Impaired cerebrovascular reactivity after acute traumatic brain injury can be detected by wavelet phase coherence analysis of the intracranial and arterial blood pressure signals

Time-Series Modeling and Forecasting of Cerebral Pressure-Flow Physiology: A Scoping Systematic Review of the Human and Animal Literature

The modeling and forecasting of cerebral pressure-flow dynamics in the time-frequency domain have promising implications for veterinary and human life sciences research, enhancing clinical care by predicting cerebral blood flow (CBF)/perfusion, nutrient delivery, and intracranial pressure (ICP)/compliance behavior in advance. Despite its potential, the literature lacks coherence regarding the optimal model type, structure, data streams, and performance. This systematic scoping review comprehensively examines the current landscape of cerebral physiological time-series modeling and forecasting. It focuses on temporally resolved cerebral pressure-flow and oxygen delivery data streams obtained from invasive/non-invasive cerebral sensors. A thorough search of databases identified 88 studies for evaluation, covering diverse cerebral physiologic signals from healthy volunteers, patients with various conditions, and animal subjects. Methodologies range from traditional statistical time-series analysis to innovative machine learning algorithms. A total of 30 studies in healthy cohorts and 23 studies in patient cohorts with traumatic brain injury (TBI) concentrated on modeling CBFv and predicting ICP, respectively. Animal studies exclusively analyzed CBF/CBFv. Of the 88 studies, 65 predominantly used traditional statistical time-series analysis, with transfer function analysis (TFA), wavelet analysis, and autoregressive (AR) models being prominent. Among machine learning algorithms, support vector machine (SVM) was widely utilized, and decision trees showed promise, especially in ICP prediction. Nonlinear models and multi-input models were prevalent, emphasizing the significance of multivariate modeling and forecasting. This review clarifies knowledge gaps and sets the stage for future research to advance cerebral physiologic signal analysis, benefiting neurocritical care applications.

Evaluation of Morlet Wavelet Analysis for Artifact Detection in Low-Frequency Commercial Near-Infrared Spectroscopy Systems

Regional cerebral oxygen saturation (rSO2), a method of cerebral tissue oxygenation measurement, is recorded using non-invasive near-infrared Spectroscopy (NIRS) devices. A major limitation is that recorded signals often contain artifacts. Manually removing these artifacts is both resource and time consuming. The objective was to evaluate the applicability of using wavelet analysis as an automated method for simple signal loss artifact clearance of rSO2 signals obtained from commercially available devices. A retrospective observational study using existing populations (healthy control (HC), elective spinal surgery patients (SP), and traumatic brain injury patients (TBI)) was conducted. Arterial blood pressure (ABP) and rSO2 data were collected in all patients. Wavelet analysis was determined to be successful in removing simple signal loss artifacts using wavelet coefficients and coherence to detect signal loss artifacts in rSO2 signals. The removal success rates in HC, SP, and TBI populations were 100%, 99.8%, and 99.7%, respectively (though it had limited precision in determining the exact point in time). Thus, wavelet analysis may prove to be useful in a layered approach NIRS signal artifact tool utilizing higher-frequency data; however, future work is needed.

Identification of moyamoya disease based on cerebral oxygen saturation signals using machine learning methods

Moyamoya is a cerebrovascular disease with a high mortality rate. Early detection and mechanistic studies are necessary. Near-infrared spectroscopy (NIRS) was used to study the signals of the cerebral tissue oxygen saturation index (TOI) and the changes in oxygenated and deoxygenated hemoglobin concentrations (HbO and Hb) in 64 patients with moyamoya disease and 64 healthy volunteers. The wavelet transforms (WT) of TOI, HbO and Hb signals, as well as the wavelet phase coherence (WPCO) of these signals from the left and right frontal lobes of the same subject, were calculated. Features were extracted from the spontaneous oscillations of TOI, HbO and Hb in five physiological activity-related frequency segments. Machine learning models based on support vector machine (SVM), random forest (RF) and extreme gradient boosting (XGBoost) have been built to classify the two groups. For 20-min signals, the 10-fold cross-validation accuracies of SVM, RF and XGBoost were 87%, 85% and 85%, respectively. For 5-min signals, the accuracies of the three methods were 88%, 88% and 84%, respectively. The method proposed in this article has potential for detecting and screening moyamoya with high proficiency. Evaluating the cerebral oxygenation with NIRS shows great potential in screening moyamoya diseases.

