Pitfalls and possibilities of using Root SedLine for continuous assessment of EEG waveform-based metrics in intensive care research.

Objective.The Root SedLine device is used for continuous electroencephalography (cEEG)-based sedation monitoring in intensive care patients. The cEEG traces can be collected for further processing and calculation of relevant metrics not already provided. Depending on the device settings during acquisition, the acquired traces may be distorted by max/min value cropping or high digitization errors. We aimed to systematically assess the impact of these distortions on metrics used for clinical research in the field of neuromonitoring.Approach.A 16 h cEEG acquired using the Root SedLine device at the optimal screen settings was analyzed. Cropping and digitization error effects were simulated by consecutive reduction of the maximum cEEG amplitude by 2µV or by reducing the vertical resolution. Metrics were calculated within ICM+ using minute-by-minute data, including the total power, alpha delta ratio (ADR), and 95% spectral edge frequency. Data were analyzed by creating violin- or box-plots.Main Results.Cropping led to a continuous reduction in total and band power, leading to corresponding changes in variability thereof. The relative power and ADR were less affected. Changes in resolution led to relevant changes. While the total power and power of low frequencies were rather stable, the power of higher frequencies increased with reducing resolution.Significance.Care must be taken when acquiring and analyzing cEEG waveforms from Root SedLine for clinical research. To retrieve good quality metrics, the screen settings must be kept within the central vertical scale, while pre-processing techniques must be applied to exclude unacceptable periods.

Association between EEG metrics and continuous cerebrovascular autoregulation assessment: a scoping review.

OBJECTIVE: Cerebrovascular autoregulation is defined as the capacity of cerebral blood vessels to maintain stable cerebral blood flow despite changing blood pressure. It is assessed using the pressure reactivity index (the correlation coefficient between mean arterial blood pressure and intracranial pressure). The objective of this scoping review is to describe the existing evidence concerning the association of EEG and cerebrovascular autoregulation in order to identify key concepts and detect gaps in the current knowledge. METHODS: Embase, MEDLINE, SCOPUS, and Web of Science were searched considering articles between their inception up to September 2023. Inclusion criteria were human (paediatric and adult) and animal studies describing correlations between continuous EEG and cerebrovascular autoregulation assessments. RESULTS: Ten studies describing 481 human subjects (67% adult, 59% critically ill) were identified. Seven studies assessed qualitative (e.g. seizures, epileptiform potentials) and five evaluated quantitative (e.g. bispectral index, alpha-delta ratio) EEG metrics. Cerebrovascular autoregulation was evaluated based on intracranial pressure, transcranial Doppler, or near infrared spectroscopy. Specific combinations of cerebrovascular autoregulation and EEG metrics were evaluated by a maximum of two studies. Seizures, highly malignant patterns or burst suppression, alpha peak frequency, and bispectral index were associated with cerebrovascular autoregulation. The other metrics showed either no or inconsistent associations. CONCLUSION: There is a paucity of studies evaluating the link between EEG and cerebrovascular autoregulation. The studies identified included a variety of EEG and cerebrovascular autoregulation acquisition methods, age groups, and diseases allowing for few overarching conclusions. However, the preliminary evidence for the presence of an association between EEG metrics and cerebrovascular autoregulation prompts further in-depth investigations.

Inducing oscillations in positive end-expiratory pressure improves assessment of cerebrovascular pressure reactivity in patients with traumatic brain injury.

