Evaluation of SEPs in asphyxiated newborns using a 4-electrode aEEG brain monitoring set-up

Neuromonitoring in neonatal critical care part II: extremely premature infants and critically ill neonates

Neonatal intensive care has expanded from cardiorespiratory care to a holistic approach emphasizing brain health. To best understand and monitor brain function and physiology in the neonatal intensive care unit (NICU), the most commonly used tools are amplitude-integrated EEG, full multichannel continuous EEG, and near-infrared spectroscopy. Each of these modalities has unique characteristics and functions. While some of these tools have been the subject of expert consensus statements or guidelines, there is no overarching agreement on the optimal approach to neuromonitoring in the NICU. This work reviews current evidence to assist decision making for the best utilization of these neuromonitoring tools to promote neuroprotective care in extremely premature infants and in critically ill neonates. Neuromonitoring approaches in neonatal encephalopathy and neonates with possible seizures are discussed separately in the companion paper. IMPACT: For extremely premature infants, NIRS monitoring has a potential role in individualized brain-oriented care, and selective use of aEEG and cEEG can assist in seizure detection and prognostication. For critically ill neonates, NIRS can monitor cerebral perfusion, oxygen delivery, and extraction associated with disease processes as well as respiratory and hypodynamic management. Selective use of aEEG and cEEG is important in those with a high risk of seizures and brain injury. Continuous multimodal monitoring as well as monitoring of sleep, sleep-wake cycling, and autonomic nervous system have a promising role in neonatal neurocritical care.

Developing Disposable EEG Cap for Infant Recordings at the Neonatal Intensive Care Unit

Long-term EEG monitoring in neonatal intensive care units (NICU) is challenged with finding solutions for setting up and maintaining a sufficient recording quality with limited technical experience. The current study evaluates different solutions for the skin-electrode interface and develops a disposable EEG cap for newborn infants. Several alternative materials for the skin-electrode interface were compared to the conventional gel and paste: conductive textiles (textured and woven), conductive Velcro, sponge, super absorbent hydrogel (SAH), and hydro fiber sheets (HF). The comparisons included the assessment of dehydration and recordings of signal quality (skin interphase impedance and powerline (50 Hz) noise) for selected materials. The test recordings were performed using snap electrodes integrated into a forearm sleeve or a forehead band along with skin-electrode interfaces to mimic an EEG cap with the aim of long-term biosignal recording on unprepared skin. In the hydration test, conductive textiles and Velcro performed poorly. While the SAH and HF remained sufficiently hydrated for over 24 h in an incubator-mimicking environment, the sponge material was dehydrated during the first 12 h. Additionally, the SAH was found to have a fragile structure and was electrically prone to artifacts after 12 h. In the electrical impedance and recording comparisons of muscle activity, the results for thick-layer HF were comparable to the conventional gel on unprepared skin. Moreover, the mechanical instability measured by 1-2 Hz and 1-20 Hz normalized relative power spectrum density was comparable with clinical EEG recordings using subdermal electrodes. The results together suggest that thick-layer HF at the skin-electrode interface is an effective candidate for a preparation-free, long-term recording, with many advantages, such as long-lasting recording quality, easy use, and compatibility with sensitive infant skin contact.

Prognostic value of somatosensory-evoked potentials in the newborn with hypoxic-ischemic encephalopathy after the introduction of therapeutic hypothermia

To establish the ability of somatosensory-evoked potentials (SEPs) to detect neurological damage in neonatal patients with hypoxic-ischemic encephalopathy (HIE) treated with therapeutic hypothermia (TH). Retrospective study including 84 neonates ≥ 36 weeks of gestational age with HIE and TH with SEPs performed in the first 14 days of life. SEPs from the median nerve were performed after completion of TH. Either unilateral or bilateral absence of N20, or unilateral or bilateral latency ≥ 36 ms, was considered pathological. All newborns underwent a cerebral resonance imaging (MRI) at between days 7 and 14 of life and a neurodevelopmental evaluation using the Brunet-Lezine test at two years of age; a global Brunet-Lezine test score < 70 was considered unfavorable. The risk of moderate-to-severe alteration on basal ganglia-thalamic (BGT) and/or white matter areas on MRI for pathological SEPs was as follows: odds ratio 95% IC: 23.1 (6.9-76.9), sensitivity 78.6%, specificity 86.3%, positive predictive value 75.9%, and negative predictive value 88%. The BGT and internal capsule were the areas with the greatest risk of lesion with an altered SEPs: odds ratio 95% IC 93.1 (11.1-777.8). The risk of neurodevelopmental impairment for pathological SEPs was odds ratio 95% IC: 38.5 (4.4-335.3), sensitivity 91.7%, specificity 77.8% positive predictive value 52.4%, and negative predictive value 97.2%.

