Comparison of wavelet and correlation indices of cerebral autoregulation in a pediatric swine model of cardiac arrest

Xiuyun Liu,Joseph Donnelly,Raymond Koehler,Marek Czosnyka,Xiao Hu,Peter Smielewski,Jennifer K Lee,Ken M Brady

doi:10.1038/s41598-020-62435-8

Abstract

Existing cerebrovascular blood pressure autoregulation metrics have not been translated to clinical care for pediatric cardiac arrest, in part because signal noise causes high index time-variability. We tested whether a wavelet method that uses near-infrared spectroscopy (NIRS) or intracranial pressure (ICP) decreases index variability compared to that of commonly used correlation indices. We also compared whether the methods identify the optimal arterial blood pressure (ABPopt) and lower limit of autoregulation (LLA). 68 piglets were randomized to cardiac arrest or sham procedure with continuous monitoring of cerebral blood flow using laser Doppler, NIRS and ICP. The arterial blood pressure (ABP) was gradually reduced until it dropped to below the LLA. Several autoregulation indices were calculated using correlation and wavelet methods, including the pressure reactivity index (PRx and wPRx), cerebral oximetry index (COx and wCOx), and hemoglobin volume index (HVx and wHVx). Wavelet methodology had less index variability with smaller standard deviations. Both wavelet and correlation methods distinguished functional autoregulation (ABP above LLA) from dysfunctional autoregulation (ABP below the LLA). Both wavelet and correlation methods also identified ABPopt with high agreement. Thus, wavelet methodology using NIRS may offer an accurate vasoreactivity monitoring method with reduced signal noise after pediatric cardiac arrest.

Highlights

Existing cerebrovascular blood pressure autoregulation metrics have not been translated to clinical care for pediatric cardiac arrest, in part because signal noise causes high index time-variability
We found that correlation between a near-infrared spectroscopy (NIRS)-derived cerebral blood volume measure and arterial blood pressure (ABP) was associated with outcome after pediatric cardiac arrest[4], we could not predict fine neurologic deficits with this method
We hypothesized that the wavelet method would reduce autoregulation index variability compared to the correlation method and that wavelet indices can distinguish functional from dysfunctional autoregulation in the developing brain after cardiac arrest

Summary

Introduction

Existing cerebrovascular blood pressure autoregulation metrics have not been translated to clinical care for pediatric cardiac arrest, in part because signal noise causes high index time-variability. We tested whether a wavelet method that uses near-infrared spectroscopy (NIRS) or intracranial pressure (ICP) decreases index variability compared to that of commonly used correlation indices. We compared whether the methods identify the optimal arterial blood pressure (ABPopt) and lower limit of autoregulation (LLA). Wavelet methodology using NIRS may offer an accurate vasoreactivity monitoring method with reduced signal noise after pediatric cardiac arrest. Our group validated a wavelet semblance method between ABP and ICP16 that was better able to identify the blood pressure lower limit of autoregulation (LLA) in piglets with intracranial hypertension than a commonly used, ICP-based, correlation metric called the pressure reactivity index (PRx)[17]. We hypothesized that the wavelet method would reduce autoregulation index variability compared to the correlation method and that wavelet indices can distinguish functional from dysfunctional autoregulation in the developing brain after cardiac arrest. We compared ABPopt values identified by wavelet to those from correlation metrics

Methods

Results

Conclusion