Dynamic Cerebral Autoregulation Reproducibility Is Affected by Physiological Variability

The time constant of the cerebral arterial bed: exploring age-related implications

The time constant of the cerebral arterial bed (τ) represents an estimation of the  transit time of flow from the point of insonation at the level of the middle cerebral artery to the arteriolar-capillary boundary, during a cardiac cycle. This study assessed differences in τ among healthy volunteers across different age groups. Simultaneous recordings of transcranial Doppler cerebral blood flow velocity (CBFV) and arterial blood pressure (ABP) were performed on two groups: young volunteers (below 30 years of age), and older volunteers (above 40 years of age). τ was estimated using mathematical transformation of ABP and CBFV pulse waveforms. 77 healthy volunteers [52 in the young group, and 25 in the old group] were included. Pulse amplitude of ABP was higher [16.7 (14.6-19.4) mmHg] in older volunteers as compared to younger ones [12.5 (10.9-14.4) mm Hg; p < 0.001]. CBFV was lower in older volunteers [59 (50-66) cm/s] as compared to younger ones [72 (63-78) cm/s p < 0.001]. τ was longer in the younger volunteers [217 (168-237) ms] as compared to the older volunteers [183 (149-211) ms; p = 0.004]. τ significantly decreased with age (rS =  - 0.27; p = 0.018). τ is potentially an integrative marker of the changes occurring in cerebral vasculature, as it encompasses the interplay between changes in compliance and resistance that occur with age.

Pretreatment Cranial Computed Tomography Perfusion Predicts Dynamic Cerebral Autoregulation Changes in Acute Hemispheric Stroke Patients Having Undergone Recanalizing Therapy: A Retrospective Study

OBJECTIVES

Blood pressure (BP) management is challenging in patients with acute ischemic supratentorial stroke undergoing recanalization therapy due to the lack of established guidelines. Assessing dynamic cerebral autoregulation (dCA) may address this need, as it is a bedside technique that evaluates the transfer function phase in the very low-frequency (VLF) range (0.02-0.07 Hz) between BP and cerebral blood flow velocity (CBFV) in the middle cerebral artery. This phase is a prognostically relevant parameter, with lower values associated with poorer outcomes. This study aimed to evaluate whether early cranial computed tomography perfusion (CTP) can predict this parameter.

METHODS

In this retrospective study, 165 consecutive patients with hemispheric strokes who underwent recanalizing therapy were included (median age: 73 years; interquartile range (IQR) 60-80; women: 43 (26%)). The cohort comprised 91 patients treated with intravenous thrombolysis (IV-lysis) alone (median National Institute of Health Stroke Scale (NIHSS) score: 5; IQR 3-7) and 74 patients treated with mechanical thrombectomy (median NIHSS: 15; IQR 9-18). Regression analysis was performed to assess the relationship between pretreatment CTP-derived ischemic penumbra and core stroke volumes and the dCA VLF phase, as well as CBFV assessed within the first 72 h post-stroke event.

RESULTS

Pretreatment penumbra volume was a significant predictor of the VLF phase (adjusted r2 = 0.040; β = -0.001, 95% confidence interval (CI): -0.0018 to -0.0002, p = 0.02). Core infarct volume was a stronger predictor of CBFV (adjusted r2 = 0.082; β = 0.205, 95% CI: 0.0968-0.3198; p = 0.0003) compared to penumbra volume (p = 0.01). Additionally, in the low-frequency range (0.07-0.20 Hz), CBFV and BP were inversely related to the gain, an index of vascular tone.

CONCLUSION

CTP metrics appear to correlate with the outcome-relevant VLF phase and reactive hyperemic CBFV, which interact with BP to influence vascular tone and gain. These aspects of dCA could potentially guide BP management in patients with acute stroke undergoing recanalization therapy. However, further validation is required.

Cerebrovascular hemodynamics association with brain structure and function in Multiple Sclerosis

BACKGROUND

Vascular risk factors seem to contribute to disease progression in Multiple Sclerosis (MS), but the mechanistic connection between vascular risk and MS is unknown. Understanding cerebrovascular hemodynamics (CVH) in MS may help advance our understanding of the link between vascular risk and MS.

OBJECTIVES

Examine the relationship between CVH [dynamic cerebral autoregulation (dCA) and vasoreactivity (VR)] and brain structure (MRI) and function (cognition, and gait) in individuals with MS.

