Noninvasive optical evaluation of spontaneous low frequency oscillations in cerebral hemodynamics

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.

Wearable fiber-free optical sensor for continuous monitoring of neonatal cerebral blood flow and oxygenation

BACKGROUND

Unstable cerebral hemodynamics places preterm infants at high risk of brain injury. We adapted an innovative, fiber-free, wearable diffuse speckle contrast flow-oximetry (DSCFO) device for continuous monitoring of both cerebral blood flow (CBF) and oxygenation in neonatal piglets and preterm infants.

METHODS

DSCFO uses two small laser diodes as focused-point and a tiny CMOS camera as a high-density two-dimensional detector to detect spontaneous spatial fluctuation of diffuse laser speckles for CBF measurement, and light intensity attenuations for cerebral oxygenation measurement. The DSCFO was first validated against the established diffuse correlation spectroscopy (DCS) in neonatal piglets and then utilized for continuous CBF and oxygenation monitoring in preterm infants during intermittent hypoxemia (IH) events.

RESULTS

Significant correlations between the DSCFO and DCS measurements of CBF variations in neonatal piglets were observed. IH events induced fluctuations in CBF, cerebral oxygenation, and peripheral cardiorespiratory vitals in preterm infants. However, no consistent correlation patterns were observed among peripheral and cerebral monitoring parameters.

CONCLUSIONS

This pilot study demonstrated the feasibility of DSCFO technology to serve as a low-cost wearable sensor for continuous monitoring of multiple cerebral hemodynamic parameters. The results suggested the importance of multi-parameter measurements for understanding deep insights of peripheral and cerebral regulations.

IMPACT

The innovative DSCFO technology may serve as a low-cost wearable sensor for continuous bedside monitoring of multiple cerebral hemodynamic parameters in neonatal intensive care units. Concurrent DSCFO and DCS measurements of CBF variations in neonatal piglet models generated consistent results. No consistent correlation patterns were observed among peripheral and cerebral monitoring parameters in preterm neonates, suggesting the importance of multi-parameter measurements for understanding deep insights of peripheral and cerebral regulations during IH events. Integrating and correlating multiple cerebral functional parameters with clinical outcomes may identify biomarkers for prediction and management of IH associated brain injury.

Correlation and asynchronization of electroencephalogram and cerebral blood flow in active and passive stimulations

Objective.Real-time brain monitoring is of importance for intraoperative surgeries and intensive care unit, in order to take timely clinical interventions. Electroencephalogram (EEG) is a conventional technique for recording neural excitations (e.g. brain waves) in the cerebral cortex, and near infrared diffuse correlation spectroscopy (DCS) is an emerging technique that can directly measure the cerebral blood flow (CBF) in microvasculature system. Currently, the relationship between the neural activities and cerebral hemodynamics that reflects the vasoconstriction features of cerebral vessels, especially under both active and passive situation, has not been elucidated thus far, which triggers the motivation of this study.Approach.We used the verbal fluency test as an active cognitive stimulus to the brain, and we manipulated blood pressure changes as a passive challenge to the brain. Under both protocols, the CBF and EEG responses were longitudinally monitored throughout the cerebral stimulus. Power spectrum approaches were applied the EEG signals and compared with CBF responses.Main results.The results show that the EEG response was significantly faster and larger in amplitude during the active cognitive task, when compared to the CBF, but with larger individual variability. By contrast, CBF is more sensitive when response to the passive task, and with better signal stability. We also found that there was a correlation (p< 0.01,r= 0.866,R2= 0.751) between CBF and EEG in initial response during the active task, but no significant correlation (p> 0.05) was found during the passive task. The similar relations were also found between regional brain waves and blood flow.Significance.The asynchronization and correlation between the two measurements indicates the necessity of monitoring both variables for comprehensive understanding of cerebral physiology. Deep exploration of their relationships provides promising implications for DCS/EEG integration in the diagnosis of various neurovascular and psychiatric diseases.

Assessment of power spectral density of microvascular hemodynamics in skeletal muscles at very low and low-frequency via near-infrared diffuse optical spectroscopies

In this work, we used a hybrid time domain near-infrared spectroscopy (TD-NIRS) and diffuse correlation spectroscopy (DCS) device to retrieve hemoglobin and blood flow oscillations of skeletal muscle microvasculature. We focused on very low (VLF) and low-frequency (LF) oscillations (i.e., frequency lower than 0.145 Hz), that are related to myogenic, neurogenic and endothelial activities. We measured power spectral density (PSD) of blood flow and hemoglobin concentration in four muscles (thenar eminence, plantar fascia, sternocleidomastoid and forearm) of 14 healthy volunteers to highlight possible differences in microvascular hemodynamic oscillations. We observed larger PSDs for blood flow compared to hemoglobin concentration, in particular in case of distal muscles (i.e., thenar eminence and plantar fascia). Finally, we compared the PSDs measured on the thenar eminence of healthy subjects with the ones measured on a septic patient in the intensive care unit: lower power in the endothelial-dependent frequency band, and larger power in the myogenic ones were observed in the septic patient, in accordance with previous works based on laser doppler flowmetry.

Pressure stimulus study on acupuncture points with multi-channel multimode-fiber diffuse speckle contrast analysis (MMF-DSCA)

A multi-channel multimode-fiber deep tissue flowmetry system has been constructed based on diffuse speckle contrast analysis (DSCA) for simultaneous blood flow measurements at different locations on the human body. This system has been utilized in an acupuncture study within the field of traditional Chinese medicine (TCM), primarily focusing on acupuncture points along the large intestine meridian. Deep tissue blood flow was monitored at four different acupuncture points (LI1, LI5, LI10, and ST25) with a sampling rate of 60 Hz while applying pressure stimulus on LI4 (hegu or hapgok). Although the blood flow index (BFI) and blood volume (BV) did not exhibit significant changes after the pressure stimulus, an increase in the amplitude and complexity of low-frequency oscillations (LFOs) in microcirculation was observed.

Non-Invasive Continuous Optical Monitoring of Cerebral Blood Flow after Traumatic Brain Injury in Mice Using Fiber Camera-Based Speckle Contrast Optical Spectroscopy

Neurocritical care focuses on monitoring cerebral blood flow (CBF) to prevent secondary brain injuries before damage becomes irreversible. Thus, there is a critical unmet need for continuous neuromonitoring methods to quantify CBF within the vulnerable cortex continuously and non-invasively. Animal models and imaging biomarkers can provide valuable insights into the mechanisms and kinetics of head injury, as well as insights for potential treatment strategies. For this purpose, we implemented an optical technique for continuous monitoring of blood flow changes after a closed head injury in a mouse model, which is based on laser speckle contrast imaging and a fiber camera-based approach. Our results indicate a significant decrease (~10%, p-value < 0.05) in blood flow within 30 min of a closed head injury. Furthermore, the low-frequency oscillation analysis also indicated much lower power in the trauma group compared to the control group. Overall, blood flow has the potential to be a biomarker for head injuries in the early phase of a trauma, and the system is useful for continuous monitoring with the potential for clinical translation.

A Wearable Fiber-Free Optical Sensor for Continuous Monitoring of Neonatal Cerebral Blood Flow and Oxygenation

Impact

The innovative DSCFO technology may serve as a low-cost wearable sensor for continuous bedside monitoring of multiple cerebral hemodynamic parameters in neonatal intensive care units.Concurrent DSCFO and DCS measurements of CBF variations in neonatal piglet models generated consistent results.No consistent correlation patterns were observed among peripheral and cerebral monitoring parameters in preterm neonates, suggesting the importance of multi-parameter measurements for understanding deep insights of peripheral and cerebral regulations during IH events.Integrating and correlating multiple cerebral functional parameters with clinical outcomes may identify biomarkers for prediction and management of IH associated brain injury.

Background

Unstable cerebral hemodynamics places preterm infants at high risk of brain injury. We adapted an innovative, fiber-free, wearable diffuse speckle contrast flow-oximetry (DSCFO) device for continuous monitoring of both cerebral blood flow (CBF) and oxygenation in neonatal piglets and preterm infants.

