Comparing Different Recording Lengths of Dynamic Cerebral Autoregulation: 5 versus 10 Minutes

Diagnostic and prognostic performance of Mxa and transfer function analysis-based dynamic cerebral autoregulation metrics

Dynamic cerebral autoregulation is often assessed by continuously recorded arterial blood pressure (ABP) and transcranial Doppler-derived mean cerebral blood flow velocity followed by analysis in the time and frequency domain, respectively. Sequential correlation (in the time domain, yielding e.g., the measure mean flow index, Mxa) and transfer function analysis (TFA) (in the frequency domain, yielding, e.g., normalised and non-normalised gain as well as phase in the low frequency domain) are commonly used approaches. This study investigated the diagnostic and prognostic performance of these metrics. We included recordings from 48 healthy volunteers, 19 patients with sepsis, 36 with traumatic brain injury (TBI), and 14 patients admitted to a neurorehabilitation unit. The diagnostic (between healthy volunteers and patients) and prognostic performance (to predict death or poor functional outcome) of Mxa and the TFA measures were assessed by area under the receiver-operating characteristic (AUROC) curves. AUROC curves generally indicated that the measures were 'no better than chance' (AUROC ∼0.5) both for distinguishing between healthy volunteers and patient groups, and for predicting outcomes in our cohort. No metric emerged as superior for distinguishing between healthy volunteers and different patient groups, for assessing the effect of interventions, or for predicting mortality or functional outcome.

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.

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.

The Effect of Data Length on the Assessment of Dynamic Cerebral Autoregulation with Transfer Function Analysis in Neurological ICU Patients

Background

Cerebral autoregulation plays an important role in safeguarding adequate cerebral perfusion and reducing the risk of secondary brain injury, which is highly important for patients in the neurological intensive care unit (neuro-ICU). Although the consensus white paper suggests that a minimum of 5 min of data are needed for assessing dynamic cerebral autoregulation with transfer function analysis (TFA), it remains unknown if the length of these data is valid for patients in the neuro-ICU, of whom are notably different than the general populations. We aimed to investigate the effect of data length using transcranial Doppler ultrasound combined with invasive blood pressure measurement for the assessment of dynamic cerebral autoregulation in patients in the neuro-ICU.

Methods

Twenty patients with various clinical conditions (severe acute encephalitis, ischemic stroke, subarachnoid hemorrhage, brain injury, cerebrovascular intervention operation, cerebral hemorrhage, intracranial space-occupying lesion, and toxic encephalopathy) were recruited for this study. Continuous invasive blood pressure, with a pressure catheter placed at the radial artery, and bilateral continuous cerebral blood flow velocity with transcranial Doppler ultrasound were simultaneously recorded for a length of 10 min for each patient. TFA was applied to derive phase shift, gain, and coherence function at all frequency bands from the first 2, 3, 4, 5, 6, 7, 8, 9, and 10 min of the 10-min recordings in each patient on both hemispheres. The variability in the autoregulatory parameters in each hemisphere was investigated by repeated measures analysis of variance.

Results

Forty-one recordings (82 hemispheres) were included in the study. According to the critical values of coherence provided by the Cerebral Autoregulation Research Network white paper, acceptable rates for the data were 100% with a length ≥ 7 min. The final analysis included 68 hemispheres. The effects of data length on trends in phase shift in the very low frequency (VLF) band (F_{1.801,120.669} = 6.321, P = 0.003), in the LF band (F_1.274,85.343 = 4.290, P = 0.032), and in the HF band (F_1.391,93.189 = 3.868, P = 0.039) were significant for 3–7 min, for 4–7 min, and for 5–8 min, respectively. Effects were also significant on the gain in the VLF band (F_{1.927,129.134} = 3.215, P = 0.045) for 2–8 min and on the coherence function in all frequency bands (VLF F_{2.846,190.671} = 90.247, P < 0.001, LF F_{2.515,168.492} = 55.770, P < 0.001, HF F_{2.411, 161.542} = 33.833, P < 0.001) for 2–10 min.

Conclusions

Considering the acceptable rates for the data and the variation in the TFA variables (phase shift and gain), we recommend recording data for a minimum length of 7 min for TFA in patients in the neuro-ICU.

Reliability of the mean flow index (Mx) for assessing cerebral autoregulation in healthy volunteers

BACKGROUND

Mean flow index (Mxa) for evaluating dynamic cerebral autoregulation is derived using varying approaches for calculation, which may explain that the reliability ranges from poor to excellent. The comparability, repeatability, stability, and internal consistency of approaches have not previously been assessed.

METHODS

We included 60 recordings from resting healthy volunteers and calculated Mxa using four different approaches: three without overlapping calculations, using intervals for averaging wave-form data (blocks) of 3, 6, and 10 s, and correlation periods (epochs) of 60, 240, and 300 s (3-60-F, 6-240-F, and 10-300-F); and one using 10-second blocks, 300 s epochs, and overlaps of 60 s (10-300-60). The comparability between the approaches was assessed using Student's t test, intraclass correlation coefficients (ICC), and Bland-Altman plot.

RESULTS

Overall, 3-60-F resulted in a higher Mxa than the other indices (p < 0.001, for all). The reliability when comparing all the approaches ranged from moderate to good (ICC: 0.68; 95%CI: 0.59-0.84), which was primarily due to similarities between 10-300-F and 10-300-60 (ICC: 0.94; 95%CI: 0.86-0.98). The reliability when comparing the first and last half was poor for 10-300-F and ranged from poor to moderate for the other approaches. Additional random artifacts resulted in poor reliability for 10-300-F, while the other approaches were more stable.

