Magdalena Kasprowicz

Impairment of Cerebral Autoregulation Predicts Delayed Cerebral Ischemia After Subarachnoid Hemorrhage: A Prospective Observational Study

Background and Purpose— Delayed cerebral ischemia (DCI) is a recognized contributor to unfavorable outcome after subarachnoid hemorrhage (SAH). Recent data challenge the concept of vasospasm as the sole cause of ischemia and suggest a multifactorial process with dysfunctional cerebral autoregulation as a component. We tested the hypothesis that early autoregulatory failure, detected using near-infrared spectroscopy–based index, TOxa and transcranial Doppler–based index, Sxa, can predict DCI. Methods— In this prospective observational study we enrolled consecutive patients with aneurysmal SAH that occurred <5 days from admission. The primary end point was the occurrence of DCI within 21 days of ictus. The predictive value of autoregulatory disturbances detected in the first 5 days was assessed using univarate proportional hazards model and a multivariate model. Results— Ninety-eight patients were included. Univariate analysis demonstrated increased odds of developing DCI when early autoregulation failure was detected (odds ratio [OR], 7.46; 95% confidence interval [CI], 3.03–18.40 and OR, 4.52; 95% CI, 1.84–11.07 for Sxa and TOxa, respectively) but not TCD-vasospasm (OR, 1.36; 95% CI, 0.56–3.33). In a multivariate model Sxa and TOxa remained independent predictors of DCI (OR, 12.66; 95% CI, 2.97–54.07 and OR, 5.34; 95% CI, 1.25–22.84 for Sxa and TOxa, respectively). Conclusions— Disturbed autoregulation in the first 5 days after SAH significantly increases the risk of DCI. Autoregulatory disturbances can be detected using near-infrared spectroscopy and transcranial Doppler technologies.

What Shapes Pulse Amplitude of Intracranial Pressure

The pulsatile component of intracranial pressure (ICP) has been shown to be a predictor of outcome in normal pressure hydrocephalus (NPH) and traumatic brain injury (TBI). Experimental studies have demonstrated that the pulse amplitude of ICP (AMP(ICP)) is dependent on the mean ICP (mICP), and on the pulse amplitude of the cerebral arterial blood volume (AMP(CaBV)), according to the exponential craniospinal compliance curve. In this study, we compared the influence of mICP and AMP(CaBV) on AMP(ICP) in patients with NPH (infusion study) and TBI (spontaneous recording). We retrospectively analyzed 25 NPH and 43 TBI patients with continuous monitoring of ICP and cerebral blood flow velocity (CBFV), as assessed with transcranial doppler. AMP(CaBV) was extracted from the CBFV waveform. The influence of mICP and AMP(CaBV) on AMP(ICP) were determined using partial coefficients a, b, and c of the multiple regression model: AMP(ICP) = a * mICP + b * AMP(CaBV) + c. AMP(ICP) was more dependent on mICP in NPH patients than in TBI patients (partial coefficient a = 0.93 versus -0.03; p < 0.001). On the contrary, AMP(ICP) was more dependent on AMP(CaBV) in patients with TBI than in those with NPH (b = 0.86 versus 0.10; p < 0.001). This study shows that AMP(ICP) depends mostly on changes in mean ICP during cerebrospinal fluid (CSF) infusion studies in patients with NPH, and on changes in cerebral arterial blood volume (AMP(CaBV)) in TBI patients. Further clinical studies will reveal whether AMP(ICP) is a better indicator of clinical severity and outcome than mICP in TBI and NPH patients.

Cerebral autoregulation after subarachnoid hemorrhage: comparison of three methods.

In patients after subarachnoid hemorrhage (SAH) failure of cerebral autoregulation is associated with delayed cerebral ischemia (DCI). Various methods of assessing autoregulation are available, but their predictive values remain unknown. We characterize the relationship between different indices of autoregulation. Patients with SAH within 5 days were included in a prospective study. The relationship between three indices of autoregulation was analyzed: two indices calculated using spontaneous blood pressure fluctuations, Sxa (based on transcranial Doppler) and TOxa (based on near-infrared spectroscopy); and transient hyperemic response test (THRT) where a brief compression of the common carotid artery is used. The predictive value of indices was assessed using data from the first 5 days. Overall there was only moderate correlation between indices. However, both Sxa and TOxa showed good accuracy in predicting impaired autoregulation evidenced by a negative THRT (area under the curve (AUC): 0.788, 95% CI: 0.723 to 0.854 and AUC: 0.827, 95% CI: 0.769 to 0.885, respectively). All indices proved accurate in predicting DCI when 0- to 5-day data were used (AUC: 0.801, 95% CI: 0.660 to 0.942; AUC: 0.857, 95% CI: 0.731 to 0.984, AUC: 0.796, 95% CI: 0.658 to 0.934 for THRT, Sxa, and TOxa, respectively). Combining all three indices had 100% specificity for predicting DCI. While multiple colinearities exist between the assessed methods, multimodal monitoring of cerebral autoregulation can aid in predicting DCI.