Methods

DSCFO uses two small laser diodes as focused-point and a tiny CMOS camera as a high-density two-dimensional detector to detect spontaneous spatial fluctuation of diffuse laser speckles for CBF measurement, and light intensity attenuations for cerebral oxygenation measurement. The DSCFO was first validated against the established diffuse correlation spectroscopy (DCS) in neonatal piglets and then utilized for continuous CBF and oxygenation monitoring in preterm infants during intermittent hypoxemia (IH) events.

Results

Consistent results between the DSCFO and DCS measurements of CBF variations in neonatal piglets were observed. IH events induced fluctuations in CBF, cerebral oxygenation, and peripheral cardiorespiratory vitals in preterm infants. However, no consistent correlation patterns were observed among peripheral and cerebral monitoring parameters.

Conclusions

This pilot study demonstrated the feasibility of DSCFO technology to serve as a low-cost wearable sensor for continuous monitoring of multiple cerebral hemodynamic parameters. The results suggested the importance of multi-parameter measurements for understanding deep insights of peripheral and cerebral regulations.

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.

Assessment of dynamic cerebral autoregulation in near-infrared spectroscopy using short channels: A feasibility study in acute ischemic stroke patients

Introduction

In acute ischemic stroke, progressive impairment of cerebral autoregulation (CA) is frequent and associated with unfavorable outcomes. Easy assessment of cerebral blood flow and CA in stroke units bedside tools like near-infrared spectroscopy (NIRS) might improve early detection of CA deterioration. This study aimed to assess dynamic CA with multichannel CW-NIRS in acute ischemic stroke (AIS) patients compared to agematched healthy controls.

Methods

CA reaction was amplified by changes in head of bed position. Long- and short channels were used to monitor systemic artery pressure- and intracranial oscillations simultaneously. Gain and phase shift in spontaneous low- and very low-frequency oscillations (LFO, VLFO) of blood pressure were assessed.

Results

A total of 54 participants, 27 with AIS and 27 age-matched controls were included. Gain was significantly lower in the AIS group in the LFO range (i) when the upper body was steadily elevated to 30. and (ii) after its abrupt elevation to 30°. No other differences were found between groups.

Discussion

This study demonstrates the feasibility of NIRS short channels to measure CA in AIS patients in one single instrument. A lower gain in AIS might indicate decreased CA activity in this pilot study, but further studies investigating the role of NIRS short channels in AIS are needed.

Brain Functional Connectivity in Middle-Aged Hong Chuan Tai Chi Players in Resting State

Tai Chi is an effective strategy for slowing cognitive decline, although the underlying mechanism remains unclear. We designed a cross-sectional study to examine brain functional connectivity in middle-aged Hong Chuan Tai Chi practitioners. Eighteen middle-aged Hong Chuan Tai Chi practitioners and 22 age-matched Tai Chi-naïve controls completed functional near-infrared spectroscopy (fNIRS) tests to evaluate oxyhemoglobin changes in the prefrontal cortex (PFC), motor cortex (MC), and occipital cortex (OC) in five frequency intervals (I, 0.6-2 Hz; II, 0.145-0.6 Hz; III, 0.052-0.145 Hz; IV, 0.021-0.052 Hz; V, 0.0095-0.021 Hz). Wavelet phase coherence was used to analyze the match between the instantaneous phases of the two signals to accurately measure brain functional connectivity. Global cognition was measured using the Montreal Cognitive Assessment scale. Compared with the control group, Hong Chuan Tai Chi practitioners had better global cognition (p < 0.01) and showed higher functional connectivity of the PFC, MC, and OC in intervals I, III, VI, and V in the resting state within the same brain hemispheres or between the left and right hemispheres. Our findings revealed that middle-aged Hong Chuan Tai Chi practitioners had higher functional connectivity of the PFC, MC, and OC across both brain hemispheres in cardiac activity, myogenic activity, sympathetic nervous system, and endothelial cell metabolic activities which may contribute to higher global cognition.

Hemodynamics and Tissue Optical Properties in Bimodal Infarctions Induced by Middle Cerebral Artery Occlusion

Various infarct sizes induced by middle cerebral artery occlusion (MCAO) generate inconsistent outcomes for stroke preclinical study. Monitoring cerebral hemodynamics may help to verify the outcome of MCAO. The aim of this study was to investigate the changes in brain tissue optical properties by frequency-domain near-infrared spectroscopy (FD-NIRS), and establish the relationship between cerebral hemodynamics and infarct variation in MCAO model. The rats were undergone transient MCAO using intraluminal filament. The optical properties and hemodynamics were measured by placing the FD-NIRS probes on the scalp of the head before, during, and at various time-courses after MCAO. Bimodal infarction severities were observed after the same 90-min MCAO condition. Significant decreases in concentrations of oxygenated hemoglobin ([HbO]) and total hemoglobin ([HbT]), tissue oxygenation saturation (StO₂), absorption coefficient (μa) at 830 nm, and reduced scattering coefficient (μs’) at both 690 and 830 nm were detected during the occlusion in the severe infarction but not the mild one. Of note, the significant increases in [HbO], [HbT], StO₂, and μa at both 690 and 830 nm were found on day 3; and increases in μs’ at both 690 and 830 nm were found on day 2 and day 3 after MCAO, respectively. The interhemispheric correlation coefficient (IHCC) was computed from low-frequency hemodynamic oscillation of both hemispheres. Lower IHCCs standing for interhemispheric desynchronizations were found in both mild and severe infarction during occlusion, and only in severe infarction after reperfusion. Our finding supports that sequential FD-NIRS parameters may associated with the severity of the infarction in MCAO model, and the consequent pathologies such as vascular dysfunction and brain edema. Further study is required to validate the potential use of FD-NIRS as a monitor for MCAO verification.

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.

Metabolic Connectivity and Hemodynamic-Metabolic Coherence of Human Prefrontal Cortex at Rest and Post Photobiomodulation Assessed by Dual-Channel Broadband NIRS

Billions of neurons in the human brain form neural networks with oscillation rhythms. Infra-slow oscillation (ISO) presents three main physiological sources: endogenic, neurogenic, and myogenic vasomotions. Having an in vivo methodology for the absolute quantification of ISO from the human brain can facilitate the detection of brain abnormalities in cerebral hemodynamic and metabolic activities. In this study, we introduced a novel measurement-plus-analysis framework for the non-invasive quantification of prefrontal ISO by (1) taking dual-channel broadband near infrared spectroscopy (bbNIRS) measurements from 12 healthy humans during a 6-min rest and 4-min post transcranial photobiomodulation (tPBM) and (2) performing wavelet transform coherence (WTC) analysis on the measured time series data. The WTC indexes (IC, between 0 and 1) enabled the assessment of ipsilateral hemodynamic-metabolic coherence and bilateral functional connectivity in each ISO band of the human prefrontal cortex. At rest, bilateral hemodynamic connectivity was consistent across the three ISO bands (IC ≅ 0.66), while bilateral metabolic connectivity was relatively weaker. For post-tPBM/sham comparison, our analyses revealed three key findings: 8-min, right-forehead, 1064-nm tPBM (1) enhanced the amplitude of metabolic oscillation bilaterally, (2) promoted the bilateral metabolic connectivity of neurogenic rhythm, and (3) made the main effect on endothelial cells, causing alteration of hemodynamic-metabolic coherence on each side of the prefrontal cortex.

