Pressure modulation algorithm to separate cerebral hemodynamic signals from extracerebral artifacts

Near-infrared diffuse optical characterization of human thyroid using ultrasound-guided hybrid time-domain and diffuse correlation spectroscopies

Thyroid vascularization and hemodynamics become altered in thyroid pathologies and could thus inform diagnostics, therapy planning, and follow-up. However, the current non-invasive monitoring methods available in clinics lack the necessary sensitivity and/or are impractical for large-scale deployment. As a step towards proposing a new modality, we applied the first platform, to our knowledge, designed to do simultaneous measurements of neck anatomy and thyroid microvascular hemodynamics and metabolism in a single probe placement, integrating state-of-the-art near-infrared spectroscopy techniques and clinical ultrasound. A rich dataset was formed with sixty-five subjects (forty-eight females), including eighteen healthy volunteers and forty-seven patients with thyroid nodules, characterizing thyroid tissue and the effects of demographic and anatomical variables while preserving the standard clinical workflow. We have found marked reductions with age and body mass index in thyroid total hemoglobin concentration (THC), tissue oxygen saturation (StO 2), and blood flow index (BFi), among others. Patients showed lower THC and BFi than healthy subjects, and the limited sample of malignant nodules showed a higher StO 2 than the benign. These findings support the need for personalized clinical approaches.

Correlations Between Quantitative EEG Parameters and Cortical Blood Flow in Patients Undergoing Extracorporeal Membrane Oxygenation With and Without Encephalopathy

PURPOSE

The neurologic examination of patients undergoing extracorporeal membrane oxygenation (ECMO) is crucial for evaluating irreversible encephalopathy but is often obscured by sedation or neuromuscular blockade. Noninvasive neuromonitoring modalities including diffuse correlation spectroscopy and EEG measure cerebral perfusion and neuronal function, respectively. We hypothesized that encephalopathic ECMO patients with greater degree of irreversible cerebral injury demonstrate less correlation between electrographic activity and cerebral perfusion than those whose encephalopathy is attributable to medications.

METHODS

We performed a prospective observational study of adults undergoing ECMO who underwent simultaneous continuous EEG and diffuse correlation spectroscopy monitoring. (Alpha + beta)/delta ratio and alpha/delta Rartio derived from quantitative EEG analysis were correlated with frontal cortical blood flow index. Patients who awakened and followed commands during sedation pauses were included in group 1, whereas patients who could not follow commands for most neuromonitoring were placed in group 2. (Alpha + beta)/delta ratio-blood flow index and ADR-BFI correlations were compared between the groups.

RESULTS

Ten patients (five in each group) underwent 39 concomitant continuous EEG and diffuse correlation spectroscopy monitoring sessions. Four patients (80%) in each group received some form of analgosedation during neuromonitoring. (Alpha + beta)/delta ratio-blood flow index correlation was significantly lower in group 2 than group 1 (left: 0.05 vs. 0.52, P = 0.03; right: -0.12 vs. 0.39, P = 0.04). Group 2 ADR-BFI correlation was lower only over the right hemisphere (-0.06 vs. 0.47, P = 0.04).

CONCLUSIONS

Correlation between (alpha + beta)/delta ratio and blood flow index were decreased in encephalopathic ECMO patients compared with awake ones, regardless of the analgosedation use. The combined use of EEG and diffuse correlation spectroscopy may have utility in monitoring cerebral function in ECMO patients.

Lawrence K. All-optics technique for monitoring absolute cerebral blood flow: validation against magnetic resonance imaging perfusion

Significance

The ability to monitor cerebral blood flow (CBF) at the bedside is essential to managing critical-care patients with neurological emergencies. Diffuse correlation spectroscopy (DCS) is ideal because it is non-invasive, portable, and inexpensive. We investigated a near-infrared spectroscopy (NIRS) approach for converting DCS measurements into physiological units of blood flow.

Aim

Using magnetic resonance imaging perfusion as a reference, we investigated the accuracy of absolute CBF measurements from a bolus-tracking NIRS method that used transient hypoxia as a flow tracer and hypercapnia-induced increases in CBF measured by DCS.

Approach

Twelve participants (7 female, 28 ± 6 years) completed a hypercapnia protocol with simultaneous CBF recordings from DCS and arterial spin labeling (ASL). Nine participants completed the transient hypoxia protocol while instrumented with time-resolved NIRS. The estimate of baseline CBF was subsequently used to calibrate hypercapnic DCS data.

Results

Moderately strong correlations at baseline ( slope = 0.79 andR 2 = 0.59 ) and during hypercapnia ( slope = 0.90 andR 2 = 0.58 ) were found between CBF values from calibrated DCS and ASL (range 34 to 85    mL / 100    g / min ).

Conclusions

Results demonstrated the feasibility of an all-optics approach that can both quantify CBF and perform continuous perfusion monitoring.

A comprehensive overview of diffuse correlation spectroscopy: Theoretical framework, recent advances in hardware, analysis, and applications

Diffuse correlation spectroscopy (DCS) is a powerful tool for assessing microvascular hemodynamic in deep tissues. Recent advances in sensors, lasers, and deep learning have further boosted the development of new DCS methods. However, newcomers might feel overwhelmed, not only by the already-complex DCS theoretical framework but also by the broad range of component options and system architectures. To facilitate new entry to this exciting field, we present a comprehensive review of DCS hardware architectures (continuous-wave, frequency-domain, and time-domain) and summarize corresponding theoretical models. Further, we discuss new applications of highly integrated silicon single-photon avalanche diode (SPAD) sensors in DCS, compare SPADs with existing sensors, and review other components (lasers, sensors, and correlators), as well as data analysis tools, including deep learning. Potential applications in medical diagnosis are discussed and an outlook for the future directions is provided, to offer effective guidance to embark on DCS research.

Chassis-based fiber-coupled optical probe design for reproducible quantitative diffuse optical spectroscopy measurements

Advanced optical neuromonitoring of cerebral hemodynamics with hybrid diffuse optical spectroscopy (DOS) and diffuse correlation spectroscopy (DCS) methods holds promise for non-invasive characterization of brain health in critically ill patients. However, the methods' fiber-coupled patient interfaces (probes) are challenging to apply in emergent clinical scenarios that require rapid and reproducible attachment to the head. To address this challenge, we developed a novel chassis-based optical probe design for DOS/DCS measurements and validated its measurement accuracy and reproducibility against conventional, manually held measurements of cerebral hemodynamics in pediatric swine (n = 20). The chassis-based probe design comprises a detachable fiber housing which snaps into a 3D-printed, circumferential chassis piece that is secured to the skin. To validate its reproducibility, eight measurement repetitions of cerebral tissue blood flow index (BFI), oxygen saturation (StO2), and oxy-, deoxy- and total hemoglobin concentration were acquired at the same demarcated measurement location for each pig. The probe was detached after each measurement. Of the eight measurements, four were acquired by placing the probe into a secured chassis, and four were visually aligned and manually held. We compared the absolute value and intra-subject coefficient of variation (CV) of chassis versus manual measurements. No significant differences were observed in either absolute value or CV between chassis and manual measurements (p > 0.05). However, the CV for BFI (mean ± SD: manual, 19.5% ± 9.6; chassis, 19.0% ± 10.8) was significantly higher than StO2 (manual, 5.8% ± 6.7; chassis, 6.6% ± 7.1) regardless of measurement methodology (p<0.001). The chassis-based DOS/DCS probe design facilitated rapid probe attachment/re-attachment and demonstrated comparable accuracy and reproducibility to conventional, manual alignment. In the future, this design may be adapted for clinical applications to allow for non-invasive monitoring of cerebral health during pediatric critical care.