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.

Morphological changes of intracranial pressure quantifies vasodilatory effect of verapamil to treat cerebral vasospasm

INTRODUCTION

After aneurysmal subarachnoid hemorrhage (SAH), both proximal and distal cerebral vasospasm can contribute to the development of delayed cerebral ischemia. Intra-arterial (IA) vasodilators are a mainstay of treatment for distal arterial vasospasm, but no methods of assessing the efficacy of interventions in real time have been established.

OBJECTIVE

To introduce a new method for continuous intraprocedural assessment of endovascular treatment for cerebral vasospasm.

METHODS

The premise of our approach was that distal cerebral arterial changes induce a consistent pattern in the morphological changes of intracranial pressure (ICP) pulse. This premise was demonstrated using a published algorithm in previous papers. In this study, we applied the algorithm to calculate the likelihood of cerebral vasodilation (VDI) and cerebral vasoconstriction (VCI) from intraprocedural ICP signals that are synchronized with injection of the IA vasodilator, verapamil. Cerebral blood flow velocities (CBFVs) on bilateral cerebral arteries were studied before and after IA therapy.

RESULTS

192 recordings of patients with SAH were reviewed, and 27 recordings had high-quality ICP waveforms. The VCI was significantly lower after the first verapamil injection (0.47±0.017) than VCI at baseline (0.49±0.020, p<0.001). A larger dose of injected verapamil resulted in a larger and longer VDI increase. CBFV of the middle cerebral artery increases across the days before the injection of verapamil and decreases after IA therapy.

CONCLUSION

This study provides preliminary validation of an algorithm for continuous assessment of distal cerebral arterial changes in response to IA vasodilator infusion in patients with vasospasm and aneurysmal SAH.

Cerebral Vascular Changes During Acute Intracranial Pressure Drop

OBJECTIVE

This study applied a new external ventricular catheter, which allows intracranial pressure (ICP) monitoring and cerebral spinal fluid (CSF) drainage simultaneously, to study cerebral vascular responses during acute CSF drainage.

METHODS

Six patients with 34 external ventricular drain (EVD) opening sessions were retrospectively analyzed. A published algorithm was used to extract morphological features of ICP recordings, and a template-matching algorithm was applied to calculate the likelihood of cerebral vasodilation index (VDI) and cerebral vasoconstriction index (VCI) based on the changes of ICP waveforms during CSF drainage. Power change (∆P) of ICP B-waves after EVD opening was also calculated. Cerebral autoregulation (CA) was assessed through phase difference between arterial blood pressure (ABP) and ICP using a previously published wavelet-based algorithm.

RESULTS

The result showed that acute CSF drainage reduced mean ICP (P = 0.016) increased VCI (P = 0.02) and reduced ICP B-wave power (P = 0.016) significantly. VCI reacted to ICP changes negatively when ICP was between 10 and 25 mmHg, and VCI remained unchanged when ICP was outside the 10-25 mmHg range. VCI negatively (r = - 0.44) and VDI positively (r = 0.82) correlated with ∆P of ICP B-waves, indicating that stronger vasoconstriction resulted in bigger power drop in ICP B-waves. Better CA prior to EVD opening triggered bigger drop in the power of ICP B-waves (r = - 0.612).

CONCLUSIONS

This study demonstrates that acute CSF drainage reduces mean ICP, and results in vasoconstriction which can be detected through an index, VCI. Cerebral vessels actively respond to ICP changes or cerebral perfusion pressure (CPP) changes in a certain range; beyond which, the vessels are insensitive to the changes in ICP and CPP.

