Reproducibility of dynamic cerebral autoregulation parameters: a multi-centre, multi-method study

Depression of dynamic cerebral autoregulation during neural activation: The role of responders and non-responders

Neurovascular coupling (NVC) interaction with dynamic cerebral autoregulation (dCA) remains unclear. We investigated the effect of task complexity and duration on the interaction with dCA. Sixteen healthy participants (31.6 ± 11.6 years) performed verbal fluency (naming-words (NW)) and serial subtraction (SS) paradigms, of varying complexity, at durations of 05, 30 and 60 s. The autoregulation index (ARI), was estimated from the bilateral middle cerebral artery blood velocity (MCAv) step response, calculated by transfer function analysis (TFA), for each paradigm during unstimulated (2 min) and neuroactivated (1 min) segments. Intraclass correlation (ICC) and coefficient of variation (CV) determined reproducibility for two visits and objective criteria were applied to classify responders (R) and non-responders (NoR) to task-induced MCAv increase. ICC values demonstrated fair reproducibility in all tasks. ARI decreased in right (RH) and left (LH) hemispheres, irrespective of paradigm complexity and duration (p < 0.0001). Bilateral ARI estimates were significantly decreased during NW for the R group only (p < 0.0001) but were reduced in both R (p < 0.0001) and NoR (p = 0.03) groups for SS tasks compared with baseline. The reproducible attenuation of dCA efficiency due to paradigm-induced NVC response, its interaction, and different behaviour in R and NoR, warrant further research in different physiological and clinical conditions.

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.

Validity and reliability of deriving the autoregulatory plateau through projection pursuit regression from driven methods

To compare the construct validity and between-day reliability of projection pursuit regression (PPR) from oscillatory lower body negative pressure (OLBNP) and squat-stand maneuvers (SSMs). Nineteen participants completed 5 min of OLBNP and SSMs at driven frequencies of 0.05 and 0.10 Hz across two visits. Autoregulatory plateaus were derived at both point-estimates and across the cardiac cycle. Between-day reliability was assessed with intraclass correlation coefficients (ICCs), Bland-Altman plots with 95% limits of agreement (LOA), coefficient of variation (CoV), and smallest real differences. Construct validity between OLBNP-SSMs were quantified with Bland-Altman plots and Cohen's d. The expected autoregulatory curve with positive rising and negative falling slopes were present in only ~23% of the data. The between-day reliability for the ICCs were poor-to-good with the CoV estimates ranging from ~50% to 70%. The 95% LOA were very wide with an average spread of ~450% for OLBNP and ~350% for SSMs. Plateaus were larger from SSMs compared to OLBNPs (moderate-to-large effect sizes). The cerebral pressure-flow relationship is a complex regulatory process, and the "black-box" nature of this system can make it challenging to quantify. The current data reveals PPR analysis does not always elicit a clear-cut central plateau with distinctive rising/falling slopes.

Transfer function analysis of dynamic cerebral autoregulation: A CARNet white paper 2022 update

Cerebral autoregulation (CA) refers to the control of cerebral tissue blood flow (CBF) in response to changes in perfusion pressure. Due to the challenges of measuring intracranial pressure, CA is often described as the relationship between mean arterial pressure (MAP) and CBF. Dynamic CA (dCA) can be assessed using multiple techniques, with transfer function analysis (TFA) being the most common. A 2016 white paper by members of an international Cerebrovascular Research Network (CARNet) that is focused on CA strove to improve TFA standardization by way of introducing data acquisition, analysis, and reporting guidelines. Since then, additional evidence has allowed for the improvement and refinement of the original recommendations, as well as for the inclusion of new guidelines to reflect recent advances in the field. This second edition of the white paper contains more robust, evidence-based recommendations, which have been expanded to address current streams of inquiry, including optimizing MAP variability, acquiring CBF estimates from alternative methods, estimating alternative dCA metrics, and incorporating dCA quantification into clinical trials. Implementation of these new and revised recommendations is important to improve the reliability and reproducibility of dCA studies, and to facilitate inter-institutional collaboration and the comparison of results between studies.