CONCLUSIONS

Mxa in general has a low sensitivity to artifacts, but otherwise seems highly dependent on the approach, with a repeatability that is moderate at best. The varying accuracy and precision renders Mxa unreliable for classifying impaired cerebral autoregulation when using healthy adults for comparison.

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.

Comparison of Pressure Reactivity Index and Mean Velocity Index to Evaluate Cerebrovascular Reactivity During Induced Arterial Blood Pressure Variations in Severe Brain Injury

OBJECTIVES

To compare the assessment of cerebral autoregulation by cerebrovascular reactivity indices based on intracranial pressure (Pressure Reactivity Index, PRx) and on transcranial Doppler (Mean Velocity Index, Mx) during controlled variations of arterial blood pressure in severe brain injury. Primary outcome was the agreement between both cerebrovascular reactivity indices measured by the Bland-and-Altman method. Secondary outcomes were the association of cerebrovascular reactivity indices with arterial blood pressure variation, and the comparison of optimal cerebral perfusion pressures determined by both indices.

METHODS

All consecutive comatose (Glasgow Coma Scale < 8) patients from the surgical intensive care unit of Bicetre Hospital who had an acute brain injury on computerized tomography and needed vasopressor support were prospectively included. Step-by-step arterial pressure variations using vasopressors were performed to compare PRx and Mx and to calculate optimal cerebral perfusion pressure (CPPopt).

MEASUREMENTS AND MAIN RESULTS

15 patients were included. Mean difference between both indices measured by Bland-and-Altman plot was - 0.07 (IC 95% [- 1.02 to 0.87]). Mx was significantly associated with arterial pressure variation (one-way ANOVA test, p = 0.007), whereas PRx was not (p = 0.44). Optimal cerebral perfusion pressure calculated with PRx and Mx was respectively 11 and 15mmHg higher than the mean perfusion pressure prescribed. Optimal cerebral perfusion pressure calculation was possible in all cases.

CONCLUSIONS

Cerebral vasoreactivity indices calculated with intracranial pressure or transcranial Doppler show only moderate agreement. Both indices nonetheless suggest substantially higher optimal cerebral perfusion pressure than those currently provided by international guidelines.

Dynamic Cerebral Autoregulation Remains Stable During the Daytime (8 a.m. to 8 p.m.) in Healthy Adults

Many functions of the human body possess a daily rhythm, disruptions of which often lead to disease. Dynamic cerebral autoregulation (dCA) stabilizes the cerebral blood flow to prompt normal neural function. However, whether dCA is stable across the day remains unknown. This study aimed to investigate the daily rhythm of dCA. Fifty-one healthy adults (38.294 ± 13.279 years, 40 females) were recruited and received six dCA measurements per individual that were conducted at predefined time points: 8:00, 9:00, 11:00, 14:00, 17:00, and 20:00. Although the blood pressure fluctuated significantly, there was no statistical difference in phase difference and gain (autoregulatory parameters) across the six time points. This study demonstrates that dCA remains stable during the interval from 8 a.m. to 8 p.m. and underscores the importance of stable dCA in maintaining cerebral blood flow and neural function.

Wavelet pressure reactivity index: a validation study

KEY POINTS

The brain is vulnerable to damage from too little or too much blood flow. A physiological mechanism termed cerebral autoregulation (CA) exists to maintain stable blood flow even if cerebral perfusion pressure (CPP) is changing. A robust method for assessing CA is not yet available. There are still some problems with the traditional measure, the pressure reactivity index (PRx). We introduce a new method, the wavelet transform method (wPRx), to assess CA using data from two sets of controlled hypotension experiments in piglets: one set had artificially manipulated arterial blood pressure (ABP) oscillations; the other group were spontaneous ABP waves. A significant linear relationship was found between wPRx and PRx in both groups, with wPRx providing a more stable result for the spontaneous waves. Although both methods showed similar accuracy in distinguishing intact and impaired CA, it seems that wPRx tends to perform better than PRx, although not significantly so.

ABSTRACT

We present a novel method to monitor cerebral autoregulation (CA) using the wavelet transform (WT). The new method is validated against the pressure reactivity index (PRx) in two piglet experiments with controlled hypotension. The first experiment (n = 12) had controlled haemorrhage with artificial stationary arterial blood pressure (ABP) and intracranial pressure (ICP) oscillations induced by sinusoidal slow changes in positive end-expiratory pressure ('PEEP group'). The second experiment (n = 17) had venous balloon inflation during spontaneous, non-stationary ABP and ICP oscillations ('non-PEEP group'). The wavelet transform phase shift (WTP) between ABP and ICP was calculated in the frequency range 0.0067-0.05 Hz. Wavelet semblance, the cosine of WTP, was used to make the values comparable to PRx, and the new index was termed wavelet pressure reactivity index (wPRx). The traditional PRx, the running correlation coefficient between ABP and ICP, was calculated. The result showed a significant linear relationship between wPRx and PRx in the PEEP group (R = 0.88) and non-PEEP group (R = 0.56). In the non-PEEP group, wPRx showed better performance than PRx in distinguishing cerebral perfusion pressure (CPP) above and below the lower limit of autoregulation (LLA). When CPP was decreased below LLA, wPRx increased from 0.43 ± 0.28 to 0.69 ± 0.12 (P = 0.003) while PRx increased from 0.07 ± 0.21 to 0.27 ± 0.37 (P = 0.04). Moreover, wPRx provided a more stable result than PRx (SD of PRx was 0.40 ± 0.07, and SD of wPRx was 0.28 ± 0.11, P = 0.001). Assessment of CA using wavelet-derived phase shift between ABP and ICP is feasible.