EEG Maturational Age Estimation: A Comparison of Visual and Automated Interpretation of the EEG in Preterm Infants

<b>Aim:</b> To assess the inter-rater agreement and accuracy of human experts' estimate of EEG maturational age (EMA) and a computer algorithm's estimate of EMA over the first days after birth in a cohort of normally developing preterm infants. In addition, we explore the influence of post-natal age (PNA) on EMA estimates. <b>Methods</b>: Analysis was performed on EEG records from newborns determined appropriate for gestational age (GA) with favorable neurodevelopment at 2 years of age and without significant neurological compromise at time of EEG monitoring. Three 1h epochs of EEG were selected from 29 newborns with GA ranging from 23 to <32 weeks, within 72 h of birth. EEG epochs were visually assessed by two pediatric neurologists and a computer algorithm. In addition, the full, long-duration EEG recording of each newborn was assessed by one pediatric neurologist. EMA estimates were compared to GA using Pearson's correlation coefficient (<i>r</i>) and bias and standard deviation of error (SDE). Intra-newborn agreements for the EMA estimates were assessed using standard deviation. Linear mixed-effects models were used to quantify the effect of PNA on EMA estimates. <b>Results</b>: The algorithm provides a more accurate estimate of GA using 1 h EEG epochs for correlation and bias: algorithm <i>r</i> = 0.83 vs. experts <i>r</i> = 0.60 and 0.66, <i>p</i> < 0.05 for <i>n</i> = 29; algorithm bias = -0.8 days vs. experts' bias = 3.6 and 7.0 days, <i>p</i> < 0.01 for <i>n</i> = 29. SDE of 8.7 days for the algorithm was not significantly lower compared to the experts' SDE = 12.4 and 13.2 days, <i>p</i> > 0.05. The algorithm has higher intra-newborn agreement compared to the experts: algorithm SDE = 4.9 days vs. experts SDE = 7.4 and 7.4 days, <i>p</i> = 0.027. For the two experts, increasing PNA is associated with an increase in EMA estimates of 6.6 days/days and 3.7 days/days. The assessment of full, long-duration EEG recordings improved the experts' estimate of EMA (<i>r</i> = 0.82; SDE = 9.2 days). <b>Conclusions</b>: Automated analysis outperforms visual interpretation of the EEG at estimating EMA for short-duration EEG recordings. PNA is an important factor in EMA estimates.