The cerebral pressure reactivity index (PRx), through intracranial pressure (ICP) measurements, informs clinicians about the cerebral autoregulation (CA) status in adult-sedated patients with traumatic brain injury (TBI). Using PRx in clinical practice is currently limited by variability over shorter monitoring periods. We applied an innovative method to reduce the PRx variability by ventilator-induced slow (1/min) positive end-expiratory pressure (PEEP) oscillations. We hypothesized that, as seen in a previous animal model, the PRx variability would be reduced by inducing slow arterial blood pressure (ABP) and ICP oscillations without other clinically relevant physiological changes. Patients with TBI were ventilated with a static PEEP for 30 min (PRx period) followed by a 30-min period of slow [1/min (0.0167 Hz)] +5 cmH2O PEEP oscillations (induced (iPRx period). Ten patients with TBI were included. No clinical monitoring was discontinued and no additional interventions were required during the iPRx period. The PRx variability [measured as the standard deviation (SD) of PRx] decreased significantly during the iPRx period from 0.25 (0.22-0.30) to 0.14 (0.09-0.17) (P = 0.006). There was a power increase around the induced frequency (1/min) for both ABP and ICP (P = 0.002). In conclusion, 1/min PEEP-induced oscillations reduced the PRx variability in patients with TBI with ICP levels <22 mmHg. No other clinically relevant physiological changes were observed. Reduced PRx variability might improve CA-guided perfusion management by reducing the time to find "optimal" perfusion pressure targets. Larger studies with prolonged periods of PEEP-induced oscillations are required to take it to routine use.NEW & NOTEWORTHY Cerebral autoregulation assessment requires sufficient slow arterial blood pressure (ABP) waves. However, spontaneous ABP waves may be insufficient for reliable cerebral autoregulation estimations. Therefore, we applied a ventilator "sigh-function" to generate positive end-expiratory pressure oscillations that induce slow ABP waves. This method demonstrated a reduced variability of the pressure reactivity index, commonly used as continuous cerebral autoregulation measure in a traumatic brain injury population.

Robotic Semi-Automated Transcranial Doppler Assessment of Cerebrovascular Autoregulation in Post-Concussion Syndrome: Methodological Considerations.

Post-concussion syndrome (PCS) refers to a constellation of physical, cognitive, and emotional symptoms after traumatic brain injury (TBI). Despite its incidence and impact, the underlying mechanisms of PCS are unclear. We hypothesized that impaired cerebral autoregulation (CA) is a contributor. In this article, we present our protocol for non-invasively assessing CA in patients with TBI and PCS in a real-world clinical setting. A prospective, observational study was integrated into outpatient clinics at a tertiary neurosurgical center. Data points included: demographics, symptom profile (Post-Concussion Symptom Scale [PCSS]) and neuropsychological assessment (Cambridge Neuropsychological Test Automated-Battery [CANTAB]). Cerebrovascular metrics (nMxa co-efficient and the transient hyperaemic-response ratio [THRR]) were collected using transcranial Doppler (TCD), finger plethysmography, and bespoke software (ICM+). Twelve participants were initially recruited but 2 were excluded after unsuccessful insonation of the middle cerebral artery (MCA); 10 participants (5 patients with TBI, 5 healthy controls) were included in the analysis (median age 26.5 years, male to female ratio: 7:3). Median PCSS scores were 6/126 for the TBI patient sub-groups. Median CANTAB percentiles were 78 (healthy controls) and 25 (TBI). nMxa was calculated for 90% of included patients, whereas THRR was calculated for 50%. Median study time was 127.5 min and feedback (n = 6) highlighted the perceived acceptability of the study. This pilot study has demonstrated a reproducible assessment of PCS and CA metrics (non-invasively) in a real-world setting. This protocol is feasible and is acceptable to participants. By scaling this methodology, we hope to test whether CA changes are correlated with symptomatic PCS in patients post-TBI.

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.

Brain Tissue Oxygen and Cerebrovascular Reactivity in Traumatic Brain Injury: A Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury Exploratory Analysis of Insult Burden.

Pressure reactivity index (PRx) and brain tissue oxygen (PbtO2) are associated with outcome in traumatic brain injury (TBI). This study explores the relationship between PRx and PbtO2 in adult moderate/severe TBI. Using the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) high resolution intensive care unit (ICU) sub-study cohort, we evaluated those patients with archived high-frequency digital intraparenchymal intracranial pressure (ICP) and PbtO2 monitoring data of, a minimum of 6 h in duration, and the presence of a 6 month Glasgow Outcome Scale -Extended (GOSE) score. Digital physiological signals were processed for ICP, PbtO2, and PRx, with the % time above/below defined thresholds determined. The duration of ICP, PbtO2, and PRx derangements was characterized. Associations with dichotomized 6-month GOSE (alive/dead, and favorable/unfavorable outcome; ≤ 4 = unfavorable), were assessed. A total of 43 patients were included. Severely impaired cerebrovascular reactivity was seen during elevated ICP and low PbtO2 episodes. However, most of the acute ICU physiological derangements were impaired cerebrovascular reactivity, not ICP elevations or low PbtO2 episodes. Low PbtO2 without PRx impairment was rarely seen. % time spent above PRx threshold was associated with mortality at 6 months for thresholds of 0 (area under the curve [AUC] 0.734, p = 0.003), > +0.25 (AUC 0.747, p = 0.002) and > +0.35 (AUC 0.745, p = 0.002). Similar relationships were not seen for % time with ICP >20 mm Hg, and PbtO2 < 20 mm Hg in this cohort. Extreme impairment in cerebrovascular reactivity is seen during concurrent episodes of elevated ICP and low PbtO2. However, the majority of the deranged cerebral physiology seen during the acute ICU phase is impairment in cerebrovascular reactivity, with most impairment occurring in the presence of normal PbtO2 levels. Measures of cerebrovascular reactivity appear to display the most consistent associations with global outcome in TBI, compared with ICP and PbtO2.

