Individual Patient Data Meta-Analysis of Dynamic Cerebral Autoregulation and Functional Outcome After Ischemic Stroke

BACKGROUND

The relationship between dynamic cerebral autoregulation (dCA) and functional outcome after acute ischemic stroke (AIS) is unclear. Previous studies are limited by small sample sizes and heterogeneity.

METHODS

We performed a 1-stage individual patient data meta-analysis to investigate associations between dCA and functional outcome after AIS. Participating centers were identified through a systematic search of the literature and direct invitation. We included centers with dCA data within 1 year of AIS in adults aged over 18 years, excluding intracerebral or subarachnoid hemorrhage. Data were obtained on phase, gain, coherence, and autoregulation index derived from transfer function analysis at low-frequency and very low-frequency bands. Cerebral blood velocity, arterial pressure, end-tidal carbon dioxide, heart rate, stroke severity and sub-type, and comorbidities were collected where available. Data were grouped into 4 time points after AIS: <24 hours, 24 to 72 hours, 4 to 7 days, and >3 months. The modified Rankin Scale assessed functional outcome at 3 months. Modified Rankin Scale was analyzed as both dichotomized (0 to 2 versus 3 to 6) and ordinal (modified Rankin Scale scores, 0-6) outcomes. Univariable and multivariable analyses were conducted to identify significant relationships between dCA parameters, comorbidities, and outcomes, for each time point using generalized linear (dichotomized outcome), or cumulative link (ordinal outcome) mixed models. The participating center was modeled as a random intercept to generate odds ratios with 95% CIs.

RESULTS

The sample included 384 individuals (35% women) from 7 centers, aged 66.3±13.7 years, with predominantly nonlacunar stroke (n=348, 69%). In the affected hemisphere, higher phase at very low-frequency predicted better outcome (dichotomized modified Rankin Scale) at <24 (crude odds ratios, 2.17 [95% CI, 1.47-3.19]; P<0.001) hours, 24-72 (crude odds ratios, 1.95 [95% CI, 1.21-3.13]; P=0.006) hours, and phase at low-frequency predicted outcome at 3 (crude odds ratios, 3.03 [95% CI, 1.10-8.33]; P=0.032) months. These results remained after covariate adjustment.

CONCLUSIONS

Greater transfer function analysis-derived phase was associated with improved functional outcome at 3 months after AIS. dCA parameters in the early phase of AIS may help to predict functional outcome.

Thalamocortical coherence and causality in different sleep stages using deep brain stimulation recordings

Previous research has shown an interplay between the thalamus and cerebral cortex during NREM sleep in humans, however the directionality of the thalamocortical synchronization is as yet unknown. In this study thalamocortical connectivity during different NREM sleep stages using sleep scalp electroencephalograms and local field potentials from the left and right anterior thalamus was measured in three epilepsy patients implanted with deep brain stimulation electrodes. Connectivity was assessed as debiased weighted phase lag index and granger causality between the thalamus and cortex for the NREM sleep stages N1, N2 and N3. Results showed connectivity was most prominently directed from cortex to thalamus. Moreover, connectivity varied in strength between the different sleep stages, but barely in direction or frequency. These results imply relatively stable thalamocortical connectivity during NREM sleep directed from the cortex to the thalamus.

Spatiotemporal patterns of sleep spindle activity in human anterior thalamus and cortex

Sleep spindles (8 - 16 Hz) are transient electrophysiological events during non-rapid eye movement sleep. While sleep spindles are routinely observed in the cortex using scalp electroencephalography (EEG), recordings of their thalamic counterparts have not been widely studied in humans. Based on a few existing studies, it has been hypothesized that spindles occur as largely local phenomena. We investigated intra-thalamic and thalamocortical spindle co-occurrence, which may underlie thalamocortical communication. We obtained scalp EEG and thalamic recordings from 7 patients that received bilateral deep brain stimulation (DBS) electrodes to the anterior thalamus for the treatment of drug resistant focal epilepsy. Spindles were categorized into subtypes based on their main frequency (i.e., slow (10±2 Hz) or fast (14±2 Hz)) and their level of thalamic involvement (spanning one channel, or spreading uni- or bilaterally within the thalamus). For the first time, we contrasted observed spindle patterns with permuted data to estimate random spindle co-occurrence. We found that multichannel spindle patterns were systematically coordinated at the thalamic and thalamocortical level. Importantly, distinct topographical patterns of thalamocortical spindle overlap were associated with slow and fast subtypes of spindles. These observations provide further evidence for coordinated spindle activity in thalamocortical networks.

