Spontaneous blood pressure oscillations and cerebral autoregulation

Abstract

The relationship between spontaneous oscillations in cerebral blood flow velocity (CBFV) and arterial blood pressure (ABP) was analysed in normal subjects in order to evaluate whether these relationships provide information about cerebral autoregulation. CBFV was measured using transcranial Doppler sonography and continuous ABP and heart rate using Finapres in 50 volunteers. Measurements were made over 5 min in a supine position and 6 min in a tilted position. Coefficients of variation were calculated using power- and cross-spectral analysis in order to quantify amplitudes within two frequency ranges: 3-9 cycles per min (cpm) (M-waves); and 9-20 cpm (R-waves). Correlations, coherence values, phase angle shifts and gains were also computed between corresponding waves in CBFV and in ABP. A clear correlation was seen for M-waves and R-waves between CBFV and ABP and coherence values were large enough to calculate phase angle shifts and gains. Phase angles for M-waves were larger and gains lower than was the case for R-waves, either tilted or supine. These data are consistent with a highpass filter model of cerebral autoregulation. Relatively high CBFV/ABP gain values (between 1.4 and 2.0) suggest that the principle of frequency-dependent vascular input impedances has to be considered in addition to autoregulatory feedback mechanisms. Spontaneous ABP oscillations in the M-wave and R-wave ranges may serve as a basis for continuous autoregulation monitoring.

Nonlinear Assessment of Cerebral Autoregulation from Spontaneous Blood Pressure and Cerebral Blood Flow Fluctuations

“…Thus, a challenging question is whether or not the dominant spontaneous oscillations at a higher frequency (e.g., entrained by respiration at < 0.1 Hz) can be used to assess cerebral autoregulation. It has been proposed that autoregulatory mechanisms act as a high-pass filter -cybernetic model (Diehl et al 1995(Diehl et al , 1998, being more active at low frequencies (< 0.1 Hz) and less effective at high frequencies ( > 0.1 Hz). Many studies that are based on the transfer function analysis support the frequency dependence of cerebral autoregulation (Giller 1990;Giller and Iacopino 1997;Zhang et al 1998;Hamner et al 2004) though there is no established physiological neural pathway that can account for the high-pass filter mechanism.…”

“…Reliable and noninvasive assessment of cerebral autoregulation is a major challenge in medical diagnostics and post-stroke care. Conventional approaches model autoregulation with BP as input and blood flow as output (using blood flow velocity (BFV) measured by transcranial Doppler ultrasound and beat-to-beat peripheral BP) (Diehl et al 1995(Diehl et al , 1998Olufsen et al 2002;Carey et al 2003) and assume that signals are composed of superimposed sinusoidal oscillations of constant amplitude and period at a presumed frequency range. However, BP and BFV signals recorded in clinical settings are often nonstationary, and are modulated by nonlinearly interacting processes at multiple time-scales corresponding to the beat-to-beat systolic pressure, respiration, spontaneous BP fluctuations, and those induced by interventions.…”

Altered phase interactions between spontaneous blood pressure and flow fluctuations in type 2 diabetes mellitus: Nonlinear assessment of cerebral autoregulation

“…It has been proposed that cerebral autoregulatory mechanisms act as a high-pass filtercybernetic model [8,13], being more active at lower frequencies (<0.1Hz) and less effective for faster spontaneous fluctuations and at respiration frequency. This model predicts that, for a normal cerebral autoregulation, a very slow oscillation in BP (frequency approaching zero) will generate an oscillation in BFV with very small amplitude and an advanced phase close to 90 degrees while a fast oscillation in BP will be completely transmitted to a BFV oscillation with phase lag close to zero.…”

“…A transfer function is typically used to explore the relationship between blood pressure (BP) and blood flow velocity (BFV) by calculating gain and phase shift between the BP and BFV power spectra [2,8,[10][11][12][13][14][15][16]. In this approach, it is presumed that signals are stationary, and are composed of superimposed sinusoidal oscillations of constant amplitude and period at a pre-determined frequency range.…”

Coherent hemodynamics spectroscopy in a single step

“…Those maneuvers have typically been used to induce oscillations at ~0.1 Hz in MAP and cerebral blood flow that have been measured using finger plethysmography and transcranial Doppler ultrasound (TCD), respectively [6]. Using transfer function analysis, MAP and CBF oscillations have been used to assess cerebral autoregulation [7]. Understanding the interplay between MAP, CBF, and associated hemodynamic changes is the goal of hemodynamic models.…”