffuse correlation spectroscopy to quantify normative features of these waveforms in a cohort of thirty healthy adults. We demonstrate they are sensitive to changes in vascular tone, as indicated by pronounced morphological changes with hypercapnia. Further, we observe significant sex-based differences in waveform morphology, with females exhibiting higher flow, greater area-under-the-curve, and lower pulsatility. Finally, we quantify normative values for cerebral critical closing pressure, i.e., the minimum pressure required to maintain flow in a given vascular region.

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

Significance

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 (pCBF i ) can be used to quantify critical closing pressure (CrCP) and cerebrovascular resistance (CVR i ).

Aim

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.

Approach

Taking advantage of the high SNR of NIRS, we demonstrate a method that uses the NIRS photoplethysmography (NIRS-PPG) pulsatile signal to model DCS pCBF i , reducing the coefficient of variation of the recovered pulsatile waveform (pCBF i - fit ) and allowing for an unprecedented temporal resolution (266 Hz) at a large source-detector separation (> 3    cm ).

Results

In 10 healthy subjects, we verified the quality of the NIRS-PPG pCBF i - fit during common tasks, showing high fidelity against pCBF i (R 2 0.98 ± 0.01 ). We recovered CrCP and CVR i at 0.25 Hz, > 10 times faster than previously achieved with DCS.

Conclusions

NIRS-PPG improves DCS pCBF i SNR, reducing the number of gate-averaged heartbeats required to recover CrCP and CVR i .

Non-invasive diffuse optical monitoring of cerebral physiology in an adult swine-model of impact traumatic brain injury

In this study, we used diffuse optics to address the need for non-invasive, continuous monitoring of cerebral physiology following traumatic brain injury (TBI). We combined frequency-domain and broadband diffuse optical spectroscopy with diffuse correlation spectroscopy to monitor cerebral oxygen metabolism, cerebral blood volume, and cerebral water content in an established adult swine-model of impact TBI. Cerebral physiology was monitored before and after TBI (up to 14 days post injury). Overall, our results suggest that non-invasive optical monitoring can assess cerebral physiologic impairments post-TBI, including an initial reduction in oxygen metabolism, development of cerebral hemorrhage/hematoma, and brain swelling.

Portable, high speed blood flow measurements enabled by long wavelength, interferometric diffuse correlation spectroscopy (LW-iDCS)

Diffuse correlation spectroscopy (DCS) is an optical technique that can be used to characterize blood flow in tissue. The measurement of cerebral hemodynamics has arisen as a promising use case for DCS, though traditional implementations of DCS exhibit suboptimal signal-to-noise ratio (SNR) and cerebral sensitivity to make robust measurements of cerebral blood flow in adults. In this work, we present long wavelength, interferometric DCS (LW-iDCS), which combines the use of a longer illumination wavelength (1064 nm), multi-speckle, and interferometric detection, to improve both cerebral sensitivity and SNR. Through direct comparison with long wavelength DCS based on superconducting nanowire single photon detectors, we demonstrate an approximate 5× improvement in SNR over a single channel of LW-DCS in the measured blood flow signals in human subjects. We show equivalence of extracted blood flow between LW-DCS and LW-iDCS, and demonstrate the feasibility of LW-iDCS measured at 100 Hz at a source-detector separation of 3.5 cm. This improvement in performance has the potential to enable robust measurement of cerebral hemodynamics and unlock novel use cases for diffuse correlation spectroscopy.

Agreement in cerebrovascular reactivity assessed with diffuse correlation spectroscopy across experimental paradigms improves with short separation regression

Significance

Cerebrovascular reactivity (CVR), i.e., the ability of cerebral vasculature to dilate or constrict in response to vasoactive stimuli, is a biomarker of vascular health. Exogenous administration of inhaled carbon dioxide, i.e., hypercapnia (HC), remains the "gold-standard" intervention to assess CVR. More tolerable paradigms that enable CVR quantification when HC is difficult/contraindicated have been proposed. However, because these paradigms feature mechanistic differences in action, an assessment of agreement of these more tolerable paradigms to HC is needed.