Signal Information Prediction of Mortality Identifies Unique Patient Subsets after Severe Traumatic Brain Injury: A Decision-Tree Analysis Approach.

Nonlinear physiological signal features that reveal information content and causal flow have recently been shown to be predictors of mortality after severe traumatic brain injury (TBI). The extent to which these features interact together, and with traditional measures to describe patients in a clinically meaningful way remains unclear. In this study, we incorporated basic demographics (age and initial Glasgow Coma Scale [GCS]) with linear and non-linear signal information based features (approximate entropy [ApEn], and multivariate conditional Granger causality [GC]) to evaluate their relative contributions to mortality using cardio-cerebral monitoring data from 171 severe TBI patients admitted to a single neurocritical care center over a 10 year period. Beyond linear modelling, we employed a decision tree analysis approach to define a predictive hierarchy of features. We found ApEn (p = 0.009) and GC (p = 0.004) based features to be independent predictors of mortality at a time when mean intracranial pressure (ICP) was not. Our combined model with both signal information-based features performed the strongest (area under curve = 0.86 vs. 0.77 for linear features only). Although low "intracranial" complexity (ApEn-ICP) outranked both age and GCS as crucial drivers of mortality (fivefold increase in mortality where ApEn-ICP <1.56, 36.2% vs. 7.8%), decision tree analysis revealed clear subsets of patient populations using all three predictors. Patients with lower ApEn-ICP who were >60 years of age died, whereas those with higher ApEn-ICP and GCS ≥5 all survived. Yet, even with low initial intracranial complexity, as long as patients maintained robust GC and "extracranial" complexity (ApEn of mean arterial pressure), they all survived. Incorporating traditional linear and novel, non-linear signal information features, particularly in a framework such as decision trees, may provide better insight into "health" status. However, caution is required when interpreting these results in a clinical setting prior to external validation.

Feasibility of Hidden Markov Models for the Description of Time-Varying Physiologic State After Severe Traumatic Brain Injury.

OBJECTIVES: Continuous assessment of physiology after traumatic brain injury is essential to prevent secondary brain insults. The present work aims at the development of a method for detecting physiologic states associated with the outcome from time-series physiologic measurements using a hidden Markov model. DESIGN: Unsupervised clustering of hourly values of intracranial pressure/cerebral perfusion pressure, the compensatory reserve index, and autoregulation status was attempted using a hidden Markov model. A ternary state variable was learned to classify the patient's physiologic state at any point in time into three categories ("good," "intermediate," or "poor") and determined the physiologic parameters associated with each state. SETTING: The proposed hidden Markov model was trained and applied on a large dataset (28,939 hr of data) using a stratified 20-fold cross-validation. PATIENTS: The data were collected from 379 traumatic brain injury patients admitted to Addenbrooke's Hospital, Cambridge between 2002 and 2016. INTERVENTIONS: Retrospective observational analysis. MEASUREMENTS AND MAIN RESULTS: Unsupervised training of the hidden Markov model yielded states characterized by intracranial pressure, cerebral perfusion pressure, compensatory reserve index, and autoregulation status that were physiologically plausible. The resulting classifier retained a dose-dependent prognostic ability. Dynamic analysis suggested that the hidden Markov model was stable over short periods of time consistent with typical timescales for traumatic brain injury pathogenesis. CONCLUSIONS: To our knowledge, this is the first application of unsupervised learning to multidimensional time-series traumatic brain injury physiology. We demonstrated that clustering using a hidden Markov model can reduce a complex set of physiologic variables to a simple sequence of clinically plausible time-sensitive physiologic states while retaining prognostic information in a dose-dependent manner. Such states may provide a more natural and parsimonious basis for triggering intervention decisions.