Continuous monitoring of cerebrovascular reactivity through pulse transit time and intracranial pressure

OBJECTIVE

Cerebrovascular reactivity (CR) is a mechanism that maintains stable blood flow supply to the brain. Pressure reactivity index (PRx), the correlation coefficient between slow waves of invasive arterial blood pressure (ABP) and intracranial pressure (ICP) has been validated for CR assessment. However, in clinical ward, not every subarachnoid hemorrhage (SAH) patient has invasive ABP monitoring. Pulse transit time (PTT), the propagation time of a pulse wave travelling from the heart to peripheral arteries, has been suggested as a surrogate measure of ABP. In this study, we proposed to use PTT instead of invasive ABP to monitor CR.

APPROACH

Forty-five SAH patients with simultaneous recordings of invasive ABP, ICP, oxygen saturation level (SpO2) and electrocardiograph (ECG) were included. PTT was calculated as the time from the ECG R-wave peak to the onset of SpO2. PTT based pressure reactivity index (tPRx) was calculated as the correlation coefficient between slow waves of PTT and ICP. Wavelet tPRx (wtRx) was calculated as the cosine of wavelet phase shift between PTT and ICP. Meanwhile, PRx and wPRx were also calculated using invasive ABP and ICP as input.

MAIN RESULTS

The result showed a negative relationship between PTT and ABP (r  =  -0.58, p   <  0.001). tPRx negatively correlated with PRx (r  =  -0.51, p   =  0.003). Wavelet method correlated well with correlation method demonstrated through positive relationship between wPRx and PRx (r  =  0.82, p   <  0.001) as well as wtPRx and tPRx (r  =  0.84, p   <  0.001).

SIGNIFICANCE

PTT demonstrates great potential as a useful tool for CR assessment when invasive ABP is unavailable. Key points • Pulse transit time (PTT), defined as the propagation time of a pulse wave travelling from the heart to the peripheral arteries, has been proposed as a surrogate measure of ABP. The relationship between PTT and ABP in SAH patients remains unknown. • Cerebrovascular reactivity (CR) assessment through PTT has advantages over invasive ABP, as it avoids bleeding and infection risk, and can be used outside of the ICU. • We introduced a new method to assess CR using PTT and ICP through correlation based method and wavelet based method. • We found that beat-to-beat PTT was negatively related with invasive ABP in SAH patients. A significant linear relationship exists between PTT-based CR parameter and a well validated method, PRx. PTT demonstrates great potential as a useful tool for CR assessment when invasive ABP is unavailable in SAH patients.

Pressure passivity of cerebral mitochondrial metabolism is associated with poor outcome following perinatal hypoxic ischemic brain injury

Hypoxic ischemic encephalopathy (HIE) leads to significant morbidity and mortality. Impaired autoregulation after hypoxia-ischaemia has been suggested to contribute further to injury. Thalamic lactate/N-Acetylasperate (Lac/NAA) peak area ratio of > 0.3 on proton (¹H) magnetic resonance spectroscopy (MRS) is associated with poor neurodevelopment outcome following HIE. Cytochrome-c-oxidase (CCO) plays a central role in mitochondrial oxidative metabolism and ATP synthesis. Using a novel broadband NIRS system, we investigated the impact of pressure passivity of cerebral metabolism (CCO), oxygenation (haemoglobin difference (HbD)) and cerebral blood volume (total haemoglobin (HbT)) in 23 term infants following HIE during therapeutic hypothermia (HT). Sixty-minute epochs of data from each infant were studied using wavelet analysis at a mean age of 48 h. Wavelet semblance (a measure of phase difference) was calculated to compare reactivity between mean arterial blood pressure (MABP) with oxCCO, HbD and HbT. OxCCO-MABP semblance correlated with thalamic Lac/NAA ( r = 0.48, p = 0.02). OxCCO-MABP semblance also differed between groups of infants with mild to moderate and severe injury measured using brain MRI score ( p = 0.04), thalamic Lac/NAA ( p = 0.04) and neurodevelopmental outcome at one year ( p = 0.04). Pressure passive changes in cerebral metabolism were associated with injury severity indicated by thalamic Lac/NAA, MRI scores and neurodevelopmental assessment at one year of age.