METHODS

Transcranial Doppler ultrasound (TCD) was utilized to assess two key markers of CVH: dCA and VR. dCA (reported as phase and gain) is calculated from the spontaneous blood pressure and flow velocity oscillations. VR is calculated as the slope of change in cerebral blood flow velocity in response to end-tidal CO2. Global gray matter (GM), white matter (WM), WM hyperintensity (WMH) volumes and WM lesion counts were measured from brain MRI. All participants underwent detailed cognitive and gait assessments.

RESULTS

Eighty participants were included (age 44 ± 11, 26 % male); 75 had relapsing-remitting MS (94 %), with disease duration of 8 (11) years [median (IQR)] since MS diagnosis and an Expanded Disability Status Scale (EDSS) of 2.0 (4.0). Higher phase (better dCA) was associated with greater GM volume, lower WHM burden and higher cognitive scores in the memory and global cognitive domains (all P values <0.05). There was no relationship between CVH and gait speed in our study participants. There was no relationship between VR and any measures of brain structure and function.

CONCLUSIONS

More efficient cerebral autoregulation is associated with better brain structure (larger GM and lower WMH volumes) and function (cognition, but not gait) in patients with MS.

Haemosync: A synchronisation algorithm for multimodal haemodynamic signals

BACKGROUND

Synchronous acquisition of haemodynamic signals is crucial for their multimodal analysis, such as dynamic cerebral autoregulation (DCA) analysis of arterial blood pressure (ABP) and transcranial Doppler (TCD)-derived cerebral blood velocity (CBv). Several technical problems can, however, lead to (varying) time-shifts between the different signals. These can be difficult to recognise and can strongly influence the multimodal analysis results.

METHODS

We have developed a multistep, cross-correlation-based time-shift detection and synchronisation algorithm for multimodal pulsatile haemodynamic signals. We have developed the algorithm using ABP and CBv measurements from a dataset that contained combinations of several time-shifts. We validated the algorithm on an external dataset with time-shifts. We additionally quantitatively validated the algorithm's performance on a dataset with artificially added time-shifts, consisting of sample clock differences ranging from -0.2 to 0.2 s/min and sudden time-shifts between -4 and 4 s. The influence of superimposed noise and variation in waveform morphology on the time-shift estimation was quantified, and their influence on DCA-indices was determined.

RESULTS

The instantaneous median absolute error (MedAE) between the artificially added time-shifts and the estimated time-shifts was 12 ms (median, IQR 12-12, range 11-14 ms) for drifts between -0.1 and 0.1 s/min and sudden time-shifts between -4 and 4 s. For drifts above 0.1 s/min, MedAE was higher (median 753, IQR 19 - 766, range 13 - 772 ms). When a certainty threshold was included (peak cross-correlation > 0.9), MedAE for all drifts-shift combinations decreased to 12 ms, with smaller variability (IQR 12 - 13, range 8 - 22 ms, p < 0.001). The time-shift estimation is robust to noise, as the MedAE was similar for superimposed white noise with variance equal to the signal variance. After time-shift correction, DCA-indices were similar to the original, non-time-shifted signals. Phase shift differed by 0.17° (median, IQR 0.13-0.2°, range 0.0038-1.1°) and 0.54° (median, IQR 0.23-1.7°, range 0.0088-5.6°) for the very low frequency and low frequency ranges, respectively.

DISCUSSION

This algorithm allows visually interpretable detection and accurate correction of time-shifts between pulsatile haemodynamic signals (ABP and CBv).

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.

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.

Dynamic cerebral autoregulation is preserved during orthostasis and intrathoracic pressure regulation in healthy subjects: A pilot study