Preliminary experience with diffuse correlation spectroscopy in acute ischemic stroke neurointerventional procedures

BACKGROUND

Diffuse correlation spectroscopy (DCS) is a non-invasive optical technique that enables continuous blood flow measurements in various organs, including the brain. DCS quantitatively measures blood flow from temporal fluctuations in the intensity of diffusely reflected light caused by the dynamic scattering of light from moving red blood cells within the tissue.

METHODS

We performed bilateral cerebral blood flow (CBF) measurements using a custom DCS device in patients undergoing neuroendovascular interventions for acute ischemic stroke. Experimental, clinical, and imaging data were collected in a prospective manner.

RESULTS

The device was successfully applied in nine subjects. There were no safety concerns or interference with the standard angiography suite or intensive care unit workflow. Six cases were selected for final analysis and interpretation. DCS measurements with photon count rates greater than 30 KHz had sufficient signal-to-noise to resolve blood flow pulsatility. We found an association between angiographic changes in cerebral reperfusion (partial or complete reperfusion established in stroke thrombectomy cases; temporary flow arrest during carotid artery stenting) and those observed intraprocedurally with CBF measurements via DCS. Limitations of the current technology included sensitivity to the interrogated tissue volume under the probe and the effect of local changes in tissue optical properties on the accuracy of CBF estimates.

CONCLUSION

Our initial experience with DCS in neurointerventional procedures showed the feasibility of this non-invasive approach in providing continuous measurement of regional CBF brain tissue properties.

Comprehensive workflow and its validation for simulating diffuse speckle statistics for optical blood flow measurements

Diffuse optical methods including speckle contrast optical spectroscopy and tomography (SCOS and SCOT), use speckle contrast (κ) to measure deep blood flow. In order to design practical systems, parameters such as signal-to-noise ratio (SNR) and the effects of limited sampling of statistical quantities, should be considered. To that end, we have developed a method for simulating speckle contrast signals including effects of detector noise. The method was validated experimentally, and the simulations were used to study the effects of physical and experimental parameters on the accuracy and precision of κ. These results revealed that systematic detector effects resulted in decreased accuracy and precision of κ in the regime of low detected signals. The method can provide guidelines for the design and usage of SCOS and/or SCOT instruments.

Non-invasive low-cost deep tissue blood flow measurement with integrated Diffuse Speckle Contrast Spectroscopy

Diffuse Correlation Spectroscopy (DCS) is a widely used non-invasive measurement technique to quantitatively measure deep tissue blood flow. Conventional implementations of DCS use expensive single photon counters as detecting elements and optical probes with bulky fiber optic cables. In recent years, newer approaches to blood flow measurement such as Diffuse Speckle Contrast Analysis (DSCA) and Speckle Contrast Optical Spectroscopy (SCOS), have adapted speckle contrast analysis methods to simplify deep tissue blood flow measurements using cameras and single photon counting avalanche detector arrays as detectors. Here, we introduce and demonstrate integrated Diffuse Speckle Contrast Spectroscopy (iDSCS), a novel optical sensor setup which leverages diffuse speckle contrast analysis for probe-level quantitative measurement of tissue blood flow. iDSCS uses a standard photodiode configured in photovoltaic mode to integrate photon intensity fluctuations over multiple integration durations using a custom electronic circuit, as opposed to the high frequency sampling of photon counts with DCS. We show that the iDSCS device is sensitive to deep-tissue blood flow measurements with experiments on a human forearm and compare the sensitivity and dynamic range of the device to a conventional DCS instrument. The iDSCS device features a low-cost, low-power, small form factor instrument design that will enable wireless probe-level measurements of deep tissue blood flow.

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.

In vivocharacterization of the optical and hemodynamic properties of the human sternocleidomastoid muscle through ultrasound-guided hybrid near-infrared spectroscopies

Objective.In this paper, we present a detailedin vivocharacterization of the optical and hemodynamic properties of the human sternocleidomastoid muscle (SCM), obtained through ultrasound-guided near-infrared time-domain and diffuse correlation spectroscopies.Approach.A total of sixty-five subjects (forty-nine females, sixteen males) among healthy volunteers and thyroid nodule patients have been recruited for the study. Their SCM hemodynamic (oxy-, deoxy- and total hemoglobin concentrations, blood flow, blood oxygen saturation and metabolic rate of oxygen extraction) and optical properties (wavelength dependent absorption and reduced scattering coefficients) have been measured by the use of a novel hybrid device combining in a single unit time-domain near-infrared spectroscopy, diffuse correlation spectroscopy and simultaneous ultrasound imaging.Main results.We provide detailed tables of the results related to SCM baseline (i.e. muscle at rest) properties, and reveal significant differences on the measured parameters due to variables such as side of the neck, sex, age, body mass index, depth and thickness of the muscle, allowing future clinical studies to take into account such dependencies.Significance.The non-invasive monitoring of the hemodynamics and metabolism of the sternocleidomastoid muscle during respiration became a topic of increased interest partially due to the increased use of mechanical ventilation during the COVID-19 pandemic. Near-infrared diffuse optical spectroscopies were proposed as potential practical monitors of increased recruitment of SCM during respiratory distress. They can provide clinically relevant information on the degree of the patient's respiratory effort that is needed to maintain an optimal minute ventilation, with potential clinical application ranging from evaluating chronic pulmonary diseases to more acute settings, such as acute respiratory failure, or to determine the readiness to wean from invasive mechanical ventilation.

Comparison of diffuse correlation spectroscopy analytical models for measuring cerebral blood flow in adults

Significance

Although multilayer analytical models have been proposed to enhance brain sensitivity of diffuse correlation spectroscopy (DCS) measurements of cerebral blood flow, the traditional homogeneous model remains dominant in clinical applications. Rigorous in vivo comparison of these analytical models is lacking.

Aim

We compare the performance of different analytical models to estimate a cerebral blood flow index (CBFi) with DCS in adults.