On the use and misuse of cerebral hemodynamics terminology using Transcranial Doppler ultrasound: a call for standardization

Cerebral hemodynamics (e.g., cerebral blood flow) can be measured and quantified using many different methods, with Transcranial Doppler ultrasound (TCD) being one of the most commonly utilized approaches. In human physiology, the terminology used to describe metrics of cerebral hemodynamics are inconsistent, and in some instances technically inaccurate; this is especially true when evaluating, reporting, and interpreting measures from TCD. Therefore, this perspectives article presents recommended terminology when reporting cerebral hemodynamic data. We discuss the current use and misuse of the terminology in the context of using TCD to measure and quantify cerebral hemodynamics and present our rationale and consensus on the terminology that we recommend moving forward. For example, one recommendation is to discontinue use of the term "cerebral blood flow velocity" in favor of "cerebral blood velocity" with precise indication of the vessel of interest. We also recommend clarity when differentiating between discrete cerebrovascular regulatory mechanisms, namely cerebral autoregulation, neurovascular coupling, and cerebrovascular reactivity. This will be a useful guide for investigators in the field of cerebral hemodynamics research.

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.

Review of studies on dynamic cerebral autoregulation in the acute phase of stroke and the relationship with clinical outcome

Acute stroke is associated with high morbidity and mortality. In the last decades, new therapies have been investigated with the aim of improving clinical outcomes in the acute phase post stroke onset. However, despite such advances, a large number of patients do not demonstrate improvement, furthermore, some unfortunately deteriorate. Thus, there is a need for additional treatments targeted to the individual patient. A potential therapeutic target is interventions to optimize cerebral perfusion guided by cerebral hemodynamic parameters such as dynamic cerebral autoregulation (dCA). This narrative led to the development of the INFOMATAS (Identifying New targets FOr Management And Therapy in Acute Stroke) project, designed to foster interventions directed towards understanding and improving hemodynamic aspects of the cerebral circulation in acute cerebrovascular disease states. This comprehensive review aims to summarize relevant studies on assessing dCA in patients suffering acute ischemic stroke, intracerebral haemorrhage, and subarachnoid haemorrhage. The review will provide to the reader the most consistent findings, the inconsistent findings which still need to be explored further and discuss the main limitations of these studies. This will allow for the creation of a research agenda for the use of bedside dCA information for prognostication and targeted perfusion interventions.

Reliability of cerebral autoregulation using different measures of perfusion pressure in patients with subarachnoid hemorrhage

Dynamic cerebral autoregulation to spontaneous fluctuations in cerebral perfusion pressure (CPP) is often assessed by transcranial Doppler (TCD) in the time domain, yielding primarily the mean flow index (Mx), or in the frequency domain using transfer function analysis (TFA), yielding gain and phase. For both domains, the measurement of blood pressure is critical. This study assessed the inter-method reliability of dynamic cerebral autoregulation using three different methods of pressure measurement. In 39 patients with aneurysmal subarachnoid hemorrhage, non-invasive arterial blood pressure (ABP), invasive ABP (measured in the radial artery) and CPP were recorded simultaneously with TCD. Intraclass correlation coefficient (ICC) was used to quantify reliability. Mx was higher when calculated using invasive ABP (0.39; 95% confidence interval [95% CI]: 0.33; 0.44) compared to non-invasive ABP, and CPP. The overall ICC showed poor to good reliability (0.65; 95% CI: 0.11; 0.84; n = 69). In the low frequency domain, the comparison between invasively measured ABP and CPP showed good to excellent (normalized gain, ICC: 0.87, 95CI: 0.81; 0.91; n = 96; non-normalized gain: 0.89, 95% CI: 0.84; 0.92; n = 96) and moderate to good reliability (phase, ICC: 0.69, 95% CI: 0.55; 0.79; n = 96), respectively. Different methods for pressure measurement in the assessment of dynamic cerebral autoregulation yield different results and cannot be used interchangeably.