Resistance breathing may restore cardiac output (CO) and cerebral blood flow (CBF) during hypovolemia. We assessed CBF and cerebral autoregulation (CA) during tilt, resistance breathing, and paced breathing in 10 healthy subjects. Blood velocities in the internal carotid artery (ICA), middle cerebral arteries (MCA, four subjects), and aorta were measured by Doppler ultrasound in 30° and 60° semi-recumbent positions. ICA blood flow and CO were calculated. Arterial blood pressure (ABP, Finometer), and end-tidal CO2 (ETCO2) were recorded. ICA blood flow response was assessed by mixed-models regression analysis. The synchronization index (SI) for the variable pairs ABP-ICA blood velocity, ABP-MCA velocities in 0.005-0.08 Hz frequency interval was calculated as a measure of CA. Passive tilting from 30° to 60° resulted in 12% decrease in CO (p = 0.001); ICA blood flow tended to fall (p = 0.04); Resistance breathing restored CO and ICA blood flow despite a 10% ETCO2 drop. ETCO2 and CO contributed to ICA blood flow variance (adjusted R2: 0.9, p < 0.0001). The median SI was low (<0.2) indicating intact CA, confirmed by surrogate date testing. The peak SI was transiently elevated during resistance breathing in the 60° position. Resistance breathing may transiently reduce CA efficiency. Paced breathing did not restore CO or ICA blood flow.

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.

Effects of posture changes on dynamic cerebral autoregulation during early pregnancy in women with obesity and/or sleep apnea

The incidence of syncope during orthostasis increases in early human pregnancy, which may be associated with cerebral blood flow (CBF) dysregulation in the upright posture. In addition, obesity and/or sleep apnea per se may influence CBF regulation due to their detrimental impacts on cerebrovascular function. However, it is unknown whether early pregnant women with obesity and/or sleep apnea could have impaired CBF regulation in the supine position and whether this impairment would be further exacerbated in the upright posture. Dynamic cerebral autoregulation (CA) was evaluated using transfer function analysis in 33 women during early pregnancy (13 with obesity, 8 with sleep apnea, 12 with normal weight) and 15 age-matched nonpregnant women during supine rest. Pregnant women also underwent a graded head-up tilt (30° and 60° for 6 min each). We found that pregnant women with obesity or sleep apnea had a higher transfer function low-frequency gain compared with nonpregnant women in the supine position (P = 0.026 and 0.009, respectively) but not normal-weight pregnant women (P = 0.945). Conversely, the transfer function low-frequency phase in all pregnancy groups decreased during head-up tilt (P = 0.001), but the phase was not different among pregnant groups (P = 0.180). These results suggest that both obesity and sleep apnea may have a detrimental effect on dynamic CA in the supine position during early pregnancy. CBF may be more vulnerable to spontaneous blood pressure fluctuations in early pregnant women during orthostatic stress compared with supine rest due to less efficient dynamic CA, regardless of obesity and/or sleep apnea.

Dynamic cerebral autoregulation measured by diffuse correlation spectroscopy

Dynamic cerebral autoregulation (dCA) can be derived from spontaneous oscillations in arterial blood pressure (ABP) and cerebral blood flow (CBF). Transcranial Doppler (TCD) measures CBF-velocity and is commonly used to assess dCA. Diffuse correlation spectroscopy (DCS) is a promising optical technique for non-invasive CBF monitoring, so here we aimed to validate DCS as a tool for quantifying dCA. In 33 healthy adults and 17 acute ischemic stroke patients, resting-state hemodynamic were monitored simultaneously with high-speed (20 Hz) DCS and TCD. dCA parameters were calcaulated by a transfer function analysis using a Fourier decomposition of ABP and CBF (or CBF-velocity). Strong correlation was found between DCS and TCD measured gain (magnitude of regulation) in healthy volunteers (r = 0.73, p < 0.001) and stroke patients (r = 0.76, p = 0.003). DCS-gain retained strong test-retest reliability in both groups (ICC 0.87 and 0.82, respectively). DCS and TCD-derived phase (latency of regulation) did not significantly correlate in healthy volunteers (r = 0.12, p = 0.50) but moderately correlated in stroke patients (r = 0.65, p = 0.006). DCS-derived phase was reproducible in both groups (ICC 0.88 and 0.90, respectively). High-frequency DCS is a promising non-invasive bedside technique that can be leveraged to quantify dCA from resting-state data, but the discrepancy between TCD and DCS-derived phase requires further investigation.

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.

The consistency of invasive and non-invasive arterial blood pressure for the assessment of dynamic cerebral autoregulation in NICU patients

Background

Studies of the clinical application of dynamic cerebral autoregulation show considerable variations, and differences in blood pressure devices may be one of the reasons for this variation. Few studies have examined the consistency of invasive and non-invasive arterial blood pressure for evaluating cerebral autoregulation. We attempted to investigate the agreement between invasive and non-invasive blood pressure methods in the assessment of dynamic cerebral autoregulation with transfer function analysis.