Optic nerve sheath diameter assessment by neurosonology: A review of methodologic discrepancies

BACKGROUND AND PURPOSE

Reported cutoff values of the optic nerve sheath diameter (ONSD) for the diagnosis of elevated intracranial pressure (ICP) are inconsistent. This hampers ONSD as a possible noninvasive bedside monitoring tool for ICP. Because the influence of methodological differences on variations in cutoff values is unknown, we performed a narrative review to identify discrepancies in ONSD assessment methodologies and to investigate their effect on reported ONSD values.

METHODS

We used a structured and quantitative approach in which each ONSD methodology found in the reviewed articles was categorized based on the characteristic appearance of the ultrasound images and ultrasound marker placement. Subsequently, we investigated the influence of the different methodologies on ONSD values by organizing the ONSDs with respect to these categories.

RESULTS

In a total of 63 eligible articles, we could determine the applied ONSD assessment methodology. Reported ultrasound images either showed the optic nerve and its sheath as a dark region with hyperechoic striped band at its edges or as a single dark region surrounded by lighter retrobulbar fat. Four different ultrasound marker positions were used to delineate the optic nerve sheath, which resulted in different ONSD values and more importantly, different sensitivities to changes in ICP.

CONCLUSIONS

Based on our observations, we recommend to place ultrasound markers at the outer edges of the hyperechoic striped bands or at the transitions from the single dark region to the hyperechoic retrobulbar fat because these locations yielded the highest sensitivity of ONSD measurements for increased ICP.

An Automated Algorithm for Optic Nerve Sheath Diameter Assessment from B-mode Ultrasound Images

BACKGROUND AND PURPOSE

The optic nerve sheath diameter (ONSD) is a promising surrogate marker for the detection of raised intracranial pressure (ICP). However, inconsistencies in manual ONSD assessment are thought to affect ONSD and the corresponding ONSD cutoff values for the diagnosis of elevated ICP, hereby hampering the full potential of ONSD. In this study, we developed an image intensity-invariant algorithm to automatically estimate ONSD from B-mode ultrasound images at multiple depths.

METHODS

The outcomes of the algorithm were validated against manual ONSD measurements by two human experts. Each expert analyzed the images twice (M1 and M2) in unknown order.

RESULTS

The algorithm proved capable of segmenting the ONSD in 39 of 42 images, hereby showing mean differences of -.08 ± .45 and -.05 ± .41 mm compared to averaged ONSD values (M1 + M2/2) of Operator 1 and Operator 2, respectively, whereas the mean difference between the two experts was .03 ± .26 mm. Moreover, differences between algorithm-derived and expert-derived ONSD values were found to be much smaller than the 1 mm difference that is expected between patients with normal and elevated ICP, making it likely that our algorithm can distinguish between these patient groups.

CONCLUSIONS

Our algorithm has the potential to improve the accuracy of ONSD as a surrogate marker for elevated ICP because it has no intrinsic variability. However, future research should be performed to validate if the algorithm does indeed result in more accurate noninvasive ICP predictions.

Deep Brain Stimulation in Epilepsy: A Role for Modulation of the Mammillothalamic Tract in Seizure Control?

BACKGROUND

Deep brain stimulation of the anterior nucleus of the thalamus (ANT-DBS) can improve seizure control for patients with drug-resistant epilepsy (DRE). Yet, one cannot overlook the high discrepancy in efficacy among patients, possibly resulting from differences in stimulation site.

OBJECTIVE

To test the hypothesis that stimulation at the junction of the ANT and mammillothalamic tract (ANT-MTT junction) increases seizure control.

METHODS

The relationship between seizure control and the location of the active contacts to the ANT-MTT junction was investigated in 20 patients treated with ANT-DBS for DRE. Coordinates and Euclidean distance of the active contacts relative to the ANT-MTT junction were calculated and related to seizure control. Stimulation sites were mapped by modelling the volume of tissue activation (VTA) and generating stimulation heat maps.

RESULTS

After 1 yr of stimulation, patients had a median 46% reduction in total seizure frequency, 50% were responders, and 20% of patients were seizure-free. The Euclidean distance of the active contacts to the ANT-MTT junction correlates to change in seizure frequency (r2 = 0.24, P = .01) and is ∼30% smaller (P = .015) in responders than in non-responders. VTA models and stimulation heat maps indicate a hot-spot at the ANT-MTT junction for responders, whereas non-responders had no evident hot-spot.

CONCLUSION

Stimulation at the ANT-MTT junction correlates to increased seizure control. Our findings suggest a relationship between the stimulation site and therapy response in ANT-DBS for epilepsy with a potential role for the MTT. DBS directed at white matter merits further exploration for the treatment of epilepsy.