Advances in Medical Wearable Biosensors: Design, Fabrication and Materials Strategies in Healthcare Monitoring

In the past decade, wearable biosensors have radically changed our outlook on contemporary medical healthcare monitoring systems. These smart, multiplexed devices allow us to quantify dynamic biological signals in real time through highly sensitive, miniaturized sensing platforms, thereby decentralizing the concept of regular clinical check-ups and diagnosis towards more versatile, remote, and personalized healthcare monitoring. This paradigm shift in healthcare delivery can be attributed to the development of nanomaterials and improvements made to non-invasive biosignal detection systems alongside integrated approaches for multifaceted data acquisition and interpretation. The discovery of new biomarkers and the use of bioaffinity recognition elements like aptamers and peptide arrays combined with the use of newly developed, flexible, and conductive materials that interact with skin surfaces has led to the widespread application of biosensors in the biomedical field. This review focuses on the recent advances made in wearable technology for remote healthcare monitoring. It classifies their development and application in terms of electrochemical, mechanical, and optical modes of transduction and type of material used and discusses the shortcomings accompanying their large-scale fabrication and commercialization. A brief note on the most widely used materials and their improvements in wearable sensor development is outlined along with instructions for the future of medical wearables.

Extraction of tissue optical property and blood flow from speckle contrast diffuse correlation tomography (scDCT) measurements

Measurement of blood flow in tissue provides vital information for the diagnosis and therapeutic monitoring of various vascular diseases. A noncontact, camera-based, near-infrared speckle contrast diffuse correlation tomography (scDCT) technique has been recently developed for 3D imaging of blood flow index (αD_B) distributions in deep tissues up to a centimeter. A limitation with the continuous-wave scDCT measurement of blood flow is the assumption of constant and homogenous tissue absorption coefficient (μ _a ). The present study took the advantage of rapid, high-density, noncontact scDCT measurements of both light intensities and diffuse speckle contrast at multiple source-detector distances and developed two-step fitting algorithms for extracting both μ _a and αD_B. The new algorithms were tested in tissue-simulating phantoms with known optical properties and human forearms. Measurement results were compared against established near-infrared spectroscopy (NIRS) and diffuse correlation spectroscopy (DCS) techniques. The accuracies of our new fitting algorithms with scDCT measurements in phantoms (up to 16% errors) and forearms (up to 23% errors) are comparable to relevant study results (up to 25% errors). Knowledge of μ _a not only improved the accuracy in calculating αD_B but also provided the potential for quantifying tissue blood oxygenation via spectral measurements. A multiple-wavelength scDCT system with new algorithms is currently developing to fit multi-wavelength and multi-distance data for 3D imaging of both blood flow and oxygenation distributions in deep tissues.

Time-evolving coupling functions for evaluating the interaction between cerebral oxyhemoglobin and arterial blood pressure with hypertension

PURPOSES

This study aimed to investigate the network coupling between arterial blood pressure (ABP) and changes in cerebral oxyhemoglobin concentration (Δ [O₂ Hb]/Δ [HHb]) oscillations based on dynamical Bayesian inference in hypertensive subjects.

METHODS

Two groups of subjects, consisting of 30 healthy (Group Control, 55.1 ± 10.6 y), and 32 hypertensive individuals (Group AH, 58.9 ± 8.7 y), participated in this study. A functional near-infrared spectroscopy system was used to measure the Δ [O₂ Hb] and Δ [HHb] signals in the bilateral prefrontal cortex (LPFC/RPFC), motor cortex (LMC/RMC), and occipital lobe (LOL/ROL) during the resting state (12 min). Based on continuous wavelet analysis and coupling functions, the directed coupling strength (CS) between ABP and cerebral hemoglobin was identified and analyzed in three frequency intervals (I: 0.6-2 Hz, II: 0.145-0.6 Hz, III: 0.01-0.08 Hz). The Pearson correlations between the CS and blood pressure parameters were calculated in the hypertension group.

RESULTS

In interval I, Group AH exhibited a significantly higher CS for the coupling from ABP to Δ [O₂ Hb] than Group Control in LMC, RMC, LOL, and ROL. In interval III, the CS from ABP to Δ [O₂ Hb] in LPFC, RPFC, LMC, RMC, LOL, and ROL was significantly higher in Group AH than in Group Control. For the patients with hypertension, diastolic blood pressure was negatively and pulse pressure was positively related to the CS from ABP to Δ [O₂ Hb] oscillations in interval III.

CONCLUSIONS

The higher CS from ABP to Δ [O₂ Hb] in interval I indicated that the components of cardiac activity in cerebral hemoglobin oscillations were more directly responsive to the changes in systematic ABP in patients with hypertension than in healthy subjects. Meanwhile, the higher CS from ABP to Δ [O₂ Hb] in interval III indicated that the cerebral hemoglobin oscillations were susceptible to changes in blood pressure in hypertensive subjects. The results may serve as evidence of impairment in cerebral autoregulation after hypertension. The Pearson correlation results showed that diastolic blood pressure and pulse pressure might be regarded as predictors of cerebral autoregulation function in patients with hypertension, and may be useful for hypertension stratification. This study provides novel insights into the interaction mechanism between ABP and cerebral hemodynamics and could help in the development of new assessment techniques for cerebral vascular disease.

Simultaneous measurements of tissue blood flow and oxygenation using a wearable fiber-free optical sensor

SIGNIFICANCE

There is an essential need to develop wearable multimodality technologies that can continuously measure both blood flow and oxygenation in deep tissues to investigate and manage various vascular/cellular diseases.

AIM

To develop a wearable dual-wavelength diffuse speckle contrast flow oximetry (DSCFO) for simultaneous measurements of blood flow and oxygenation variations in deep tissues.

APPROACH

A wearable fiber-free DSCFO probe was fabricated using 3D printing to confine two small near-infrared laser diodes and a tiny CMOS camera in positions for DSCFO measurements. The spatial diffuse speckle contrast and light intensity measurements at the two different wavelengths enable quantification of tissue blood flow and oxygenation, respectively. The DSCFO was first calibrated using tissue phantoms and then tested in adult forearms during artery cuff occlusion.

RESULTS

Phantom tests determined the largest effective source-detector distance (15 mm) and optimal camera exposure time (10 ms) and verified the accuracy of DSCFO in measuring absorption coefficient variations. The DSCFO detected substantial changes in forearm blood flow and oxygenation resulting from the artery occlusion, which meet physiological expectations and are consistent with previous study results.

CONCLUSIONS

The wearable DSCFO may be used for continuous and simultaneous monitoring of blood flow and oxygenation variations in freely behaving subjects.

Noncontact optical imaging of brain hemodynamics in preterm infants: a preliminary study

Extremely preterm infants' hemodynamic instability places them at high risk of brain injury. Currently there is no reliable bedside method to continuously monitor cerebral hemodynamics in the neonatal intensive care unit (NICU). This paper reports a feasibility study to adapt and test an innovative speckle contrast diffuse correlation tomography (scDCT) device for noncontact, high-density, 3D imaging of cerebral blood flow (CBF) in preterm infants. The scDCT scans a focused point near-infrared illumination to multiple source positions for deep tissue penetration, and controls an electron multiplying charge-coupled-device camera with thousands of pixels to achieve a high-density sampling. The optimized scDCT for use in preterm infants was first evaluated against an established diffuse correlation spectroscopy in an infant-head-simulating phantom with known properties. The observed significant correlation between the two measurements verified the capability of scDCT for transcranial brain imaging. The insignificant influence of transparent incubator wall on scDCT measurements was then confirmed by comparing adult forearm blood flow responses to artery cuff occlusions measured inside and outside the incubator. Finally, the scDCT device was moved to the NICU to image CBF variations in two preterm infants. Infant #1 with no major organ deficits showed little CBF fluctuation over the first 3 weeks of life. Infant #2 showed a significant CBF increase after the 2 h pharmacotherapy for patent ductus arteriosus closure. While these CBF variations meet physiological expectations, the fact that no significant changes are noted with peripheral monitoring of blood oxygen saturation suggests necessity of direct cerebral monitoring. This feasibility study with timely technology development is an important and necessary step towards larger clinical studies with more subjects to further validate it for continuous monitoring and instant management of cerebral pathologies and interventions in the NICU.

Validation of a Novel NeurOs Cerebral Oximetry Monitor Against the INVOS Monitor During Cardiac Surgery

OBJECTIVES

To compare the performance of a novel NeurOs cerebral oximetry monitor against the INVOS monitor during the entire intraoperative phase of cardiac surgery, including periods of known fluctuation in brain oxygenation, such as preoxygenation, induction, cannulation, and cardiopulmonary bypass.