Reliability and validity of the mean flow index (Mx) for assessing cerebral autoregulation in humans: A systematic review of the methodology

Cerebral autoregulation is a complex mechanism that serves to keep cerebral blood flow relatively constant within a wide range of cerebral perfusion pressures. The mean flow index (Mx) is one of several methods to assess dynamic cerebral autoregulation, but its reliability and validity have never been assessed systematically. The purpose of the present systematic review was to evaluate the methodology, reliability and validity of Mx.Based on 128 studies, we found inconsistency in the pre-processing of the recordings and the methods for calculation of Mx. The reliability in terms of repeatability and reproducibility ranged from poor to excellent, with optimal repeatability when comparing overlapping recordings. The discriminatory ability varied depending on the patient populations; in general, those with acute brain injury exhibited a higher Mx than healthy volunteers. The prognostic ability in terms of functional outcome and mortality ranged from chance result to moderate accuracy.Since the methodology was inconsistent between studies, resulting in varying reliability and validity estimates, the results were difficult to compare. The optimal method for deriving Mx is currently unknown.

Cerebral Vasoreactivity Changes Over Time in Patients With Different Clinical Manifestations of Cerebral Small Vessel Disease

Objectives: Endothelial dysfunction (ED) has been linked to the pathogenesis of cerebral small vessel disease (SVD). We aimed to assess ED and cerebrovascular reactivity (CVR) in the patients with a diverse manifestation of SVD, with similar and extensive white matter lesions (WMLs, modified Fazekas scale grade ≥2), compared with a control group (CG) without the MRI markers of SVD, matched for age, gender, hypertension, diabetes, and to evaluate the change of CVR following 24 months. Methods: We repeatedly measured the vasomotor reactivity reserve (VMRr) and breath-holding index (BHI) of the middle cerebral artery (MCA) by the transcranial Doppler ultrasound (TCD) techniques in 60 subjects above 60 years with a history of lacunar stroke (LS), vascular dementia (VaD), or parkinsonism (VaP) (20 in each group), and in 20 individuals from a CG. Results: The mean age, frequency of the main vascular risk factors, and sex distribution were similar in the patients with the SVD groups and a CG. The VMRr and the BHI were more severely impaired at baseline (respectively, 56.7 ± 18% and 0.82 ± 0.39) and at follow-up (respectively, 52.3 ± 16.7% and 0.71 ± 0.38) in the patients with SVD regardless of the clinical manifestations (ANOVA, p > 0.1) than in the CG (respectively, baseline VMRr 77.2 ± 15.6%, BHI 1.15 ± 0.47, p < 0.001; follow-up VMRr 74.3 ± 17.6%, BHI 1.11 ± 0.4, p < 0.001). All the assessed CVR measures (VMRr and BHI) significantly decreased over time in the subjects with SVD (Wilcoxon's signed-rank test p = 0.01), but this was not observed in the CG (p > 0.1) and the decrease of CVR measures was not related to the SVD radiological progression (p > 0.1). Conclusions: This study provided evidence that the change in CVR measures is detectable over a 24-month period in patients with different clinical manifestations of SVD. Compared with the patients in CG with similar atherothrombotic risk factors, all the CVR measures (BMRr and BHI) significantly declined over time in the subjects with SVD. The reduction in CVR was not related to the SVD radiological progression.

Regulation of cerebral blood flow in humans: physiology and clinical implications of autoregulation

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 interrelationships 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.