Combining Gamma With Alpha and Beta Power Modulation for Enhanced Cortical Mapping in Patients With Focal Epilepsy

About one third of patients with epilepsy have seizures refractory to the medical treatment. Electrical stimulation mapping (ESM) is the gold standard for the identification of “eloquent” areas prior to resection of epileptogenic tissue. However, it is time-consuming and may cause undesired side effects. Broadband gamma activity (55–200 Hz) recorded with extraoperative electrocorticography (ECoG) during cognitive tasks may be an alternative to ESM but until now has not proven of definitive clinical value. Considering their role in cognition, the alpha (8–12 Hz) and beta (15–25 Hz) bands could further improve the identification of eloquent cortex. We compared gamma, alpha and beta activity, and their combinations for the identification of eloquent cortical areas defined by ESM. Ten patients with intractable focal epilepsy (age: 35.9 ± 9.1 years, range: 22–48, 8 females, 9 right handed) participated in a delayed-match-to-sample task, where syllable sounds were compared to visually presented letters. We used a generalized linear model (GLM) approach to find the optimal weighting of each band for predicting ESM-defined categories and estimated the diagnostic ability by calculating the area under the receiver operating characteristic (ROC) curve. Gamma activity increased more in eloquent than in non-eloquent areas, whereas alpha and beta power decreased more in eloquent areas. Diagnostic ability of each band was close to 0.7 for all bands but depended on multiple factors including the time period of the cognitive task, the location of the electrodes and the patient’s degree of attention to the stimulus. We show that diagnostic ability can be increased by 3–5% by combining gamma and alpha and by 7.5–11% when gamma and beta were combined. We then show how ECoG power modulation from cognitive testing can be used to map the probability of eloquence in individual patients and how this probability map can be used in clinical settings to optimize ESM planning. We conclude that the combination of gamma and beta power modulation during cognitive testing can contribute to the identification of eloquent areas prior to ESM in patients with refractory focal epilepsy.

Influence of Anesthesia and Clinical Variables on the Firing Rate, Coefficient of Variation and Multi-Unit Activity of the Subthalamic Nucleus in Patients with Parkinson's Disease

Background: Microelectrode recordings (MER) are used to optimize lead placement during subthalamic nucleus deep brain stimulation (STN-DBS). To obtain reliable MER, surgery is usually performed while patients are awake. Procedural sedation and analgesia (PSA) is often desirable to improve patient comfort, anxiolysis and pain relief. The effect of these agents on MER are largely unknown. The objective of this study was to determine the effects of commonly used PSA agents, dexmedetomidine, clonidine and remifentanil and patient characteristics on MER during DBS surgery. Methods: Data from 78 patients with Parkinson’s disease (PD) who underwent STN-DBS surgery were retrospectively reviewed. The procedures were performed under local anesthesia or under PSA with dexmedetomidine, clonidine or remifentanil. In total, 4082 sites with multi-unit activity (MUA) and 588 with single units were acquired. Single unit firing rates and coefficient of variation (CV), and MUA total power were compared between patient groups. Results: We observed a significant reduction in MUA, an increase of the CV and a trend for reduced firing rate by dexmedetomidine. The effect of dexmedetomidine was dose-dependent for all measures. Remifentanil had no effect on the firing rate but was associated with a significant increase in CV and a decrease in MUA. Clonidine showed no significant effect on firing rate, CV or MUA. In addition to anesthetic effects, MUA and CV were also influenced by patient-dependent variables. Conclusion: Our results showed that PSA influenced neuronal properties in the STN and the dexmedetomidine (DEX) effect was dose-dependent. In addition, patient-dependent characteristics also influenced MER.

Cross-database evaluation of EEG based epileptic seizures detection driven by adaptive median feature baseline correction

OBJECTIVE

In long-term electroencephalogram (EEG) signals, automated classification of epileptic seizures is desirable in diagnosing epilepsy patients, as it otherwise depends on visual inspection. To the best of the author's knowledge, existing studies have validated their algorithms using cross-validation on the same database and less number of attempts have been made to extend their work on other databases to test the generalization capability of the developed algorithms. In this study, we present the algorithm for cross-database evaluation for classification of epileptic seizures using five EEG databases collected from different centers. The cross-database framework helps when sufficient epileptic seizures EEG data are not available to build automated seizure detection model.

METHODS

Two features, namely successive decomposition index and matrix determinant were extracted at a segmentation length of 4 s (50% overlap). Then, adaptive median feature baseline correction (AM-FBC) was applied to overcome the inter-patient and inter-database variation in the feature distribution. The classification was performed using a support vector machine classifier with leave-one-database-out cross-validation. Different classification scenarios were considered using AM-FBC, smoothing of the train and test data, and post-processing of the classifier output.