DESIGN

This study was a prospective, nonrandomized, healthcare-provider and outcome-assessor blinded study.

SETTING

Tertiary care university hospital; single institutional study.

PARTICIPANTS

Twenty-three patients who underwent cardiac surgery with cardiopulmonary bypass.

INTERVENTIONS

Both self-adhesive INVOS sensors and the assembled NeurOs sensors were placed accordingly when the patient arrived in the operating room.

MEASUREMENTS AND MAIN RESULTS

Ten out of 13 cases under the normal mode and eight out of the 10 cases under the high- sensitivity mode showed significant correlations between the NeurOs and INVOS groups (p < 0.05, r value from 0.24-0.88). When all cases were combined, NeurOs demonstrated significant correlation with INVOS (r = 0.5, 95% confidence interval [CI] 0.44-0.56, p < 0.01 for normal mode; r = 0.69, 95% CI 0.64 to 0.74, p < 0.01 for high-sensitivity mode) in both modes. To evaluate the data diversity, the authors performed a cluster analysis and found much less variation existed in the NeurOs normal mode when compared with INVOS (standard deviation [SD] 16.6% in INVOS, 4% in NeurOs normal mode) but similar patterns in the high-sensitivity mode (SD 17.6% in INVOS, 15.2% in NeurOs high-sensitivity mode). Bland-Altman plot analysis showed that most of the data fell between ± 1.96 SD lines, which demonstrated good consistency between these two methods under both modes of NeurOs (-28.8 to 30.8 in the normal mode; -36.6 to 32.7 in high-sensitivity mode). In the normal mode of NeurOs monitoring, receiver operating characteristic analysis suggested a 2% cutoff point was most optimal from the baseline for detecting hyperoxia (sensitivity 73%; specificity 66%) and minus 1% (sensitivity 66%; specificity 67%) for detecting hypoxia. Whereas in the high-sensitivity mode, the optimal cutoff point was 3% from baseline for detecting hyperoxia (sensitivity 75%; specificity 68%), and minus 3% for detecting hypoxia (sensitivity 90%; specificity 45%).

CONCLUSIONS

In conclusion, the novel NeurOs system was found to correlate with INVOS cerebral oximetry measurements during cardiac surgery.

Diffuse optical assessment of cerebral-autoregulation in older adults stratified by cerebrovascular risk

Diagnosis of cerebrovascular disease (CVD) at early stages is essential for preventing sequential complications. CVD is often associated with abnormal cerebral microvasculature, which may impact cerebral-autoregulation (CA). A novel hybrid near-infrared diffuse optical instrument and a finger plethysmograph were used to simultaneously detect low-frequency oscillations (LFOs) of cerebral blood flow (CBF), oxy-hemoglobin concentration ([HbO₂ ]), deoxy-hemoglobin concentration ([Hb]) and mean arterial pressure (MAP) in older adults before, during and after 70° head-up-tilting (HUT). The participants with valid data were divided based on Framingham risk score (FRS, 1-30 points) into low-risk (FRS ≤15, n = 13) and high-risk (FRS >15, n = 11) groups for developing CVD. The LFO gains were determined by transfer function analyses with MAP as the input, and CBF, [HbO₂ ] and [Hb] as the outputs (CA ∝ 1/Gain). At resting-baseline, LFO gains in the high-risk group were relatively lower compared to the low-risk group. The lower baseline gains in the high-risk group may attribute to compensatory mechanisms to maintain stronger steady-state CAs. However, HUT resulted in smaller gain reductions in the high-risk group compared to the low-risk group, suggesting weaker dynamic CAs. LFO gains are potentially valuable biomarkers for early detection of CVD based on associations with CAs.

PV-MBLL algorithm for extraction of absolute tissue oxygenation information by diffuse optical spectroscopy

BACKGROUND AND OBJECTIVE

Tissue blood oxygenation contains critical information for biomedical studies and healthcare. The primary approach to extract the absolute value of tissue blood oxygenation (e.g., oxygen saturation) is spatial-resolved algorithm for near-infrared diffuse optical spectroscopy with continues-wave (CW) light, which require acquisition of the optical signals from multiple pairs of sources and detectors (S-D). This study reports the first attempt for absolute oxygenation measurement with single S-D pair of optical signals.

METHODS

A novel algorithm, namely, phantom-validation modified Beer-Lambert law (PV-MBLL), was created to fully utilize the optical signals from single S-D pair. This algorithm is combined with two-step phantom measurement to extract the absolute value of tissue oxygenation in CW system. The proposed PV-MBLL algorithm was compared with the conventional spatial-resolved algorithm on both step-varied liquid phantom and human experiment of cuff occlusion on arms. The one-way ANOVA analysis was performed to investigate the difference between the two algorithms.

RESULTS

By using the PV-MBLL algorithm, the reconstructed tissue absorption coefficient is highly accurate (not larger than 5.35% in error) over a wide range (0.02-0.20 cm^-1). By contrast, the spatial-resolved algorithm leads to much larger errors (up to 37.57% in error). Moreover, the responses of oxygen saturation to cuff occlusion differ significantly (p < 0.005) with the two algorithms.

CONCLUSIONS

The proposed PV-MBLL algorithm has promising potential for accurate acquisition of oxygenation information. Additionally, the single S-D pair greatly reduces the size of optical probe and instrument cost, thus it is highly appropriate for the tissues with small size and large curvature.

Methodological Approaches and Recommendations for Functional Near-Infrared Spectroscopy Applications in HF/E Research

OBJECTIVE

The objective of this study was to systematically document current methods and protocols employed when using functional near-infrared spectroscopy (fNIRS) techniques in human factors and ergonomics (HF/E) research and generate recommendations for conducting and reporting fNIRS findings in HF/E applications.

METHOD

A total of 1,687 articles were identified through Ovid-MEDLINE, PubMed, Web of Science, and Scopus databases, of which 37 articles were included in the review based on review inclusion/exclusion criteria.

RESULTS

A majority of the HF/E fNIRS investigations were found in transportation, both ground and aviation, and in assessing cognitive (e.g., workload, working memory) over physical constructs. There were large variations pertaining to data cleaning, processing, and analysis approaches across the studies that warrant standardization of methodological approaches. The review identified major challenges in transparency and reporting of important fNIRS data collection and analyses specifications that diminishes study replicability, introduces potential biases, and increases likelihood of inaccurate results. As such, results reported in existing fNIRS studies need to be cautiously approached.

CONCLUSION

To improve the quality of fNIRS investigations and/or to facilitate its adoption and integration in different HF/E applications, such as occupational ergonomics and rehabilitation, recommendations for fNIRS data collection, processing, analysis, and reporting are provided.

The Development of a Practical Artificial Intelligence Tool for Diagnosing and Evaluating Autism Spectrum Disorder: Multicenter Study

Background

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder with an unknown etiology. Early diagnosis and intervention are key to improving outcomes for patients with ASD. Structural magnetic resonance imaging (sMRI) has been widely used in clinics to facilitate the diagnosis of brain diseases such as brain tumors. However, sMRI is less frequently used to investigate neurological and psychiatric disorders, such as ASD, owing to the subtle, if any, anatomical changes of the brain.

Objective

This study aimed to investigate the possibility of identifying structural patterns in the brain of patients with ASD as potential biomarkers in the diagnosis and evaluation of ASD in clinics.

Methods

We developed a novel 2-level histogram-based morphometry (HBM) classification framework in which an algorithm based on a 3D version of the histogram of oriented gradients (HOG) was used to extract features from sMRI data. We applied this framework to distinguish patients with ASD from healthy controls using 4 datasets from the second edition of the Autism Brain Imaging Data Exchange, including the ETH Zürich (ETH), NYU Langone Medical Center: Sample 1, Oregon Health and Science University, and Stanford University (SU) sites. We used a stratified 10-fold cross-validation method to evaluate the model performance, and we applied the Naive Bayes approach to identify the predictive ASD-related brain regions based on classification contributions of each HOG feature.