What comes first? The dynamics of cerebral oxygenation and blood flow in response to changes in arterial pressure and intracranial pressure after head injury

BACKGROUND Brain tissue partial oxygen pressure (Pbt(O(2))) and near-infrared spectroscopy (NIRS) are novel methods to evaluate cerebral oxygenation. We studied the response patterns of Pbt(O(2)), NIRS, and cerebral blood flow velocity (CBFV) to changes in arterial pressure (AP) and intracranial pressure (ICP). METHODS Digital recordings of multimodal brain monitoring from 42 head-injured patients were retrospectively analysed. Response latencies and patterns of Pbt(O(2)), NIRS-derived parameters [tissue oxygenation index (TOI) and total haemoglobin index (THI)], and CBFV reactions to fluctuations of AP and ICP were studied. RESULTS One hundred and twenty-one events were identified. In reaction to alterations of AP, ICP reacted first [4.3 s; inter-quartile range (IQR) -4.9 to 22.0 s, followed by NIRS-derived parameters and CBFV (10.9 s; IQR: -5.9 to 39.6 s, 12.1 s; IQR: -3.0 to 49.1 s, 14.7 s; IQR: -8.8 to 52.3 s for THI, CBFV, and TOI, respectively), with Pbt(O(2)) reacting last (39.6 s; IQR: 16.4 to 66.0 s). The differences in reaction time between NIRS parameters and Pbt(O(2)) were significant (P<0.001). Similarly when reactions to ICP changes were analysed, NIRS parameters preceded Pbt(O(2)) (7.1 s; IQR: -8.8 to 195.0 s, 18.1 s; IQR: -20.6 to 80.7 s, 22.9 s; IQR: 11.0 to 53.0 s for THI, TOI, and Pbt(O(2)), respectively). Two main patterns of responses to AP changes were identified. With preserved cerebrovascular reactivity, TOI and Pbt(O(2)) followed the direction of AP. With impaired cerebrovascular reactivity, TOI and Pbt(O(2)) decreased while AP and ICP increased. In 77% of events, the direction of TOI changes was concordant with Pbt(O(2)). CONCLUSIONS NIRS and transcranial Doppler signals reacted first to AP and ICP changes. The reaction of Pbt(O(2)) is delayed. The results imply that the analysed modalities monitor different stages of cerebral oxygenation.

The monitoring of relative changes in compartmental compliances of brain

The study aimed to develop a computational method for assessing relative changes in compartmental compliances within the brain: the arterial bed and the cerebrospinal space. The method utilizes the relationship between pulsatile components in the arterial blood volume, arterial blood pressure (ABP) and intracranial pressure (ICP). It was verified by using clinical recordings of intracranial pressure plateau waves, when massive vasodilatation accompanying plateau waves produces changes in brain compliances of the arterial bed (C(a)) and compliance of the cerebrospinal space (C(i)). Ten patients admitted after head injury with a median Glasgow Coma Score of 6 were studied retrospectively. ABP was directly monitored from the radial artery. Changes in the cerebral arterial blood volume were assessed using Transcranial Doppler (TCD) ultrasonography by digital integration of inflow blood velocity. During plateau waves, ICP increased (P = 0.001), CPP decreased (P = 0.001), ABP remained constant (P = 0.532), blood flow velocity decreased (P = 0.001). Calculated compliance of the arterial bed C(a) increased significantly (P = 0.001); compliance of the CSF space C(i) decreased (P = 0.001). We concluded that the method allows for continuous monitoring of relative changes in brain compartmental compliances. Plateau waves affect the balance between vascular and CSF compartments, which is reflected by the inverse change of compliance of the cerebral arterial bed and global compliance of the CSF space.

