Novel EEG metric correlates with intracranial pressure in an animal model

Abstract

Introduction Intracranial Pressure (ICP) can be continuously and reliably measured using invasive monitoring through an external ventricular catheter or an intraparenchymal probe. We explore Electroencephelograhy (EEG) to identify a reliable real time, non-invasive ICP correlate. Methods Utilizing a previously described porcine model of intracranial hypertension, we examine the cross correlation between ICP time series and the slope of the EEG power spectral density as described by Φ. We calculate Φ= tan−1(slope of PSD) and normalized it by π where slope is that of the power-law fit (log frequency versus log power) to the power spectral density of the EEG signal. Additionally, we explore the relationship between the Φ time series and cerebral perfusion pressure (CPP). A total of 11 intracranial hypertension episodes across three different animals are studied. Results Mean correlation between Φ-angle and ICP was -0.85 (0.15); mean correlation with CPP 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). Conclusion EEG Φ-angle is a promising real-time noninvasive measure of ICP/cerebral perfusion using surface electroencephalography. While intra-species variation is presumably minimal, validation in human subjects is needed.