Wavelet pressure reactivity index: a validation study

KEY POINTS

The brain is vulnerable to damage from too little or too much blood flow. A physiological mechanism termed cerebral autoregulation (CA) exists to maintain stable blood flow even if cerebral perfusion pressure (CPP) is changing. A robust method for assessing CA is not yet available. There are still some problems with the traditional measure, the pressure reactivity index (PRx). We introduce a new method, the wavelet transform method (wPRx), to assess CA using data from two sets of controlled hypotension experiments in piglets: one set had artificially manipulated arterial blood pressure (ABP) oscillations; the other group were spontaneous ABP waves. A significant linear relationship was found between wPRx and PRx in both groups, with wPRx providing a more stable result for the spontaneous waves. Although both methods showed similar accuracy in distinguishing intact and impaired CA, it seems that wPRx tends to perform better than PRx, although not significantly so.

ABSTRACT

We present a novel method to monitor cerebral autoregulation (CA) using the wavelet transform (WT). The new method is validated against the pressure reactivity index (PRx) in two piglet experiments with controlled hypotension. The first experiment (n = 12) had controlled haemorrhage with artificial stationary arterial blood pressure (ABP) and intracranial pressure (ICP) oscillations induced by sinusoidal slow changes in positive end-expiratory pressure ('PEEP group'). The second experiment (n = 17) had venous balloon inflation during spontaneous, non-stationary ABP and ICP oscillations ('non-PEEP group'). The wavelet transform phase shift (WTP) between ABP and ICP was calculated in the frequency range 0.0067-0.05 Hz. Wavelet semblance, the cosine of WTP, was used to make the values comparable to PRx, and the new index was termed wavelet pressure reactivity index (wPRx). The traditional PRx, the running correlation coefficient between ABP and ICP, was calculated. The result showed a significant linear relationship between wPRx and PRx in the PEEP group (R = 0.88) and non-PEEP group (R = 0.56). In the non-PEEP group, wPRx showed better performance than PRx in distinguishing cerebral perfusion pressure (CPP) above and below the lower limit of autoregulation (LLA). When CPP was decreased below LLA, wPRx increased from 0.43 ± 0.28 to 0.69 ± 0.12 (P = 0.003) while PRx increased from 0.07 ± 0.21 to 0.27 ± 0.37 (P = 0.04). Moreover, wPRx provided a more stable result than PRx (SD of PRx was 0.40 ± 0.07, and SD of wPRx was 0.28 ± 0.11, P = 0.001). Assessment of CA using wavelet-derived phase shift between ABP and ICP is feasible.

Dynamic cerebral autoregulation is preserved during isometric handgrip and head-down tilt in healthy volunteers

In healthy humans, cerebral blood flow (CBF) is autoregulated against changes in arterial blood pressure. Spontaneous fluctuations in mean arterial pressure (MAP) and CBF can be used to assess cerebral autoregulation. We hypothesized that dynamic cerebral autoregulation is affected by changes in autonomic activity, MAP, and cardiac output (CO) induced by handgrip (HG), head‐down tilt (HDT), and their combination. In thirteen healthy volunteers, we recorded blood velocity by ultrasound in the internal carotid artery (ICA), HR, MAP and CO‐estimates from continuous finger blood pressure, and end‐tidal CO₂. Instantaneous ICA beat volume (ICABV, mL) and ICA blood flow (ICABF, mL/min) were calculated. Wavelet synchronization index γ (0–1) was calculated for the pairs: MAP–ICABF, CO–ICABF and HR–ICABV in the low (0.05–0.15 Hz; LF) and high (0.15–0.4 Hz; HF) frequency bands. ICABF did not change between experimental states. MAP and CO were increased during HG (+16% and +15%, respectively, P < 0.001) and during HDT + HG (+12% and +23%, respectively, P < 0.001). In the LF interval, median γ for the MAP–ICABF pair (baseline: 0.23 [0.12–0.28]) and the CO–ICABF pair (baseline: 0.22 [0.15–0.28]) did not change with HG, HDT, or their combination. High γ was observed for the HR–ICABV pair at the respiratory frequency, the oscillations in these variables being in inverse phase. The unaltered ICABF and the low synchronization between MAP and ICABF in the LF interval suggest intact dynamic cerebral autoregulation during HG, HDT, and their combination.