Results

On the basis of the 3D HOG feature extraction method, our proposed HBM framework achieved an area under the curve (AUC) of >0.75 in each dataset, with the highest AUC of 0.849 in the ETH site. We compared the 3D HOG algorithm with the original 2D HOG algorithm, which showed an accuracy improvement of >4% in each dataset, with the highest improvement of 14% (6/42) in the SU site. A comparison of the 3D HOG algorithm with the scale-invariant feature transform algorithm showed an AUC improvement of >18% in each dataset. Furthermore, we identified ASD-related brain regions based on the sMRI images. Some of these regions (eg, frontal gyrus, temporal gyrus, cingulate gyrus, postcentral gyrus, precuneus, caudate, and hippocampus) are known to be implicated in ASD in prior neuroimaging literature. We also identified less well-known regions that may play unrecognized roles in ASD and be worth further investigation.

Conclusions

Our research suggested that it is possible to identify neuroimaging biomarkers that can distinguish patients with ASD from healthy controls based on the more cost-effective sMRI images of the brain. We also demonstrated the potential of applying data-driven artificial intelligence technology in the clinical setting of neurological and psychiatric disorders, which usually harbor subtle anatomical changes in the brain that are often invisible to the human eye.

Phase dual-slopes in frequency-domain near-infrared spectroscopy for enhanced sensitivity to brain tissue: First applications to human subjects

We present a first in vivo application of phase dual-slopes (DSϕ), measured with frequency-domain near-infrared spectroscopy on four healthy human subjects, to demonstrate their enhanced sensitivity to cerebral hemodynamics. During arterial blood pressure oscillations elicited at a frequency of 0.1 Hz, we compare three different ways to analyze either intensity (I) or phase (ϕ) data collected on the subject's forehead at multiple source-detector distances: Single-distance, single-slope and DS. Theoretical calculations based on diffusion theory show that the method with the deepest maximal sensitivity (at about 11 mm) is DSϕ. The in vivo results indicate a qualitative difference of phase data (especially DSϕ) and intensity data (especially single-distance intensity [SDI]), which we assign to stronger contributions from scalp hemodynamics to SDI and from cortical hemodynamics to DSϕ. Our findings suggest that scalp hemodynamic oscillations may be dominated by blood volume dynamics, whereas cortical hemodynamics may be dominated by blood flow velocity dynamics.

Cerebral Microcirculatory Blood Flow Dynamics During Rest and a Continuous Motor Task

Objectives: To examine the brain’s microcirculatory response over the course of a continuous 5-min elbow movement task in order to estimate its potential role in grading vaso-neural coupling compared to the macrocirculatory response.

Methods: We simultaneously recorded cerebral blood flow velocity (CBFV), changes in oxygenated/deoxygenated hemoglobin concentrations ([oxHb], [deoxHb]), blood pressure (BP), and end-tidal CO₂ over 5-min periods of rest and left elbow movements in 24 healthy persons (13 women and 11 men of mean age ± SD, 38 ± 11 years). A low frequency range (0.07–0.15 Hz) was used for analysis by transfer function estimates of phase and gain.

Results: Elbow movement led to a small BP increase (mean BP at rest 83 mm Hg, at movement 87; p < 0.01) and a small ETCO₂ decrease (at rest 44.6 mm Hg, at movement 41.7 mm Hg; p < 0.01). Further, it increased BP-[oxHb] phase from 55° (both sides) to 74° (right; p < 0.05)/69° (left; p < 0.05), and BP-[deoxHb] phase from 264° (right)/270° (left) to 288° (right; p < 0.05)/297° (left; p = 0.09). The cerebral mean transit time at 0.1 Hz of 5.6 s of rest remained unchanged by movement. Elbow movement significantly decreased BP-CBFV gain on both sides, and BP-CBFV phase only on the right side (p = 0.05).

Conclusion: Elbow movement leads to an increased time delay between BP and [oxHb]/[deoxHb] while leaving the cerebral mean transit time unchanged. Phase shifting is usually the more robust parameter when using a transfer function to estimate dynamic cerebral autoregulation; phase shifting at the microcirculatory level seems to be a better marker of VNC-induced changes than phase shifting between BP and CBFV.

Neural Efficiency of Human-Robotic Feedback Modalities Under Stress Differs With Gender

Sensory feedback, which can be presented in different modalities - single and combined, aids task performance in human-robotic interaction (HRI). However, combining feedback modalities does not always lead to optimal performance. Indeed, it is not known how feedback modalities affect operator performance under stress. Furthermore, there is limited information on how feedback affects neural processes differently for males and females and under stress. This is a critical gap in the literature, particularly in the domain of surgical robotics, where surgeons are under challenging socio-technical environments that burden them physiologically. In the present study, we posited operator performance as the summation of task performance and neurophysiological cost of maintaining that performance. In a within-subject design, we used functional near-infrared spectroscopy to assess cerebral activations of 12 participants who underwent a 3D manipulation task within a virtual environment with concurrent feedback (visual and visual + haptic) in the presence and absence of a cognitive stressor. Cognitive stress was induced with the serial-7 subtraction test. We found that while task performance was higher with visual than visual + haptic feedback, it degraded under stress. The two feedback modalities were found to be associated with varying neural activities and neural efficiencies, and these were stress- and gender-dependent. Our findings engender further investigation into effectiveness of feedback modalities on males and females under stressful conditions in HRI.

Portable Near-Infrared Technologies and Devices for Noninvasive Assessment of Tissue Hemodynamics

Tissue hemodynamics, including the blood flow, oxygenation, and oxygen metabolism, are closely associated with many diseases. As one of the portable optical technologies to explore human physiology and assist in healthcare, near-infrared diffuse optical spectroscopy (NIRS) for tissue oxygenation measurement has been developed for four decades. In recent years, a dynamic NIRS technology, namely, diffuse correlation spectroscopy (DCS), has been emerging as a portable tool for tissue blood flow measurement. In this article, we briefly describe the basic principle and algorithms for static NIRS and dynamic NIRS (i.e., DCS). Then, we elaborate on the NIRS instrumentation, either commercially available or custom-made, as well as their applications to physiological studies and clinic. The extension of NIRS/DCS from spectroscopy to imaging was depicted, followed by introductions of advanced algorithms that were recently proposed. The future prospective of the NIRS/DCS and their feasibilities for routine utilization in hospital is finally discussed.

A Wearable Fiberless Optical Sensor for Continuous Monitoring of Cerebral Blood Flow in Mice

Continuous and longitudinal monitoring of cerebral blood flow (CBF) in animal models provides information for studying the mechanisms and interventions of various cerebral diseases. Since anesthesia may affect brain hemodynamics, researchers have been seeking wearable devices for use in conscious animals. We present a wearable diffuse speckle contrast flowmeter (DSCF) probe for monitoring CBF variations in mice. The DSCF probe consists of a small low-power near-infrared laser diode as a point source and an ultra-small low-power CMOS camera as a 2D detector array, which can be affixed on a mouse head. The movement of red blood cells in brain cortex (i.e., CBF) produces spatial fluctuations of laser speckles, which are captured by the camera. The DSCF system was calibrated using tissue phantoms and validated in a human forearm and mouse brains for continuous monitoring of blood flow increases and decreases against the established technologies. Significant correlations were observed among these measurements (R² ≥ 0.80, p < 10^-5). This small fiberless probe has the potential to be worn by a freely moving conscious mouse. Moreover, the flexible source-detector configuration allows for varied probing depths up to ~8 mm, which is sufficient for transcranially detecting CBF in the cortices of rodents and newborn infants.