Aim

We aim to determine the agreement of CVR assessed during HC, breath-hold (BH), and resting state (RS) paradigms.

Approach

Healthy adults were subject to HC, BH, and RS paradigms. End tidal carbon dioxide (EtCO2) and cerebral blood flow (CBF, assessed with diffuse correlation spectroscopy) were monitored continuously. CVR (%/mmHg) was quantified via linear regression of CBF versus EtCO2 or via a general linear model (GLM) that was used to minimize the influence of systemic and extracerebral signal contributions.

Results

Strong agreement ( CCC ≥ 0.69 ; R ≥ 0.76 ) among CVR paradigms was demonstrated when utilizing a GLM to regress out systemic/extracerebral signal contributions. Linear regression alone showed poor agreement across paradigms ( CCC ≤ 0.35 ; R ≤ 0.45 ).

Conclusions

More tolerable experimental paradigms coupled with regression of systemic/extracerebral signal contributions may offer a viable alternative to HC for assessing CVR.

Microvascular cerebral blood flow response to intrathecal nicardipine is associated with delayed cerebral ischemia

One of the common complications of non-traumatic subarachnoid hemorrhage (SAH) is delayed cerebral ischemia (DCI). Intrathecal (IT) administration of nicardipine, a calcium channel blocker (CCB), upon detection of large-artery cerebral vasospasm holds promise as a treatment that reduces the incidence of DCI. In this observational study, we prospectively employed a non-invasive optical modality called diffuse correlation spectroscopy (DCS) to quantify the acute microvascular cerebral blood flow (CBF) response to IT nicardipine (up to 90 min) in 20 patients with medium-high grade non-traumatic SAH. On average, CBF increased significantly with time post-administration. However, the CBF response was heterogeneous across subjects. A latent class mixture model was able to classify 19 out of 20 patients into two distinct classes of CBF response: patients in Class 1 (n = 6) showed no significant change in CBF, while patients in Class 2 (n = 13) showed a pronounced increase in CBF in response to nicardipine. The incidence of DCI was 5 out of 6 in Class 1 and 1 out of 13 in Class 2 (p &lt; 0.001). These results suggest that the acute (&lt;90 min) DCS-measured CBF response to IT nicardipine is associated with intermediate-term (up to 3 weeks) development of DCI.

Interferometric diffusing wave spectroscopy imaging with an electronically variable time-of-flight filter

Diffuse optics (DO) is a light-based technique used to study the human brain, but it suffers from low brain specificity. Interferometric diffuse optics (iDO) promises to improve the quantitative accuracy and depth specificity of DO, and particularly, coherent light fluctuations (CLFs) arising from blood flow. iDO techniques have alternatively achieved either time-of-flight (TOF) discrimination or highly parallel detection, but not both at once. Here, we break this barrier with a single iDO instrument. Specifically, we show that rapid tuning of a temporally coherent laser during the sensor integration time increases the effective linewidth seen by a highly parallel interferometer. Using this concept to create a continuously variable and user-specified TOF filter, we demonstrate a solution to the canonical problem of DO, measuring optical properties. Then, with a deep TOF filter, we reduce scalp sensitivity of CLFs by 2.7 times at 1 cm source-collector separation. With this unique combination of desirable features, i.e., TOF-discrimination, spatial localization, and highly parallel CLF detection, we perform multiparametric imaging of light intensities and CLFs via the human forehead.

Transfer function analysis of dynamic cerebral autoregulation: A CARNet white paper 2022 update

Cerebral autoregulation (CA) refers to the control of cerebral tissue blood flow (CBF) in response to changes in perfusion pressure. Due to the challenges of measuring intracranial pressure, CA is often described as the relationship between mean arterial pressure (MAP) and CBF. Dynamic CA (dCA) can be assessed using multiple techniques, with transfer function analysis (TFA) being the most common. A 2016 white paper by members of an international Cerebrovascular Research Network (CARNet) that is focused on CA strove to improve TFA standardization by way of introducing data acquisition, analysis, and reporting guidelines. Since then, additional evidence has allowed for the improvement and refinement of the original recommendations, as well as for the inclusion of new guidelines to reflect recent advances in the field. This second edition of the white paper contains more robust, evidence-based recommendations, which have been expanded to address current streams of inquiry, including optimizing MAP variability, acquiring CBF estimates from alternative methods, estimating alternative dCA metrics, and incorporating dCA quantification into clinical trials. Implementation of these new and revised recommendations is important to improve the reliability and reproducibility of dCA studies, and to facilitate inter-institutional collaboration and the comparison of results between studies.