Cerebral critical closing pressure and resistance-area product: the influence of dynamic cerebral autoregulation, age and sex

Instantaneous arterial pressure-flow (or velocity) relationships indicate the existence of a cerebral critical closing pressure (CrCP), with the slope of the relationship expressed by the resistance-area product (RAP). In 194 healthy subjects (20-82 years, 90 female), cerebral blood flow velocity (CBFV, transcranial Doppler), arterial blood pressure (BP, Finapres) and end-tidal CO2 (EtCO2, capnography) were measured continuously for five minutes during spontaneous fluctuations of BP at rest. The dynamic cerebral autoregulation (CA) index (ARI) was extracted with transfer function analysis from the CBFV step response to the BP input and step responses were also obtained for the BP-CrCP and BP-RAP relationships. ARI was shown to decrease with age at a rate of -0.025 units/year in men (p = 0.022), but not in women (p = 0.40). The temporal patterns of the BP-CBFV, BP-CrCP and BP-RAP step responses were strongly influenced by the ARI (p < 0.0001), but not by sex. Age was also a significant determinant of the peak of the CBFV step response and the tail of the RAP response. Whilst the RAP step response pattern is consistent with a myogenic mechanism controlling dynamic CA, further work is needed to explore the potential association of the CrCP step response with the flow-mediated component of autoregulation.

CAAos platform: an integrated platform for analysis of cerebral hemodynamics data

OBJECTIVE

The purpose of this article is to introduce the readers to the concept and structure of CAAos (Cerebral Autoregulation Assessment Open Source) platform, and provide evidence of its functionality.

APPROACH

CAAos platform is a new open-source software research tool, developed in Python 3 language, that combines existing and novel methods for interactive visual inspection, batch processing and analysis of multichannel records. The platform is scalable, allowing for customization and inclusion of new tools.

MAIN RESULTS

Currently CAAos platform is composed of two main modules, preprocessing (containing artefact removal, filtering and signal beat to beat extraction tools) and cerebral autoregulation (CA) analysis modules. Two methods for assessing CA have been implemented into CAAos platform: transfer function analysis (TFA) and autoregulation index (ARI). In order to provide validation of TFA and ARI estimates derived from CAAos platform, the results were compared with those derived from two other algorithms. Validation was performed using data from twenty-eight participants, corresponding to 13 acute ischemic stroke patients and 13 age- and sex-matched control subjects. Agreement between estimates was assessed by intraclass correlation coefficient and Bland-Altman analysis. No significant statistical difference between algorithms was found. Moreover, there was an excellent correspondence between the curves of all parameters analysed, with intraclass correlation coefficient ranging from 0.98 (95%CI 0.976-0.999) to 1.00 (95%CI 1 -1). The mean differences revealed a very small magnitude bias indicating an excellent agreement between the estimates.

SIGNIFICANCE

As open-source software, the source code for the software is freely available for non-commercial use, reducing barriers to performing CA analysis, allowing inspection of the inner-workings of the algorithms, and facilitating networked activities with common standards. CAAos platform is a tailored software solution for the scientific community in the cerebral hemodynamic field and contributes to increasing use and reproducibility of CA assessment.

Cerebral autoregulation assessed by near-infrared spectroscopy: validation using transcranial Doppler in patients with controlled hypertension, cognitive impairment and controls

PURPOSE

Cerebral autoregulation (CA) aims to attenuate the effects of blood pressure variation on cerebral blood flow. This study assessed the criterion validity of CA derived from near-infrared spectroscopy (NIRS) as an alternative for Transcranial Doppler (TCD).

METHODS

Measurements of continuous blood pressure (BP), oxygenated hemoglobin (O₂Hb) using NIRS and cerebral blood flow velocity (CBFV) using TCD (gold standard) were performed in 82 controls, 27 patients with hypertension and 94 cognitively impaired patients during supine rest (all individuals) and repeated sit to stand transitions (cognitively impaired patients). The BP-CBFV and BP-O₂Hb transfer function phase shifts (TF_φ) were computed as CA measures. Spearman correlations (ρ) and Bland Altman limits of agreement (BAloa) between NIRS- and TCD-derived CA measures were computed. BAloa separation < 50° was considered a high absolute agreement.

RESULTS

NIRS- and TCD-derived CA estimates were significantly correlated during supine rest (ρ = 0.22-0.30, N = 111-120) and repeated sit-to-stand transitions (ρ = 0.46-0.61, N = 19-32). BAloa separation ranged between 87° and 112° (supine rest) and 65°-77° (repeated sit to stand transitions).