Depth dependence of coherent hemodynamics in the human head

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

The meaning of "coherent" and its quantification in coherent hemodynamics spectroscopy

We have recently introduced a new technique, coherent hemodynamics spectroscopy (CHS), which aims at characterizing a specific kind of tissue hemodynamics that feature a high level of covariation with a given physiological quantity. In this study, we carry out a detailed analysis of the significance of coherence and phase synchronization between oscillations of arterial blood pressure (ABP) and total hemoglobin concentration ([Hbt]), measured with near-infrared spectroscopy (NIRS) during a typical protocol for CHS, based on a cyclic thigh cuff occlusion and release. Even though CHS is based on a linear time invariant model between ABP (input) and NIRS measurands (outputs), for practical reasons in a typical CHS protocol, we induce finite "groups" of ABP oscillations, in which each group is characterized by a different frequency. For this reason, ABP (input) and NIRS measurands (output) are not stationary processes, and we have used wavelet coherence and phase synchronization index (PSI), as a metric of coherence and phase synchronization, respectively. PSI was calculated by using both the wavelet cross spectrum and the Hilbert transform. We have also used linear coherence (which requires stationary process) for comparison with wavelet coherence. The method of surrogate data is used to find critical values for the significance of covariation between ABP and [Hbt]. Because we have found similar critical values for wavelet coherence and PSI by using five of the most used methods of surrogate data, we propose to use the data-independent Gaussian random numbers (GRNs), for CHS. By using wavelet coherence and wavelet cross spectrum, and GRNs as surrogate data, we have found the same results for the significance of coherence and phase synchronization between ABP and [Hbt]: on a total set of 20 periods of cuff oscillations, we have found 17 coherent oscillations and 17 phase synchronous oscillations. Phase synchronization assessed with Hilbert transform yielded similar results with 14 phase synchronous oscillations. Linear coherence and wavelet coherence overall yielded similar number of significant values. We discuss possible reasons for this result. Despite the similarity of linear and wavelet coherence, we argue that wavelet coherence is preferable, especially if one wants to use baseline spontaneous oscillations, in which phase locking and coherence between signals might be only temporary.

Prolonged monitoring of cerebral blood flow and autoregulation with diffuse correlation spectroscopy in neurocritical care patients

Monitoring of cerebral blood flow (CBF) and autoregulation are essential components of neurocritical care, but continuous noninvasive methods for CBF monitoring are lacking. Diffuse correlation spectroscopy (DCS) is a noninvasive diffuse optical modality that measures a CBF index ( CBF i ) in the cortex microvasculature by monitoring the rapid fluctuations of near-infrared light diffusing through moving red blood cells. We tested the feasibility of monitoring CBF i with DCS in at-risk patients in the Neurosciences Intensive Care Unit. DCS data were acquired continuously for up to 20 h in six patients with aneurysmal subarachnoid hemorrhage, as permitted by clinical care. Mean arterial blood pressure was recorded synchronously, allowing us to derive autoregulation curves and to compute an autoregulation index. The autoregulation curves suggest disrupted cerebral autoregulation in most patients, with the severity of disruption and the limits of preserved autoregulation varying between subjects. Our findings suggest the potential of the DCS modality for noninvasive, long-term monitoring of cerebral perfusion, and autoregulation.

Lawrence K, Amendolia O, Quattrone F, Balu R, Kofke WA, Yodh AG. Noninvasive continuous optical monitoring of absolute cerebral blood flow in critically ill adults

We investigate a scheme for noninvasive continuous monitoring of absolute cerebral blood flow (CBF) in adult human patients based on a combination of time-resolved dynamic contrast-enhanced near-infrared spectroscopy (DCE-NIRS) and diffuse correlation spectroscopy (DCS) with semi-infinite head model of photon propogation. Continuous CBF is obtained via calibration of the DCS blood flow index (BFI) with absolute CBF obtained by intermittent intravenous injections of the optical contrast agent indocyanine green. A calibration coefficient ( γ ) for the CBF is thus determined, permitting conversion of DCS BFI to absolute blood flow units at all other times. A study of patients with acute brain injury ( N = 7 ) is carried out to ascertain the stability of γ . The patient-averaged DCS calibration coefficient across multiple monitoring days and multiple patients was determined, and good agreement between the two calibration coefficients measured at different times during single monitoring days was found. The patient-averaged calibration coefficient of 1.24 × 10 9    ( mL / 100    g / min ) / ( cm 2 / s ) was applied to previously measured DCS BFI from similar brain-injured patients; in this case, absolute CBF was underestimated compared with XeCT, an effect we show is primarily due to use of semi-infinite homogeneous models of the head.

Critical bounds on noise and SNR for robust estimation of real-time brain activity from functional near infra-red spectroscopy

The robust characterization of real-time brain activity carries potential for many applications. However, the contamination of measured signals by various instrumental, environmental, and physiological sources of noise introduces a substantial amount of signal variance and, consequently, challenges real-time estimation of contributions from underlying neuronal sources. Functional near infra-red spectroscopy (fNIRS) is an emerging imaging modality whose real-time potential is yet to be fully explored. The objectives of the current study are to (i) validate a time-dependent linear model of hemodynamic responses in fNIRS, and (ii) test the robustness of this approach against measurement noise (instrumental and physiological) and mis-specification of the hemodynamic response basis functions (amplitude, latency, and duration). We propose a linear hemodynamic model with time-varying parameters, which are estimated (adapted and tracked) using a dynamic recursive least square algorithm. Owing to the linear nature of the activation model, the problem of achieving robust convergence to an accurate estimation of the model parameters is recast as a problem of parameter error stability around the origin. We show that robust convergence of the proposed method is guaranteed in the presence of an acceptable degree of model misspecification and we derive an upper bound on noise under which reliable parameters can still be inferred. We also derived a lower bound on signal-to-noise-ratio over which the reliable parameters can still be inferred from a channel/voxel. Whilst here applied to fNIRS, the proposed methodology is applicable to other hemodynamic-based imaging technologies such as functional magnetic resonance imaging.

Assessing low-frequency oscillations in cerebrovascular diseases and related conditions with near-infrared spectroscopy: a plausible method for evaluating cerebral autoregulation?

BACKGROUND

Cerebral autoregulation (CA) is the brain's ability to always maintain an adequate and relatively constant blood supply, which is often impaired in cerebrovascular diseases. Near-infrared spectroscopy (NIRS) examines oxygenated hemoglobin (OxyHb) in the cerebral cortex. Low- and very low-frequency oscillations ( LFOs ≈ 0.1    Hz and VLFOs ≈ 0.05 to 0.01 Hz) in OxyHb have been proposed to reflect CA.

AIM

To systematically review published results on OxyHb LFOs and VLFOs in cerebrovascular diseases and related conditions measured with NIRS.

APPROACH

A systematic search was performed in the MEDLINE database, which generated 36 studies relevant for inclusion.

RESULTS

Healthy people have relatively stable LFOs. LFO amplitude seems to reflect myogenic CA being decreased by vasomotor paralysis in stroke, by smooth muscle damage or as compensatory action in other conditions but can also be influenced by the sympathetic tone. VLFO amplitude is believed to reflect neurogenic and metabolic CA and is lower in stroke, atherosclerosis, and with aging. Both LFO and VLFO synchronizations appear disturbed in stroke, while the former is also altered in internal carotid stenosis and hypertension.

CONCLUSION

We conclude that amplitudes of LFOs and VLFOs are relatively robust measures for evaluating mechanisms of CA and synchronization analyses can show temporal disruption of CA. Further research and more coherent methodologies are needed.

