Cerebral autoregulation is the intrinsic ability of the brain to maintain adequate cerebral perfusion in the presence of blood pressure changes. A large number of methods to assess the quality of cerebral autoregulation have been proposed over the last 30 years. However, no single method has been universally accepted as a gold standard. Therefore, the choice of which method to employ to quantify cerebral autoregulation remains a matter of personal choice. Nevertheless, given the concept that cerebral autoregulation represents the dynamic relationship between blood pressure (stimulus or input) and cerebral blood flow (response or output), transfer function analysis became the most popular approach adopted in studies based on spontaneous fluctuations of blood pressure. Despite its sound theoretical background, the literature shows considerable variation in implementation of transfer function analysis in practice, which has limited comparisons between studies and hindered progress towards clinical application. Therefore, the purpose of the present white paper is to improve standardisation of parameters and settings adopted for application of transfer function analysis in studies of dynamic cerebral autoregulation. The development of these recommendations was initiated by (but not confined to) theCerebral Autoregulation Research Network(CARNet -www.car-net.org).

Assessment of cerebral autoregulation is an important adjunct to measurement of cerebral blood flow for diagnosis, monitoring or prognosis of cerebrovascular disease. The most common approach tests the effects of changes in mean arterial blood pressure on cerebral blood flow, known as pressure autoregulation. A 'gold standard' for this purpose is not available and the literature shows considerable disparity of methods and criteria. This is understandable because cerebral autoregulation is more a concept rather than a physically measurable entity. Static methods utilize steady-state values to test for changes in cerebral blood flow (or velocity) when mean arterial pressure is changed significantly. This is usually achieved with the use of drugs, shifts in blood volume or by observing spontaneous changes. The long time interval between measurements is a particular concern in many of the studies reviewed. Parallel changes in other critical variables, such as pCO2, haematocrit, brain activation and sympathetic tone, are rarely controlled for. Proposed indices of static autoregulation are based on changes in cerebrovascular resistance, on parameters of the linear regression of flow/velocity versus pressure changes, or only on the absolute changes in flow. The limitations of studies which assess patient groups rather than individual cases are highlighted. Newer methods of dynamic assessment are based on transient changes in cerebral blood flow (or velocity) induced by the deflation of thigh cuffs, Valsalva manoeuvres, tilting and induced or spontaneous oscillations in mean arterial blood pressure. Dynamic testing overcomes several limitations of static methods but it is not clear whether the two approaches are interchangeable. Classification of autoregulation performance using dynamic methods has been based on mathematical modelling, coherent averaging, transfer function analysis, crosscorrelation function or impulse response analysis. More research on reproducibility and inter-method comparisons is urgently needed, particularly involving the assessment of pressure autoregulation in individuals rather than patient groups.

Brain function critically depends on a close matching between metabolic demands, appropriate delivery of oxygen and nutrients, and removal of cellular waste. This matching requires continuous regulation of cerebral blood flow (CBF), which can be categorized into four broad topics: 1) autoregulation, which describes the response of the cerebrovasculature to changes in perfusion pressure, 2) vascular reactivity to vasoactive stimuli [including carbon dioxide (CO2)], 3) neurovascular coupling (NVC), i.e., the CBF response to local changes in neural activity (often standardized cognitive stimuli in humans), and 4) endothelium-dependent responses. This review focuses primarily on autoregulation and its clinical implications. To place autoregulation in a more precise context, and to better understand integrated approaches in the cerebral circulation, we also briefly address reactivity to CO2 and NVC. In addition to our focus on effects of perfusion pressure (or blood pressure), we describe the impact of select stimuli on regulation of CBF (i.e., arterial blood gases, cerebral metabolism, neural mechanisms, and specific vascular cells), the inter-relationships between these stimuli, and implications for regulation of CBF at the level of large arteries and the microcirculation. We review clinical implications of autoregulation in aging, hypertension, stroke, mild cognitive impairment, anesthesia, and dementias. Finally, we discuss autoregulation in the context of common daily physiological challenges, including changes in posture (e.g., orthostatic hypotension, syncope) and physical activity.

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Short-term regulation of cerebral blood flow (CBF) is controlled by myogenic, metabolic and neurogenic mechanisms, which maintain flow within narrow limits, despite large changes in arterial blood pressure (ABP). Static cerebral autoregulation (CA) represents the steady-state relationship between CBF and ABP, characterized by a plateau of nearly constant CBF for ABP changes in the interval 60-150 mmHg. The transient response of the CBF-ABP relationship is usually referred to as dynamic CA and can be observed during spontaneous fluctuations in ABP or from sudden changes in ABP induced by thigh cuff deflation, changes in posture and other manoeuvres. Modelling the dynamic ABP-CBFV relationship is an essential step to gain better insight into the physiology of CA and to obtain clinically relevant information from model parameters. This paper reviews the literature on the application of CA models to different clinical conditions. Although mathematical models have been proposed and should be pursued, most studies have adopted linear input-output ('black-box') models, despite the inherently non-linear nature of CA. The most common of these have been transfer function analysis (TFA) and a second-order differential equation model, which have been the main focus of the review. An index of CA (ARI), and frequency-domain parameters derived from TFA, have been shown to be sensitive to pathophysiological changes in patients with carotid artery disease, stroke, severe head injury, subarachnoid haemorrhage and other conditions. Non-linear dynamic models have also been proposed, but more work is required to establish their superiority and applicability in the clinical environment. Of particular importance is the development of multivariate models that can cope with time-varying parameters, and protocols to validate the reproducibility and ranges of normality of dynamic CA parameters extracted from these models.