Feasibility of individualised severe traumatic brain injury management using an automated assessment of optimal cerebral perfusion pressure: the COGiTATE phase II study protocol.

INTRODUCTION: Individualising therapy is an important challenge for intensive care of patients with severe traumatic brain injury (TBI). Targeting a cerebral perfusion pressure (CPP) tailored to optimise cerebrovascular autoregulation has been suggested as an attractive strategy on the basis of a large body of retrospective observational data. The objective of this study is to prospectively assess the feasibility and safety of such a strategy compared with fixed thresholds which is the current standard of care from international consensus guidelines. METHODS AND ANALYSIS: CPPOpt Guided Therapy: Assessment of Target Effectiveness (COGiTATE) is a prospective, multicentre, non-blinded randomised, controlled trial coordinated from Maastricht University Medical Center, Maastricht (The Netherlands). The other original participating centres are Cambridge University NHS Foundation Trust, Cambridge (UK), and University Hospitals Leuven, Leuven (Belgium). Adult severe TBI patients requiring intracranial pressure monitoring are randomised within the first 24 hours of admission in neurocritical care unit. For the control arm, the CPP target is the Brain Trauma Foundation guidelines target (60-70 mm Hg); for the intervention group an automated CPP target is provided as the CPP at which the patient's cerebrovascular reactivity is best preserved (CPPopt). For a maximum of 5 days, attending clinicians review the CPP target 4-hourly. The main hypothesis of COGiTATE are: (1) in the intervention group the percentage of the monitored time with measured CPP within a range of 5 mm Hg above or below CPPopt will reach 36%; (2) the difference in between groups in daily therapy intensity level score will be lower or equal to 3. ETHICS AND DISSEMINATION: Ethical approval has been obtained for each participating centre. The results will be presented at international scientific conferences and in peer-reviewed journals. TRIAL REGISTRATION NUMBER: NCT02982122.

Cerebrovascular assessment of patients undergoing shoulder surgery in beach chair position using a multiparameter transcranial Doppler approach.

Although the beach-chair position (BCP) is widely used during shoulder surgery, it has been reported to associate with a reduction in cerebral blood flow, oxygenation, and risk of brain ischaemia. We assessed cerebral haemodynamics using a multiparameter transcranial Doppler-derived approach in patients undergoing shoulder surgery. 23 anaesthetised patients (propofol (2 mg/kg)) without history of neurologic pathology undergoing elective shoulder surgery were included. Arterial blood pressure (ABP, monitored with a finger-cuff plethysmograph calibrated at the auditory meatus level) and cerebral blood flow velocity (FV, monitored in the middle cerebral artery) were recorded in supine and in BCP. All subjects underwent interscalene block ipsilateral to the side of FV measurement. We evaluated non-invasive intracranial pressure (nICP) and cerebral perfusion pressure (nCPP) calculated with a black-box mathematical model; critical closing pressure (CrCP); diastolic closing margin (DCM-pressure reserve available to avoid diastolic flow cessation); cerebral autoregulation index (Mxa); pulsatility index (PI). Significant changes occured for DCM [mean decrease of 6.43 mm Hg (p = 0.01)] and PI [mean increase of 0.11 (p = 0.05)]. ABP, FV, nICP, nCPP and CrCP showed a decreasing trend. Cerebral autoregulation was dysfunctional (Mxa > 0.3) and PI deviated from normal ranges (PI > 0.8) in both phases. ABP and nCPP values were low (< 60 mm Hg) in both phases. Changes between phases did not result in CrCP reaching diastolic ABP, therefore DCM did not reach critical values (≤ 0 mm Hg). BCP resulted in significant cerebral haemodynamic changes. If left untreated, reduction in cerebral blood flow may result in brain ischaemia and post-operative neurologic deficit.

Non-invasive Intracranial Pressure Assessment in Brain Injured Patients Using Ultrasound-Based Methods.