CONCLUSION

The present study demonstrates the good predictive capacity of SEPs performed in the first two weeks of life in newborns with HIE and TH to detect an increased risk of neuroimaging lesions and neurodevelopmental impairment at two years of age.

WHAT IS KNOWN

• Bilateral absence of the N20 cortical component of somatosensory evoked potentials has been associated with poor neurological outcome in neonates with hypoxic-ischemic encephalopathy.

WHAT IS NEW

• This work confirms the predictive capacity of SEPs by adding two important aspects: the value of latency when interpreting SEPs results and the absence of effect of the hypothermia method used on the results of SEPs.

Neurophysiological recordings improve the accuracy of the evaluation of the outcome in perinatal hypoxic ischemic encephalopathy

OBJECTIVES

Our objective was to evaluate the potential additional value of electroencephalogram (EEG) and evoked potentials in neonates with hypoxic-ischemic encephalopathy to predict their disability at 1 and 2 years old.

METHODS

30 full-term infants after perinatal asphyxia who underwent therapeutic hypothermia were evaluated at 1 year and 2 years for disability using International Classification of Functioning, Disability and Health classification. Scores for EEG, sensory evoked potentials and brainstem auditory evoked potentials were evaluated after withdrawal of therapeutic hypothermia that lasted 72 h. A regression approach was investigated to build models allowing to distinguish neonates according to their disability at 1 and 2 years. Two models were built, the first by considering the clinical data and EEG before and after therapeutic hypothermia and the second by incorporating evoked potentials recording.

RESULTS

Adding EEG and evoked potentials data after rewarming improved dramatically the accuracy of the model considering outcome at 1 and 2 years.

INTERPRETATION

We propose to record systematically EEG and evoked potentials following rewarming to predict the outcome of neonates with hypoxic ischemic encephalopathy. Combination of altered evoked potentials with no improvement of EEG after rewarming appeared to be a robust criterion for a poor outcome.

Convolutional neural networks ensemble model for neonatal seizure detection

BACKGROUND

Neonatal seizures are a common occurrence in clinical settings, requiring immediate attention and detection. Previous studies have proposed using manual feature extraction coupled with machine learning, or deep learning to classify between seizure and non-seizure states.

NEW METHOD

In this paper a deep learning based approach is used for neonatal seizure classification using electroencephalogram (EEG) signals. The architecture detects seizure activity in raw EEG signals as opposed to common state-of-art, where manual feature extraction with machine learning algorithms is used. The architecture is a two-dimensional (2D) convolutional neural network (CNN) to classify between seizure/non-seizure states.

RESULTS

The dataset used for this study is annotated by three experts and as such three separate models are trained on individual annotations, resulting in average accuracies (ACC) of 95.6 %, 94.8 % and 90.1 % respectively, and average area under the receiver operating characteristic curve (AUC) of 99.2 %, 98.4 % and 96.7 % respectively. The testing was done using 10-cross fold validation, so that the performance can be an accurate representation of the architectures classification capability in a clinical setting. After training/testing of the three individual models, a final ensemble model is made consisting of the three models. The ensemble model gives an average ACC and AUC of 96.3 % and 99.3 % respectively.

COMPARISON WITH EXISTING METHODS

This study outperforms previous studies, with increased ACC and AUC results coupled with use of small time windows (1 s) used for evaluation.

CONCLUSION

The proposed approach is promising for detecting seizure activity in unseen neonate data in a clinical setting.

Towards multimodal brain monitoring in asphyxiated newborns with amplitude-integrated EEG and simultaneous somatosensory evoked potentials

BACKGROUND

Somatosensory evoked potentials (SEPs) offer an additional bedside tool for outcome prediction after perinatal asphyxia.

AIMS

To assess the reliability of SEPs recorded with bifrontoparietal amplitude-integrated electroencephalography (aEEG) brain monitoring setup for outcome prediction in asphyxiated newborns undergoing therapeutic hypothermia.

STUDY DESIGN

Retrospective observational single-center study.

SUBJECTS

27 consecutive asphyxiated full- or near-term newborns (25 under hypothermia) that underwent median nerve aEEG-SEPs as part of their clinical evaluation at the neonatal intensive care unit of Helsinki University Hospital.

OUTCOME MEASURES

aEEG-SEP classification (present, absent or unreliable) was compared to classification of SEPs recorded with a full EEG montage (EEG-SEP), and outcome determined from medical records at approximately 12-months-age. Unfavorable outcome included death, cerebral palsy, or severe epilepsy.