Fast estimation of adult cerebral blood content and oxygenation with hyperspectral time-resolved near-infrared spectroscopy

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.

Diffuse correlation spectroscopy: current status and future outlook

Diffuse correlation spectroscopy (DCS) has emerged as a versatile, noninvasive method for deep tissue perfusion assessment using near-infrared light. A broad class of applications is being pursued in neuromonitoring and beyond. However, technical limitations of the technology as originally implemented remain as barriers to wider adoption. A wide variety of approaches to improve measurement performance and reduce cost are being explored; these include interferometric methods, camera-based multispeckle detection, and long path photon selection for improved depth sensitivity. We review here the current status of DCS technology and summarize future development directions and the challenges that remain on the path to widespread adoption.

Interferometric diffuse optics: recent advances and future outlook

The field of diffuse optics has provided a rich set of neurophotonic tools to measure the human brain noninvasively. Interferometric detection is a recent, exciting methodological development in this field. The approach is especially promising for the measurement of diffuse fluctuation signals related to blood flow. Benefitting from inexpensive sensor arrays, the interferometric approach has already dramatically improved throughput, enabling the measurement of brain blood flow faster and deeper. The interferometric approach can also achieve time-of-flight resolution, improving the accuracy of acquired signals. We provide a historical perspective and summary of recent work in the nascent area of interferometric diffuse optics. We predict that the convergence of interferometric technology with existing economies of scale will propel many advances in the years to come.

Numerical approach to quantify depth-dependent blood flow changes in real-time using the diffusion equation with continuous-wave and time-domain diffuse correlation spectroscopy

Diffuse correlation spectroscopy (DCS) is a non-invasive optical technique that can measure brain perfusion by quantifying temporal intensity fluctuations of multiply scattered light. A primary limitation for accurate quantitation of cerebral blood flow (CBF) is the fact that experimental measurements contain information about both extracerebral scalp blood flow (SBF) as well as CBF. Separating CBF from SBF is typically achieved using multiple source-detector channels when using continuous-wave (CW) light sources, or more recently with use of time-domain (TD) techniques. Analysis methods that account for these partial volume effects are often employed to increase CBF contrast. However, a robust, real-time analysis procedure that can separate and quantify SBF and CBF with both traditional CW and TD-DCS measurements is still needed. Here, we validate a data analysis procedure based on the diffusion equation in layered media capable of quantifying both extra- and cerebral blood flow in the CW and TD. We find that the model can quantify SBF and CBF coefficients with less than 5% error compared to Monte Carlo simulations using a 3-layered brain model in both the CW and TD. The model can accurately fit data at a rate of <10 ms for CW data and <250 ms for TD data when using a least-squares optimizer.

Dual-task related frontal cerebral blood flow changes in older adults with mild cognitive impairment: A functional diffuse correlation spectroscopy study

Introduction

In a worldwide aging population with a high prevalence of motor and cognitive impairment, it is paramount to improve knowledge about underlying mechanisms of motor and cognitive function and their interplay in the aging processes.

Methods

We measured prefrontal cerebral blood flow (CBF) using functional diffuse correlation spectroscopy during motor and dual-task. We aimed to compare CBF changes among 49 older adults with and without mild cognitive impairment (MCI) during a dual-task paradigm (normal walk, 2- forward count walk, 3-backward count walk, obstacle negotiation, and heel tapping). Participants with MCI walked slower during the normal walk and obstacle negotiation compared to participants with normal cognition (NC), while gait speed during counting conditions was not different between the groups, therefore the dual-task cost was higher for participants with NC. We built a linear mixed effects model with CBF measures from the right and left prefrontal cortex.

