EEG phase-amplitude coupling to stratify encephalopathy severity in the developing brain.

BACKGROUND: Neonatal hypoxic ischemic encephalopathy (HIE) is difficult to classify within the narrow therapeutic window of hypothermia. Neurophysiological biomarkers are needed for timely differentiation of encephalopathy severity within the short therapeutic window for initiation of hypothermia therapy. METHODS: A novel analysis of mean Phase Amplitude Coupling index, PACm, of amplitudes high frequencies (12-30 Hz) coupled with phases of low (1,2 Hz) frequencies was calculated from the 6 h EEG recorded during the first day of life. PACm values were compared to identify differences between mild versus higher-grade HIE, respectively, for each of the EEG electrodes. A receiver operating characteristic curve was generated to examine the performance of PACm. RESULTS: 38 newborns with different HIE grades were enrolled in the first 6 h of life. Threshold PACm 0.001 at Fz, O1, O2, P3, and P4 had AUC >0.9 to differentiate HIE severity and predict the persistence of moderate to severe encephalopathy that requires treatment with hypothermia. CONCLUSION: PAC is a promising biomarker to identify mild from higher severity of HIE after birth.

Wavelet-based neurovascular coupling can predict brain abnormalities in neonatal encephalopathy.

BACKGROUND: Hypoxic-ischemic encephalopathy (HIE) is a leading cause of morbidity and mortality in neonates, but quantitative methods to predict outcomes early in their course of illness remain elusive. Real-time physiologic biomarkers of neurologic injury are needed in order to predict which neonates will benefit from therapies. Neurovascular coupling (NVC) describes the correlation of neural activity with cerebral blood flow, and the degree of impairment could predict those at risk for poor outcomes. OBJECTIVE: To determine if neurovascular coupling (NVC) calculated in the first 24-hours of life based on wavelet transform coherence analysis (WTC) of near-infrared spectroscopy (NIRS) and amplitude-integrated electroencephalography (aEEG) can predict abnormal brain MRI in neonatal HIE. METHODS: WTC analysis was performed between dynamic oscillations of simultaneously recorded aEEG and cerebral tissue oxygen saturation (SctO2) signals for the first 24 h after birth. The squared cross-wavelet coherence, R2, of the time-frequency domain described by the WTC, is a localized correlation coefficient (ranging between 0 and 1) between these two signals in the time-frequency domain. Statistical analysis was based on Monte Carlo simulation with a 95% confidence interval to identify the time-frequency areas from the WTC scalograms. Brain MRI was performed on all neonates and classified as normal or abnormal based on an accepted classification system for HIE. Wavelet metrics of % significant SctO2-aEEG coherence was compared between the normal and abnormal MRI groups. RESULT: This prospective study recruited a total of 36 neonates with HIE. A total of 10 had an abnormal brain MRI while 26 had normal MRI. The analysis showed that the SctO2-aEEG coherence between the group with normal and abnormal MRI were significantly different (p = 0.0007) in a very low-frequency (VLF) range of 0.06-0.2 mHz. Using receiver operating characteristic (ROC) curves, the use of WTC-analysis of NVC had an area under the curve (AUC) of 0.808, and with a cutoff of 10% NVC. Sensitivity was 69%, specificity was 90%, positive predictive value (PPV) was 94%, and negative predictive value (NPV) was 52% for predicting brain injury on MRI. This was superior to the clinical Total Sarnat score (TSS) where AUC was 0.442 with sensitivity 61.5%, specificity 30%, PPV 75%, and NPV 31%. CONCLUSION: NVC is a promising neurophysiological biomarker in neonates with HIE, and in our prospective cohort was superior to the clinical Total Sarnat score for prediction of abnormal brain MRI.

Early Use of Transcranial Doppler Ultrasonography to Stratify Neonatal Encephalopathy.

BACKGROUND: The dynamic nature of neonatal hypoxic-ischemic encephalopathy (HIE) after birth necessitates reliable biomarkers to identify infants with evolving brain injury. This prospective cohort aims to use serial Doppler ultrasonography (US) to measure cerebral blood flow velocity and resistance index (RI) to help detect the time and evolution of the clinical encephalopathy. METHODS: A total of 60 neonates were enrolled all ≥36 weeks' gestation with perinatal acidemia, defined as a blood gas pH ≤ 7.0 or base deficit ≥16 mmol/L and encephalopathy including a matched control group without encephalopathy. Each neonate received one to three serial Doppler recordings starting at six to 24 hours of life. Mean RI ≤ 0.55 was considered abnormal. RESULTS: Mean RIs obtained shortly after birth were significantly lower with increasing severity of encephalopathy. On the first Doppler recordings, abnormal mean RIs were seen in 11 of 18 (61%) neonates with mild, 13 of 17 (76%) with moderate, and two of two (100%) with severe HIE. Of the neonates with mild HIE and abnormal mean RIs, congruity abnormal amplitude electroencephalography (45%), brain magnetic resonance imaging (45%), and abnormal head ultrasound (44%) are here reported. CONCLUSIONS: Doppler measurements can provide bedside adjunct biomarkers indicating the time and severity of neonatal HIE.

