Decomposition of Near-Infrared Spectroscopy Signals Using Oblique Subspace Projections: Applications in Brain Hemodynamic Monitoring

Monitoring of Cerebral Oxygen Saturation in Interhospital Transport of Patients Receiving Extracorporeal Membrane Oxygenation

Extracorporeal membrane oxygenation (ECMO) in acute respiratory distress syndrome (ARDS) is used to achieve oxygenation and protect lung ventilation. Near infrared spectroscopy (NIRS) measures cerebral regional tissue oxygenation (rSO 2 ) and may contribute to patient safety during interhospital transport under ECMO support. We evaluated 16 adult ARDS patients undergoing interhospital ECMO transport by measuring cerebral rSO 2 before and after initiation of ECMO support and continuously during transport. To compare peripheral oxygen saturation (SpO 2 ) measurement with rSO 2 , both parameters were analyzed. NIRS monitoring for initiation of ECMO and interhospital transport under ECMO support was feasible, and there was no significant difference in the percentage of achievable valid measurements over time between cerebral rSO 2 (88.4% [95% confidence interval {CI}, 81.3-95.0%]) and standard SpO 2 monitoring 91.7% (95% CI, 86.1-94.2%), p = 0.68. No change in cerebral rSO 2 was observed before 77% (73.5-81%) (median [interquartile range {IQR}]) and after initiation of ECMO support 78% (75-81%), p = 0.2. NIRS for cerebral rSO 2 measurement is feasible during ECMO initiation and interhospital transport. Achievement of valid measurements of cerebral rSO 2 was not superior to SpO 2 . In distinct patients ( e.g. , shock), measurement of cerebral rSO 2 may contribute to improvement of patient safety during interhospital ECMO transport.

Cerebral oxygen saturation and autoregulation during hypotension in extremely preterm infants

BACKGROUND

The impact of the permissive hypotension approach in clinically well infants on regional cerebral oxygen saturation (rScO₂) and autoregulatory capacity (CAR) remains unknown.

METHODS

Prospective cohort study of blinded rScO₂ measurements within a randomized controlled trial of management of hypotension (HIP trial) in extremely preterm infants. rScO₂, mean arterial blood pressure, duration of cerebral hypoxia, and transfer function (TF) gain inversely proportional to CAR, were compared between hypotensive infants randomized to receive dopamine or placebo and between hypotensive and non-hypotensive infants, and related to early intraventricular hemorrhage or death.

RESULTS

In 89 potentially eligible HIP trial patients with rScO₂ measurements, the duration of cerebral hypoxia was significantly higher in 36 hypotensive compared to 53 non-hypotensive infants. In 29/36 hypotensive infants (mean GA 25 weeks, 69% males) receiving the study drug, no significant difference in rScO₂ was observed after dopamine (n = 13) compared to placebo (n = 16). Duration of cerebral hypoxia was associated with early intraventricular hemorrhage or death.  Calculated TF gain (n = 49/89) was significantly higher reflecting decreased CAR in 16 hypotensive compared to 33 non-hypotensive infants.

CONCLUSIONS

Dopamine had no effect on rScO₂ compared to placebo in hypotensive infants. Hypotension and cerebral hypoxia are associated with early intraventricular hemorrhage or death.

IMPACT

Treatment of hypotension with dopamine in extremely preterm infants increases mean arterial blood pressure, but does not improve cerebral oxygenation. Hypotensive extremely preterm infants have increased duration of cerebral hypoxia and reduced cerebral autoregulatory capacity compared to non-hypotensive infants. Duration of cerebral hypoxia and hypotension are associated with early intraventricular hemorrhage or death in extremely preterm infants. Since systematic treatment of hypotension may not be associated with better outcomes, the diagnosis of cerebral hypoxia in hypotensive extremely preterm infants might guide treatment.