Approach

Resting-state data were obtained on a cohort of 20 adult patients with subarachnoid hemorrhage. Data at 1 and 2.5 cm source-detector separations were analyzed with the homogenous, two-layer, and three-layer models to estimate scalp blood flow index and CBFi. The performance of each model was quantified via fitting convergence, fit stability, brain-to-scalp flow ratio (BSR), and correlation with transcranial Doppler ultrasound (TCD) measurements of cerebral blood flow velocity in the middle cerebral artery (MCA).

Results

The homogeneous model has the highest pass rate (100%), lowest coefficient of variation (CV) at rest (median [IQR] at 1 Hz of 0.18 [0.13, 0.22]), and most significant correlation with MCA blood flow velocities (R s = 0.59 , p = 0.010 ) compared with both the two- and three-layer models. The multilayer model pass rate was significantly correlated with extracerebral layer thicknesses. Discarding datasets with non-physiological BSRs increased the correlation between DCS measured CBFi and TCD measured MCA velocities for all models.

Conclusions

We found that the homogeneous model has the highest pass rate, lowest CV at rest, and most significant correlation with MCA blood flow velocities. Results from the multilayer models should be taken with caution because they suffer from lower pass rates and higher coefficients of variation at rest and can converge to non-physiological values for CBFi. Future work is needed to validate these models in vivo, and novel approaches are merited to improve the performance of the multimodel models.

Diffuse Correlation Spectroscopy: A Review of Recent Advances in Parallelisation and Depth Discrimination Techniques

Diffuse correlation spectroscopy is a non-invasive optical modality used to measure cerebral blood flow in real time, and it has important potential applications in clinical monitoring and neuroscience. As such, many research groups have recently been investigating methods to improve the signal-to-noise ratio, imaging depth, and spatial resolution of diffuse correlation spectroscopy. Such methods have included multispeckle, long wavelength, interferometric, depth discrimination, time-of-flight resolution, and acousto-optic detection strategies. In this review, we exhaustively appraise this plethora of recent advances, which can be used to assess limitations and guide innovation for future implementations of diffuse correlation spectroscopy that will harness technological improvements in the years to come.

scatterBrains: an open database of human head models and companion optode locations for realistic Monte Carlo photon simulations

Significance

Monte Carlo (MC) simulations are currently the gold standard in the near-infrared and diffuse correlation spectroscopy (NIRS/DCS) communities for generating light transport paths through tissue. However, realistic and diverse models that capture complex tissue layers are not easily available to all; moreover, manually placing optodes on such models can be tedious and time consuming. Such limitations may hinder the adoption of representative models for basic simulations and the use of these models for large-scale simulations, e.g., for training machine learning algorithms.

Aim

We aim to provide the NIRS/DCS communities with an open-source, user-friendly database of morphologically and optically realistic head models, as well as a succinct software pipeline to prepare these models for mesh-based Monte Carlo simulations of light transport.

Approach

Sixteen anatomical models were created from segmented T1-weighted magnetic resonance imaging (MRI) head scans and converted to tetrahedral mesh volumes. Approximately 800 companion scalp surface locations were distributed on each model, comprising full head coverage. A pipeline was created to place custom source and optical detectors at each location, and guidance is provided on how to use these parameters to set up MC simulations.

Results

The models, head surface locations, and all associated code are freely available under the scatterBrains project on Github.

Conclusions

The NIRS/DCS community benefits from having shared resources for conducting MC simulations on realistic head geometries. We hope this will make MRI-based head models and virtual optode placement easily accessible to all. Contributions to the database are welcome and encouraged.

Characterization of cerebral macro- and microvascular hemodynamics during transient hypotension

The aim of the current study was to establish the interplay between blood flow patterns within a large cerebral artery and a downstream microvascular segment under conditions of transiently reduced mean arterial pressure (MAP). We report data from nine young, healthy participants (5 women; 26 ± 4 yr) acquired during a 15-s bout of sudden-onset lower body negative pressure (LBNP; -80 mmHg). Simultaneous changes in microvascular cerebral blood flow (CBF) and middle cerebral artery blood velocity (MCAvmean) were captured using diffuse correlation spectroscopy (DCS) and transcranial Doppler ultrasound (TCD), respectively. Brachial blood pressure (finger photoplethysmography) and TCD waveforms were extracted at baseline and during the nadir blood pressure (BP) response to LBNP and analyzed using a modified Windkessel model to calculate indices of cerebrovascular resistance (Ri) and compliance (Ci). Compared with baseline, rapid-onset LBNP decreased MAP by 22 ± 16% and Ri by 14 ± 10% (both P ≤ 0.03). Ci increased (322 ± 298%; P < 0.01) but MCAvmean (-8 ± 16%; P = 0.09) and CBF (-2 ± 3%; P = 0.29) were preserved. The results provide evidence that changes in both vascular resistance and compliance preserve CBF, as indexed by no significant changes in MCAvmean or DCS microvascular flow, during transient hypotension.NEW & NOTEWORTHY To characterize the relationship between cerebrovascular patterns within the large middle cerebral artery (MCA) and a downstream microvascular segment, we used a novel combination of transcranial Doppler ultrasound of the MCA and optical monitoring of a downstream microvascular segment, respectively, under conditions of transiently reduced mean arterial pressure (i.e., lower body negative pressure, -80 mmHg). A rapid increase in vessel compliance accompanied the maintenance of MCA blood velocity and downstream microvascular flow.

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.

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.

Epinephrine iontophoresis attenuates changes in skin blood flow and abolishes cutaneous contamination of near-infrared diffuse correlation spectroscopy estimations of muscle perfusion

Near-infrared diffuse correlation spectroscopy (NIR-DCS) is an optical imaging technique for measuring relative changes in skeletal muscle microvascular perfusion (i.e., fold change above baseline) during reactive hyperemia testing and exercise and is reported as a blood flow index (BFI). Although it is generally accepted that changes in BFI are primarily driven by changes in muscle perfusion, it is well known that large, hyperthermia-induced changes in cutaneous blood flow can uncouple this relationship. What remains unknown, is how much of an impact that changes in cutaneous perfusion have on NIR-DCS BFI and estimates of skeletal muscle perfusion under thermoneutral conditions, where changes in cutaneous blood flow are assumed to be relatively low. We therefore used epinephrine iontophoresis to pharmacologically block changes in cutaneous perfusion throughout a battery of experimental procedures. The data show that 1) epinephrine iontophoresis attenuates changes in cutaneous perfusion for up to 4-h posttreatment, even in the face of significant neural and local stimuli, 2) under thermoneutral conditions, cutaneous perfusion does not significantly impact NIR-DCS BFI during reactive hyperemia testing or moderate-intensity exercise, and 3) during passive whole body heat stress, when cutaneous vasodilation is pronounced, epinephrine iontophoresis preserves NIR-DCS measures of skeletal muscle BFI during moderate-intensity exercise. Collectively, these data suggest that cutaneous perfusion is unlikely to have a major impact on NIR-DCS estimates of skeletal muscle BFI under thermoneutral conditions, but that epinephrine iontophoresis can be used to abolish cutaneous contamination of the NIR-DCS BFI signal during studies where skin blood flow may be elevated but skeletal muscle perfusion is of specific interest.

