Novel EEG Metric Correlates with Intracranial Pressure in an Animal Model

Abstract

Background: Intracranial pressure (ICP) can be continuously and reliably measured using invasive monitoring through an external ventricular catheter or an intraparenchymal probe. We explore electroencephalography (EEG) to identify a reliable real-time noninvasive ICP correlate. Methods: Using a previously described porcine model of intracranial hypertension, we examined the cross correlation between ICP time series and the slope of the EEG power spectral density as described by ϕ. We calculated ϕ as tan−1 (slope of power spectral density) and normalized it by π, where slope is that of the power-law fit (log frequency vs. log power) to the power spectral density of the EEG signal. Additionally, we explored the relationship between the ϕ time series and cerebral perfusion pressure. A total of 11 intracranial hypertension episodes across three different animals were studied. Results: The mean correlation between ϕ angle and ICP was − 0.85 (0.15); the mean correlation with cerebral perfusion pressure was 0.92 (0.02). Significant correlation occurred at zero lag. In the absence of intracranial hypertension, the absolute value of the ϕ angle was greater than 0.9 (mean 0.936 radians). However, during extreme intracranial hypertension causing cerebral circulatory arrest, the ϕ angle is on average below 0.9 radians (mean 0.855 radians). Conclusions: EEG ϕ angle is a promising real-time noninvasive measure of ICP/cerebral perfusion using surface electroencephalography.