RESULTS

Simulation results revealed the highest area under the curve-sensitivity-specificity-false detections (per hour) of 1-1-1-0.15, 0.89-0.99-0.82-2.5, 0.99-0.73-1-1, 0.95-0.97-0.85-1.7, 0.99-0.99-0.92-1.1 using the Ramaiah Medical College and Hospitals, Children's Hospital Boston-Massachusetts Institute of Technology, Temple University Hospital, Maastricht University Medical Centre, and University of Bonn databases respectively.

CONCLUSIONS

We observe that the AM-FBC plays a significant role in improving seizure detection results by overcoming inter-database variation of feature distribution.

SIGNIFICANCE

To the best of the author's knowledge, this is the first study reporting on the cross-database evaluation of classification of epileptic seizures and proven to be better generalization capability when evaluated using five databases and can contribute to accurate and robust detection of epileptic seizures in real-time.

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.

Dynamic Cerebral Autoregulation Reproducibility Is Affected by Physiological Variability

Parameters describing dynamic cerebral autoregulation (DCA) have limited reproducibility. In an international, multi-center study, we evaluated the influence of multiple analytical methods on the reproducibility of DCA. Fourteen participating centers analyzed repeated measurements from 75 healthy subjects, consisting of 5 min of spontaneous fluctuations in blood pressure and cerebral blood flow velocity signals, based on their usual methods of analysis. DCA methods were grouped into three broad categories, depending on output types: (1) transfer function analysis (TFA); (2) autoregulation index (ARI); and (3) correlation coefficient. Only TFA gain in the low frequency (LF) band showed good reproducibility in approximately half of the estimates of gain, defined as an intraclass correlation coefficient (ICC) of >0.6. None of the other DCA metrics had good reproducibility. For TFA-like and ARI-like methods, ICCs were lower than values obtained with surrogate data (p < 0.05). For TFA-like methods, ICCs were lower for the very LF band (gain 0.38 ± 0.057, phase 0.17 ± 0.13) than for LF band (gain 0.59 ± 0.078, phase 0.39 ± 0.11, p ≤ 0.001 for both gain and phase). For ARI-like methods, the mean ICC was 0.30 ± 0.12 and for the correlation methods 0.24 ± 0.23. Based on comparisons with ICC estimates obtained from surrogate data, we conclude that physiological variability or non-stationarity is likely to be the main reason for the poor reproducibility of DCA parameters.

Reproducibility of dynamic cerebral autoregulation parameters: a multi-centre, multi-method study

OBJECTIVE

Different methods to calculate dynamic cerebral autoregulation (dCA) parameters are available. However, most of these methods demonstrate poor reproducibility that limit their reliability for clinical use. Inter-centre differences in study protocols, modelling approaches and default parameter settings have all led to a lack of standardisation and comparability between studies. We evaluated reproducibility of dCA parameters by assessing systematic errors in surrogate data resulting from different modelling techniques.

APPROACH

Fourteen centres analysed 22 datasets consisting of two repeated physiological blood pressure measurements with surrogate cerebral blood flow velocity signals, generated using Tiecks curves (autoregulation index, ARI 0-9) and added noise. For reproducibility, dCA methods were grouped in three broad categories: 1. Transfer function analysis (TFA)-like output; 2. ARI-like output; 3. Correlation coefficient-like output. For all methods, reproducibility was determined by one-way intraclass correlation coefficient analysis (ICC).

MAIN RESULTS

For TFA-like methods the mean (SD; [range]) ICC gain was 0.71 (0.10; [0.49-0.86]) and 0.80 (0.17; [0.36-0.94]) for VLF and LF (p  =  0.003) respectively. For phase, ICC values were 0.53 (0.21; [0.09-0.80]) for VLF, and 0.92 (0.13; [0.44-1.00]) for LF (p  <  0.001). Finally, ICC for ARI-like methods was equal to 0.84 (0.19; [0.41-0.94]), and for correlation-like methods, ICC was 0.21 (0.21; [0.056-0.35]).

SIGNIFICANCE

When applied to realistic surrogate data, free from the additional exogenous influences of physiological variability on cerebral blood flow, most methods of dCA modelling showed ICC values considerably higher than what has been reported for physiological data. This finding suggests that the poor reproducibility reported by previous studies may be mainly due to the inherent physiological variability of cerebral blood flow regulatory mechanisms rather than related to (stationary) random noise and the signal analysis methods.