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.

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.

Influence of oversimplifying the head anatomy on cerebral blood flow measurements with diffuse correlation spectroscopy

Significance

Diffuse correlation spectroscopy (DCS) is an emerging optical modality for non-invasive assessment of an index of regional cerebral blood flow. By the nature of this noninvasive measurement, light must pass through extracerebral layers (i.e., skull, scalp, and cerebral spinal fluid) before detection at the tissue surface. To minimize the contribution of these extracerebral layers to the measured signal, an analytical model has been developed that treats the head as a series of three parallel and infinitely extending slabs (mimicking scalp, skull, and brain). The three-layer model has been shown to provide a significant improvement in cerebral blood flow estimation over the typically used model that treats the head as a bulk homogenous medium. However, the three-layer model is still a gross oversimplification of the head geometry that ignores head curvature, the presence of cerebrospinal fluid (CSF), and heterogeneity in layer thickness.

Aim

Determine the influence of oversimplifying the head geometry on cerebral blood flow estimated with the three-layer model.

Approach

Data were simulated with Monte Carlo in a four-layer slab medium and a three-layer sphere medium to isolate the influence of CSF and curvature, respectively. Additionally, simulations were performed on magnetic resonance imaging (MRI) head templates spanning a wide-range of ages. Simulated data were fit to both the homogenous and three-layer model for CBF. Finally, to mitigate the errors in potential CBF estimation due to the difficulty in defining layer thickness, we investigated an approach to identify an equivalent, "optimized" thickness via a pressure modulation.

Results

Both head curvature and failing to account for CSF lead to significant errors in the estimation of CBF. However, the effect of curvature and CSF on relative changes in CBF is minimal. Further, we found that CBF was underestimated in all MRI-templates, although the magnitude of these underestimations was highly influenced by small variations in the source and detector optode positioning. The optimized thickness obtained from pressure modulation did not improve estimation accuracy of CBF, although it did significantly improve the estimation accuracy of relative changes in CBF.

Conclusions

In sum, these findings suggest that the three-layer model holds promise for improving estimation of relative changes in cerebral blood flow; however, estimations of absolute cerebral blood flow with the approach should be viewed with caution given that it is difficult to account for appreciable sources of error, such as curvature and CSF.

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.

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.

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.

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.

Influence of source-detector separation on diffuse correlation spectroscopy measurements of cerebral blood flow with a multilayered analytical model

Significance: Diffuse correlation spectroscopy (DCS) is an emerging noninvasive optical technology for bedside monitoring of cerebral blood flow. However, extracerebral hemodynamics can significantly influence DCS estimations of cerebral perfusion. Advanced analytical models can be used to remove the contribution of extracerebral hemodynamics; however, these models are highly sensitive to measurement noise. There is a need for an empirical determination of the optimal source-detector separation(s) (SDS) that improves the accuracy and reduces sensitivity to noise in the estimation of cerebral blood flow with these models. Aim: To determine the influence of SDS on solution uniqueness, measurement accuracy, and sensitivity to inaccuracies in model parameters when using the three-layer model to estimate cerebral blood flow with DCS. Approach: We performed a series of in silico simulations on samples spanning a wide range of physiologically-relevant layer optical properties, thicknesses, and flow. Data were simulated at SDS ranging from 0.5 to 3.0 cm using the three-layer solution to the correlation diffusion equation (with and without noise added) and using three-layer slab Monte Carlo simulations. We quantified the influence of SDS on uniqueness, accuracy, and sensitivity to inaccuracies in model parameters using the three-layer inverse model. Results: Two SDS are required to ensure a unique solution of cerebral blood flow index (CBFi). Combinations of 0.5/1.0/1.5 and 2.5 cm provide the optimal choice for balancing the depth penetration with signal-to-noise ratio to minimize the error in CBFi across a wide range of samples with varying optical properties, thicknesses, and dynamics. Conclusions: These results suggest that the choice of SDS is critical for minimizing the estimated error of cerebral blood flow when using the three-layer model to analyze DCS data.

Quantifying tissue optical properties of human heads in vivo using continuous-wave near-infrared spectroscopy and subject-specific three-dimensional Monte Carlo models

SIGNIFICANCE

Quantifying subject-specific optical properties (OPs) including absorption and transport scattering coefficients of tissues in the human head could improve the modeling of photon propagation for the analysis of functional near-infrared spectroscopy (fNIRS) data and dosage quantification in therapeutic applications. Current methods employ diffuse approximation, which excludes a low-scattering cerebrospinal fluid compartment and causes errors.

AIM

This work aims to quantify OPs of the scalp, skull, and gray matter in vivo based on accurate Monte Carlo (MC) modeling.

APPROACH

Iterative curve fitting was applied to quantify tissue OPs from multidistance continuous-wave NIR reflectance spectra. An artificial neural network (ANN) was trained using MC-simulated reflectance values based on subject-specific voxel-based tissue models to replace MC simulations as the forward model in curve fitting. To efficiently generate sufficient data for training the ANN, the efficiency of MC simulations was greatly improved by white MC simulations, increasing the detectors' acceptance angle, and building a lookup table for interpolation.

RESULTS

The trained ANN was six orders of magnitude faster than the original MC simulations. OPs of the three tissue compartments were quantified from NIR reflectance spectra measured at the forehead of five healthy subjects and their uncertainties were estimated.

CONCLUSIONS

This work demonstrated an MC-based iterative curve fitting method to quantify subject-specific tissue OPs in-vivo, with all OPs except for scattering coefficients of scalp within the ranges reported in the literature, which could aid the modeling of photon propagation in human heads.

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.

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.

Measurement of Adult Human Brain Responses to Breath-Holding by Multi-Distance Hyperspectral Near-Infrared Spectroscopy

A major limitation of near-infrared spectroscopy (NIRS) is its high sensitivity to the scalp and low sensitivity to the brain of adult humans. In the present work we used multi-distance hyperspectral NIRS (hNIRS) to investigate the optimal source-detector distances, wavelength ranges, and analysis techniques to separate cerebral responses to 30 s breath-holds (BHs) from the responses in the superficial tissue layer in healthy adult humans. We observed significant responses to BHs in the scalp hemodynamics. Cerebral responses to BHs were detected in the cytochrome C oxidase redox (rCCO) at 4 cm without using data from the short-distance channel. Using the data from the 1 cm channel in the two-layer regression algorithm showed that cerebral hemodynamic and rCCO responses also occurred at 3 cm. We found that the waveband 700–900 nm was optimal for the detection of cerebral responses to BHs in adults.