Methods

Continuous cerebral blood flow velocity and continuous invasive and non-invasive arterial blood pressure were simultaneously recorded for 15 min. Transfer function analysis was applied to derive the phase shift, gain and coherence function at all frequency bands from the first 5, 10, and 15 min of the 15-min recordings. The consistency was assessed with Bland-Altman analysis and intraclass correlation coefficient.

Results

The consistency of invasive and noninvasive blood pressure methods for the assessment of dynamic cerebral autoregulation was poor at 5 min, slightly improved at 10 min, and good at 15 min. The values of the phase shift at the low-frequency band measured by the non-invasive device were higher than those measured with invasive equipment. The coherence function values measured by the invasive technique were higher than the values derived from the non-invasive method.

Conclusion

Both invasive and non-invasive arterial blood pressure methods have good agreement in evaluating dynamic cerebral autoregulation when the recording duration reaches 15 min. The phase shift values measured with non-invasive techniques are higher than those measured with invasive devices. We recommend selecting the most appropriate blood pressure device to measure cerebral autoregulation based on the disease, purpose, and design.

Validity of transcranial Doppler ultrasonography-determined dynamic cerebral autoregulation estimated using transfer function analysis

Transcranial Doppler ultrasonography (TCD) is used widely to evaluate dynamic cerebral autoregulation (dCA). However, the validity of TCD-determined dCA remains unknown because TCD is only capable of measuring blood velocity and thus only provides an index as opposed to true blood flow. To test the validity of TCD-determined dCA, in nine healthy subjects, dCA was evaluated by transfer function analysis (TFA) using cerebral blood flow (CBF) or TCD-measured cerebral blood velocity during a perturbation that induces reductions in TCD-determined dCA, lower body negative pressure (LBNP) at two different stages: LBNP - 15 mmHg and - 50 mmHg. Internal carotid artery blood flow (ICA Q) was assessed as an index of CBF using duplex Doppler ultrasound. The TFA low frequency (LF) normalized gain (ngain) calculated using ICA Q increased during LBNP at - 50 mmHg (LBNP50) from rest (P = 0.005) and LBNP at - 15 mmHg (LBNP15) (P = 0.015), indicating an impaired dCA. These responses were the same as those obtained using TCD-measured cerebral blood velocity (from rest and LBNP15; P = 0.001 and P = 0.015). In addition, the ICA Q-determined TFA LF ngain from rest to LBNP50 was significantly correlated with TCD-determined TFA LF ngain (r = 0.460, P = 0.016) despite a low intraclass correlation coefficient. Moreover, in the Bland-Altman analysis, the difference in the TFA LF ngains determined by blood flow and velocity was within the margin of error, indicating that the two measurement methods can be interpreted as equivalent. These findings suggest that TCD-determined dCA can be representative of actual dCA evaluated with CBF.

Menstrual cycle and oral contraceptives influence cerebrovascular dynamics during hypercapnia

Women experience fluctuating orthostatic intolerance during the menstrual cycle, suggesting sex hormones may influence cerebral blood flow. Young (aged 18-30) healthy women, either taking oral contraceptives (OC; n = 14) or not taking OC (NOC; n = 12), were administered hypercapnic gas (5%) for 5 min in the low hormone (LH; placebo pill) and high hormone (HH; active pill) menstrual phases. Hemodynamic and cerebrovascular variables were continuously measured. Cerebral blood velocity changes were monitored using transcranial doppler ultrasound of the middle cerebral artery to determine cerebrovascular reactivity. Cerebral autoregulation was assessed using steady-state analysis (static cerebral autoregulation) and transfer function analysis (dynamic cerebral autoregulation; dCA). In response to hypercapnia, menstrual phase did not influence static cardiovascular or cerebrovascular responses (all p > 0.07); however, OC users had a greater increase of mean middle cerebral artery blood velocity compared to NOC (NOC-LH 12 ± 6 cm/s vs. NOC-HH 16 ± 9 cm/s; OC-LH 18 ± 5 cm/s vs. OC-HH 17 ± 11 cm/s; p = 0.048). In all women, hypercapnia improved high frequency (HF) and very low frequency (VLF) cerebral autoregulation (decreased nGain; p = 0.002 and <0.001, respectively), whereas low frequency (LF) Phase decreased in NOC-HH (p = 0.001) and OC-LH (p = 0.004). Therefore, endogenous sex hormones reduce LF dCA during hypercapnia in the HH menstrual phase. In contrast, pharmaceutical sex hormones (OC use) have no acute influence (HH menstrual phase) yet elicit a chronic attenuation of LF dCA (LH menstrual phase) during hypercapnia.