Critical closing pressure determined with a model of cerebrovascular impedance.

Critical closing pressure (CCP) is the arterial blood pressure (ABP) at which brain vessels collapse and cerebral blood flow (CBF) ceases. Using the concept of impedance to CBF, CCP can be expressed with brain-monitoring parameters: cerebral perfusion pressure (CPP), ABP, blood flow velocity (FV), and heart rate. The novel multiparameter method (CCPm) was compared with traditional transcranial Doppler (TCD) calculations of CCP (CCP1). Digital recordings of ABP, intracranial pressure (ICP), and TCD-based FV from previously published studies of 29 New Zealand White rabbits were reanalyzed. Overall, CCP1 and CCPm showed correlation across wide ranges of ABP, ICP, and PaCO2 (R = 0.93, P < 0.001). Three physiological perturbations were studied: increase in ICP (n = 29) causing both CCP1 and CCPm to increase (P < 0.001 for both); reduction of ABP (n = 10) resulting in decrease of CCP1 (P = 0.006) and CCPm (P = 0.002); and controlled increase of PaCO2 (n = 8) to hypercapnic levels, which decreased CCP1 and CCPm, albeit insignificantly (P = 0.123 and P = 0.306 respectively), caused by a spontaneous significant increase in ABP (P = 0.025). Multiparameter mathematical model of critical closing pressure explains the relationship of CCP on brain-monitoring variables, allowing the estimation of CCP during cases such as hypercapnia-induced hyperemia, where traditional calculations, like CCP1, often reach negative non-physiological values.

Analysis of intracranial pressure during and after the infusion test in patients with communicating hydrocephalus

The cerebrospinal fluid (CSF) infusion test is used to evaluate the dynamics of CSF circulation in patients with communicating hydrocephalus and is based on constant-rate infusion of the normal saline into cerebrospinal fluid space. The aim of the study was to refine methods of the analysis of intracranial pressure (ICP) recorded during and after the infusion test. The mathematical model of cerebrospinal fluid circulation was extended by the equation describing ICP decrease after the infusion. The nonlinear least-squares method of Levenberg–Marquardt was used to estimate the parameters describing the CSF compensatory mechanisms. Twenty-seven infusion tests were studied. Both phases of the test—the increase and the decrease of ICP—were recorded and the compensatory parameters were calculated for each of them. ICP often does not return to the resting level after the infusion test within the period equivalent to the time of infusion in all cases. In 20 tests the differences between post- and pre-infusion resting ICP (ΔICP) was higher than 1 mmHg, which was considered as significant. The mean value of ΔICP for 20 infusion tests was 3.0 ± 0.7 mmHg. The cerebral elasticity evaluated during the infusion was greater than the elasticity estimated from the decreasing phase after the infusion (0.24 ± 0.07 ml−1 versus 0.14 ± 0.03 ml−1; p < 0.01).

The limitations of near-infrared spectroscopy to assess cerebrovascular reactivity: the role of slow frequency oscillations.

BACKGROUND:A total hemoglobin reactivity index (THx) derived from near-infrared spectroscopy (NIRS) has recently been introduced to assess cerebrovascular reactivity noninvasively. Analogously to the pressure reactivity index (PRx), THx is calculated as correlation coefficient with arterial blood pressure (ABP). However, the reliability of THx in the injured brain is uncertain. Although slow oscillations have been described in NIRS signals, their significance for assessment of autoregulation remains unclear. In the current study, we investigated the role of slow oscillations of total hemoglobin for NIRS-based cerebrovascular reactivity monitoring. METHODS:This study was based on a retrospective analysis of data that were consecutively recorded for a different project published previously. Thirty-seven patients with traumatic brain injury and admitted to Addenbrookes Neurosciences Critical Care Unit between June 2008 and June 2009 were included. After artifact removal, we performed spectral analysis of the tissue hemoglobin index (THI, a measure of oxy- and deoxygenated hemoglobin) and intracranial pressure (ICP) signal. PRx and THx were calculated as moving correlations between ICP and ABP, and THI and ABP, respectively. The agreement between PRx and THx as a function of normalized power of slow oscillations (0.015–0.055 Hz) contained in the input signals was assessed performing between-subject and within-subject correlation analyses. Furthermore, the correlation between the THx values derived from the right and left sides was analyzed. RESULTS:The agreement between PRx and THx depended on the power of slow oscillations in the input signals. Between-subject comparisons revealed a significant correlation between THx and PRx (r = 0.80, 95% confidence interval 0.53–0.92, P < 0.01) for patients with normalized slow wave activity >0.4 in the THI signal, compared with r = 0.07 (95% confidence interval −0.40 to 0.51, P = 0.79) in the remaining files. Furthermore, within-subject comparisons suggested that THx may be used as a substitute for PRx only when there is an at least moderate agreement (r = 0.36) between the THx values derived from the right and left sides. CONCLUSIONS:Our results suggest that the NIRS-based cerebrovascular reactivity index THx can be used as a noninvasive substitute for PRx, but only during phases with sufficient slow wave power in the input signal. Furthermore, a good agreement between the THx measures on both sides seems to be a prerequisite for comparison of a global (PRx) versus the more local (THx) index. Nevertheless, noninvasive assessment of cerebrovascular reactivity may be desirable in patients without ICP monitoring and help to guide ABP management in these patients.