Improved epileptic seizure detection combining dynamic feature normalization with EEG novelty detection

Continuous electroencephalographic monitoring of critically ill patients is an established procedure in intensive care units. Seizure detection algorithms, such as support vector machines (SVM), play a prominent role in this procedure. To correct for inter-human differences in EEG characteristics, as well as for intra-human EEG variability over time, dynamic EEG feature normalization is essential. Recently, the median decaying memory (MDM) approach was determined to be the best method of normalization. MDM uses a sliding baseline buffer of EEG epochs to calculate feature normalization constants. However, while this method does include non-seizure EEG epochs, it also includes EEG activity that can have a detrimental effect on the normalization and subsequent seizure detection performance. In this study, EEG data that is to be incorporated into the baseline buffer are automatically selected based on a novelty detection algorithm (Novelty-MDM). Performance of an SVM-based seizure detection framework is evaluated in 17 long-term ICU registrations using the area under the sensitivity-specificity ROC curve. This evaluation compares three different EEG normalization methods, namely a fixed baseline buffer (FB), the median decaying memory (MDM) approach, and our novelty median decaying memory (Novelty-MDM) method. It is demonstrated that MDM did not improve overall performance compared to FB (p < 0.27), partly because seizure like episodes were included in the baseline. More importantly, Novelty-MDM significantly outperforms both FB (p = 0.015) and MDM (p = 0.0065).

Optimal training dataset composition for SVM-based, age-independent, automated epileptic seizure detection

Automated seizure detection is a valuable asset to health professionals, which makes adequate treatment possible in order to minimize brain damage. Most research focuses on two separate aspects of automated seizure detection: EEG feature computation and classification methods. Little research has been published regarding optimal training dataset composition for patient-independent seizure detection. This paper evaluates the performance of classifiers trained on different datasets in order to determine the optimal dataset for use in classifier training for automated, age-independent, seizure detection. Three datasets are used to train a support vector machine (SVM) classifier: (1) EEG from neonatal patients, (2) EEG from adult patients and (3) EEG from both neonates and adults. To correct for baseline EEG feature differences among patients feature, normalization is essential. Usually dedicated detection systems are developed for either neonatal or adult patients. Normalization might allow for the development of a single seizure detection system for patients irrespective of their age. Two classifier versions are trained on all three datasets: one with feature normalization and one without. This gives us six different classifiers to evaluate using both the neonatal and adults test sets. As a performance measure, the area under the receiver operating characteristics curve (AUC) is used. With application of FBC, it resulted in performance values of 0.90 and 0.93 for neonatal and adult seizure detection, respectively. For neonatal seizure detection, the classifier trained on EEG from adult patients performed significantly worse compared to both the classifier trained on EEG data from neonatal patients and the classier trained on both neonatal and adult EEG data. For adult seizure detection, optimal performance was achieved by either the classifier trained on adult EEG data or the classifier trained on both neonatal and adult EEG data. Our results show that age-independent seizure detection is possible by training one classifier on EEG data from both neonatal and adult patients. Furthermore, our results indicate that for accurate age-independent seizure detection, it is important that EEG data from each age category are used for classifier training. This is particularly important for neonatal seizure detection. Our results underline the under-appreciated importance of training dataset composition with respect to accurate age-independent seizure detection.

Hemodilution Combined With Hypercapnia Impairs Cerebral Autoregulation During Normothermic Cardiopulmonary Bypass

OBJECTIVE

To investigate the influence of hemodilution and arterial pCO2 on cerebral autoregulation and cerebral vascular CO2 reactivity.

DESIGN

Prospective interventional study.

SETTING

University hospital-based single-center study.

PARTICIPANTS

Forty adult patients undergoing elective cardiac surgery using normothermic cardiopulmonary bypass.

INTERVENTIONS

Blood pressure variations induced by 6/minute metronome-triggered breathing (baseline) and cyclic 6/min changes of indexed pump flow at 3 levels of arterial pCO2.

MEASUREMENTS AND MAIN RESULTS

Based on median hematocrit on bypass, patients were assigned to either a group of a hematocrit ≥28% or<28%. The autoregulation index was calculated from cerebral blood flow velocity and mean arterial blood pressure using transfer function analysis. Cerebral vascular CO2 reactivity was calculated using cerebral tissue oximetry data. Cerebral autoregulation as reflected by autoregulation index (baseline 7.5) was significantly affected by arterial pCO2 (median autoregulation index amounted to 5.7, 4.8, and 2.8 for arterial pCO2 of 4.0, 5.3, and 6.6 kPa, p≤0.002) respectively. Hemodilution resulted in a decreased autoregulation index; however, during hypocapnia and normocapnia, there were no significant differences between the two hematocrit groups. Moreover, the autoregulation index was lowest during hypercapnia when hematocrit was<28% (autoregulation index 3.3 versus 2.6 for hematocrit ≥28% and<28%, respectively, p = 0.014). Cerebral vascular CO2 reactivity during hypocapnia was significantly lower when perioperative hematocrit was<28% (p = 0.018).