Neurovascular coupling (NVC) in newborns using processed EEG versus amplitude-EEG.

There is a critical need for development of real time physiological biomarkers for birth asphyxia that constitutes a major global public health burden. Our recent study (Scientific Reports, V10:9183, 2020) established a novel non-invasive neurovascular coupling (NVC) assessment in newborns using dynamic wavelet transform coherence (WTC) analysis irrespective of different aEEG algorithms. As an extended study, the current paper examines whether the variability in processed EEG and amplitude-EEG (aEEG) outputs would impact the determination of NVC in newborns with encephalopathy. Concurrent processed EEG tracings and regional near infrared spectroscopy (NIRS)-based cerebral tissue oxygen saturation (SctO2) readings during a period of twenty hours in their first day of life were selected and processed in this study. After bandpass-filtered in 2-15 Hz, rectified, and down-sampled at 0.21 Hz, the processed EEG tracings along with NIRS-SctO2 (0.21 Hz) were used to perform WTC analysis, followed by comparison of WTC-metrics between SctO2-processed EEG coherence and SctO2-aEEG coherence using Bland-Altman statistics. Our results demonstrated high and significant correlation (R2 = 0.96, p < 0.001) between NVC assessments by SctO2-processed EEG and SctO2-aEEG coherence, confirming that band-passed, rectified, and down-sampled processed EEG, or aEEG, can be paired with NIRS-SctO2 to assess NVC in newborns with encephalopathy. Findings indicate the feasibility of a simpler approach to NVC in neonates by using directly processed EEG, instead of aEEG.

Regional heterogeneity of cerebral hemodynamics in mild neonatal encephalopathy measured with multichannel near-infrared spectroscopy.

BACKGROUND: Neuromonitoring at the bedside is the key to understand the pathophysiological mechanisms of brain injury associated with neonatal encephalopathy. The current practice is to monitor the forehead using a noninvasive cerebral oximetry-it remains unknown to what extent cerebral hemodynamics in other brain regions is different to the frontal region. METHOD: A multichannel near-infrared spectroscopy (NIRS) system was used to monitor neonates (n = 14) with fetal acidosis and mild neonatal encephalopathy at four brain regions (the frontal, posterior, left temporal, and right temporal lobes). The data were compared to delineate the regional difference in (1) cerebral hemodynamics and (2) pressure autoregulation. For both analyses, wavelet transform coherence was applied. RESULTS: We observed frontal-posterior heterogeneity as indicated by significantly lower coherence between these two regions (p = 0.02). Furthermore, areas with regional magnetic resonance imaging (MRI)-detected lesions showed greater hemodynamic variations compared to non-affected areas (p = 0.03), while cerebral autoregulation was not affected and showed no difference. CONCLUSION: Cerebral hemodynamics in mild neonatal encephalopathy is heterogeneous across different brain regions, while cerebral autoregulation remains intact. These findings indicate the robustness of the wavelet measure of cerebral autoregulation in this population, but need to be further investigated in the presence of severe injury. IMPACT: This proof-of-concept study is the first to investigate the regional difference of cerebral hemodynamics and autoregulation in mild neonatal encephalopathy. Study findings confirm that brain functions are complex in the developing neonatal brain and that cerebral hemodynamics are region specific in newborns with frontal-posterior heterogeneity among brain regions probed by multichannel NIRS. Regional MRI lesions were associated with differences across NIRS regional channels among the affected side. Cerebral autoregulation with multichannel NIRS is not affected by regional MRI abnormalities.

Rigor of Neurovascular Coupling (NVC) Assessment in Newborns Using Different Amplitude EEG Algorithms.

Birth asphyxia constitutes a major global public health burden for millions of infants with a critical need for real time physiological biomarkers. This proof of concept study targets the translational rigor of such biomarkers and aims to examine whether the variability in the amplitude-integrated EEG (aEEG) outputs impact the determination of neurovascular coupling (NVC) in newborns with encephalopathy. A convenience sample with neonatal asphyxia were monitored for twenty hours in the first day of life with EEG and near infrared spectroscopy (NIRS)-based cerebral tissue oxygen saturation (SctO2). NVC between aEEG and NIRS-SctO2 was assessed using wavelet transform coherence (WTC) analysis, specifically by the wavelet total pixel number of significant coherences within 95% confidence interval. The raw EEG was converted to aEEG using three different methods: Method (M1) derives from the algorithm by Zhang and Ding. Method (M2) uses a Neonatal EEG Analysis Toolbox (WU-NEAT). Method (M3) extracts output directly from a commercial platform with an undisclosed algorithm. Our results demonstrate excellent agreement with Bland Altman comparisons for WTC-based NVC irrespective of the algorithms used, despite significant heterogeneities in the aEEG tracings produced by three algorithms. Our findings confirm the robustness of NVC wavelet analysis in Neonatal Encephalopathy related to HIE.