CONCLUSION

Criterion validity of NIRS-derived CA measures allows for comparison between groups but was insufficient for clinical application in individuals.

Reliability of the transcranial Doppler ultrasound-derived mean flow index for assessing dynamic cerebral autoregulation in healthy volunteers

The transcranial Doppler ultrasound-derived mean flow index (Mxa) is widely used for assessing dynamic cerebral autoregulation (dCA) in different clinical populations. This study aimed at estimating the relative and absolute reliability of Mxa in healthy participants in the supine position and during head-up tilt (HUT). Fourteen healthy participants were examined on two separate occasions during which, mean middle cerebral artery blood flow velocity (MCAv), non-invasive blood pressure, and heart rate were continuously recorded in the supine position and during HUT. Mxa was calculated as the correlation coefficient between mean arterial blood pressure and MCAv using either 3-, 5-, or 10-second averages collected over a 300 second period. Intraclass correlation coefficient (ICC_1.1) was calculated to assess relative reliability, while the standard error of measurement (SEM), and limits of agreement (LOA) were used to assess absolute reliability. Mxa-based 3-second averages yielded a similar relative and absolute reliability in both positions. When Mxa was calculated from 5-second averages, the most reliable values were obtained during HUT. The poorest reliability was achieved using 10-second averages, regardless of posture. The Mxa shows fair reliability with acceptable LOA in healthy volunteers when based on 3-second averages, both in the supine position and during HUT.

Vascular and haemodynamic issues of brain ageing

The population is ageing worldwide, thus increasing the burden of common age-related disorders to the individual, society and economy. Cerebrovascular diseases (stroke, dementia) contribute a significant proportion of this burden and are associated with high morbidity and mortality. Thus, understanding and promoting healthy vascular brain ageing are becoming an increasing priority for healthcare systems. In this review, we consider the effects of normal ageing on two major physiological processes responsible for vascular brain function: Cerebral autoregulation (CA) and neurovascular coupling (NVC). CA is the process by which the brain regulates cerebral blood flow (CBF) and protects against falls and surges in cerebral perfusion pressure, which risk hypoxic brain injury and pressure damage, respectively. In contrast, NVC is the process by which CBF is matched to cerebral metabolic activity, ensuring adequate local oxygenation and nutrient delivery for increased neuronal activity. Healthy ageing is associated with a number of key physiological adaptations in these processes to mitigate age-related functional and structural declines. Through multiple different paradigms assessing CA in healthy younger and older humans, generating conflicting findings, carbon dioxide studies in CA have provided the greatest understanding of intrinsic vascular anatomical factors that may mediate healthy ageing responses. In NVC, studies have found mixed results, with reduced, equivalent and increased activation of vascular responses to cognitive stimulation. In summary, vascular and haemodynamic changes occur in response to ageing and are important in distinguishing “normal” ageing from disease states and may help to develop effective therapeutic strategies to promote healthy brain ageing.

Reliability, reproducibility and validity of dynamic cerebral autoregulation in a large cohort with transient ischaemic attack or minor stroke

Objective

Cerebral autoregulation (CA) is critical to maintenance of cerebral perfusion but its relevance to the risk of stroke and dementia has been under-studied due to small study sizes and a lack of consensus as to the optimal method of measurement. We determined the reliability and reproducibility of multiple CA indices and the effect of intensive data-processing in a large population with transient ischaemic attack or minor stroke.

Approach

Consecutive, consenting patients in the population-based OXVASC (Oxford Vascular Study) Phenotyped cohort underwent up to 10-min supine continuous blood pressure monitoring (Finometer) with bilateral middle cerebral artery (MCA) transcranial ultrasound (DWL-Dopplerbox). Un-processed waveforms (Un-A) were median-filtered, systematically reviewed, artefacts corrected and their quality blindly graded (optimal (A) to worst (E)). CA metrics were derived in time-domain (autoregulatory index (ARI), Pearson’s Mx, Sx, Dx) and in very-low (VLF) and low-frequency (LF) domains (WPS-SI: wavelet phase synchronisation, transfer function analysis), stratified by recording quality. Reliability and reproducibility (Cronbach’s Alpha) were determined comparing MCA sides and the first vs. second 5-min of monitoring.