CONCLUSIONS

Hemodilution down to a hematocrit of<28% combined with hypercapnia negatively affects dynamic cerebral autoregulation, which underlines the importance of tight control of both hematocrit and paCO2 during CPB.

Assessment of dynamic cerebral autoregulation and cerebral carbon dioxide reactivity during normothermic cardiopulmonary bypass

Despite increased risk of neurological complications after cardiac surgery, monitoring of cerebral hemodynamics during cardiopulmonary bypass (CPB) is still not a common practice. Therefore, a technique to evaluate dynamic cerebral autoregulation and cerebral carbon dioxide reactivity (CO2R) during normothermic nonpulsatile CPB is presented. The technique uses continuous recording of invasive arterial blood pressure, middle cerebral artery blood flow velocity, absolute cerebral tissue oxygenation, in-line arterial carbon dioxide levels, and pump flow measurement in 37 adult male patients undergoing elective CPB. Cerebral autoregulation is estimated by transfer function analysis and the autoregulation index, based on the response to blood pressure variation induced by cyclic 6/min changes of indexed pump flow from 2.0 to 2.4 up to 2.8 L/min/m(2). CO2R was calculated from recordings of both cerebral blood flow velocity and cerebral tissue oxygenation. Cerebral autoregulation and CO2R were estimated at hypocapnia, normocapnia, and hypercapnia. CO2R was preserved during CPB, but significantly lower for hypocapnia compared with hypercapnia (p < 0.01). Conversely, cerebral autoregulation parameters such as gain, phase, and autoregulation index were significantly higher (p < 0.01) during hypocapnia compared with both normocapnia and hypercapnia. Assessing cerebral autoregulation and CO2R during CPB, by cyclic alteration of pump flow, showed an impaired cerebral autoregulation during hypercapnia.

A lumped parameter model of cerebral blood flow control combining cerebral autoregulation and neurovascular coupling

Cerebral blood flow regulation is based on a variety of different mechanisms, of which the relative regulatory role remains largely unknown. The cerebral regulatory system expresses two regulatory properties: cerebral autoregulation and neurovascular coupling. Since partly the same mechanisms play a role in cerebral autoregulation and neurovascular coupling, this study aimed to develop a physiologically based mathematical model of cerebral blood flow regulation combining these properties. A lumped parameter model of the P2 segment of the posterior cerebral artery and its distal vessels was constructed. Blood flow regulation is exerted at the arteriolar level by vascular smooth muscle and implements myogenic, shear stress based, neurogenic, and metabolic mechanisms. In eight healthy subjects, cerebral autoregulation and neurovascular coupling were challenged by squat-stand maneuvers and visual stimulation using a checkerboard pattern, respectively. Cerebral blood flow velocity was measured using transcranial Doppler, whereas blood pressure was measured by finger volume clamping. In seven subjects, the model proposed fits autoregulation and neurovascular coupling measurement data well. Myogenic regulation is found to dominate the autoregulatory response. Neurogenic regulation, although only implemented as a first-order mechanism, describes neurovascular coupling responses to a great extent. It is concluded that our single, integrated model of cerebral blood flow control may be used to identify the main mechanisms affecting cerebral blood flow regulation in individual subjects.

Dynamic cerebral autoregulation: different signal processing methods without influence on results and reproducibility

Cerebral autoregulation controls cerebral blood flow under changing cerebral perfusion pressure. Standards for measurement and analysis of dynamic cerebral autoregulation (dCA) are lacking. In this study, dCA reproducibility, quantified by intraclass correlation coefficient, is evaluated for different methodological approaches of transfer function analysis (TFA) and compared with multimodal pressure flow analysis (MMPF). dCA parameters were determined in 19 healthy volunteers during three 15-min lasting epochs of spontaneous breathing. Every spontaneous breathing epoch was followed by 5 min of paced breathing at 6 cycles/min. These six measurements were performed in both a morning and an afternoon session. Analysis compared raw data pre-processing by mean subtraction versus smoothness priors detrending. The estimation of spectral density was either performed by averaging of subsequent time windows or by smoothing the spectrum of the whole recording. No significant influence of pre-processing and spectral estimation on dCA parameters was found. Therefore, there seems to be no need to prescribe a specific signal-processing regime. Poor reproducibility of gain and phase was found for TFA as well as for MMPF. Based on reproducibility, no preference can be made for morning versus afternoon measurements, neither for spontaneous versus paced breathing. Finally, reproducibility results are not in favour of TFA or MMPF.