Cerebrovascular pressure reactivity monitoring using wavelet analysis in traumatic brain injury patients: A retrospective study

BACKGROUND

After traumatic brain injury (TBI), the ability of cerebral vessels to appropriately react to changes in arterial blood pressure (pressure reactivity) is impaired, leaving patients vulnerable to cerebral hypo- or hyperperfusion. Although, the traditional pressure reactivity index (PRx) has demonstrated that impaired pressure reactivity is associated with poor patient outcome, PRx is sometimes erratic and may not be reliable in various clinical circumstances. Here, we introduce a more robust transform-based wavelet pressure reactivity index (wPRx) and compare its performance with the widely used traditional PRx across 3 areas: its stability and reliability in time, its ability to give an optimal cerebral perfusion pressure (CPPopt) recommendation, and its relationship with patient outcome.

METHODS AND FINDINGS

Five hundred and fifteen patients with TBI admitted in Addenbrooke's Hospital, United Kingdom (March 23rd, 2003 through December 9th, 2014), with continuous monitoring of arterial blood pressure (ABP) and intracranial pressure (ICP), were retrospectively analyzed to calculate the traditional PRx and a novel wavelet transform-based wPRx. wPRx was calculated by taking the cosine of the wavelet transform phase-shift between ABP and ICP. A time trend of CPPopt was calculated using an automated curve-fitting method that determined the cerebral perfusion pressure (CPP) at which the pressure reactivity (PRx or wPRx) was most efficient (CPPopt_PRx and CPPopt_wPRx, respectively). There was a significantly positive relationship between PRx and wPRx (r = 0.73), and wavelet wPRx was more reliable in time (ratio of between-hour variance to total variance, wPRx 0.957 ± 0.0032 versus PRx and 0.949 ± 0.047 for PRx, p = 0.002). The 2-hour interval standard deviation of wPRx (0.19 ± 0.07) was smaller than that of PRx (0.30 ± 0.13, p < 0.001). wPRx performed better in distinguishing between mortality and survival (the area under the receiver operating characteristic [ROC] curve [AUROC] for wPRx was 0.73 versus 0.66 for PRx, p = 0.003). The mean difference between the patients' CPP and their CPPopt was related to outcome for both calculation methods. There was a good relationship between the 2 CPPopts (r = 0.814, p < 0.001). CPPopt_wPRx was more stable than CPPopt_PRx (within patient standard deviation 7.05 ± 3.78 versus 8.45 ± 2.90; p < 0.001). Key limitations include that this study is a retrospective analysis and only compared wPRx with PRx in the cohort of patients with TBI. Prior prospective validation is required to better assess clinical utility of this approach.

CONCLUSIONS

wPRx offers several advantages to the traditional PRx: it is more stable in time, it yields a more consistent CPPopt recommendation, and, importantly, it has a stronger relationship with patient outcome. The clinical utility of wPRx should be explored in prospective studies of critically injured neurological patients.

Searching for a truly "iso-metabolic" gas challenge in physiological MRI

Hypercapnia challenge (e.g. inhalation of CO2) has been used in calibrated fMRI as well as in the mapping of vascular reactivity in cerebrovascular diseases. An important assumption underlying these measurements is that CO2 is a pure vascular challenge but does not alter neural activity. However, recent reports have suggested that CO2 inhalation may suppress neural activity and brain metabolic rate. Therefore, the goal of this study is to propose and test a gas challenge that is truly "iso-metabolic," by adding a hypoxic component to the hypercapnic challenge, since hypoxia has been shown to enhance cerebral metabolic rate of oxygen (CMRO2). Measurement of global CMRO2 under various gas challenge conditions revealed that, while hypercapnia (P = 0.002) and hypoxia (P = 0.002) individually altered CMRO2 (by -7.6 ± 1.7% and 16.7 ± 4.1%, respectively), inhalation of hypercapnic-hypoxia gas (5% CO2/13% O2) did not change brain metabolism (CMRO2 change: 1.5 ± 3.9%, P = 0.92). Moreover, cerebral blood flow response to the hypercapnic-hypoxia challenge (in terms of % change per mmHg CO2 change) was even greater than that to hypercapnia alone (P = 0.007). Findings in this study suggest that hypercapnic-hypoxia gas challenge may be a useful maneuver in physiological MRI as it preserves vasodilatory response yet does not alter brain metabolism.