Alterations in the coupling functions between cerebral oxyhaemoglobin and arterial blood pressure signals in post-stroke subjects

Cerebral autoregulation (CA) is the complex homeostatic regulatory relationship between blood pressure (BP) and cerebral blood flow (CBF). This study aimed to analyze the frequency-specific coupling function between cerebral oxyhemoglobin concentrations (delta [HbO₂]) and mean arterial pressure (MAP) signals based on a model of coupled phase oscillators and dynamical Bayesian inference. Delta [HbO₂] was measured by 24-channel near-infrared spectroscopy (NIRS) and arterial BP signals were obtained by simultaneous resting-state measurements in patients with stroke, that is, 9 with left hemiparesis (L–H group), 8 with right hemiparesis (R–H group), and 17 age-matched healthy individuals as control (healthy group). The coupling functions from MAP to delta [HbO₂] oscillators were identified and analyzed in four frequency intervals (I, 0.6–2 Hz; II, 0.145–0.6 Hz; III, 0.052–0.145 Hz; and IV, 0.021–0.052 Hz). In L–H group, the CS from MAP to delta [HbO₂] in interval III in channel 8 was significantly higher than that in healthy group (p = 0.003). Compared with the healthy controls, the coupling in MAP→delta [HbO₂] showed higher amplitude in interval I and IV in patients with stroke. The increased CS and coupling amplitude may be an evidence of impairment in CA, thereby confirming the presence of impaired CA in patients with stroke. In interval III, the CS in L–H group from MAP to delta [HbO₂] in channel 16 (p = 0.001) was significantly lower than that in healthy controls, which might indicate the compensatory mechanism in CA of the unaffected side in patients with stroke. No significant difference in region-wise CS between affected and unaffected sides was observed in stroke groups, indicating an evidence of globally impaired CA. These findings provide a method for the assessment of CA and will contribute to the development of therapeutic interventions in stroke patients.

Frequency-specific Effective Connectivity in Subjects with Cerebral Infarction as Revealed by NIRS Method

A connectivity-based approach can highlight the network reorganization in the chronic phases after stroke and contributes to the development of therapeutic interventions. Using dynamic Bayesian inference, this study aimed to assess the effective connectivity (EC) in various frequency bands through the near-infrared spectroscopy (NIRS) method in subjects with cerebral infarction (CI). A phase-coupling model was established based on phase information extracted using the wavelet transform of NIRS signals. Coupling strength and the main coupling direction were estimated using dynamic Bayesian inference. Wilcoxon test and chi-square test were used to determine the significant difference in EC between two groups. Results showed that the coupling strength of the EC in the CI group significantly decreased relative to that in the healthy group. The decrease was most significant in the frequency intervals IV (0.021 Hz-0.052 Hz; p = 0.0006) and VI (0.005 Hz-0.095 Hz; p = 0.0028). The main coupling direction changed from the right prefrontal cortex to the right motor cortex and left motor cortex in the frequency intervals IV (p₁ = 0.041, p₂ = 0.047) and II (p₁ = 0.0017, p₂ = 0.0036), respectively. The EC decreased or was even lost significantly in the EC map of the CI group. Experimental results indicated that information propagation was blocked in the CI group than in the healthy group and resulted in the decreased coupling strength and connectivity loss. The main coupling direction of the motor section changed from driving into being driven because of the degradation of limb movement function.

An effective model of cerebrovascular pressure reactivity and blood flow autoregulation

Understanding cerebral blood flow dynamics is crucial for the care of patients at risk of poor cerebral perfusion. We describe an effective model of cerebral hemodynamics designed to reveal important macroscopic features of cerebral blood flow without having to resolve the detailed microvasculature of the brain. Based on principles of fluid and elastic dynamics and vascular pressure-reactivity, the model quantifies the physical means by which the vasculature executes autoregulatory reflexes. We demonstrate that the frequency response of the proposed model matches experimental measurements and explains the influence of mechanical factors on the autoregulatory performance. Analysis of the model indicates the existence of an optimal mean arterial pressure which minimizes the sensitivity of the flow to changes in perfusion pressure across the frequency spectrum of physiological oscillations. We highlight the simplicity of the model and its potential to improve monitoring of brain perfusion via real-time computational simulations of cerebro- and cardio-vascular interventions.

Noninvasive optical monitoring of critical closing pressure and arteriole compliance in human subjects

The critical closing pressure ( CrCP) of the cerebral circulation depends on both tissue intracranial pressure and vasomotor tone. CrCP defines the arterial blood pressure ( ABP) at which cerebral blood flow approaches zero, and their difference ( ABP -  CrCP) is an accurate estimate of cerebral perfusion pressure. Here we demonstrate a novel non-invasive technique for continuous monitoring of CrCP at the bedside. The methodology combines optical diffuse correlation spectroscopy (DCS) measurements of pulsatile cerebral blood flow in arterioles with concurrent ABP data during the cardiac cycle. Together, the two waveforms permit calculation of CrCP via the two-compartment Windkessel model for flow in the cerebral arterioles. Measurements of CrCP by optics (DCS) and transcranial Doppler ultrasound (TCD) were carried out in 18 healthy adults; they demonstrated good agreement (R = 0.66, slope = 1.14 ± 0.23) with means of 11.1 ± 5.0 and 13.0 ± 7.5 mmHg, respectively. Additionally, a potentially useful and rarely measured arteriole compliance parameter was derived from the phase difference between ABP and DCS arteriole blood flow waveforms. The measurements provide evidence that DCS signals originate predominantly from arteriole blood flow and are well suited for long-term continuous monitoring of CrCP and assessment of arteriole compliance in the clinic.

Mapping breast cancer blood flow index, composition, and metabolism in a human subject using combined diffuse optical spectroscopic imaging and diffuse correlation spectroscopy

Diffuse optical spectroscopic imaging (DOSI) and diffuse correlation spectroscopy (DCS) are model-based near-infrared (NIR) methods that measure tissue optical properties (broadband absorption, ? a , and reduced scattering, ? s ? ) and blood flow (blood flow index, BFI), respectively. DOSI-derived ? a values are used to determine composition by calculating the tissue concentration of oxy- and deoxyhemoglobin ( HbO 2 , HbR), water, and lipid. We developed and evaluated a combined, coregistered DOSI/DCS handheld probe for mapping and imaging these parameters. We show that uncertainties of 0.3 ?? mm ? 1 (37%) in ? s ? and 0.003 ?? mm ? 1 (33%) in ? a lead to ? 53 % and 9% errors in BFI, respectively. DOSI/DCS imaging of a solid tissue-simulating flow phantom and

Clinical applications of near-infrared diffuse correlation spectroscopy and tomography for tissue blood flow monitoring and imaging

OBJECTIVE

Blood flow is one such available observable promoting a wealth of physiological insight both individually and in combination with other metrics.

APPROACH

Near-infrared diffuse correlation spectroscopy (DCS) and, to a lesser extent, diffuse correlation tomography (DCT), have increasingly received interest over the past decade as noninvasive methods for tissue blood flow measurements and imaging. DCS/DCT offers several attractive features for tissue blood flow measurements/imaging such as noninvasiveness, portability, high temporal resolution, and relatively large penetration depth (up to several centimeters).

MAIN RESULTS

This review first introduces the basic principle and instrumentation of DCS/DCT, followed by presenting clinical application examples of DCS/DCT for the diagnosis and therapeutic monitoring of diseases in a variety of organs/tissues including brain, skeletal muscle, and tumor.

SIGNIFICANCE

Clinical study results demonstrate technical versatility of DCS/DCT in providing important information for disease diagnosis and intervention monitoring.

Functional connectivity analysis using fNIRS in healthy subjects during prolonged simulated driving

Noninvasive and accurate assessment of driving fatigue in relation to brain activity during long-term driving can contribute to traffic safety and accident prevention. This study evaluated functional connectivity (FC) in relevant brain regions. Synergistic mechanisms in different brain regions were detected by a novel simulator, which combined semi-immersive virtual reality technology and functional near-infrared spectroscopy. Each subject was instructed to complete driving tasks coupled with a mental calculation task. Wavelet coherence (WCO) and wavelet phase coherence (WPCO) were calculated and assessed in frequency intervals (I) 0.6-2 and (II) 0.145-0.6Hz as global connectivity measures; (III) 0.052-0.145, (IV) 0.021-0.052, (V) 0.0095-0.021 and (VI) 0.005-0.0095Hz as FC. WCO and WPCO revealed the strength and synchronization of cerebral connectivity, respectively. Significantly low WCO levels were found in intervals I and III in prefrontal cortex (PFC) and IV in motor cortex (MC) at the end of the driving task. Furthermore, significantly low WPCO were found in intervals I, and III in PFC and interval IV in MC. Experimental findings suggested that progressive mental fatigue adversely influences the cognitive function in the PFC and the cooperative mechanism between the PFC and MC.