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.

Long-term heart transplant recipients: heart rate-related effects on augmented transfer function coherence during repeated squat-stand maneuvers in males

Previous research has highlighted that squat-stand maneuvers (SSMs) augment coherence values within the cerebral pressure-flow relationship to ∼0.99. However, it is not fully elucidated if mean arterial pressure (MAP) leads to this physiological entrainment independently, or if heart rate (HR) and/or the partial pressure of carbon dioxide (Pco₂) also have contributing influences. A 2:1 control-to-case model was used in the present investigation [participant number (n) = 40; n = 16 age-matched (AM); n = 16 donor control (DM); n = 8 heart transplant recipients (HTRs)]. The latter group was used to mechanistically isolate the extent to which HR influences the cerebral pressure-flow relationship. Participants completed 5 min of squat-stand maneuvers at 0.05 Hz (10 s) and 0.10 Hz (5 s). Linear transfer function analysis (TFA) examined the relationship between different physiological inputs (i.e., MAP, HR, and Pco₂) and output [cerebral blood velocity (CBV)] during SSM; and cardiac baroreceptor sensitivity (BRS). Compared with DM, cardiac BRS was reduced in AM (P < 0.001), which was further reduced in HTR (P < 0.045). In addition, during the SSM, HR was elevated in HTR compared with both control groups (P < 0.001), but all groups had near-maximal coherence metrics ≥0.98 at 0.05 Hz and ≥0.99 at 0.10 Hz (P ≥ 0.399). In contrast, the mean HR-CBV/Pco₂-CBV relationships ranged from 0.38 (HTR) to 0.81 (DM). Despite near abolishment of BRS and blunted HR following heart transplantation, long-term HTR exhibited near-maximal coherence within the MAP-CBV relationship, comparable with AM and DM. Therefore, these results show that the augmented coherence with SSM is driven by blood pressure, whereas elevations in TFA coherence as a result of HR contribution are likely correlational in nature.

Estimating confidence intervals for cerebral autoregulation: a parametric bootstrap approach

Cerebral autoregulation (CA) refers to the ability of the brain vasculature to control blood flow in the face of changing blood pressure. One of the methods commonly used to assess cerebral autoregulation, especially in participants at rest, is the analysis of phase derived from transfer function analysis (TFA), relating arterial blood pressure (ABP) to cerebral blood flow (CBF). This and other indexes of CA can provide consistent results when comparing groups of subjects (e.g. patients and healthy controls or normocapnia and hypercapnia) but can be quite variable within and between individuals. The objective of this paper is to present a novel parametric bootstrap method, used to estimate the sampling distribution and hence confidence intervals (CIs) of the mean phase estimate in the low-frequency band, in order to optimise estimation of measures of CA function and allow more robust inferences on the status of CA from individual recordings. A set of simulations was used to verify the proposed method under controlled conditions. In 20 healthy adult volunteers (age 25.53.5 years), ABP and CBF velocity (CBFV) were measured at rest, using a Finometer device and Transcranial Doppler (applied to the middle cerebral artery), respectively. For each volunteer, five individual recordings were taken on different days, each approximately 18 min long. Phase was estimated using TFA. Analysis of recorded data showed widely changing CIs over the duration of recordings, which could be reduced when noisy data and frequencies with low coherence were excluded from the analysis (Wilcoxon signed rank testp= 0.0065). The TFA window-lengths of 50s gave smaller CIs than lengths of 100s (p< 0.001) or 20s (p< 0.001), challenging the usual recommendation of 100s. The method adds a much needed flexible statistical tool for CA analysis in individual recordings.

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.