Fast diffuse correlation spectroscopy with a low-cost, fiber-less embedded diode laser

Diffuse correlation spectroscopy (DCS), a popular optical technique for fast noninvasive measurement of blood flow, is commonly implemented using expensive fiber-coupled long coherence length laser systems. Here, we report the development of a portable and fiber-less approach that can be used as a low-cost alternative to illuminate tissue in DCS instruments. We validate the accuracy and noise characteristics of the fiber-less DCS laser source, by comparisons against traditional DCS light sources, with experiments on controlled tissue-simulating phantoms and in humans.

Accuracy of diffuse correlation spectroscopy measurements of cerebral blood flow when using a three-layer analytical model

Diffuse correlation spectroscopy (DCS) is a non-invasive optical technology for the assessment of an index of cerebral blood flow (CBFi). Analytical methods that model the head as a three-layered medium (i.e., scalp, skull, brain) are becoming more commonly used to minimize the contribution of extracerebral layers to the measured DCS signal in adult cerebral blood flow studies. However, these models rely on a priori knowledge of layer optical properties and thicknesses. Errors in these values can lead to errors in the estimation of CBFi, although the magnitude of this influence has not been rigorously characterized. Herein, we investigate the accuracy of measuring cerebral blood flow with a three-layer model when errors in layer optical properties or thicknesses are present. Through a series of in silico experiments, we demonstrate that CBFi is highly sensitive to errors in brain optical properties and skull and scalp thicknesses. Relative changes in CBFi are less sensitive to optical properties but are influenced by errors in layer thickness. Thus, when using the three-layer model, accurate estimation of scalp and skull thickness are required for reliable results.

Comparison of functional activation responses from the auditory cortex derived using multi-distance frequency domain and continuous wave near-infrared spectroscopy

Significance: Quantitative measurements of cerebral hemodynamic changes due to functional activation are widely accomplished with commercial continuous wave (CW-NIRS) instruments despite the availability of the more rigorous multi-distance frequency domain (FD-NIRS) approach. A direct comparison of the two approaches to functional near-infrared spectroscopy can help in the interpretation of optical data and guide implementations of diffuse optical instruments for measuring functional activation. Aim: We explore the differences between CW-NIRS and multi-distance FD-NIRS by comparing measurements of functional activation in the human auditory cortex. Approach: Functional activation of the human auditory cortex was measured using a commercial frequency domain near-infrared spectroscopy instrument for 70 dB sound pressure level broadband noise and pure tone (1000 Hz) stimuli. Changes in tissue oxygenation were calculated using the modified Beer-Lambert law (CW-NIRS approach) and the photon diffusion equation (FD-NIRS approach). Results: Changes in oxygenated hemoglobin measured with the multi-distance FD-NIRS approach were about twice as large as those measured with the CW-NIRS approach. A finite-element simulation of the functional activation problem was performed to demonstrate that tissue oxygenation changes measured with the CW-NIRS approach is more accurate than that with multi-distance FD-NIRS. Conclusions: Multi-distance FD-NIRS approaches tend to overestimate functional activation effects, in part due to partial volume effects.

Impact of Cutaneous Blood Flow on NIR-DCS Measures of Skeletal Muscle Blood Flow Index

Near-infrared diffuse correlation spectroscopy (NIR-DCS) is an optical technique for estimating relative changes in skeletal muscle perfusion during exercise, but may be affected by changes in cutaneous blood flow, as photons emitted by the laser must first pass through the skin. Accordingly, the purpose of this investigation was to examine how increased cutaneous blood flow affects NIR-DCS blood flow index (BFI) at rest and during exercise using a passive whole-body heating protocol that increases cutaneous, but not skeletal muscle, perfusion in the uncovered limb. BFI and cutaneous perfusion (laser Doppler flowmetry) were assessed in 15 healthy young subjects before (e.g., rest) and during 5-minutes of moderate-intensity hand-grip exercise in normothermic conditions and after cutaneous blood flow was elevated via whole-body heating. Hyperthermia significantly increased both cutaneous perfusion (~7.3-fold; p≤0.001) and NIR-DCS BFI (~4.5-fold; p≤0.001). Although relative BFI (i.e., fold-change above baseline) exhibited a typical exponential increase in muscle perfusion during normothermic exercise (2.81±0.95), there was almost no change in BFI during hyperthermic exercise (1.43±0.44). A subset of 8 subjects were subsequently treated with intradermal injection of botulinum toxin-A (Botox) to block heating-induced elevations in cutaneous blood flow, which 1) nearly abolished the hyperthermia-induced increase in BFI, and 2) restored BFI kinetics during hyperthermic exercise to values that were not different from normothermic exercise (p=0.091). Collectively, our results demonstrate that cutaneous blood flow can have a substantial, detrimental impact on NIR-DCS estimates of skeletal muscle perfusion and highlight the need for technical and/or pharmacological advancements to overcome this issue moving forward.

Functional interferometric diffusing wave spectroscopy of the human brain

Cerebral blood flow (CBF) is essential for brain function, and CBF-related signals can inform us about brain activity. Yet currently, high-end medical instrumentation is needed to perform a CBF measurement in adult humans. Here, we describe functional interferometric diffusing wave spectroscopy (fiDWS), which introduces and collects near-infrared light via the scalp, using inexpensive detector arrays to rapidly monitor coherent light fluctuations that encode brain blood flow index (BFI), a surrogate for CBF. Compared to other functional optical approaches, fiDWS measures BFI faster and deeper while also providing continuous wave absorption signals. Achieving clear pulsatile BFI waveforms at source-collector separations of 3.5 cm, we confirm that optical BFI, not absorption, shows a graded hypercapnic response consistent with human cerebrovascular physiology, and that BFI has a better contrast-to-noise ratio than absorption during brain activation. By providing high-throughput measurements of optical BFI at low cost, fiDWS will expand access to CBF.

Blood flow response to orthostatic challenge identifies signatures of the failure of static cerebral autoregulation in patients with cerebrovascular disease

Background

The cortical microvascular cerebral blood flow response (CBF) to different changes in head-of-bed (HOB) position has been shown to be altered in acute ischemic stroke (AIS) by diffuse correlation spectroscopy (DCS) technique. However, the relationship between these relative ΔCBF changes and associated systemic blood pressure changes has not been studied, even though blood pressure is a major driver of cerebral blood flow.