Pattern Recognition of Overnight Intracranial Pressure Slow Waves using Morphological Features of Intracranial Pressure Pulse

This study aimed to develop a new approach to detect intracranial pressure (ICP) slow waves based on morphological changes of ICP pulse waveforms. A recently proposed Morphological Clustering and Analysis of ICP Pulse (MOCAIP) algorithm was utilized to calculate a set of metrics that characterize ICP pulse morphology. A regularized linear quadratic classifier was used to test the hypothesis that classification between ICP slow wave and flat ICP could be achieved using features composed of mean values and dispersion of 24 MOCAIP metrics. To optimize the classification performance, three feature selection techniques (differential evolution, discriminant analysis and analysis of variance) were applied to find an optimal set of MOCAIP metrics under different criteria. In addition, we selected three sets of metrics common to those found by combination of two selection methods, to be used as classification features (differential evolution and analysis of variance, discriminant analysis and analysis of variance, and combination of differential evolution and discriminant analysis). To test the approach, a total of 276 selections of ICP recordings corresponding to two patterns without waves and containing slow waves were obtained from overnight ICP studies of 44 hydrocephalus patients performed at the UCLA Adult Hydrocephalus Center. Our results showed that the best classification performance of differentiation of slow waves from the ICP recording without slow waves was obtained using the combination of metrics common to both differential evolution and analysis of variance methods; achieving an accuracy of 89%, specificity 96%, and sensitivity 83%.

Cerebrovascular time constant: dependence on cerebral perfusion pressure and end-tidal carbon dioxide concentration.

Abstract Objective: The cerebrovascular time constant (τ) describes the time to establish a change in cerebral blood volume after a step transient in arterial blood pressure (ABP). We studied the relationship between τ, ABP, intracranial pressure (ICP), and end-tidal carbon dioxide concentration (EtCO2). Method: Recordings from 46 anaesthetized, paralysed and ventilated New Zealand rabbits were analysed retrospectively. ABP was directly monitored in the femoral artery, transcranial Doppler (TCD) cerebral blood flow velocity (CBFV) from the basilar artery, and ICP using an intraparenchymal sensor. In nine animals end-tidal CO2 (EtCO2) was monitored continuously. ABP was decreased with injection of trimetophan (n = 11) or haemorrhage (n = 6) and increased by boluses of dopamine (n = 11). ICP was increased by infusion of normal saline into the lumbar cerebrospinal fluid space (n = 9). Changes in cerebral compliance (Ca) were estimated as a ratio of the pulse amplitude of the cerebral arterial blood volume (CBV) and the pulse amplitude of ABP. Changes in cerebrovascular resistance (CVR) were expressed as mean ABP or cerebral perfusion pressure (CPP) divided by mean CBFV. Time constant τ was calculated as the product of CVR and Ca. Results: The time constant changed inversely to the direction of the change in ABP (during arterial hypo- and hypertension) and CPP (during intracranial hypertension). Ca increased with decreasing CPP, while CVR decreased. During a decrease in CPP, changes in Ca exceeded changes in CVR. In contrast, during hypercapnia, the decrease in CVR was more pronounced than the increase in Ca, resulting in a decreasein τ. Conclusion: Cerebrovascular time constant τ is modulated by ABP, ICP, and EtCO2.