Dynamic Cerebral Autoregulation Reproducibility Is Affected by Physiological Variability

Parameters describing dynamic cerebral autoregulation (DCA) have limited reproducibility. In an international, multi-center study, we evaluated the influence of multiple analytical methods on the reproducibility of DCA. Fourteen participating centers analyzed repeated measurements from 75 healthy subjects, consisting of 5 min of spontaneous fluctuations in blood pressure and cerebral blood flow velocity signals, based on their usual methods of analysis. DCA methods were grouped into three broad categories, depending on output types: (1) transfer function analysis (TFA); (2) autoregulation index (ARI); and (3) correlation coefficient. Only TFA gain in the low frequency (LF) band showed good reproducibility in approximately half of the estimates of gain, defined as an intraclass correlation coefficient (ICC) of >0.6. None of the other DCA metrics had good reproducibility. For TFA-like and ARI-like methods, ICCs were lower than values obtained with surrogate data (p < 0.05). For TFA-like methods, ICCs were lower for the very LF band (gain 0.38 ± 0.057, phase 0.17 ± 0.13) than for LF band (gain 0.59 ± 0.078, phase 0.39 ± 0.11, p ≤ 0.001 for both gain and phase). For ARI-like methods, the mean ICC was 0.30 ± 0.12 and for the correlation methods 0.24 ± 0.23. Based on comparisons with ICC estimates obtained from surrogate data, we conclude that physiological variability or non-stationarity is likely to be the main reason for the poor reproducibility of DCA parameters.

Functional form estimation using oblique projection matrices for LS-SVM regression models

Kernel regression models have been used as non-parametric methods for fitting experimental data. However, due to their non-parametric nature, they belong to the so-called "black box" models, indicating that the relation between the input variables and the output, depending on the kernel selection, is unknown. In this paper we propose a new methodology to retrieve the relation between each input regressor variable and the output in a least squares support vector machine (LS-SVM) regression model. The method is based on oblique subspace projectors (ObSP), which allows to decouple the influence of input regressors on the output by including the undesired variables in the null space of the projection matrix. Such functional relations are represented by the nonlinear transformation of the input regressors, and their subspaces are estimated using appropriate kernel evaluations. We exploit the properties of ObSP in order to decompose the output of the obtained regression model as a sum of the partial nonlinear contributions and interaction effects of the input variables, we called this methodology Nonlinear ObSP (NObSP). We compare the performance of the proposed algorithm with the component selection and smooth operator (COSSO) for smoothing spline ANOVA models. We use as benchmark 2 toy examples and a real life regression model using the concrete strength dataset from the UCI machine learning repository. We showed that NObSP is able to outperform COSSO, producing stable estimations of the functional relations between the input regressors and the output, without the use of prior-knowledge. This methodology can be used in order to understand the functional relations between the inputs and the output in a regression model, retrieving the physical interpretation of the regression models.

Reproducibility of dynamic cerebral autoregulation parameters: a multi-centre, multi-method study

OBJECTIVE

Different methods to calculate dynamic cerebral autoregulation (dCA) parameters are available. However, most of these methods demonstrate poor reproducibility that limit their reliability for clinical use. Inter-centre differences in study protocols, modelling approaches and default parameter settings have all led to a lack of standardisation and comparability between studies. We evaluated reproducibility of dCA parameters by assessing systematic errors in surrogate data resulting from different modelling techniques.

APPROACH

Fourteen centres analysed 22 datasets consisting of two repeated physiological blood pressure measurements with surrogate cerebral blood flow velocity signals, generated using Tiecks curves (autoregulation index, ARI 0-9) and added noise. For reproducibility, dCA methods were grouped in three broad categories: 1. Transfer function analysis (TFA)-like output; 2. ARI-like output; 3. Correlation coefficient-like output. For all methods, reproducibility was determined by one-way intraclass correlation coefficient analysis (ICC).

MAIN RESULTS

For TFA-like methods the mean (SD; [range]) ICC gain was 0.71 (0.10; [0.49-0.86]) and 0.80 (0.17; [0.36-0.94]) for VLF and LF (p  =  0.003) respectively. For phase, ICC values were 0.53 (0.21; [0.09-0.80]) for VLF, and 0.92 (0.13; [0.44-1.00]) for LF (p  <  0.001). Finally, ICC for ARI-like methods was equal to 0.84 (0.19; [0.41-0.94]), and for correlation-like methods, ICC was 0.21 (0.21; [0.056-0.35]).