Methods

Transcranial DCS data from four studies measuring bilateral frontal microvascular cerebral blood flow in healthy controls (n = 15), patients with asymptomatic severe internal carotid artery stenosis (ICA, n = 27), and patients with acute ischemic stroke (AIS, n = 72) were aggregated. DCS-measured CBF was measured in response to a short head-of-bed (HOB) position manipulation protocol (supine/elevated/supine, 5 min at each position). In a sub-group (AIS, n = 26; ICA, n = 14; control, n = 15), mean arterial pressure (MAP) was measured dynamically during the protocol.

Results

After elevated positioning, DCS CBF returned to baseline supine values in controls (p = 0.890) but not in patients with AIS (9.6% [6.0,13.3], mean 95% CI, p < 0.001) or ICA stenosis (8.6% [3.1,14.0], p = 0.003)). MAP in AIS patients did not return to baseline values (2.6 mmHg [0.5, 4.7], p = 0.018), but in ICA stenosis patients and controls did. Instead ipsilesional but not contralesional CBF was correlated with MAP (AIS 6.0%/mmHg [− 2.4,14.3], p = 0.038; ICA stenosis 11.0%/mmHg [2.4,19.5], p < 0.001).

Conclusions

The observed associations between ipsilateral CBF and MAP suggest that short HOB position changes may elicit deficits in cerebral autoregulation in cerebrovascular disorders. Additional research is required to further characterize this phenomenon.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12883-021-02179-8.

Improved accuracy of cerebral blood flow quantification in the presence of systemic physiology cross-talk using multi-layer Monte Carlo modeling

Significance: Contamination of diffuse correlation spectroscopy (DCS) measurements of cerebral blood flow (CBF) due to systemic physiology remains a significant challenge in the clinical translation of DCS for neuromonitoring. Tunable, multi-layer Monte Carlo-based (MC) light transport models have the potential to remove extracerebral flow cross-talk in cerebral blood flow index ( CBF i ) estimates. Aim: We explore the effectiveness of MC DCS models in recovering accurate CBF i changes in the presence of strong systemic physiology variations during a hypercapnia maneuver. Approach: Multi-layer slab and head-like realistic (curved) geometries were used to run MC simulations of photon propagation through the head. The simulation data were post-processed into models with variable extracerebral thicknesses and used to fit DCS multi-distance intensity autocorrelation measurements to estimate CBF i timecourses. The results of the MC CBF i values from a set of human subject hypercapnia sessions were compared with CBF i values estimated using a semi-infinite analytical model, as commonly used in the field. Results: Group averages indicate a gradual systemic increase in blood flow following a different temporal profile versus the expected rapid CBF response. Optimized MC models, guided by several intrinsic criteria and a pressure modulation maneuver, were able to more effectively separate CBF i changes from scalp blood flow influence than the analytical fitting, which assumed a homogeneous medium. Three-layer models performed better than two-layer ones; slab and curved models achieved largely similar results, though curved geometries were closer to physiological layer thicknesses. Conclusion: Three-layer, adjustable MC models can be useful in separating distinct changes in scalp and brain blood flow. Pressure modulation, along with reasonable estimates of physiological parameters, can help direct the choice of appropriate layer thicknesses in MC models.

Towards detection of brain injury using multimodal non-invasive neuromonitoring in adults undergoing extracorporeal membrane oxygenation

Extracorporeal membrane oxygenation (ECMO) is a form of cardiopulmonary bypass that provides life-saving support to critically ill patients whose illness is progressing despite maximal conventional support. Use in adults is expanding, however neurological injuries are common. Currently, the existing brain imaging tools are a snapshot in time and require high-risk patient transport. Here we assess the feasibility of measuring diffuse correlation spectroscopy, transcranial Doppler ultrasound, electroencephalography, and auditory brainstem responses at the bedside, and developing a cerebral autoregulation metric. We report preliminary results from two patients, demonstrating feasibility and laying the foundation for future studies monitoring neurological health during ECMO.

Lawrence K. Direct assessment of extracerebral signal contamination on optical measurements of cerebral blood flow, oxygenation, and metabolism

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 (r SD = 3    cm ) and 6 times (r SD = 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.

Lawrence K. Characterizing dynamic cerebral vascular reactivity using a hybrid system combining time-resolved near-infrared and diffuse correlation spectroscopy

This study presents the characterization of dynamic cerebrovascular reactivity (CVR) in healthy adults by a hybrid optical system combining time-resolved (TR) near-infrared spectroscopy (NIRS) and diffuse correlation spectroscopy (DCS). Blood flow and oxygenation (oxy- and deoxy-hemoglobin) responses to a step hypercapnic challenge were recorded to characterize dynamic and static components of CVR. Data were acquired at short and long source-detector separations (r _SD) to assess the impact of scalp hemodynamics, and moment analysis applied to the TR-NIRS to further enhance the sensitivity to the brain. Comparing blood flow and oxygenation responses acquired at short and long r _SD demonstrated that scalp contamination distorted the CVR time courses, particularly for oxyhemoglobin. This effect was significantly diminished by the greater depth sensitivity of TR NIRS and less evident in the DCS data due to the higher blood flow in the brain compared to the scalp. The reactivity speed was similar for blood flow and oxygenation in the healthy brain. Given the ease-of-use, portability, and non-invasiveness of this hybrid approach, it is well suited to investigate if the temporal relationship between CBF and oxygenation is altered by factors such as age and cerebrovascular disease.

Quantification of cerebral blood flow in adults by contrast-enhanced near-infrared spectroscopy: Validation against MRI

The purpose of this study was to assess the accuracy of absolute cerebral blood flow (CBF) measurements obtained by dynamic contrast-enhanced (DCE) near-infrared spectroscopy (NIRS) using indocyanine green as a perfusion contrast agent. For validation, CBF was measured independently using the MRI perfusion method arterial spin labeling (ASL). Data were acquired at two sites and under two flow conditions (normocapnia and hypercapnia). Depth sensitivity was enhanced using time-resolved detection, which was demonstrated in a separate set of experiments using a tourniquet to temporally impede scalp blood flow. A strong correlation between CBF measurements from ASL and DCE-NIRS was observed (slope = 0.99 ± 0.08, y-intercept = -1.7 ± 7.4 mL/100 g/min, and R2 = 0.88). Mean difference between the two techniques was 1.9 mL/100 g/min (95% confidence interval ranged from -15 to 19 mL/100g/min and the mean ASL CBF was 75.4 mL/100 g/min). Error analysis showed that structural information and baseline absorption coefficient were needed for optimal CBF reconstruction with DCE-NIRS. This study demonstrated that DCE-NIRS is sensitive to blood flow in the adult brain and can provide accurate CBF measurements with the appropriate modeling techniques.