Wavelet coherence analysis of cerebral oxygenation signals measured by near-infrared spectroscopy in sailors: an exploratory, experimental study

OBJECTIVE

The objective of this study was to assess the effects of long-term offshore work on cerebral oxygenation oscillations in sailors based on the wavelet phase coherence (WPCO) of near-infrared spectroscopy (NIRS) signals.

METHODS

The fatigue severity scale (FSS) was first applied to assess the fatigue level of sailors and age-matched controls. Continuous recordings of NIRS signals were then obtained from the prefrontal lobes in 30 healthy sailors and 30 age-matched controls during the resting state. WPCO between the left and right prefrontal oscillations was analysed and Pearson correlation analysis was used to study the relationship between the FSS and the wavelet amplitude (WA), and between the FSS and the WPCO level.

RESULTS

The periodic oscillations of Delta (HbO₂) signals were identified at six 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); and VI (0.005-0.0095 Hz). The WA in intervals I (F=8.823, p=0.004) and III (F=4.729, p=0.034) was significantly lower in sailors than that in the controls. The WPCO values of sailor group were significantly lower in intervals III (F=4.686, p=0.039), IV (F=4.864, p=0.036) and V (F=5.195, p=0.03) than those of the control group. In the sailor group, the WA in interval I (r=-0.799, p<0.01) and in interval III (r=-0.721, p<0.01) exhibited a negative correlation with the FSS. Also, the WPCO exhibited a negative correlation with the FSS in intervals III (r=-0.839, p<0.01), IV (r=-0.765, p<0.01) and V (r=-0.775, p<0.01) in the sailor group.

CONCLUSIONS

The negative correlation between WA and FSS indicates that the lower oscillatory activities might contribute to the development of fatigue. The low WPCO in intervals III, IV and V represents a reduced phase synchronisation of myogenic, neurogenic and endothelial metabolic activities respectively and this may suggest a decline of cognitive function.

Age-related alterations in phase synchronization of oxyhemoglobin concentration changes in prefrontal tissues as measured by near-infrared spectroscopy signals

The prefrontal cortex plays an important role in planning complex cognitive behavior, personality expression, and decision making. This study aims to assess the phase synchronization of signals of the oxyhemoglobin concentration changes (Δ[HbO2]) in the left and right prefrontal tissues through near-infrared spectroscopy (NIRS) with wavelet phase coherence (WPCO) method. The NIRS signals were continuously recorded from the left and right prefrontal lobes in 43 healthy elderly subjects (age: 69.6 ± 8.4 years) and 40 young healthy subjects (age: 24.5 ± 1.7 years) during the resting state. Phase synchronization between the left and right prefrontal oscillations in six 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; and VI, 0.005-0.0095 Hz) was analyzed using the WPCO method. The WPCO values of elderly subjects were significantly lower in frequency intervals I (F=7.376, p=0.010) and III (F=6.418, p=0.016) than those of the young subjects. Low phase coherence in intervals I and III indicates reduced synchronization of cardiac activity in the prefrontal area and weakened prefrontal functional connectivity, respectively.

Monitoring cerebral autoregulation after brain injury: multimodal assessment of cerebral slow-wave oscillations using near-infrared spectroscopy

BACKGROUND

Continuous monitoring of cerebral autoregulation might provide novel treatment targets and identify therapeutic windows after acute brain injury. Slow oscillations of cerebral hemodynamics (0.05-0.003 Hz) are visible in multimodal neuromonitoring and may be analyzed to provide novel, surrogate measures of autoregulation. Near-infrared spectroscopy (NIRS) is an optical neuromonitoring technique, which shows promise for widespread clinical applicability because it is noninvasive and easily delivered across a wide range of clinical scenarios. The aim of this study is to identify the relationship between NIRS signal oscillations and multimodal neuromonitoring, examining the utility of near infrared derived indices of cerebrovascular reactivity.