Near-Infrared Spectroscopy-Derived Dynamic Cerebral Autoregulation in Experimental Human Endotoxemia-An Exploratory Study

Cerebral perfusion may be altered in sepsis patients. However, there are conflicting findings on cerebral autoregulation (CA) in healthy participants undergoing the experimental endotoxemia protocol, a proxy for systemic inflammation in sepsis. In the current study, a newly developed near-infrared spectroscopy (NIRS)-based CA index is investigated in an endotoxemia study population, together with an index of focal cerebral oxygenation.

Methods: Continuous-wave NIRS data were obtained from 11 healthy participants receiving a continuous infusion of bacterial endotoxin for 3 h (ClinicalTrials.gov NCT02922673) under extensive physiological monitoring. Oxygenated–deoxygenated hemoglobin phase differences in the (very)low frequency (VLF/LF) bands and the Tissue Saturation Index (TSI) were calculated at baseline, during systemic inflammation, and at the end of the experiment 7 h after the initiation of endotoxin administration.

Results: The median (inter-quartile range) LF phase difference was 16.2° (3.0–52.6°) at baseline and decreased to 3.9° (2.0–8.8°) at systemic inflammation (p = 0.03). The LF phase difference increased from systemic inflammation to 27.6° (12.7–67.5°) at the end of the experiment (p = 0.005). No significant changes in VLF phase difference were observed. The TSI (mean ± SD) increased from 63.7 ± 3.4% at baseline to 66.5 ± 2.8% during systemic inflammation (p = 0.03) and remained higher at the end of the experiment (67.1 ± 4.2%, p = 0.04). Further analysis did not reveal a major influence of changes in several covariates such as blood pressure, heart rate, PaCO₂, and temperature, although some degree of interaction could not be excluded.

Discussion: A reversible decrease in NIRS-derived cerebral autoregulation phase difference was seen after endotoxin infusion, with a small, sustained increase in TSI. These findings suggest that endotoxin administration in healthy participants reversibly impairs CA, accompanied by sustained microvascular vasodilation.

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.

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.

Separation of normal and impaired dynamic cerebral autoregulation using deep embedded clustering: a proof-of-concept study

Objective. A previous study has shown that a data-driven approach can significantly improve the discriminative power of transfer function analysis (TFA) used to differentiate between normal and impaired cerebral autoregulation (CA) in two groups of data. The data was collected from both healthy subjects (assumed to have normal CA) and symptomatic patients with severe stenosis (assumed to have impaired CA). However, the sample size of the labeled data was relatively small, owing to the difficulty in data collection. Therefore, in this proof-of-concept study, we investigate the feasibility of using an unsupervised learning model to differentiate between normal and impaired CA on TFA variables without requiring labeled data for learning.Approach. Continuous arterial blood pressure (ABP) and cerebral blood flow velocity (CBFV), which were recorded simultaneously for approximately 10 min, were included from 148 subjects (41 healthy subjects, 31 with mild stenosis, 13 with moderate stenosis, 22 asymptomatic patients with severe stenosis, and 41 symptomatic patients with severe stenosis). Tiecks' model was used to generate surrogate data with normal and impaired CA. A recently proposed unsupervised learning model was optimized and applied to separate the normal and impaired CA for both the surrogate data and real data.Main results. It achieved 98.9% and 74.1% accuracy for the surrogate and real data, respectively.Significance. To our knowledge, this is the first attempt to employ an unsupervised data-driven approach to assess CA using TFA. This method enables the development of a classifier to determine the status of CA, which is currently lacking.

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.

What recording duration is required to provide physiologically valid and reliable dynamic cerebral autoregulation transfer functional analysis estimates?