SIGNIFICANCE

When applied to realistic surrogate data, free from the additional exogenous influences of physiological variability on cerebral blood flow, most methods of dCA modelling showed ICC values considerably higher than what has been reported for physiological data. This finding suggests that the poor reproducibility reported by previous studies may be mainly due to the inherent physiological variability of cerebral blood flow regulatory mechanisms rather than related to (stationary) random noise and the signal analysis methods.

Unconstrained Estimation of HRV Indices After Removing Respiratory Influences From Heart Rate

OBJECTIVE

This paper proposes an approach to better estimate the sympathovagal balance (SB) and the respiratory sinus arrhythmia (RSA) after separating respiratory influences from the heart rate (HR).

METHODS

The separation is performed using orthogonal subspace projections and the approach is first tested using simulated HR and respiratory signals with different spectral properties. Then, RSA and SB are estimated during autonomic blockade and stress using the proposed approach and the classical heart rate variability (HRV) analysis. Both real- and ECG-derived respiration (EDR) are used and the reliability of the EDR is evaluated.

RESULTS

Mean absolute percentage errors lower than [Formula: see text] were obtained after removing previously known respiratory signals from simulated HR. The proposed indices were able to improve the quantification of SB during autonomic withdrawal. In the stress data, differences ( ) among relaxed and stressful phases were found with the proposed approach, using both the real respiration and the EDR, but they disappeared when using the classical HRV.

CONCLUSION

A better assessment of the autonomic nervous system' response to pharmacological blockade and stress can be achieved after removing respiratory influences from HR, and this can be done using either the real respiration or the EDR.

SIGNIFICANCE

This work can be used to better identify vagal withdrawal and increased sympathetic activation when the classical HRV analysis fails due to the respiratory influences on HR. Furthermore, it can be computed using only the ECG, which is an advantage when developing wearable systems with limited number of sensors.

Cerebral autoregulation and activity after propofol for endotracheal intubation in preterm neonates

BACKGROUND

Despite increasing use of propofol in neonates, observations on cerebral effects are limited.

AIM

To investigate cerebral autoregulation (CAR) and activity after propofol for endotracheal intubation in preterm neonates.

METHODS

Twenty-two neonates received propofol before intubation as part of a published dose-finding study. Mean arterial blood pressure (MABP), near-infrared spectroscopy-derived cerebral oxygenation (rScO₂), and amplitude-integrated electroencephalography (aEEG) were analyzed until 180 min after propofol. CAR was expressed as transfer function (TF) gain, indicating % change in rScO₂ per 1 mmHg change in MABP. Values exceeding mean TF gain + 2 standard deviations (SD) defined impaired CAR.

RESULTS

After intubation with a median propofol dose of 1 (0.5-4.5) mg/kg, rScO₂ remained stable during decreasing MABP. Mean (±SD) TF gain was 0.8 (±0.3)%/mmHg. Impaired CAR was identified in 1 and 5 patient(s) during drug-related hypotension and normal to raised MABP, respectively. Suppressed aEEG was observed up to 60 min after propofol.

CONCLUSIONS

Drug-related hypotension and decreased cerebral activity after intubation with low propofol doses in preterm neonates were observed, without evidence of cerebral ischemic hypoxia. CAR remained intact during drug-related hypotension in 95.5% of patients. Cerebral monitoring including CAR clarifies the cerebral impact of MABP fluctuations.

Measuring Near-Infrared Spectroscopy Derived Cerebral Autoregulation in Neonates: From Research Tool Toward Bedside Multimodal Monitoring