Non-Invasive Estimation of Intracranial Pressure by Diffuse Optics: A Proof-of-Concept Study

Intracranial pressure (ICP) is an important parameter to monitor in several neuropathologies. However, because current clinically accepted methods are invasive, its monitoring is limited to patients in critical conditions. On the other hand, there are other less critical conditions for which ICP monitoring could still be useful; therefore, there is a need to develop non-invasive methods. We propose a new method to estimate ICP based on the analysis of the non-invasive measurement of pulsatile, microvascular cerebral blood flow with diffuse correlation spectroscopy. This is achieved by training a recurrent neural network using only the cerebral blood flow as the input. The method is validated using a 50% split sample method using the data from a proof-of-concept study. The study involved a population of infants (n = 6) with external hydrocephalus (initially diagnosed as benign enlargement of subarachnoid spaces) as well as a population of adults (n = 6) with traumatic brain injury. The algorithm was applied to each cohort individually to obtain a model and an ICP estimate. In both diverse cohorts, the non-invasive estimation of ICP was achieved with an accuracy of <4 mm Hg and a negligible small bias. Further, we have achieved a good correlation (Pearson's correlation coefficient >0.9) and good concordance (Lin's concordance correlation coefficient >0.9) in comparison with standard clinical, invasive ICP monitoring. This preliminary work paves the way for further investigations of this tool for the non-invasive, bedside assessment of ICP.

Real-Time Non-invasive Assessment of Cerebral Hemodynamics With Diffuse Optical Spectroscopies in a Neuro Intensive Care Unit: An Observational Case Study

Prevention of secondary damage is an important goal in the treatment of severe neurological conditions, such as major head trauma or stroke. However, there is currently a lack of non-invasive methods for monitoring cerebral physiology. Diffuse optical methods have been proposed as an inexpensive, non-invasive bedside monitor capable of providing neurophysiology information in neurocritical patients. However, the reliability of the technique to provide accurate longitudinal measurement during the clinical evolution of a patient remains largely unaddressed. Here, we report on the translation of a hybrid diffuse optical system combining frequency domain diffuse optical spectroscopy (FD-DOS) and diffuse correlation spectroscopy (DCS) for real-time monitoring of cerebral physiology in a neuro intensive care unit (neuro-ICU). More specifically, we present a case study of a patient admitted with a high-grade aneurysmal subarachnoid hemorrhage, who was monitored throughout hospitalization. We show that the neurophysiological parameters measured by diffuse optics at the bedside are consistent with the clinical evolution of the patient at all the different stages following its brain lesion. These data provide support for clinical translation of DOS/DCS as a useful biomarker of neurophysiology in the neuro-ICU, particularly in locations where other clinical resources are limited.

Non-invasive optical neuromonitoring of the temperature-dependence of cerebral oxygen metabolism during deep hypothermic cardiopulmonary bypass in neonatal swine

Management of deep hypothermic (DH) cardiopulmonary bypass (CPB), a critical neuroprotective strategy, currently relies on non-invasive temperature to guide cerebral metabolic suppression during complex cardiac surgery in neonates. Considerable inter-subject variability in temperature response and residual metabolism may contribute to the persisting risk for postoperative neurological injury. To characterize and mitigate this variability, we assess the sufficiency of conventional nasopharyngeal temperature (NPT) guidance, and in the process, validate combined non-invasive frequency-domain diffuse optical spectroscopy (FD-DOS) and diffuse correlation spectroscopy (DCS) for direct measurement of cerebral metabolic rate of oxygen (CMRO₂). During CPB, n = 8 neonatal swine underwent cooling from normothermia to 18℃, sustained DH perfusion for 40 min, and then rewarming to simulate cardiac surgery. Continuous non-invasive and invasive measurements of intracranial temperature (ICT) and CMRO₂ were acquired. Significant hysteresis (p < 0.001) between cooling and rewarming periods in the NPT versus ICT and NPT versus CMRO₂ relationships were found. Resolution of this hysteresis in the ICT versus CMRO₂ relationship identified a crucial insufficiency of conventional NPT guidance. Non-invasive CMRO₂ temperature coefficients with respect to NPT (Q₁₀ = 2.0) and ICT (Q₁₀ = 2.5) are consistent with previous reports and provide further validation of FD-DOS/DCS CMRO₂ monitoring during DH CPB to optimize management.

Functional near-infrared spectroscopy for speech protocols: characterization of motion artifacts and guidelines for improving data analysis

Monitoring speech tasks with functional near-infrared spectroscopy (fNIRS) enables investigation of speech production mechanisms and informs treatment strategies for speech-related disorders such as stuttering. Unfortunately, due to movement of the temporalis muscle, speech production can induce relative movement between probe optodes and skin. These movements generate motion artifacts during speech tasks. In practice, spurious hemodynamic responses in functional activation signals arise from lack of information about the consequences of speech-related motion artifacts, as well as from lack of standardized processing procedures for fNIRS signals during speech tasks. To this end, we characterize the effects of speech production on fNIRS signals, and we introduce a systematic analysis to ameliorate motion artifacts. The study measured 50 healthy subjects performing jaw movement (JM) tasks and found that JM produces two different patterns of motion artifacts in fNIRS. To remove these unwanted contributions, we validate a hybrid motion-correction algorithm based sequentially on spline interpolation and then wavelet filtering. We compared performance of the hybrid algorithm with standard algorithms based on spline interpolation only and wavelet decomposition only. The hybrid algorithm corrected 94% of the artifacts produced by JM, and it did not lead to spurious responses in the data. We also validated the hybrid algorithm during a reading task performed under two different conditions: reading aloud and reading silently. For both conditions, we observed significant cortical activation in brain regions related to reading. Moreover, when comparing the two conditions, good agreement of spatial and temporal activation patterns was found only when data were analyzed using the hybrid approach. Overall, the study demonstrates a standardized processing scheme for fNIRS data during speech protocols. The scheme decreases spurious responses and intersubject variability due to motion artifacts.

Portable System for Time-Domain Diffuse Correlation Spectroscopy

We introduce a portable system for clinical studies based on time-domain diffuse correlation spectroscopy (DCS). After evaluating different lasers and detectors, the final system is based on a pulsed laser with about 550 ps pulsewidth, a coherence length of 38 mm, and two types of single-photon avalanche diodes (SPAD). The higher efficiency of the red-enhanced SPAD maximizes detection of the collected light, increasing the signal-to-noise ratio, while the better timing response of the CMOS SPAD optimizes the selection of late photons and increases spatial resolution. We discuss component selection and performance, and we present a full characterization of the system, measurement stability, a phantom-based validation study, and preliminary in vivo results collected from the forearms and the foreheads of four healthy subjects. With this system, we are able to resolve blood flow changes 1 cm below the skin surface with improved depth sensitivity and spatial resolution with respect to continuous wave DCS.

Cerebral Blood Flow Response During Bolus Normal Saline Infusion After Ischemic Stroke

GOALS

We quantified cerebral blood flow response to a 500 cc bolus of 0.9%% normal saline (NS) within 96 hours of acute ischemic stroke (AIS) using diffuse correlation spectroscopy (DCS).