METHODS

Twenty-seven sedated, ventilated, brain-injured patients were included in this observational study. Intracranial pressure, transcranial Doppler-derived flow velocity in the middle cerebral artery, and ipsilateral cerebral NIRS variables were continuously monitored. Signals were compared using wavelet measures of phase and coherence to examine the spectral features involved in reactivity index calculations. Established indices of autoregulatory reserve such as the pressure reactivity index (PRx) and mean velocity index (Mx) and the NIRS indices such as total hemoglobin reactivity index (THx) and tissue oxygen reactivity index (TOx) were compared using correlation and Bland-Altman analysis.

RESULTS

NIRS indices correlated significantly between PRx and THx (rs = 0.63, P < 0.001), PRx and TOx (r = 0.40, P = 0.04), and Mx and TOx (r = 0.61, P = 0.004) but not between Mx and THx (rs = 0.26, P = 0.28) and demonstrated wide limits between these variables: PRx and THx (bias, -0.06; 95% limits, -0.44 to 0.32) and Mx and TOx (bias, +0.15; 95% limits, -0.34 to 0.64). Analysis of slow-wave activity throughout the intracranial pressure, transcranial Doppler, and NIRS recordings revealed statistically significant interrelationships, which varied dynamically and were nonsignificant at frequencies <0.008 Hz.

CONCLUSIONS

Although slow-wave activity in intracranial pressure, transcranial Doppler, and NIRS is significantly similar, it varies dynamically in both time and frequency, and this manifests as incomplete agreement between reactivity indices. Analysis informed by a priori knowledge of physiology underpinning NIRS variables combined with sophisticated analysis techniques has the potential to deliver noninvasive surrogate measures of autoregulation, guiding therapy.

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.

A Review of Wavelet Transform Time-Frequency Methods for NIRS-Based Analysis of Cerebral Autoregulation

Near-infrared spectroscopy (NIRS) has been proposed as a suitable technique for the analysis of cerebral autoregulation as it provides a simpler acquisition methodology and more artifact-free signal. A number of sophisticated wavelet transform methods have recently emerged to quantify the cerebral autoregulation mechanism using NIRS and blood pressure signals. These provide an enhanced partitioning of signal information via the time-frequency plane, which facilitates improved extraction of the components of interest. This area is reviewed, and enhancements to this form of analysis are suggested.

Cerebral autoregulation in response to posture change in elderly subjects-assessment by wavelet phase coherence analysis of cerebral tissue oxyhemoglobin concentrations and arterial blood pressure signals

This study aims to assess the dynamic cerebral autoregulation (dCA) in response to posture change using wavelet phase coherence (WPCO) of cerebral tissue oxyhemoglobin concentrations (Delta [HbO2]) and arterial blood pressure (ABP) signals in healthy elderly subjects. Continuous recordings of near-infrared spectroscopy (NIRS) and ABP signals were obtained from simultaneous measurements in 16 healthy elderly subjects (age: 68.9±7.1 years) and 19 young subjects (age: 24.9±3.2 years). The phase coherence between Delta [HbO2] and ABP oscillations in six frequency intervals (I, 0.6-2 Hz; II, 0.15-0.6 Hz; III, 0.05-0.15 Hz; IV, 0.02-0.05 Hz, V, 0.0095-0.02 Hz and VI, 0.005-0.0095 Hz) was analyzed using WPCO. The sit-to-stand posture change induces significantly lower WPCO in interval III (F=5.50 p=0.025) in the elderly subjects than in the young subjects. However, the stand-to-sit posture change induces higher WPCO in intervals II (F=5.25 p=0.028) and V (F=6.22 p=0.018) in the elderly subjects than in the young subjects. The difference of WPCO in response to posture change between the elderly and the young subjects indicates an altered CA due to aging. This study provides new insight into the dynamics of CA and may be useful in identifying the risk for dCA processes.