Objective. Currently, a recording of 300 s is recommended to obtain accurate dynamic cerebral autoregulation estimates using transfer function analysis (TFA). Therefore, this investigation sought to explore the concurrent validity and the within- and between-day reliability of TFA estimates derived from shorter recording durations from squat-stand maneuvers.Approach. Retrospective analyses were performed on 70 young, recreationally active or endurance-trained participants (17 females; age: 26 ± 5 years, [range: 20-39 years]; body mass index: 24 ± 3 kg m^-2). Participants performed 300 s of squat-stands at frequencies of 0.05 and 0.10 Hz, where shorter recordings of 60, 120, 180, and 240 s were extracted. Continuous transcranial Doppler ultrasound recordings were taken within the middle and posterior cerebral arteries. Coherence, phase, gain, and normalized gain metrics were derived. Bland-Altman plots with 95% limits of agreement (LOA), repeated measures ANOVA's, two-tailed paired t-tests, coefficient of variation, Cronbach's alpha, intraclass correlation coefficients, and linear regressions were conducted.Main results. When examining the concurrent validity across different recording durations, group differences were noted within coherence (F₍₄₁₅₅₎ > 11.6,p < 0.001) but not phase (F₍₄₁₅₅₎ < 0.27,p > 0.611), gain (F₍₄₁₅₅₎ < 0.61,p > 0.440), or normalized gain (F₍₄₁₅₅₎ < 0.85,p > 0.359) parameters. The Bland-Altman 95% LOA measuring the concurrent validity, trended to narrow as recording duration increased (60 s: < ±0.4, 120 s: < ±0.3, 180 s  < ±0.3, 240 s: < ±0.1). The validity of the 180 and 240 s recordings further increased when physiological covariates were included within regression models.Significance. Future studies examining autoregulation should seek to have participants perform 300 s of squat-stand maneuvers. However, valid and reliable TFA estimates can be drawn from 240 s or 180 s recordings if physiological covariates are controlled.

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.

A Data-Driven Approach to Transfer Function Analysis for Superior Discriminative Power: Optimized Assessment of Dynamic Cerebral Autoregulation

Transfer function analysis (TFA) is extensively used to assess human physiological functions. However, extracting parameters from TFA is not usually optimized for detecting impaired function. In this study, we propose to use data-driven approaches to improve the performance of TFA in assessing blood flow control in the brain (dynamic cerebral autoregulation, dCA). Data were collected from two distinct groups of subjects deemed to have normal and impaired dCA. Continuous arterial blood pressure (ABP) and cerebral blood flow velocity (CBFV) were simultaneously recorded for approximately 10 mins in 82 subjects (including 41 healthy controls) to give 328 labeled samples of the TFA variables. The recordings were further divided into 4,294 short data segments to generate 17,176 unlabeled samples of the TFA variables. We optimized TFA post-processing with a generic semi-supervised learning strategy and a novel semi-supervised stacked ensemble learning (SSEL) strategy for classification into normal and impaired dCA. The generic strategy led to a performance with no significant difference to that of the conventional dCA analysis methods, whereas the proposed new strategy boosted the performance of TFA to an accuracy of 93.3%. To our knowledge, this is the best dCA discrimination performance obtained to date and the first attempt at optimizing TFA through machine learning techniques. Equivalent methods can potentially also be applied to assessing a wide spectrum of other human physiological functions.

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.

Assessment of cerebral autoregulation indices - a modelling perspective

Various methodologies to assess cerebral autoregulation (CA) have been developed, including model - based methods (e.g. autoregulation index, ARI), correlation coefficient - based methods (e.g. mean flow index, Mx), and frequency domain - based methods (e.g. transfer function analysis, TF). Our understanding of relationships among CA indices remains limited, partly due to disagreement of different studies by using real physiological signals, which introduce confounding factors. The influence of exogenous noise on CA parameters needs further investigation. Using a set of artificial cerebral blood flow velocities (CBFV) generated from a well-known CA model, this study aims to cross-validate the relationship among CA indices in a more controlled environment. Real arterial blood pressure (ABP) measurements from 34 traumatic brain injury patients were applied to create artificial CBFVs. Each ABP recording was used to create 10 CBFVs corresponding to 10 CA levels (ARI from 0 to 9). Mx, TF phase, gain and coherence in low frequency (LF) and very low frequency (VLF) were calculated. The influence of exogenous noise was investigated by adding three levels of colored noise to the artificial CBFVs. The result showed a significant negative relationship between Mx and ARI (r = −0.95, p < 0.001), and it became almost purely linear when ARI is between 3 to 6. For transfer function parameters, ARI positively related with phase (r = 0.99 at VLF and 0.93 at LF, p < 0.001) and negatively related with gain_VLF(r = −0.98, p < 0.001). Exogenous noise changed the actual values of the CA parameters and increased the standard deviation. Our results show that different methods can lead to poor correlation between some of the autoregulation parameters even under well controlled situations, undisturbed by unknown confounding factors. They also highlighted the importance of exogenous noise, showing that even the same CA value might correspond to different CA levels under different ‘noise’ 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.