Rapid pressure-to-flow dynamics of cerebral autoregulation induced by instantaneous changes of arterial CO2

Time-domain methods for quantifying dynamic cerebral blood flow autoregulation: Review and recommendations. A white paper from the Cerebrovascular Research Network (CARNet)

Cerebral Autoregulation (CA) is an important physiological mechanism stabilizing cerebral blood flow (CBF) in response to changes in cerebral perfusion pressure (CPP). By maintaining an adequate, relatively constant supply of blood flow, CA plays a critical role in brain function. Quantifying CA under different physiological and pathological states is crucial for understanding its implications. This knowledge may serve as a foundation for informed clinical decision-making, particularly in cases where CA may become impaired. The quantification of CA functionality typically involves constructing models that capture the relationship between CPP (or arterial blood pressure) and experimental measures of CBF. Besides describing normal CA function, these models provide a means to detect possible deviations from the latter. In this context, a recent white paper from the Cerebrovascular Research Network focused on Transfer Function Analysis (TFA), which obtains frequency domain estimates of dynamic CA. In the present paper, we consider the use of time-domain techniques as an alternative approach. Due to their increased flexibility, time-domain methods enable the mitigation of measurement/physiological noise and the incorporation of nonlinearities and time variations in CA dynamics. Here, we provide practical recommendations and guidelines to support researchers and clinicians in effectively utilizing these techniques to study CA.

The INfoMATAS project: Methods for assessing cerebral autoregulation in stroke

Cerebral autoregulation refers to the physiological mechanism that aims to maintain blood flow to the brain approximately constant when blood pressure changes. Impairment of this protective mechanism has been linked to a number of serious clinical conditions, including carotid stenosis, head trauma, subarachnoid haemorrhage and stroke. While the concept and experimental evidence is well established, methods for the assessment of autoregulation in individual patients remains an open challenge, with no gold-standard having emerged. In the current review paper, we will outline some of the basic concepts of autoregulation, as a foundation for experimental protocols and signal analysis methods used to extract indexes of cerebral autoregulation. Measurement methods for blood flow and pressure are discussed, followed by an outline of signal pre-processing steps. An outline of the data analysis methods is then provided, linking the different approaches through their underlying principles and rationale. The methods cover correlation based approaches (e.g. Mx) through Transfer Function Analysis to non-linear, multivariate and time-variant approaches. Challenges in choosing which method may be 'best' and some directions for ongoing and future research conclude this work.

Can interhemispheric desynchronization of cerebral blood flow anticipate upcoming vasospasm in aneurysmal subarachnoid haemorrhage patients?

BACKGROUND

Asymmetry of cerebral autoregulation (CA) was demonstrated in patients after aneurysmal subarachnoid haemorrhage (aSAH). A classical method for CA assessment requires simultaneous measurement of both arterial blood pressure (ABP) and cerebral blood flow velocity (CBFV). In this study, we have proposed a cerebral blood flow asymmetry index based only on CBFV and analysed its association with the occurrence of vasospasm after aSAH.

NEW METHOD

The phase shifts (PS) between slow oscillations in left and right CBFV (side-to-side PS) and between ABP and CBFV (CBFV-ABP PS) were estimated using multichannel matching pursuit (MMP) and cross-spectral analysis.

RESULTS

We retrospectively analysed data collected from 45 aSAH patients (26 with vasospasm). Data were analysed up to 7th day after aSAH unless the vasospasm was detected earlier. A progressive asymmetry, manifested by a gradual increase in side-to-side PS on consecutive days after aSAH, was observed in patients who developed vasospasm (R_adj² = 0.14, p = 0.009). In these patients, early side-to-side PS was more positive than in patients without vasospasm (2.8° ± 5.6° vs -1.7° ± 5.7°, p = 0.011). No such a difference was found in CBFV-ABP PS. Patients with positive side-to-side PS were more likely to develop vasospasm than patients with negative side-to-side PS (21/7 vs 5/12, p = 0.0047).

COMPARISON WITH EXISTING METHOD

MMP, in contrast to the spectral approach, accounts for non-stationarity of analysed signals. MMP applied to the PS estimation reflects the cerebral blood flow asymmetry in aSAH better than the spectral analysis.

CONCLUSIONS

Changes in side-to-side PS might be helpful to identify patients who are at risk of vasospasm.

Revisiting human cerebral blood flow responses to augmented blood pressure oscillations

KEY POINTS

Cerebral autoregulation is most effective in buffering against pressure fluctuations slower than 0.03 Hz (∼30 s). This suggests that frequency bands for characterizing cerebral autoregulation should be redefined Low cross-spectral coherence below 0.03 Hz highlights the limitations of transfer function approaches Haemodynamic changes induced by lower body pressure could not fully explain the differences in autoregulation estimated from spontaneous vs. augmented fluctuations, and thus, observations of spontaneous fluctuations should not be relied on whenever possible.

