Seizures in Preterm Infants:

2D Wavelet-Scalogram Deep-Learning for Seizures Pattern Identification in the Post-Hypoxic-Ischemic EEG of Preterm Fetal Sheep

Neonatal seizures after an hypoxic-ischemic (HI) event in preterm newborns can contribute to neural injury and cause impaired brain development. Preterm neonatal seizures are often not detected or their occurrence underestimated. Therefore, there is a need to improve knowledge about preterm seizures that can help establish diagnostic tools for accurate identification of seizures and for determining morphological differences. We have previously shown the superior utility of deep-learning algorithms for the accurate identification and quantification of post-HI microscale epileptiform transients (e.g., gamma spikes and sharp waves) in preterm fetal sheep models; before the irreversible secondary phase of cerebral energy failure starts by the bursts of high-amplitude stereotypic evolving seizures (HAS) in the signal. We have previously developed successful deep-learning algorithms that accurately identify and quantify the micro-scale transients, during the latent phase. Building up on our deep-learning strategies, this work introduces a real-time deep-learning-based pattern fusion approach to identify HAS in the 256Hz sampled post-HI data from our preterm fetuses. Here, for the first time, we propose a 17-layer deep convolutional neural network (CNN) classifier fed with 2D wavelet-scalogram (WS) images of the EEG patterns for accurate seizure identification. The WS-CNN classifier was cross-validated over 1812 manually annotated EEG segments during ~6 to 48 hours post-HI recordings. The classifier accurately recognized HAS patterns with 97.19% overall accuracy (AUC = 0.96).Clinical relevance-The promising results from this preliminary work indicate the ability of the proposed WS-CNN pattern classifier to identify HI-related seizures in the neonatal preterm brain using 256Hz EEG; the frequency commonly used clinically for data collection.

CARFS7: A guide and proforma for reading a preterm neonate's EEG

OBJECTIVES

The important role of the EEG in preterm and term babies in investigating brain function and seizures, predicting outcomes, evaluating therapeutic interventions and decision-making is being increasingly acknowledged. Development of the brain in the last trimester of pregnancy results in rapid changes in the EEG patterns in this period. Acquiring and interpreting the EEG of a preterm baby can be challenging. The aim of this study was to develop a proforma titled CARFS⁷ (Continuity, Amplitude, Reactivity, Frequency, Synchrony, Symmetry, Sleep, Sharps, Shapes, Size and Seizures) to enable neurologists to read EEGs of premature babies with greater confidence, ease and accuracy and produce a report more easily repeatable and homogenous among operators.

METHODS

The CARFS⁷proforma was developed based on a literature review and the personal experience of the authors. The parameters of the EEG evaluated and scored in the proforma are Continuity, Amplitude, Reactivity/Variability, Frequency, Synchrony, Symmetry, Sleep, Sharps, Shapes/Patterns, Size and Seizures. We also assessed the interrater reliability of the proposed scoring system incorporated in the proforma.

RESULTS

CARFS⁷ proforma incorporates a number of parameters that help evaluate the preterm EEG. The interrater reliability of the proposed scoring system in the CARFS⁷proforma was high.

CONCLUSIONS

CARFS⁷ is a user friendly proforma for reading EEGs in the preterm infant. Interrater reliability using Cohen's k shows high agreement between two child neurologists who independently rated the EEGs of 25 premature babies using this proforma. CARFS⁷ has the potential to provide, accurate, reproducible and valuable information on brain function in the preterm infant in clinical practice.

How Early Can a Seizure Happen? Pathophysiological Considerations of Extremely Premature Infant Brain Development

Seizures in neonates represent a neurologic emergency requiring prompt recognition, determination of etiology, and treatment. Yet, the definition and identification of neonatal seizures remain challenging and controversial, in part due to the unique physiology of brain development at this life stage. These issues are compounded when considering seizures in premature infants, in whom the complexities of brain development may engender different clinical and electrographic seizure features at different points in neuronal maturation. In extremely premature infants (< 28 weeks gestational age), seizure pathophysiology has not been explored in detail. This review discusses the physiological and structural development of the brain in this developmental window, focusing on factors that may lead to seizures and their consequences at this early time point. We hypothesize that the clinical and electrographic phenomenology of seizures in extremely preterm infants reflects the specific pathophysiology of brain development in that age window.

Seizures in newborn infants without hypoxic ischemic encephalopathy - antenatal and labor-related risk factors: a case-control study

Objective: To identify antepartum and intrapartum risk factors for neonatal seizures in the absence of hypoxic ischemic encephalopathy (HIE).Methods: Population-based case-control study. Of 98 484 births, 40 newborns at 34 gestational weeks or later had seizures within the first 7 days of life. Cases (n = 40) and controls (n = 160) were retrieved from the University hospitals of Örebro for 1994-2013 and Uppsala for 2003-2013. Demographics and characteristics of pregnancy, labor, delivery, and neonatal data were analyzed. Crude odds ratio (OR) and adjusted odds ratios (AOR) with 95% confidence intervals (CIs) for antenatal and intrapartum factors were calculated using logistic regression analysis. Main outcome measure was neonatal seizures within the first 7 days of life.Results: The incidence of neonatal seizures without HIE was 0.41/1000 live births. Antenatal risk factors for neonatal seizures were as follows: short maternal stature (AOR: 5.4; 1.8-16.5); previous caesarean section (AOR: 4.8; 1.5-15.0); and assisted fertilization (AOR: 6.8; 1.3-35.2). Intrapartum risk factors were as follows: induction of labor (AOR: 5.7; 1.8-17.7); preterm birth (AOR: 13.5; 3.7-48.9); and head circumference >37 cm (AOR: 6.9; 1.4-34.8).Conclusions: Preterm birth was the strongest risk factor for neonatal seizures in the absence of HIE. The results also indicate that feto-pelvic disproportion is associated with the occurrence of seizures.Rationale: Antepartum and intrapartum risk factors for newborn seizures in the absence of HIE were investigated in a case-control study. Out of 98 484 births at 34 gestational weeks or more, 40 newborns had seizures without HIE. All had a normal Apgar score although they later presented with seizures. Preterm birth was the strongest risk factor (OR: 13.5; 95% CI: 3.7-48.9). Our results also indicate that feto-pelvic disproportion is of importance. Furthermore, a history of prior caesarean was associated with seizures. This is the first study to assess obstetric risk factors for newborn seizures separate from those with seizures and concomitant HIE. The distinction is of importance due to different etiologies, treatments, and preventive strategies.