Results

MCI (n = 34) showed a higher increase in CBF from the normal walk to the 2-forward count walk (estimate = 0.34, 95% CI [0.02, 0.66], p = 0.03) compared to participants with NC, related to a right- sided activation. Both groups showed a higher CBF during the 3-backward count walk compared to the normal walk, while only among MCI, CFB was higher during the 2-forward count walk.

Discussion

Our findings suggest a differential prefrontal hemodynamic pattern in older adults with MCI compared to their NC counterparts during the dual-task performance, possibly as a response to increasing attentional demand.

Model of dynamic speckle evolution for evaluating laser speckle contrast measurements of tissue dynamics

We introduce a dynamic speckle model (DSM) to simulate the temporal evolution of fully developed speckle patterns arising from the interference of scattered light reemitted from dynamic tissue. Using this numerical tool, the performance of laser speckle contrast imaging (LSCI) or speckle contrast optical spectroscopy (SCOS) systems which quantify tissue dynamics using the spatial contrast of the speckle patterns with a certain camera exposure time is evaluated. We have investigated noise sources arising from the fundamental speckle statistics due to the finite sampling of the speckle patterns as well as those induced by experimental measurement conditions including shot noise, camera dark and read noise, and calibrated the parameters of an analytical noise model initially developed in the fundamental or shot noise regime that quantifies the performance of SCOS systems using the number of independent observables (NIO). Our analysis is particularly focused on the low photon flux regime relevant for human brain measurements, where the impact of shot noise and camera read noise can become significant. Our numerical model is also validated experimentally using a novel fiber based SCOS (fb-SCOS) system for a dynamic sample. We have found that the signal-to-noise ratio (SNR) of fb-SCOS measurements plateaus at a camera exposure time, which marks the regime where shot and fundamental noise dominates over camera read noise. For a fixed total measurement time, there exists an optimized camera exposure time if temporal averaging is utilized to improve SNR. For a certain camera exposure time, photon flux value, and camera noise properties, there exists an optimized speckle-to-pixel size ratio (s/p) at which SNR is maximized. Our work provides the design principles for any LSCI or SCOS systems given the detected photon flux and properties of the instruments, which will guide the experimental development of a high-quality, low-cost fb-SCOS system that monitors human brain blood flow and functions.

Transcranial optical monitoring for detecting intracranial pressure alterations in children with benign external hydrocephalus: a proof-of-concept study

SIGNIFICANCE

Benign external hydrocephalus (BEH) is considered a self-limiting pathology with a good prognosis. However, some children present a pathological intracranial pressure (ICP) characterized by quantitative and qualitative alterations (the so-called B-waves) that can lead to neurological sequelae.

AIM

Our purpose was to evaluate whether there were cerebral hemodynamic changes associated with ICP B-waves that could be evaluated with noninvasive neuromonitoring.

APPROACH

We recruited eleven patients (median age 16 months, range 7 to 55 months) with BEH and an unfavorable evolution requiring ICP monitoring. Bedside, nocturnal monitoring using near-infrared time-resolved and diffuse correlation spectroscopies synchronized to the clinical monitoring was performed.

RESULTS

By focusing on the timing of different ICP patterns that were identified manually by clinicians, we detected significant tissue oxygen saturation ( StO 2 ) changes ( p = 0.002 ) and blood flow index (BFI) variability ( p = 0.005 ) between regular and high-amplitude B-wave patterns. A blinded analysis looking for analogs of ICP patterns in BFI time traces achieved 90% sensitivity in identifying B-waves and 76% specificity in detecting the regular patterns.

CONCLUSIONS

We revealed the presence of StO 2 and BFI variations-detectable with optical techniques-during ICP B-waves in BEH children. Finally, the feasibility of detecting ICP B-waves in hemodynamic time traces obtained noninvasively was shown.