The visually-evoked cerebral blood flow response in women with a recent history of preeclampsia and/or eclampsia

Several studies provide evidence for altered cerebral hemodynamics during (pre)eclampsia. Whether (pre)eclampsia has a persistent negative impact on cerebral hemodynamics, possibly contributing to an elevated risk of premature stroke, is unknown. The aims of this study were (i) to refine and apply a control system-based method previously introduced by Rosengarten to quantify the visually-evoked blood flow response of the posterior cerebral artery (PCA); and (ii) to test the hypothesis with this method that cerebral hemodynamics in women with a recent history of (pre)eclampsia is abnormal relative to that in parous controls. Hereto, we recorded cerebral blood flow velocity (CBFV) in the PCA by transcranial Doppler (TCD) sonography during cyclic visual stimulation in 15 former preeclamptics, 13 former eclamptics and 13 controls. The typical CBFV response was fitted with the step response of a second-order-linear model enabling quantification by parameters K (gain), zeta (damping), omega (natural frequency), T(v) (rate time) and T(d) (time delay). The method refinement introduced here consisted of response filtering before quantification and of considering the individual instead of group-averaged response patterns. Application of this refinement reduced the fitting errors (1.4 +/- 1.2 vs. 3.2 +/- 1.8, p < 0.01). Intergroup differences in model parameters were not found. Although statistically not significant, a trend was observed that critical damping (zeta>1) occurred more frequently in the combined group of former patients than in the controls (7 of 28 vs.1 of 13, p = 0.16). Critical damping (zeta>1) reflects an abnormal response, which is either compensated for by a rise in rate time ("intermediate"; zeta>1; T(v) > 20) or remains uncompensated ("sluggish"; zeta>1; T(v) < 20). Critical damping increased significantly (p = 0.039) with (pre-)eclampsia-to-test-interval in the PE+E patients with abnormal responses (zeta>1), suggesting that (pre)eclampsia might induce diminishing cerebral hemodynamic function over time. Based on a system-analytical classification approach, the data of this study provide evidence for individual CBFV responses to be abnormal in former (pre)eclamptics compared with controls. Further study is needed to reveal how the abnormal CBFV response classification reflects cerebrovascular dysfunction.

European clinical experience with a dual chamber single pass sensing and pacing defibrillation lead

Dual chamber ICDs are increasingly implanted nowadays, mainly to improve discrimination between supraventricular and ventricular arrhythmias but also to maintain AV synchrony in patients with bradycardia. The aim of this study was to investigate a new single pass right ventricular defibrillation lead capable of true bipolar sensing and pacing in the right atrium and integrated bipolar sensing and pacing in the right ventricle. The performance of the lead was evaluated in 57 patients (age 61 +/- 12 years; New York Heart Association 1.9 +/- 0.6, left ventricular ejection fraction 0.38 +/- 0.15) at implant, at prehospital discharge, and during a 1-year follow-up. Sensing and pacing behavior of the lead was evaluated in six different body positions. In four patients, no stable position of the atrial electrode could intraoperatively be found. The intraoperative atrial sensing was 2.3 +/- 1.6 mV and the atrial pacing threshold 0.8 +/- 0.5 V at 0.5 ms. At follow-up, the atrial sensing ranged from 1.5 mV to 2.2 mV and the atrial pacing threshold product from 0.8 to 1.7 V/ms. In 11 patients, an intermittent atrial sensing problem and in 24 patients an atrial pacing dysfunction were observed in at least one body position. In 565 episodes, a sensitivity of 100% and a specificity of 96.5% were found for ventricular arrhythmias. In conclusion, this single pass defibrillation lead performed well as a VDD lead and for dual chamber arrhythmia discrimination. However, loss of atrial capture in 45% of patients preclude its use in patients depending on atrial pacing.

Validity of a non-invasive determination of the isovolumetric bladder pressure during voiding in men with LUTS

Invasive pressure flow analysis is the gold standard for discriminating between hypocontractile bladder muscle function and infravesical obstruction in male patients with lower urinary tract symptoms. Here a non-invasive method to determine the isovolumetric bladder pressure to judge contractility is presented. This is based on interruption of urine flow by sudden occlusion of a specially fixed condom catheter. The pressure inside the condom is recorded and used to estimate the isovolumetric bladder pressure. Combined with, for example, home uroflowmetry, this non-invasive method may overcome some of the disadvantages (e.g., invasiveness, cost) of the conventional pressure flow test. To determine the isovolumetric bladder pressure reliably with this non-invasive method, two constraints have to be met. First, the bladder neck and urethra have to remain open after occlusion of the condom catheter. This was tested combining the non-invasive test with radiography in five patients. Second, a steady state has to be reached, i.e., the flow in the urethra, due to the elastic properties of the biological and the condom systems, should come to a stop when the bladder pressure and the condom pressure equilibrate. This was investigated by comparing the non-invasively recorded condom pressure with the simultaneously invasively recorded intravesical pressure in 52 patients. In these patients, three different methods of condom fixation were evaluated. The results show that the bladder neck and urethra remain open during the test. However, a steady state is often not reached. In more than 80% of the cases with the best condom fixation, the bladder pressure has not stabilized, although the condom pressure reached a plateau. Therefore, this method of sudden occlusion is not yet clinically applicable for determining the isovolumetric bladder pressure. Neurourol. Urodynam. 18:477-486, 1999.