Main results

In 453 patients, following manual data-cleaning, there was good reliability of indices when comparing MCA sides (Mx: 0.77; WPS-SI-VLF: 0.85; WPS-SI-LF 0.84), or repeated five minute epochs (Mx: 0.57; WPS-SI-VLF: 0.69; WPS-SI-LF 0.90), with persistently good reliability between sides even in lower quality Groups (Group D: Mx: 0.79; WPS-SI-VLF: 0.92; WPS-SI-LF: 0.91). Reliability was greatest for Pearson’s Mx and wavelet synchronisation index, with reasonable reliability of transfer function analyses, but ARI was prone to occasional, potentially defective, extreme estimates (Left vs right MCA: 0.68).

Significance

Resting-state measures of CA were valid, reproducible and robust to moderate noise, but require careful data-processing. Mx and wavelet synchronisation index were the most reliable indices for determining the prognostic value of CA in large epidemiological cohorts and its potential as a treatment target.

COHmax: an algorithm to maximise coherence in estimates of dynamic cerebral autoregulation

OBJECTIVE

The reliability of dynamic cerebral autoregulation (dCA) parameters, obtained with transfer function analysis (TFA) of spontaneous fluctuations in arterial blood pressure (BP), require statistically significant values of the coherence function. A new algorithm (COH_max) is proposed to increase values of coherence by means of the automated, selective removal of sub-segments of data.

APPROACH

Healthy subjects were studied at baseline (normocapnia) and during 5% breathing of CO₂ (hypercapnia). BP (Finapres), cerebral blood flow velocity (CBFV, transcranial Doppler), end-tidal CO₂ (EtCO₂, capnography) and heart rate (ECG) were recorded continuously during 5 min in each condition. TFA was performed with sub-segments of data of duration (SEG_D) 100 s, 50 s or 25 s and the autoregulation index (ARI) was obtained from the CBFV response to a step change in BP. The area-under-the curve (AUC) was obtained from the receiver-operating characteristic (ROC) curve for the detection of changes in dCA resulting from hypercapnia.

MAIN RESULTS

In 120 healthy subjects (69 male, age range 20-77 years), CO₂ breathing was effective in changing mean EtCO₂ and CBFV (p < 0.001). For SEG_D = 100 s, ARI changed from 5.8 ± 1.4 (normocapnia) to 4.0 ± 1.7 (hypercapnia, p < 0.0001), with similar differences for SEG_D = 50 s or 25 s. Depending on the value of SEG_D, in normocapnia, 15.8% to 18.3% of ARI estimates were rejected due to poor coherence, with corresponding rates of 8.3% to 13.3% in hypercapnia. With increasing coherence, 36.4% to 63.2% of these could be recovered in normocapnia (p < 0.001) and 50.0% to 83.0% in hypercapnia (p < 0.005). For SEG_D = 100 s, ROC AUC was not influenced by the algorithm, but it was superior to corresponding values for SEG_D = 50 s or 25 s.

SIGNIFICANCE

COH_max has the potential to improve the yield of TFA estimates of dCA parameters, without introducing a bias or deterioration of their ability to detect impairment of autoregulation. Further studies are needed to assess the behaviour of the algorithm in patients with different cerebrovascular conditions.

Chasing the evidence: the influence of data segmentation on estimates of dynamic cerebral autoregulation

OBJECTIVE

Transfer function analysis (TFA) of dynamic cerebral autoregulation (dCA) requires smoothing of spectral estimates using segmentation of the data (S_D). Systematic studies are required to elucidate the potential influence of S_D on dCA parameters.