MATERIALS AND METHODS

Subjects with AIS in the anterior, middle, or posterior cerebral artery territory were enrolled within 96 hours of symptom onset. DCS measured relative cerebral blood flow (rCBF) in the bilateral frontal lobes for 15 minutes at rest (baseline), during a 30-minute infusion of 500 cc NS (bolus), and for 15 minutes after completion (post-bolus). Mean rCBF for each time period was calculated for individual subjects and median rCBF for the population was compared between time periods. Linear regression was used to evaluate for associations between rCBF and clinical features.

RESULTS

Among 57 subjects, median rCBF (IQR) increased relative to baseline in the ipsilesional hemisphere by 17% (-2.0%, 43.1%), P< 0.001, and in the contralesional hemisphere by 13.3% (-4.3%, 36.0%), P < .004. No significant associations were found between ipsilesional changes in rCBF and age, race, infarct size, infarct location, presence of large vessel stenosis, NIH stroke scale, or symptom duration.

CONCLUSION

A 500 cc bolus of .9% NS produced a measurable increase in rCBF in both the affected and nonaffected hemispheres. Clinical features did not predict rCBF response.

Continuous non-invasive optical monitoring of cerebral blood flow and oxidative metabolism after acute brain injury

Rapid detection of ischemic conditions at the bedside can improve treatment of acute brain injury. In this observational study of 11 critically ill brain-injured adults, we employed a monitoring approach that interleaves time-resolved near-infrared spectroscopy (TR-NIRS) measurements of cerebral oxygen saturation and oxygen extraction fraction (OEF) with diffuse correlation spectroscopy (DCS) measurement of cerebral blood flow (CBF). Using this approach, we demonstrate the clinical promise of non-invasive, continuous optical monitoring of changes in CBF and cerebral metabolic rate of oxygen (CMRO₂). In addition, the optical CBF and CMRO₂ measures were compared to invasive brain tissue oxygen tension (PbtO₂), thermal diffusion flowmetry CBF, and cerebral microdialysis measures obtained concurrently. The optical CBF and CMRO₂ information successfully distinguished between ischemic, hypermetabolic, and hyperemic conditions that arose spontaneously during patient care. Moreover, CBF monitoring during pressor-induced changes of mean arterial blood pressure enabled assessment of cerebral autoregulation. In total, the findings suggest that this hybrid non-invasive neurometabolic optical monitor (NNOM) can facilitate clinical detection of adverse physiological changes in brain injured patients that are otherwise difficult to measure with conventional bedside monitoring techniques.

Influence of probe pressure on the pulsatile diffuse correlation spectroscopy blood flow signal on the forearm and forehead regions

In a pilot study of 11 healthy adults (24 to 39 years, all male), we characterize the influence of external probe pressure on optical diffuse correlation spectroscopy (DCS) measurements of pulsatile blood flow obtained on the forearm and forehead. For external probe pressure control, a hand inflatable air balloon is inserted between the tissue and an elastic strap. The air balloon is sequentially inflated to achieve a wide range of external probe pressures between 20 and 250 mmHg on the forearm and forehead, which are measured with a flexible pressure sensor underneath the probe. At each probe pressure, the pulsatility index (PI) of arteriole blood flow on the forehead and forearm is measured with DCS (2.1-cm source-detector separation). We observe a strong correlation between probe pressure and PI on the forearm ( R = 0.66 , p < 0.001 ), but not on the forehead ( R = - 0.11 , p = 0.4 ). The forearm measurements demonstrate the sensitivity of the DCS PI to skeletal muscle tissue pressure, whereas the forehead measurements indicate that DCS PI measurements are not sensitive to scalp tissue pressure. Note, in contrast to pulsatility, the time-averaged DCS blood flow index on the forehead was significantly correlated with probe pressure ( R = - 0.55 , p < 0.001 ). This pilot data appears to support the initiation of more comprehensive clinical studies on DCS to detect trends in internal pressure in brain and skeletal muscle.

Transcranial Optical Monitoring of Cerebral Hemodynamics in Acute Stroke Patients during Mechanical Thrombectomy

INTRODUCTION

Mechanical thrombectomy is revolutionizing treatment of acute stroke due to large vessel occlusion (LVO). Unfortunately, use of the modified Thrombolysis in Cerebral Infarction score (mTICI) to characterize recanalization of the cerebral vasculature does not address microvascular perfusion of the distal parenchyma, nor provide more than a vascular "snapshot." Thus, little is known about tissue-level hemodynamic consequences of LVO recanalization. Diffuse correlation spectroscopy (DCS) and diffuse optical spectroscopy (DOS) are promising methods for continuous, noninvasive, contrast-free transcranial monitoring of cerebral microvasculature.

METHODS

Here, we use a combined DCS/DOS system to monitor frontal lobe hemodynamic changes during endovascular treatment of 2 patients with ischemic stroke due to internal carotid artery (ICA) occlusions.

RESULTS AND DISCUSSION

The monitoring instrument identified a recanalization-induced increase in ipsilateral cerebral blood flow (CBF) with little or no concurrent change in contralateral CBF and extracerebral blood flow. The results suggest that diffuse optical monitoring is sensitive to intracerebral hemodynamics in patients with ICA occlusion and can measure microvascular responses to mechanical thrombectomy.

Clinical Brain Monitoring with Time Domain NIRS: A Review and Future Perspectives

Near-infrared spectroscopy (NIRS) is an optical technique that can measure brain tissue oxygenation and haemodynamics in real-time and at the patient bedside allowing medical doctors to access important physiological information. However, despite this, the use of NIRS in a clinical environment is hindered due to limitations, such as poor reproducibility, lack of depth sensitivity and poor brain-specificity. Time domain NIRS (or TD-NIRS) can resolve these issues and offer detailed information of the optical properties of the tissue, allowing better physiological information to be retrieved. This is achieved at the cost of increased instrument complexity, operation complexity and price. In this review, we focus on brain monitoring clinical applications of TD-NIRS. A total of 52 publications were identified, spanning the fields of neonatal imaging, stroke assessment, traumatic brain injury (TBI) assessment, brain death assessment, psychiatry, peroperative care, neuronal disorders assessment and communication with patient with locked-in syndrome. In all the publications, the advantages of the TD-NIRS measurement to (1) extract absolute values of haemoglobin concentration and tissue oxygen saturation, (2) assess the reduced scattering coefficient, and (3) separate between extra-cerebral and cerebral tissues, are highlighted; and emphasize the utility of TD-NIRS in a clinical context. In the last sections of this review, we explore the recent developments of TD-NIRS, in terms of instrumentation and methodologies that might impact and broaden its use in the hospital.