ABSTRACT

There is currently little empirical basis for time scales that are considered to be most significant in cerebrovascular counter-regulation of changes in arterial pressure. Although it is well established that cerebral autoregulation behaves as a 'high-pass' filter, recommended frequency bands have been largely arbitrarily determined. To test effectiveness of cerebral autoregulation, we refined oscillatory lower body pressure (LBP) to augment resting pressure fluctuations below 0.1 Hz by a factor of two in 13 young male volunteers, and thoroughly characterized the time and frequency responses of cerebral autoregulation. We observed that despite a threefold increase in arterial pressure power <0.03 Hz with oscillatory LBP, there was no change in cerebral blood flow power, indicating near perfect counter-regulation. By contrast, in the range 0.03-0.10 Hz, both cerebral blood flow and arterial pressure power more than doubled. Our data demonstrate that cerebral autoregulation is most effective in buffering against pressure fluctuations slower than 0.03 Hz (∼30 s). This suggests that frequency bands of interest should be redefined and recording length should be increased considerably to account for this. Furthermore, low cross-spectral coherence below 0.03 Hz, even when pressure fluctuations were augmented, highlights the uncertainty in transfer function approaches and the need to either report precision or use non-linear approaches. Finally, haemodynamic changes induced by LBP could not fully explain the differences in autoregulation estimated from spontaneous vs. augmented fluctuations, and thus, observations of spontaneous fluctuations should not be relied on whenever possible.

Applying time-frequency analysis to assess cerebral autoregulation during hypercapnia

OBJECTIVE

Classic methods for assessing cerebral autoregulation involve a transfer function analysis performed using the Fourier transform to quantify relationship between fluctuations in arterial blood pressure (ABP) and cerebral blood flow velocity (CBFV). This approach usually assumes the signals and the system to be stationary. Such an presumption is restrictive and may lead to unreliable results. The aim of this study is to present an alternative method that accounts for intrinsic non-stationarity of cerebral autoregulation and the signals used for its assessment.

METHODS

Continuous recording of CBFV, ABP, ECG, and end-tidal CO2 were performed in 50 young volunteers during normocapnia and hypercapnia. Hypercapnia served as a surrogate of the cerebral autoregulation impairment. Fluctuations in ABP, CBFV, and phase shift between them were tested for stationarity using sphericity based test. The Zhao-Atlas-Marks distribution was utilized to estimate the time-frequency coherence (TFCoh) and phase shift (TFPS) between ABP and CBFV in three frequency ranges: 0.02-0.07 Hz (VLF), 0.07-0.20 Hz (LF), and 0.20-0.35 Hz (HF). TFPS was estimated in regions locally validated by statistically justified value of TFCoh. The comparison of TFPS with spectral phase shift determined using transfer function approach was performed.

RESULTS

The hypothesis of stationarity for ABP and CBFV fluctuations and the phase shift was rejected. Reduced TFPS was associated with hypercapnia in the VLF and the LF but not in the HF. Spectral phase shift was also decreased during hypercapnia in the VLF and the LF but increased in the HF. Time-frequency method led to lower dispersion of phase estimates than the spectral method, mainly during normocapnia in the VLF and the LF.

CONCLUSION

The time-frequency method performed no worse than the classic one and yet may offer benefits from lower dispersion of phase shift as well as a more in-depth insight into the dynamic nature of cerebral autoregulation.

Impaired cerebral autoregulation: measurement and application to stroke

Cerebral autoregulation (CA) is a protective mechanism that maintains cerebral blood flow at a relatively constant level despite fluctuations of cerebral perfusion pressure or arterial blood pressure. It is a universal physiological mechanism that may involve myogenic, neural control as well as metabolic regulations of cerebral vasculature in response to changes in pressure or cerebral blood flow. Traditionally, CA has been represented by a sigmoid curve with a wide plateau between about 50 mm Hg and 170 mm Hg of steady-state changes in mean arterial pressure, defined as static CA. With the advent of transcranial Doppler, measurement of cerebral blood flow in response to transient changes in arterial pressure has been used to assess dynamic CA. However, a gold standard for measuring CA is not currently available. Stroke has been the leading cause of long-term adult disability throughout the world. A better understanding of CA and its response to pathological derangements can help assess the severity of stroke, guide management decisions, assess response to interventions and provide prognostic information. The objective of this review is to provide a comprehensive insight about physiology of autoregulation, measurement methodologies and clinical applications in stroke to help build a consensus for what should be included in an internationally agreed protocol for CA testing and monitoring, and to promote its translation into clinical bedside practice for stroke management.

Cerebrovascular effects of the thigh cuff maneuver

Arterial hypotension can be induced by sudden release of inflated thigh cuffs (THC), but its effects on the cerebral circulation have not been fully described. In nine healthy subjects [aged 59 (9) yr], bilateral cerebral blood flow velocity (CBFV) was recorded in the middle cerebral artery (MCA), noninvasive arterial blood pressure (BP) in the finger, and end-tidal CO2 (ETCO2) with nasal capnography. Three THC maneuvers were performed in each subject with cuff inflation 20 mmHg above systolic BP for 3 min before release. Beat-to-beat values were extracted for mean CBFV, BP, ETCO2 , critical closing pressure (CrCP), resistance-area product (RAP), and heart rate (HR). Time-varying estimates of the autoregulation index [ARI(t)] were also obtained using an autoregressive-moving average model. Coherent averages synchronized by the instant of cuff release showed significant drops in mean BP, CBFV, and RAP with rapid return of CBFV to baseline. HR, ETCO2 , and ARI(t) were transiently increased, but CrCP remained relatively constant. Mean values of ARI(t) for the 30 s following cuff release were not significantly different from the classical ARI [right MCA 5.9 (1.1) vs. 5.1 (1.6); left MCA 5.5 (1.4) vs. 4.9 (1.7)]. HR was strongly correlated with the ARI(t) peak after THC release (in 17/22 and 21/24 recordings), and ETCO2 was correlated with the subsequent drop in ARI(t) (19/22 and 20/24 recordings). These results suggest a complex cerebral autoregulatory response to the THC maneuver, dominated by myogenic mechanisms and influenced by concurrent changes in ETCO2 and possible involvement of the autonomic nervous system and baroreflex.