BACKGROUND: Non-invasive measurement of intracranial pressure (ICP) can be invaluable in the management of critically ill patients. Invasive measurement of ICP remains the "gold standard" and should be performed when clinical indications are met, but it is invasive and brings some risks. In this project, we aim to validate the non-invasive ICP (nICP) assessment models based on arterious and venous transcranial Doppler ultrasonography (TCD) and optic nerve sheath diameter (ONSD). METHODS: We included brain injured patients requiring invasive ICP monitoring (intraparenchymal or intraventricular). We assessed the concordance between ICP measured non-invasively with arterious [flow velocity diastolic formula (ICPFVd) and pulsatility index (PI)], venous TCD (vPI) and ICP derived from ONSD (nICPONSD) compared to invasive ICP measurement. RESULTS: Linear regression showed a positive relationship between nICP and ICP for all the methods, except PIv. ICPONSD showed the strongest correlation with invasive ICP (r = 0.61) compared to the other methods (ICPFVd, r = 0.26, p value = 0.0015; PI, r = 0.19, p value = 0.02, vPI, r = 0.056, p value = 0.510). The ability to predict intracranial hypertension was highest for ICPONSD (AUC = 0.91; 95% CI, 0.85-0.97 at ICP > 20 mmHg), with a sensitivity and specificity of 85%, followed by ICPFVd (AUC = 0.67; 95% CI, 0.54-0.79). CONCLUSIONS: Our results demonstrate that among the non-invasive methods studied, ONSD showed the best accuracy in the detection of ICP.

Continuous Autoregulatory Indices Derived from Multi-Modal Monitoring: Each One Is Not Like the Other.

We assess the relationships between various continuous measures of autoregulatory capacity in a cohort of adults with traumatic brain injury (TBI). We assessed relationships between autoregulatory indices derived from intracranial pressure (ICP: PRx, PAx, RAC), transcranial Doppler (TCD: Mx, Sx, Dx), brain tissue-oxygenation (ORx), and spatially resolved near infrared spectroscopy (NIRS resolved: TOx, THx). Relationships between indices were assessed using Pearson correlation coefficient, Friedman test, principal component analysis (PCA), agglomerative hierarchal clustering (AHC) and k-means cluster analysis (KMCA). All analytic techniques were repeated for a range of temporal resolutions of data, including minute-by-minute averages, moving means of 30 samples, and grand mean for each patient. Thirty-seven patients were studied. The PRx displayed strong association with PAx/RAC across all the analytical techniques: Pearson correlation (r = 0.682/r = 0.677, p < 0.0001), PCA, AHC, and KMCA in the grand mean data sheet. Most TCD-based indices (Mx, Dx) were correlated and co-clustered on PCA, AHC, and KMCA. The Sx was found to be more closely associated with ICP-derived indices on Pearson correlation, PCA, AHC, and KMCA. The NIRS indices displayed variable correlation with each other and with indices derived from ICP and TCD signals. Of interest, TOx and THx co-cluster with ICP-based indices on PCA and AHC. The ORx failed to display any meaningful correlations with other indices in neither of the analytical method used. Thirty-minute moving average and minute-by-minute data set displayed similar results across all the methods. The RAC, Mx, and Sx were the strongest predictors of outcome at six months. Continuously updating autoregulatory indices are not all correlated with one another. Caution must be advised when utilizing less commonly described autoregulation indices (i.e., ORx) for the clinical assessment of autoregulatory capacity, because they appear to not be related to commonly measured/establish indices, such as PRx. Further prospective validation is required.

Regulation of the cerebral circulation: bedside assessment and clinical implications.

Regulation of the cerebral circulation relies on the complex interplay between cardiovascular, respiratory, and neural physiology. In health, these physiologic systems act to maintain an adequate cerebral blood flow (CBF) through modulation of hydrodynamic parameters; the resistance of cerebral vessels, and the arterial, intracranial, and venous pressures. In critical illness, however, one or more of these parameters can be compromised, raising the possibility of disturbed CBF regulation and its pathophysiologic sequelae. Rigorous assessment of the cerebral circulation requires not only measuring CBF and its hydrodynamic determinants but also assessing the stability of CBF in response to changes in arterial pressure (cerebral autoregulation), the reactivity of CBF to a vasodilator (carbon dioxide reactivity, for example), and the dynamic regulation of arterial pressure (baroreceptor sensitivity). Ideally, cerebral circulation monitors in critical care should be continuous, physically robust, allow for both regional and global CBF assessment, and be conducive to application at the bedside. Regulation of the cerebral circulation is impaired not only in primary neurologic conditions that affect the vasculature such as subarachnoid haemorrhage and stroke, but also in conditions that affect the regulation of intracranial pressure (such as traumatic brain injury and hydrocephalus) or arterial blood pressure (sepsis or cardiac dysfunction). Importantly, this impairment is often associated with poor patient outcome. At present, assessment of the cerebral circulation is primarily used as a research tool to elucidate pathophysiology or prognosis. However, when combined with other physiologic signals and online analytical techniques, cerebral circulation monitoring has the appealing potential to not only prognosticate patients, but also direct critical care management.