Two-layer analytical model for estimation of layer thickness and flow using Diffuse Correlation Spectroscopy

Diffuse correlation spectroscopy (DCS) has been widely explored for its ability to measure cerebral blood flow (CBF), however, mostly under the assumption that the human head is homogenous. In addition to CBF, knowledge of extracerebral layers, such as skull thickness, can be informative and crucial for patient with brain complications such as traumatic brain injuries. To bridge the gap, this study explored the feasibility of simultaneously extracting skull thickness and flow in the cortex layer using DCS. We validated a two-layer analytical model that assumed the skull as top layer with a finite thickness and the brain cortex as bottom layer with semi-infinite geometry. The model fitted for thickness of the top layer and flow of the bottom layer, while assumed other parameters as constant. The accuracy of the two-layer model was tested against the conventional single-layer model using measurements from custom made two-layer phantoms mimicking skull and brain. We found that the fitted top layer thickness at each source detector (SD) distance is correlated with the expected thickness. For the fitted bottom layer flow, the two-layer model fits relatively consistent flow across all top layer thicknesses. In comparison, the conventional one-layer model increasingly underestimates the bottom layer flow as top layer thickness increases. The overall accuracy of estimating first layer thickness and flow depends on the SD distance in relationship to first layer thickness. Lastly, we quantified the influence of uncertainties in the optical properties of each layer. We found that uncertainties in the optical properties only mildly influence the fitted thickness and flow. In this work we demonstrate the feasibility of simultaneously extracting of layer thickness and flow using a two-layer DCS model. Findings from this work may introduce a robust and cost-effective approach towards simultaneous bedside assessment of skull thickness and cerebral blood flow.

Intraoperative Cerebral Hemodynamic Monitoring during Carotid Endarterectomy via Diffuse Correlation Spectroscopy and Near-Infrared Spectroscopy

Objective: This pilot study aims to show the feasibility of noninvasive and real-time cerebral hemodynamic monitoring during carotid endarterectomy (CEA) via diffuse correlation spectroscopy (DCS) and near-infrared spectroscopy (NIRS). Methods: Cerebral blood flow index (CBFi) was measured unilaterally in seven patients and bilaterally in seventeen patients via DCS. In fourteen patients, hemoglobin oxygenation changes were measured bilaterally and simultaneously via NIRS. Cerebral autoregulation (CAR) and cerebrovascular resistance (CVR) were estimated using CBFi and arterial blood pressure data. Further, compensatory responses to the ipsilateral hemisphere were investigated at different contralateral stenosis levels. Results: Clamping of carotid arteries caused a sharp increase of CVR (~70%) and a marked decrease of ipsilateral CBFi (57%). From the initial drop, we observed partial recovery in CBFi, an increase of blood volume, and a reduction in CVR in the ipsilateral hemisphere. There were no significant changes in compensatory responses between different contralateral stenosis levels as CAR was intact in both hemispheres throughout the CEA phase. A comparison between hemispheric CBFi showed lower ipsilateral levels during the CEA and post-CEA phases (p < 0.001, 0.03). Conclusion: DCS alone or combined with NIRS is a useful monitoring technique for real-time assessment of cerebral hemodynamic changes and allows individualized strategies to improve cerebral perfusion during CEA by identifying different hemodynamic metrics.

Open-source FlexNIRS: A low-cost, wireless and wearable cerebral health tracker

Currently, there is great interest in making neuroimaging widely accessible and thus expanding the sampling population for better understanding and preventing diseases. The use of wearable health devices has skyrocketed in recent years, allowing continuous assessment of physiological parameters in patients and research cohorts. While most health wearables monitor the heart, lungs and skeletal muscles, devices targeting the brain are currently lacking. To promote brain health in the general population, we developed a novel, low-cost wireless cerebral oximeter called FlexNIRS. The device has 4 LEDs and 3 photodiode detectors arranged in a symmetric geometry, which allows for a self-calibrated multi-distance method to recover cerebral hemoglobin oxygenation (SO2) at a rate of 100 Hz. The device is powered by a rechargeable battery and uses Bluetooth Low Energy (BLE) for wireless communication. We developed an Android application for portable data collection and real-time analysis and display. Characterization tests in phantoms and human participants show very low noise (noise-equivalent power <70 fW/√Hz) and robustness of SO2 quantification in vivo. The estimated cost is on the order of $50/unit for 1000 units, and our goal is to share the device with the research community following an open-source model. The low cost, ease-of-use, smart-phone readiness, accurate SO2 quantification, real time data quality feedback, and long battery life make prolonged monitoring feasible in low resource settings, including typically medically underserved communities, and enable new community and telehealth applications.