The linear dynamic relationship between systemic arterial blood pressure (ABP) and cerebral blood flow velocity (CBFV) was studied by time- and frequency-domain analysis methods. A nonlinear moving-average approach was also implemented using Volterra-Wiener kernels. In 47 normal subjects, ABP was measured with Finapres and CBFV was recorded with Doppler ultrasound in both middle cerebral arteries at rest in the supine position and also during ABP drops induced by the sudden deflation of thigh cuffs. Impulse response functions estimated by Fourier transfer function analysis, a second-order mathematical model proposed by Tiecks, and the linear kernel of the Volterra-Wiener moving-average representation provided reconstructed velocity model responses, for the same segment of data, with significant correlations to CBFV recordings corresponding to r = 0.52 ± 0.19, 0.53 ± 0.16, and 0.67 ± 0.12 (mean ± SD), respectively. The correlation coefficient for the linear plus quadratic kernels was 0.82 ± 0.08, significantly superior to that for the linear models ( P < 10−6). The supine linear impulse responses were also used to predict the velocity transient of a different baseline segment of data and of the thigh cuff velocity response with significant correlations. In both cases, the three linear methods provided equivalent model performances, but the correlation coefficient for the nonlinear model dropped to 0.26 ± 0.25 for the baseline test set of data and to 0.21 ± 0.42 for the thigh cuff data. Whereas it is possible to model dynamic cerebral autoregulation in humans with different linear methods, in the supine position a second-order nonlinear component contributes significantly to improve model accuracy for the same segment of data used to estimate model parameters, but it cannot be automatically extended to represent the nonlinear component of velocity responses of different segments of data or transient changes induced by the thigh cuff test.

Arterial pCO2 is known to influence cerebral autoregulation but its effect on the dynamic relationship between mean arterial blood pressure (ABP) and mean cerebral blood flow velocity (CBFV), obtained from spontaneous fluctuations in ABP, has not been established. In 16 normal subjects, ABP was measured non-invasively (Finapres), CBFV was estimated with Doppler ultrasound in the middle cerebral artery, and end-tidal CO2 (EtCO2) was measured with an infrared capnograph. Recordings were made before, during and after breathing a mixture of 5% CO2 in air. The coherence function, amplitude and phase frequency responses, and impulse and step responses for the effects of ABP on CBFV were calculated by spectral analysis of beat-to-beat changes in mean ABP and CBFV before (mean CO2 5.55 +/- 0.38 kPa), during (6.43 +/- 0.31 kPa) and after 5% CO2 (5.43 +/- 0.26 kPa). During 5% CO2, the coherence function and the amplitude frequency response were significantly increased for frequencies below 0.05 Hz and the phase was reduced for the frequency range 0.02-0.1 Hz. The impulse and step responses indicated that 5% CO2 reduces the efficiency of the autoregulatory mechanism. A 20.7% average increase in CBFV induced by a 14.4% increase in EtCO2 was found to be mediated by a 25.9% reduction in critical closing pressure, while the change in resistance area product was non-significant.

It remains unclear as to whether dynamic and static cerebral autoregulation (CA) are impaired in acute ischaemic stroke, and whether these changes are related to stroke subtype. This could have important implications with regard to post-stroke prognosis and the management of blood pressure (BP) in the acute post-ictal period. Using transcranial Doppler ultrasonography and non-invasive manipulation of BP, we compared both mechanisms in 61 patients with ischaemic stroke within 96 h of ictus, and 54 age- and sex-matched controls. There was no difference in static and dynamic CA indices between the various stroke subtypes. Combining all stroke subtypes dynamic autoregulation, as measured using thigh cuff release, was significantly impaired in both the affected and non-affected stroke hemispheres compared to controls (mean autoregulation index 4.1 ± 3.3, 4.8 ± 3.1 and 6.2 ± 2.3, respectively, p < 0.05). By comparison static autoregulation, assessed using isometric hand grip and thigh cuff inflation, was not significantly different. In conclusion, dynamic but not static CA appears to be globally impaired in acute ischaemic stroke. This deserves further study and may identify possibilities for therapeutic intervention.