Derangement of Cerebral Blood Flow Autoregulation During Intracranial Pressure Plateau Waves as Detected by Time and Frequency-Based Methods.

Plateau waves are sudden elevations of intracranial pressure (ICP) above 40 mmHg, lasting at least 5 min, and are associated with cerebral vasodilatation. We studied the performance of several parameters for cerebral autoregulation assessment during 30 plateau waves of 24 patients with traumatic brain injury. Continuous signals were collected for ICP, arterial blood pressure (ABP) and transcranial Doppler flow velocity (FV). Parameters both in the time domain (autoregulation index, ARI and mean flow index, Mx) and the frequency domain (transfer function gain, phase and coherence) were analysed. The role of different inputs, using either ABP or cerebral perfusion pressure (CPP) as input, was also tested.Autoregulation deteriorated from baseline to plateau, which could be demonstrated by a significant decrease in both ARI between ABP and FV (p = 0.013) and ARI between CPP and FV (p = 0.014). There was also a significant increase in Mx between CPP and FV (p = 0.004), but not in Mx between ABP and FV (p = 0.472). From the baseline to plateau, there was a significant increase in coherence between the ABP and FV at the very low frequency (p = 0.004). The transfer function phase and gain, on the other hand, revealed inconsistent performance.

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.

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.

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.