Functional Time Domain Diffuse Correlation Spectroscopy

Time-domain diffuse correlation spectroscopy (TD-DCS) offers a novel approach to high-spatial resolution functional brain imaging based on the direct quantification of cerebral blood flow (CBF) changes in response to neural activity. However, the signal-to-noise ratio (SNR) offered by previous TD-DCS instruments remains a challenge to achieving the high temporal resolution needed to resolve perfusion changes during functional measurements. Here we present a next-generation optimized functional TD-DCS system that combines a custom 1,064 nm pulse-shaped, quasi transform-limited, amplified laser source with a high-resolution time-tagging system and superconducting nanowire single-photon detectors (SNSPDs). System characterization and optimization was conducted on homogenous and two-layer intralipid phantoms before performing functional CBF measurements in six human subjects. By acquiring CBF signals at over 5 Hz for a late gate start time of the temporal point spread function (TPSF) at 15 mm source-detector separation, we demonstrate for the first time the measurement of blood flow responses to breath-holding and functional tasks using TD-DCS.

Lawrence K, Tachtsidis I, Tong Y, Torricelli A, Urner T, Wabnitz H, Wolf M, Wolf U, Xu S, Yang C, Yodh AG, Yücel MA, Zhou W. Optical imaging and spectroscopy for the study of the human brain: status report

This report is the second part of a comprehensive two-part series aimed at reviewing an extensive and diverse toolkit of novel methods to explore brain health and function. While the first report focused on neurophotonic tools mostly applicable to animal studies, here, we highlight optical spectroscopy and imaging methods relevant to noninvasive human brain studies. We outline current state-of-the-art technologies and software advances, explore the most recent impact of these technologies on neuroscience and clinical applications, identify the areas where innovation is needed, and provide an outlook for the future directions.

Non-Invasive Intracranial Pressure Monitoring and Its Applicability in Spaceflight

INTRODUCTION: Neuro-ophthalmic findings collectively defined as Spaceflight-Associated Neuro-ocular Syndrome (SANS) are one of the leading health priorities in astronauts engaging in long duration spaceflight or prolonged microgravity exposure. Though multifactorial in etiology, similarities to terrestrial idiopathic intracranial hypertension (IIH) suggest these changes may result from an increase or impairing in intracranial pressure (ICP). Finding a portable, accessible, and reliable method of monitoring ICP is, therefore, crucial in long duration spaceflight. A review of recent literature was conducted on the biomedical literature search engine PubMed using the search term “non-invasive intracranial pressure”. Studies investigating accuracy of noninvasive and portable methods were assessed. The search retrieved different methods that were subsequently grouped by approach and technique. The majority of publications included the use of ultrasound-based methods with variable accuracies. One of which, noninvasive ICP estimation by optical nerve sheath diameter measurement (nICP_ONSD), presented the highest statistical correlation and prediction values to invasive ICP, with area under the curve (AUC) ranging from 0.75 to 0.964. One study even considers a combination of ONSD with transcranial Doppler (TCD) for an even higher performance. Other methods, such as near-infrared spectroscopy (NIRS), show positive and promising results [good statistical correlation with invasive techniques when measuring cerebral perfusion pressure (CPP): r = 0.83]. However, for its accessibility, portability, and accuracy, ONSD seems to present itself as the up to date, most reliable, noninvasive ICP surrogate and a valuable spaceflight asset.Félix H, Santos Oliveira E. Non-invasive intracranial pressure monitoring and its applicability in spaceflight. Aerosp Med Hum Perform. 2022; 93(6):517–531.