Introduction: Cerebral autoregulation (CAR), the ability of the human body to maintain cerebral blood flow (CBF) in a wide range of perfusion pressures, can be calculated by describing the relation between arterial blood pressure (ABP) and cerebral oxygen saturation measured by near-infrared spectroscopy (NIRS). In literature, disturbed CAR is described in different patient groups, using multiple measurement techniques and mathematical models. Furthermore, it is unclear to what extent cerebral pathology and outcome can be explained by impaired CAR. Aim and methods: In order to summarize CAR studies using NIRS in neonates, a systematic review was performed in the PUBMED and EMBASE database. To provide a general overview of the clinical framework used to study CAR, the different preprocessing methods and mathematical models are described and explained. Furthermore, patient characteristics, definition of impaired CAR and the outcome according to this definition is described organized for the different patient groups. Results: Forty-six articles were included in this review. Four patient groups were established: preterm infants during the transitional period, neonates receiving specific medication/treatment, neonates with congenital heart disease and neonates with hypoxic-ischemic encephalopathy (HIE) treated with therapeutic hypothermia. Correlation, coherence and transfer function (TF) gain are the mathematical models most frequently used to describe CAR. The definition of impaired CAR is depending on the mathematical model used. The incidence of intraventricular hemorrhage in preterm infants is the outcome variable most frequently correlated with impaired CAR. Hypotension, disease severity, dopamine treatment, injury on magnetic resonance imaging (MRI) and long term outcome are associated with impaired CAR. Prospective interventional studies are lacking in all research areas. Discussion and conclusion: NIRS derived CAR measurement is an important research tool to improve knowledge about central hemodynamic fluctuations during the transitional period, cerebral pharmacodynamics of frequently used medication (sedatives-inotropes) and cerebral effects of specific therapies in neonatology. Uniformity regarding measurement techniques and mathematical models is needed. Multimodal monitoring databases of neonatal intensive care patients of multiple centers, together with identical outcome parameters are needed to compare different techniques and make progress in this field. Real-time bedside monitoring of CAR, together with conventional monitoring, seems a promising technique to improve individual patient care.

Impact of Changes in Systemic Physiology on fNIRS/NIRS Signals: Analysis Based on Oblique Subspace Projections Decomposition

Measurements of cerebral and muscle oxygenation (StO₂) and perfusion ([tHb]) with functional near-infrared spectroscopy (fNIRS) and near infrared spectroscopy (NIRS), respectively, can be influenced by changes in systemic physiology. The aim of our study was to apply the oblique subspace projections signal decomposition (OSPSD) to find the contribution from systemic physiology, i.e. heart rate (HR), electrocardiography (ECG)-derived respiration (EDR) and partial pressure of carbon dioxide (pCO₂) to StO₂ and [tHb] signals measured on the prefrontal cortex (PFC) and calf muscle. OSPSD was applied to two datasets (n₁ = 42, n₂ = 79 measurements) from two fNIRS/NIRS speech studies. We found that (i) all StO₂ and [tHb] signals contained components related to changes in systemic physiology, (ii) the contribution from systemic physiology varied strongly between subjects, and (iii) changes in systemic physiology generally influenced fNIRS signals on the left and right PFC to a similar degree.

Bifurcation in Blood Oscillatory Rhythms for Patients with Ischemic Stroke: A Small Scale Clinical Trial using Laser Doppler Flowmetry and Computational Modeling of Vasomotion

We describe application of spectral analysis of laser Doppler flowmetry (LDF) signals to investigation of cerebrovascular haemodynamics in patients with post-acute ischemic stroke (AIS) and cerebrovascular insufficiency. LDF was performed from 3 to 7 days after the onset of AIS on forehead in the right and left supraorbital regions in patients. Analysis of LDF signals showed that perfusion in the microvasculature in AIS patients was lower than that in patients with cerebrovascular insufficiency. As a result of wavelet analysis of the LDF signals we obtained activation of the vasomotion in the frequency range of myogenic oscillation of 0.1 Hz and predominantly nutritive regime microcirculation after systemic thrombolytic therapy of the AIS patients. In case of significant stroke size, myogenic activity, and nutritive pattern microhaemodynamics were reduced, in some cases non-nutritive pattern and/or venular stasis was revealed. Wavelet analysis of the LDF signals also showed asymmetry in wavelet spectra of the LDF signals obtained in stroke-affected and unaffected hemispheres in the AIS patients. A mechanism underlying the observed asymmetry was analyzed by computational modeling of vasomotion developed in Arciero and Secomb (2012). We applied this model to describe relaxation oscillation of arteriole diameter which is forced by myogenic oscillation induced by synchronous calcium oscillation in vascular smooth muscle cells. Calculation showed that vasomotion frequency spectrum at the low-frequency range (0.01 Hz) is reciprocally modulated by myogenic oscillation (0.1 Hz) that correlates with experimental observation of inter-hemispheric variation in the LDF spectrum.