RESULTS

The aEEG-SEP and EEG-SEP classifications were concordant in 21 of the 22 newborns with both recordings available. All five newborns with bilaterally absent aEEG-SEPs had absent EEG-SEPs and the four with outcome information available had an unfavorable outcome (one was lost to follow-up). Of the newborns with aEEG-SEPs present, all with follow-up exams available had bilaterally present EEG-SEPs and a favorable outcome (one was lost to follow-up). One newborn with unilaterally absent aEEG-SEP at 25 h of age had bilaterally present EEG-SEPs on the next day, and a favorable outcome.

CONCLUSIONS

aEEG-SEPs recorded during therapeutic hypothermia on the first postnatal days are reliable for assessing brain injury severity. Adding SEP into routine aEEG brain monitoring offers an additional tool for very early outcome prediction after birth asphyxia.

Cortical responses to tactile stimuli in preterm infants

The conventional assessment of preterm somatosensory functions using averaged cortical responses to electrical stimulation ignores the characteristic components of preterm somatosensory evoked responses (SERs). Our study aimed to systematically evaluate the occurrence and development of SERs after tactile stimulus in preterm infants. We analysed SERs performed during 45 electroencephalograms (EEGs) from 29 infants at the mean post-menstrual age of 30.7 weeks. Altogether 2,087 SERs were identified visually at single-trial level from unfiltered signals capturing also their slowest components. We observed salient SERs with a high-amplitude slow component at a high success rate after hand (95%) and foot (83%) stimuli. There was a clear developmental change in both the slow wave and the higher-frequency components of the SERs. Infants with intraventricular haemorrhage (IVH; eleven infants) had initially normal SERs, but those with bilateral IVH later showed a developmental decrease in the ipsilateral SER occurrence after 30 weeks of post-menstrual age. Our study shows that tactile stimulus applied at bedside elicits salient SERs with a large slow component and an overriding fast oscillation, which are specific to the preterm period. Prior experimental research indicates that such SERs allow studying both subplate and cortical functions. Our present findings further suggest that they might offer a window to the emergence of neurodevelopmental sequelae after major structural brain lesions and, hence, an additional tool for both research and clinical neurophysiological evaluation of infants before term age.

Bedside neurophysiological tests can identify neonates with stroke leading to cerebral palsy

OBJECTIVE

The unspecific symptoms of neonatal stroke still challenge its bedside diagnosis. We studied the accuracy of routine electroencephalography (EEG) and simultaneously recorded somatosensory evoked potentials (EEG-SEP) for diagnosis and outcome prediction of neonatal stroke.

METHODS

We evaluated EEG and EEG-SEPs from a hospital cohort of 174 near-term neonates with suspected seizures or encephalopathy, 32 of whom were diagnosed with acute ischemic or hemorrhagic stroke in MRI. EEG was scored for background activity and seizures. SEPs were classified as present or absent. Developmental outcome of stroke survivors was evaluated from medical records at 8- to 18-months age.

RESULTS

The combination of continuous EEG and uni- or bilaterally absent SEP (n = 10) was exclusively seen in neonates with a middle cerebral artery (MCA) stroke (specificity 100%). Moreover, 80% of the neonates with this finding developed with cerebral palsy. Bilaterally present SEPs did not exclude stroke, but predicted favorable neuromotor outcome in stroke survivors (positive predictive value 95%).

CONCLUSIONS

Absent SEP combined with continuous EEG background in near-term neonates indicates an MCA stroke and a high risk for cerebral palsy.

SIGNIFICANCE

EEG-SEP offers a bedside method for diagnostic screening and a reliable prediction of neuromotor outcome in neonates suspected of having a stroke.

A dataset of neonatal EEG recordings with seizure annotations

Neonatal seizures are a common emergency in the neonatal intensive care unit (NICU). There are many questions yet to be answered regarding the temporal/spatial characteristics of seizures from different pathologies, response to medication, effects on neurodevelopment and optimal detection. The dataset presented in this descriptor contains EEG recordings from human neonates, the visual interpretation of the EEG by the human experts, supporting clinical data and codes to assist access. Multi-channel EEG was recorded from 79 term neonates admitted to the NICU at the Helsinki University Hospital. The median recording duration was 74 min (IQR: 64 to 96 min). The presence of seizures in the EEGs was annotated independently by three experts. An average of 460 seizures were annotated per expert in the dataset; 39 neonates had seizures and 22 were seizure free, by consensus. The dataset can be used as a reference set of neonatal seizures, in studies of inter-observer agreement and for the development of automated methods of seizure detection and other EEG analyses.