Tracking the Dynamics of the Cerebral Autoregulation Response to Sudden Changes of PaCO2

Abstract

Cerebral autoregulation has been studied by linear filter systems, with arterial blood pressure (ABP) as the input and cerebral blood flow velocity (CBFV – from transcranial Doppler Ultrasound) as the output. The current work extends this by using adaptive filters to investigate the dynamics of time-varying cerebral autoregulation during step-wise changes in arterial pCO2. Cerebral autoregulation was transiently impaired in 12 normal adult volunteers, by switching inspiratory air to CO2/air mixture (5% CO2, 30% O2 and 65% N2) for approximately 2 minutes and then back to the ambient air, causing step-wise changes in end-tidal CO2 (EtCO2). Simultaneously, ABP and CBFV were recorded continuously. Simulated data corresponding to the same protocol were also generated using an established physiological model, in order to refine the signal analysis methods. This consisted of adaptive filter modeling followed by the extraction of time-varying autoregulatory parameters (phase-lead, autoregulation index – ARI). The adaptive filter was able to follow rapid changes in autoregulation, as was confirmed in the simulated data. In the recorded signals, there was a slow decrease in autoregulatory function following the step-wise increase in pCO2 (not reaching a steady state within approximately 2 minutes), with a more rapid change in autoregulation on return to normocapnia. Adaptive filter modeling can demonstrate time-varying autoregulation. Impairment and recovery of autoregulation during transient increases in EtCO2 occur at differing rates.