Noninvasive Assessment of ICP: Evaluation of New TBI Data.

BACKGROUND: In a previously introduced mathematical model, intracranial pressure (ICP) was noninvasively assessed using cerebral blood flow velocity (CBFV) and arterial blood pressure (ABP). In this study this method is evaluated using new data from patients with traumatic brain injury (TBI). MATERIALS AND METHODS: Three hundred fifteen data recordings of 137 patients (114 men; age 14-78 years, mean age 37 ± 17 years) with severe TBI were studied. CBFV, ABP, and invasively assessed ICP were simultaneously recorded for 1 h. Noninvasive ICP (nICP) was calculated and compared with ICP. RESULTS: On 315 recordings, average deviation between ICP and nICP (± standard deviation) was 4.9 ± 3.3 mmHg. The standard deviation of differences (ICP - nICP) was 5.6 mmHg. The 95 % confidence interval of ICP prediction ranged from -9.6 to 12.3 mmHg. Mean ICP was 16.7 mmHg and mean nICP was 18.0 mmHg. When nICP was adjusted by their difference 1.3 mmHg (nICPadj = nICP - 1.3), the 95 % confidence limits of ICP prediction became ±11.0 mmHg. In recordings with highly dynamic ICP signals (n = 27), ICP and nICP correlated on average with R = 0.51 ± 0.47. CONCLUSIONS: nICP assessment showed reasonable accuracy and may be used in clinical studies of patients without any indication for ICP probe implantation.

Prospective Study on Noninvasive Assessment of Intracranial Pressure in Traumatic Brain-Injured Patients: Comparison of Four Methods.

Elevation of intracranial pressure (ICP) may occur in many diseases, and therefore the ability to measure it noninvasively would be useful. Flow velocity signals from transcranial Doppler (TCD) have been used to estimate ICP; however, the relative accuracy of these methods is unclear. This study aimed to compare four previously described TCD-based methods with directly measured ICP in a prospective cohort of traumatic brain-injured patients. Noninvasive ICP (nICP) was obtained using the following methods: 1) a mathematical "black-box" model based on interaction between TCD and arterial blood pressure (nICP_BB); 2) based on diastolic flow velocity (nICP_FVd); 3) based on critical closing pressure (nICP_CrCP); and 4) based on TCD-derived pulsatility index (nICP_PI). In time domain, for recordings including spontaneous changes in ICP greater than 7 mm Hg, nICP_PI showed the best correlation with measured ICP (R = 0.61). Considering every TCD recording as an independent event, nICP_BB generally showed to be the best estimator of measured ICP (R = 0.39; p < 0.05; 95% confidence interval [CI] = 9.94 mm Hg; area under the curve [AUC] = 0.66; p < 0.05). For nICP_FVd, although it presented similar correlation coefficient to nICP_BB and marginally better AUC (0.70; p < 0.05), it demonstrated a greater 95% CI for prediction of ICP (14.62 mm Hg). nICP_CrCP presented a moderate correlation coefficient (R = 0.35; p < 0.05) and similar 95% CI to nICP_BB (9.19 mm Hg), but failed to distinguish between normal and raised ICP (AUC = 0.64; p > 0.05). nICP_PI was not related to measured ICP using any of the above statistical indicators. We also introduced a new estimator (nICP_Av) based on the average of three methods (nICP_BB, nICP_FVd, and nICP_CrCP), which overall presented improved statistical indicators (R = 0.47; p < 0.05; 95% CI = 9.17 mm Hg; AUC = 0.73; p < 0.05). nICP_PI appeared to reflect changes in ICP in time most accurately. nICP_BB was the best estimator for ICP "as a number." nICP_Av demonstrated to improve the accuracy of measured ICP estimation.

Comparison of frequency and time domain methods of assessment of cerebral autoregulation in traumatic brain injury.