Wavelet coherence analysis of prefrontal tissue oxyhaemoglobin signals as measured using near-infrared spectroscopy in elderly subjects with cerebral infarction

This study aims to assess the prefrontal functional connectivity using wavelet coherence analysis of cerebral tissue oxyhaemoglobin concentration (Delta [HbO2]) signals in elderly subjects with cerebral infarction (CI) during the resting state. Continuous recordings of near-infrared spectroscopy (NIRS) signals were obtained from the left and right prefrontal lobes in 10 subjects with CI (age: 74.4±9.0years) and 18 healthy elderly subjects (age: 69.9±7.3years) during the resting state. The coherence between left and right prefrontal Delta [HbO2] oscillations in four frequency intervals (I, 0.6-2Hz; II, 0.145-0.6Hz; III, 0.052-0.145Hz and IV, 0.021-0.052Hz) was analyzed using wavelet coherence analysis. In healthy elderly subjects, the Delta [HbO2] oscillations were significantly wavelet coherent in intervals I and III (p<0.05), wavelet phase coherent in intervals from I to IV. In elderly subjects with CI, the left and right Delta [HbO2] oscillations were significantly wavelet coherent and phase coherent in interval I (p<0.05). In elderly subjects with CI, the power and phase coherences were significantly lower in interval III (p<0.01) than in healthy subjects. The difference in wavelet coherence between the healthy elderly and elderly with CI indicates an altered brain functional connectivity in CI patients. This may be useful for assessing the effectiveness of functional recovery following a CI.

Age-related changes in inter-joint coordination during walking

Existing methods to assess inter-joint coordination in human walking have several important weaknesses. These methods are unable to define 1) the instantaneous changes in coordination within the stride cycle, 2) coordination between multiple joints, or 3) the coupling strength of joint rotations rather than their phase relationships. The present paper introduces a new method called generalized wavelet coherence analysis (GWCA) that solves these three fundamental limitations of previous methods. GWCA combines wavelet coherence analysis with a matrix correlation method to define instantaneous correlation coefficients as the coupling strength for an arbitrary number of joint rotations. The main purpose of the present study is to develop GWCA to quantify inter-joint coordination and thereby assess age-related differences in the coordination of human gaits. Nine young and 19 healthy older persons walked 5 min on a treadmill at three different gait speeds. Joint rotations of the lower extremities were assessed by a Vicon three-dimensional motion capture system. The main results indicated that the older group had significant weaker correlations (t-tests: P < 0.0001) in the preswing phase compared with the younger group for all gait speeds. The age-related differences in inter-joint coordination were more pronounced than the age-related differences in rotations of the individual joints. The intra-stride changes in inter-joint coordination were in agreement with recent findings of intra-stride modulations in neural activity in the sensorimotor cortex. Thus change in the inter-joint coordination assessed by GWCA might be an early indicator of functional decline.

Wavelet coherence analysis of spontaneous oscillations in cerebral tissue oxyhemoglobin concentrations and arterial blood pressure in elderly subjects

This study aims to assess the relationship between spontaneous oscillations in changes in cerebral tissue oxyhemoglobin concentrations (Delta [HbO2]) and arterial blood pressure (ABP) signals in healthy elderly subjects during the resting state using wavelet coherence analysis. Continuous recordings of near-infrared spectroscopy (NIRS) and ABP signals were obtained from simultaneous measurements in 33 healthy elderly subjects (age: 70.7±7.9 years) and 27 young subjects (age: 25.2±3.7 years) during the resting state. The coherence between Delta [HbO2] and ABP oscillations in six frequency intervals (I, 0.4-2 Hz; II, 0.15-0.4 Hz; III, 0.05-0.15 Hz; IV, 0.02-0.05 Hz, V, 0.005-0.0095 Hz and VI, 0.005-0.0095 Hz) was analyzed using wavelet coherence analysis. In elderly subjects, the Delta [HbO2] and ABP oscillations were significantly wavelet coherent in interval I, and wavelet phase coherent in intervals I, II and IV. The wavelet coherence in interval I was significantly higher (p=0.040), in elderly subjects than in young subjects whereas that in interval V significantly lower (p=0.015). In addition, the wavelet phase coherence in interval IV was significantly higher in elderly subjects than in young subjects (p=0.028). The difference in the wavelet coherence of the elderly subjects and the young subjects indicates an altered cerebral autoregulation caused by aging. This study provides new insight into the dynamics of Delta [HbO2] and ABP oscillations and may be useful in identifying the risk for dynamic cerebral autoregulation processes.