Complete head cerebral sensitivity mapping for diffuse correlation spectroscopy using subject-specific magnetic resonance imaging models

We characterize cerebral sensitivity across the entire adult human head for diffuse correlation spectroscopy, an optical technique increasingly used for bedside cerebral perfusion monitoring. Sixteen subject-specific magnetic resonance imaging-derived head models were used to identify high sensitivity regions by running Monte Carlo light propagation simulations at over eight hundred uniformly distributed locations on the head. Significant spatial variations in cerebral sensitivity, consistent across subjects, were found. We also identified correlates of such differences suitable for real-time assessment. These variations can be largely attributed to changes in extracerebral thickness and should be taken into account to optimize probe placement in experimental settings.

First-in-clinical application of a time-gated diffuse correlation spectroscopy system at 1064 nm using superconducting nanowire single photon detectors in a neuro intensive care unit

Recently proposed time-gated diffuse correlation spectroscopy (TG-DCS) has significant advantages compared to conventional continuous wave (CW)-DCS, but it is still in an early stage and clinical capability has yet to be established. The main challenge for TG-DCS is the lower signal-to-noise ratio (SNR) when gating for the deeper traveling late photons. Longer wavelengths, such as 1064 nm have a smaller effective attenuation coefficient and a higher power threshold in humans, which significantly increases the SNR. Here, we demonstrate the clinical utility of TG-DCS at 1064 nm in a case study on a patient with severe traumatic brain injury admitted to the neuro-intensive care unit (neuroICU). We showed a significant correlation between TG-DCS early (ρ = 0.67) and late (ρ = 0.76) gated against invasive thermal diffusion flowmetry. We also analyzed TG-DCS at high temporal resolution (50 Hz) to elucidate pulsatile flow data. Overall, this study demonstrates the first clinical translation capability of the TG-DCS system at 1064 nm using a superconducting nanowire single-photon detector.

Assessing cerebral blood flow, oxygenation and cytochrome c oxidase stability in preterm infants during the first 3 days after birth

A major concern with preterm birth is the risk of neurodevelopmental disability. Poor cerebral circulation leading to periods of hypoxia is believed to play a significant role in the etiology of preterm brain injury, with the first three days of life considered the period when the brain is most vulnerable. This study focused on monitoring cerebral perfusion and metabolism during the first 72 h after birth in preterm infants weighing less than 1500 g. Brain monitoring was performed by combining hyperspectral near-infrared spectroscopy to assess oxygen saturation and the oxidation state of cytochrome c oxidase (oxCCO), with diffuse correlation spectroscopy to monitor cerebral blood flow (CBF). In seven of eight patients, oxCCO remained independent of CBF, indicating adequate oxygen delivery despite any fluctuations in cerebral hemodynamics. In the remaining infant, a significant correlation between CBF and oxCCO was found during the monitoring periods on days 1 and 3. This infant also had the lowest baseline CBF, suggesting the impact of CBF instabilities on metabolism depends on the level of blood supply to the brain. In summary, this study demonstrated for the first time how continuous perfusion and metabolic monitoring can be achieved, opening the possibility to investigate if CBF/oxCCO monitoring could help identify preterm infants at risk of brain injury.

Scanning interferometric near-infrared spectroscopy

In diffuse optics, quantitative assessment of the human brain is confounded by the skull and scalp. To better understand these superficial tissues, we advance interferometric near-infrared spectroscopy (iNIRS) to form images of the human superficial forehead blood flow index (BFI). We present a null source-collector (S-C) polarization splitting approach that enables galvanometer scanning and eliminates unwanted backscattered light. Images show an order-of-magnitude heterogeneity in superficial dynamics, implying an order-of-magnitude heterogeneity in brain specificity, depending on forehead location. Along the time-of-flight dimension, autocorrelation decay rates support a three-layer model with increasing BFI from the skull to the scalp to the brain. By accurately characterizing superficial tissues, this approach can help improve specificity for the human brain.