The impulse response (IR)-based autoregulation index (ARI) allows for continuous monitoring of cerebral autoregulation using spontaneous fluctuations of arterial blood pressure (ABP) and cerebral flow velocity (FV). We compared three methods of autoregulation assessment in 288 traumatic brain injury (TBI) patients managed in the Neurocritical Care Unit: (1) IR-based ARI; (2) transfer function (TF) phase, gain, and coherence; and (3) mean flow index (Mx). Autoregulation index was calculated using the TF estimation (Welch method) and classified according to the original Tiecks' model. Mx was calculated as a correlation coefficient between 10-second averages of ABP and FV using a moving 300-second data window. Transfer function phase, gain, and coherence were extracted in the very low frequency (VLF, 0 to 0.05 Hz) and low frequency (LF, 0.05 to 0.15 Hz) bandwidths. We studied the relationship between these parameters and also compared them with patients' Glasgow outcome score. The calculations were performed using both cerebral perfusion pressure (CPP; suffix 'c') as input and ABP (suffix 'a'). The result showed a significant relationship between ARI and Mx when using either ABP (r=-0.38, P<0.001) or CPP (r=-0.404, P<0.001) as input. Transfer function phase and coherence_a were significantly correlated with ARI_a and ARI_c (P<0.05). Only ARI_a, ARI_c, Mx_a, Mx_c, and phase_c were significantly correlated with patients' outcome, with Mx_c showing the strongest association.

Reliability of the blood flow velocity pulsatility index for assessment of intracranial and cerebral perfusion pressures in head-injured patients.

BACKGROUND: It has been postulated that the Gosling pulsatility index (PI) assessed with transcranial Doppler (TCD) has a diagnostic value for noninvasive estimation of intracranial pressure (ICP) and cerebral perfusion pressure (CPP). OBJECTIVE: To revisit this hypothesis with the use of a database of digitally stored signals from a cohort of head-injured patients. METHODS: We analyzed prospectively collected data of patients admitted to the Cambridge Neuroscience critical care unit who had continuous recordings of arterial blood pressure, ICP, and cerebral blood flow velocities (FVs) using TCD. PI was calculated (FVsys-FVdia)/FVmean over each recording session. Statistical analysis was performed using Spearman rank correlation, receiver-operator-characteristics methods, and modeling of a nonlinear PI-ICP/CPP graph. RESULTS: Seven hundred sixty-two recorded daily sessions from 290 patients were analyzed with a total recording time of 499.9 hours. The correlation between PI and ICP was 0.31 (P<.001) and for PI and CPP -0.41 (P<.001). The 95% prediction interval of ICP values for a given PI was more than ±15 mm Hg and for CPP more than ±25 mm Hg. The diagnostic value of PI to assess ICP area under the curve ranged from 0.62 (ICP>15 mm Hg) to 0.74 (ICP>35 mm Hg). For CPP, the area under the curve ranged from 0.68 (CPP<70 mm Hg) to 0.81 (CPP<50 mm Hg). Probability charts for elevated ICP/lowered CPP depending on PI were created. CONCLUSION: Overall, the value of TCD-PI to assess ICP and CPP noninvasively is very limited. However, extreme values of PI can still potentially be used in support of a decision for invasive ICP monitoring.

ICM+: a versatile software for assessment of CSF dynamics.

ICM+ software was introduced into the Cerebrospinal Fluid (CSF) Dynamics Laboratory, Addenbrooke's Hospital, Cambridge, UK, in 2003. Since then 1,447 constant rate infusion tests and 123 overnight ICP monitoring sessions (using intraparenchymal bolt) were performed. Various configurations were used: ICP only (identification of CSF dynamics model and overnight ICP monitoring with analysis of compensatory reserve and B waves); ICP and arterial pressure (ABP; analysis of the pressure reactivity index); ICP, ABP and transcranial Doppler blood flow velocity (for assessment of cerebral autoregulation); ICP, ABP and near-infrared spectroscopy (for analysis of the fluctuation of cerebral blood volume); ICP, sagittal sinus pressure and jugular vein pressure (in patients with idiopathic intracranial hypertension to assess the hydrodynamic consequences of cerebral venous sinus stenosis). To assess vascular factors of hydrocephalus a combination of CSF infusion study with PET-CBF studies was performed. The software contains a database of the shunts tested in the Cambridge Shunt Evaluation Laboratory, aiding shunt assessment in vivo in the case of possible underdrainage or overdrainage. The software also enables the digital recording of data, ready for post-hoc manual or batch analysis, the creation of virtual signals (such as critical closing pressure, cerebral compliance etc.) and analysis of their dependency on primary modalities. A collected database of cases and signals forms a powerful reference tool in the investigation and understanding of the complex pathophysiology of hydrocephalus.