Pulsation-limited oxygen diffusion in the tumour microenvironment

Hypoxia is central to tumour evolution, growth, invasion and metastasis. Mathematical models of hypoxia based on reaction-diffusion equations provide seemingly incomplete descriptions as they fail to predict the measured oxygen concentrations in the tumour microenvironment. In an attempt to explain the discrepancies, we consider both the inhomogeneous distribution of oxygen-consuming cells in solid tumours and the dynamics of blood flow in the tumour microcirculation. We find that the low-frequency oscillations play an important role in the establishment of tumour hypoxia. The oscillations interact with consumption to inhibit oxygen diffusion in the microenvironment. This suggests that alpha-blockers-a class of drugs used to treat hypertension and stress disorders, and known to lower or even abolish low-frequency oscillations of arterial blood flow -may act as adjuvant drugs in the radiotherapy of solid tumours by enhancing the oxygen effect.

Vasovagal Syncope: Hypothesis Focusing on Its Being a Clinical Feature Unique to Humans

Humans live primarily in the upright position; as a result, there is a constant struggle between gravity and needed supply of blood flow to the brain. In certain circumstances brain blood supply may become temporarily insufficient, resulting in syncope. Among the numerous causes of syncope in humans, vasovagal syncope (VVS) is by far the most common. However, despite intensive research, many aspects of the pathophysiology of VVS remain unknown; among these, one of the least well understood is the basis for why VVS is restricted, among vertebrates, to Homo sapiens. In this manuscript we review proposals that have been offered in an attempt to address the issue of the origin of VVS and, although highly speculative, we suggest a new hypothesis (the "brain theory") to try to address the question of why humans, to the exclusion of other species, remain susceptible to VVS. This theory suggests that VVS evolved to offer protection to the brain's functional integrity under certain conditions of severe threat. Although seemingly a disadvantageous evolutionary adaptation, the faint causes the body to take on a gravitationally neutral position, and thereby provides a better chance of restoring brain blood supply and preserving long-term brain function.

Fast blood flow monitoring in deep tissues with real-time software correlators

We introduce, validate and demonstrate a new software correlator for high-speed measurement of blood flow in deep tissues based on diffuse correlation spectroscopy (DCS). The software correlator scheme employs standard PC-based data acquisition boards to measure temporal intensity autocorrelation functions continuously at 50 - 100 Hz, the fastest blood flow measurements reported with DCS to date. The data streams, obtained in vivo for typical source-detector separations of 2.5 cm, easily resolve pulsatile heart-beat fluctuations in blood flow which were previously considered to be noise. We employ the device to separate tissue blood flow from tissue absorption/scattering dynamics and thereby show that the origin of the pulsatile DCS signal is primarily flow, and we monitor cerebral autoregulation dynamics in healthy volunteers more accurately than with traditional instrumentation as a result of increased data acquisition rates. Finally, we characterize measurement signal-to-noise ratio and identify count rate and averaging parameters needed for optimal performance.

Tutorial on platform for optical topography analysis tools

Optical topography/functional near-infrared spectroscopy (OT/fNIRS) is a functional imaging technique that noninvasively measures cerebral hemoglobin concentration changes caused by neural activities. The fNIRS method has been extensively implemented to understand the brain activity in many applications, such as neurodisorder diagnosis and treatment, cognitive psychology, and psychiatric status evaluation. To assist users in analyzing fNIRS data with various application purposes, we developed a software called platform for optical topography analysis tools (POTATo). We explain how to handle and analyze fNIRS data in the POTATo package and systematically describe domain preparation, temporal preprocessing, functional signal extraction, statistical analysis, and data/result visualization for a practical example of working memory tasks. This example is expected to give clear insight in analyzing data using POTATo. The results specifically show the activated dorsolateral prefrontal cortex is consistent with previous studies. This emphasizes analysis robustness, which is required for validating decent preprocessing and functional signal interpretation. POTATo also provides a self-developed plug-in feature allowing users to create their own functions and incorporate them with established POTATo functions. With this feature, we continuously encourage users to improve fNIRS analysis methods. We also address the complications and resolving opportunities in signal analysis.

Frequency-specific functional connectivity revealed by wavelet-based coherence analysis in elderly subjects with cerebral infarction using NIRS method

PURPOSE

Resting-state functional connectivity in subjects with cerebral infarction (CI) was assessed using wavelet-based coherence analysis of near-infrared spectroscopy (NIRS) signals.

METHODS

Continuous recordings of NIRS signals were measured from the prefrontal cortex and sensorimotor cortical areas of 12 subjects with CI (CI group) and 16 healthy subjects (healthy group) during the resting state. The channels in these areas were divided into four connection types: homologous connectivity, frontoposterior connectivity, contralateral connectivity, and homolateral connectivity. Wavelet coherence (WCO) and wavelet phase coherence (WPCO) were calculated in six frequency intervals in each channel pair: I, 0.6-2 Hz; II, 0.145-0.6 Hz; III, 0.052-0.145 Hz; IV, 0.021-0.052 Hz; V, 0.0095-0.021 Hz; and VI, 0.005-0.0095 Hz.

RESULTS

WCO in the six frequency intervals was significant for all channels in the healthy group. By contrast, WCO in frequency intervals II-VI showed weakened connectivity in the CI group, especially in terms of frontoposterior connectivity. WCO was significantly lower in the CI group than in the healthy group in the following connectivities and frequency intervals: front-posterior, IV-VI (p < 0.05); homologous, III-V (p < 0.01); motor-contralateral, III-V (p < 0.05); and motor-homolateral, III-V (p < 0.05). WPCO in frequency intervals III (F = 5.032, p = 0.033) and IV (F = 11.95, p = 0.002) in frontoposterior connectivity, as well as in intervals III-V in homologous, motor-contralateral and motor-homolateral connectivities were significantly lower (p < 0.05) in the CI group than in the healthy group. However, WPCO in interval I showed significantly higher levels in motor-homolateral connectivity in the CI group than in the healthy group (F = 4.241, p = 0.049).

CONCLUSIONS

The authors' results suggest that CI causes a frequency-specific disruption in resting-state connectivity. This may be useful for assessing the effectiveness of functional recovery after CI.

Phase synchronization analysis of prefrontal tissue oxyhemoglobin oscillations in elderly subjects with cerebral infarction

PURPOSE

This study aims to assess the phase relationship of prefrontal tissue oxyhemoglobin oscillations using wavelet phase coherence analysis of cerebral Delta [HbO₂] signals in cerebral infarction (CI) patients during the resting state.

METHODS

Continuous recordings of near-infrared spectroscopy signals were obtained from the left and right prefrontal lobes in 21 subjects with CI (Group CI, age: 76.6 ± 8.5 yr) and 21 healthy elderly subjects (Group Healthy, age: 69.0 ± 7.4 yr) during the resting state. The Group CI was further divide into two groups: CI with hypertension and CI without hypertension. The phase synchronization between left and right prefrontal Delta [HbO₂] oscillations in four frequency intervals (I, 0.6-2 Hz; II, 0.145-0.6 Hz; III, 0.052-0.145 Hz; and IV, 0.021-0.052 Hz) was analyzed using wavelet phase coherence method.

RESULTS

The phase coherences in intervals III and IV were significantly lower in CI with hypertension than in healthy elderly subjects (F = 12.974, p = 0.001 for III and F = 10.073, p = 0.004 for interval IV). The phase coherence of CI without hypertension in interval III was significantly lower than in healthy elderly subjects (F = 9.909, p = 0.004). Also, the phase coherence in interval IV was significantly lower in CI with hypertension than in CI without hypertension (F = 5.665, p = 0.028). Also, the phase agreement in interval IV showed evident difference between Group CI with hypertension and without hypertension.

CONCLUSIONS

The difference in phase characteristics of prefrontal tissue oxyhemoglobin oscillations between the CI patients and healthy elderly indicates altered phase synchronization. Moreover, the CI combined with hypertension would aggravate this process. This study provides new insight into the phase dynamics of cerebral oxygenation and may be useful in assessing the risk for stroke.