APPROACH

Healthy subjects (HS, n = 237) and acute ischaemic stroke patients (AIS, n = 98) were included. Cerebral blood flow velocity (CBFV, transcranial Doppler ultrasound) was recorded supine at rest with continuous arterial blood pressure (BP, Finometer) for a minimum of 5 min. TFA was performed with durations S_D = 100, 50 or 25 s and 50% superposition to derive estimates of coherence, gain and phase for the BP-CBFV relationship. The autoregulation index (ARI) was estimated from the CBFV step response. Intrasubject reproducibility was expressed by the intraclass correlation coefficient (ICC).

MAIN RESULTS

In HS, the ARI, coherence, gain, and phase (low frequency) were influenced by S_D, but in AIS, phase (very low frequency) and ARI were not affected. ICC was excellent (>0.75) for all parameters, for both HS and AIS. For S_D = 100 s, ARI was different between HS and AIS (mean ± sdev: 5.70 ± 1.61 vs 5.1 ± 2.0; p < 0.01) and the significance of this difference was maintained for S_D = 50 s and 25 s. Using S_D = 100 s as reference, the rate of misclassification, based on a threshold of ARI ⩽ 4, was 6.3% for S_D = 50 s and 8.1% for S_D = 25 s in HS, with corresponding values of 11.7% and 8.2% in AIS patients, respectively.

SIGNIFICANCE

Further studies are warranted with S_D values lower than the recommended standard of S_D = 100 s, to explore possibilities of improving the reproducibility, sensitivity and prognostic value of TFA parameters used as metrics of dCA.

INFOMATAS multi-center systematic review and meta-analysis individual patient data of dynamic cerebral autoregulation in ischemic stroke

Rationale

Disturbances in dynamic cerebral autoregulation after ischemic stroke may have important implications for prognosis. Recent meta-analyses have been hampered by heterogeneity and small samples.

Aim and/or hypothesis

The aim of study is to undertake an individual patient data meta-analysis (IPD-MA) of dynamic cerebral autoregulation changes post-ischemic stroke and to determine a predictive model for outcome in ischemic stroke using information combined from dynamic cerebral autoregulation, clinical history, and neuroimaging.

Sample size estimates

To detect a change of 2% between categories in modified Rankin scale requires a sample size of ∼1500 patients with moderate to severe stroke, and a change of 1 in autoregulation index requires a sample size of 45 healthy individuals (powered at 80%, α = 0.05). Pooled estimates of mean and standard deviation derived from this study will be used to inform sample size calculations for adequately powered future dynamic cerebral autoregulation studies in ischemic stroke.

Methods and design

This is an IPD-MA as part of an international, multi-center collaboration (INFOMATAS) with three phases. Firstly, univariate analyses will be constructed for primary (modified Rankin scale) and secondary outcomes, with key co-variates and dynamic cerebral autoregulation parameters. Participants clustering from within studies will be accounted for with random effects. Secondly, dynamic cerebral autoregulation variables will be validated for diagnostic and prognostic accuracy in ischemic stroke using summary receiver operating characteristic curve analysis. Finally, the prognostic accuracy will be determined for four different models combining clinical history, neuroimaging, and dynamic cerebral autoregulation parameters.

Study outcome(s)

The outcomes for this study are to determine the relationship between clinical outcome, dynamic cerebral autoregulation changes, and baseline patient demographics, to determine the diagnostic and prognostic accuracy of dynamic cerebral autoregulation parameters, and to develop a prognostic model using dynamic cerebral autoregulation in ischemic stroke.

Discussion

This is the first international collaboration to use IPD-MA to determine prognostic models of dynamic cerebral autoregulation for patients with ischemic stroke.

Assessment of dynamic cerebral autoregulation in humans: Is reproducibility dependent on blood pressure variability?