A non-invasive method for bladder electromyography in humans

No convincing correlation of bladder EMG in humans to simultaneously measured intravesical pressure has been reported in the literature. In most studies on bladder EMG the electrodes contact the bladder wall itself. This causes problems in the discrimination between very small extracellular signals, reflecting actual membrane potential changes of bladder muscle cells, and large electro-mechanical artefact caused by electrode movement as the tissue contracts. Aim of this study is to investigate whether bladder EMG can be performed non-invasively with Ag-AgCl surface electrodes that are placed on the abdominal skin of healthy volunteers. Bipolar electrode signals are obtained in a diagonal, vertical and horizontal direction of the abdominal electrodes. A conventional urodynamic investigation is performed according to International Continence Society standards simultaneously with bladder EMG. This new method shows that voiding is accompanied by a slow voltage change in bipolar electrode signals. The contribution of abdominal and other striated muscle activity to the bipolar electrode signals can clearly be distinguished from the slow voltage changes related to voiding. Free flowmetry shows that the electrical activity picked up by the abdominal electrodes is related to bladder emptying. In pressure/flow studies a relation between the electrical activity and the detrusor pressure is found. The present results suggest that the slow voltage changes found during bladder contraction are caused by summed membrane potential changes of bladder muscle cells, but this concept needs further testing. Also, validation for clinical use remains to be established.

A method for the electromyographic mapping of the detrusor smooth muscle

Various methods for detrusor EMG in the living mammal have been described in the literature. These methods do insufficiently take into account signal components that are caused by movement between the electrodes and the bladder wall. Reliable detrusor EMG has not been achieved yet. This study investigates the feasibility of a new experimental set-up, in which the electrical activity of the detrusor smooth muscle can be examined. In six rabbits, after cervical dislocation, laparotomy and after excision of the heart, electrical signals of the detrusor muscle are measured with 240 electrodes. The electrodes are positioned on the serosal surface of the filled and isovolumetric bladder. During the recordings, no bladder contractions are deliberately evoked by any stimulus. Consistent results in all six animals show a repetitive spike pattern on multiple electrodes with a repetition frequency of 1.2 Hz. Spikes are triphasic and have a mean duration of 0.47 s (STD = 0.15 s, n = 40) and a mean amplitude of 0.29 mV (STD = 0.07 mV, n = 40). On adjacent electrodes a time shift between the spikes is found, suggesting the propagation of electrical activity across the detrusor surface. The maximum conduction velocity of an arbitrary spike front in the direction of propagation is approximately 30 mm/s. In two animals slow waves are found on the edge of the highpass filter setting. Extensive control experiments are executed to validate the set-up and to interpret the data obtained by the animal experiments. The bladder is still able to contract thirty minutes post mortem. The heart, as a distant signal source, generates a signal that is present on all electrodes and shows no detectable time shift from one electrode to any other. Motion imposed on the electrodes relative to the bladder wall does not reproduce the slow waves and spikes found in the animal experiments. The control experiments support that the results of the animal experiments show electrical activity originating from the detrusor muscle itself. With the experimental set-up described in this paper, nearly artefact free detrusor EMG can be recorded. An electromyographic map of a considerable detrusor smooth muscle area can be obtained.

Ambulatory urodynamics

Ambulatory monitoring of lower and upper urinary tract continues to develop. The addition of electronic urine-loss measurements to indicate the exact time-related loss is an important new feature. In the near future, quantitative urine-loss measurements will become available. The additional possibility of plugging in a flowmeter completes the technique with respect to pressure-flow analysis. At present, however, ambulatory urodynamics is still confined to specialized urodynamic centers. Ambulatory urodynamic monitoring has shown that de-novo detrusor instability after a suspension operation is frequently missed as a preoperative diagnosis of detrusor overactivity. The first steps are being taken toward giving a quantitative analysis of detrusor activity during the filling phase. This justifies a more widespread use of this ambulatory monitoring.