We tested the influence of blood pressure variability on the reproducibility of dynamic cerebral autoregulation (DCA) estimates. Data were analyzed from the 2^nd CARNet bootstrap initiative, where mean arterial blood pressure (MABP), cerebral blood flow velocity (CBFV) and end tidal CO2 were measured twice in 75 healthy subjects. DCA was analyzed by 14 different centers with a variety of different analysis methods. Intraclass Correlation (ICC) values increased significantly when subjects with low power spectral density MABP (PSD-MABP) values were removed from the analysis for all gain, phase and autoregulation index (ARI) parameters. Gain in the low frequency band (LF) had the highest ICC, followed by phase LF and gain in the very low frequency band. No significant differences were found between analysis methods for gain parameters, but for phase and ARI parameters, significant differences between the analysis methods were found. Alternatively, the Spearman-Brown prediction formula indicated that prolongation of the measurement duration up to 35 minutes may be needed to achieve good reproducibility for some DCA parameters. We conclude that poor DCA reproducibility (ICC<0.4) can improve to good (ICC > 0.6) values when cases with low PSD-MABP are removed, and probably also when measurement duration is increased.

Cerebral Microcirculatory Blood Flow Dynamics During Rest and a Continuous Motor Task

Objectives: To examine the brain’s microcirculatory response over the course of a continuous 5-min elbow movement task in order to estimate its potential role in grading vaso-neural coupling compared to the macrocirculatory response.

Methods: We simultaneously recorded cerebral blood flow velocity (CBFV), changes in oxygenated/deoxygenated hemoglobin concentrations ([oxHb], [deoxHb]), blood pressure (BP), and end-tidal CO₂ over 5-min periods of rest and left elbow movements in 24 healthy persons (13 women and 11 men of mean age ± SD, 38 ± 11 years). A low frequency range (0.07–0.15 Hz) was used for analysis by transfer function estimates of phase and gain.

Results: Elbow movement led to a small BP increase (mean BP at rest 83 mm Hg, at movement 87; p < 0.01) and a small ETCO₂ decrease (at rest 44.6 mm Hg, at movement 41.7 mm Hg; p < 0.01). Further, it increased BP-[oxHb] phase from 55° (both sides) to 74° (right; p < 0.05)/69° (left; p < 0.05), and BP-[deoxHb] phase from 264° (right)/270° (left) to 288° (right; p < 0.05)/297° (left; p = 0.09). The cerebral mean transit time at 0.1 Hz of 5.6 s of rest remained unchanged by movement. Elbow movement significantly decreased BP-CBFV gain on both sides, and BP-CBFV phase only on the right side (p = 0.05).

Conclusion: Elbow movement leads to an increased time delay between BP and [oxHb]/[deoxHb] while leaving the cerebral mean transit time unchanged. Phase shifting is usually the more robust parameter when using a transfer function to estimate dynamic cerebral autoregulation; phase shifting at the microcirculatory level seems to be a better marker of VNC-induced changes than phase shifting between BP and CBFV.

Dynamic Cerebral Autoregulation Reproducibility Is Affected by Physiological Variability

Parameters describing dynamic cerebral autoregulation (DCA) have limited reproducibility. In an international, multi-center study, we evaluated the influence of multiple analytical methods on the reproducibility of DCA. Fourteen participating centers analyzed repeated measurements from 75 healthy subjects, consisting of 5 min of spontaneous fluctuations in blood pressure and cerebral blood flow velocity signals, based on their usual methods of analysis. DCA methods were grouped into three broad categories, depending on output types: (1) transfer function analysis (TFA); (2) autoregulation index (ARI); and (3) correlation coefficient. Only TFA gain in the low frequency (LF) band showed good reproducibility in approximately half of the estimates of gain, defined as an intraclass correlation coefficient (ICC) of >0.6. None of the other DCA metrics had good reproducibility. For TFA-like and ARI-like methods, ICCs were lower than values obtained with surrogate data (p < 0.05). For TFA-like methods, ICCs were lower for the very LF band (gain 0.38 ± 0.057, phase 0.17 ± 0.13) than for LF band (gain 0.59 ± 0.078, phase 0.39 ± 0.11, p ≤ 0.001 for both gain and phase). For ARI-like methods, the mean ICC was 0.30 ± 0.12 and for the correlation methods 0.24 ± 0.23. Based on comparisons with ICC estimates obtained from surrogate data, we conclude that physiological variability or non-stationarity is likely to be the main reason for the poor reproducibility of DCA parameters.