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A new embolus detection system (EDS) is presented, built with the intention of detecting ongoing cerebral embolization in patients at risk of transient ischaemic attacks or stroke. It is based on the analysis of the audio-Doppler signal of a transcranial Doppler machine. The algorithm of the EDS estimates the intensity, duration and zero-crossing dynamics of the audio signal. The EDS has a multi-layer neural network which classifies events into micro-emboli signals (MES) or artefacts. The decision-making component of the software has been validated against human experts. Data from patients in the post-operative phase of carotid surgery were used for the validation process. The results showed agreement in MES and artefact classification of > 93%. Apart from a monitoring display, the monitoring system includes a verification unit that allows the user to listen and to look at all data of individual MES and artefacts. Moreover, the system allows the user to record, store and re-calculate all data files. Data are stored using European Data Format, which allows data transportation over the Internet. The EDS may have a potential in stroke risk stratification, evaluating the effect of novel anti-thrombotic therapies, and in peri-operative and remote monitoring of carotid endarterectomy.

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The National Health Council of the Netherlands has released a report entitled 'Brain damage in boxers and soccer players'. It examines epidemiology and prevention of cerebral damage from professional and amateur sports, focusing particularly on soccer and boxing. The connection between cerebral injuries and acute and chronic sports injuries is well established. However, proper diagnosis and therapy may be difficult in acute head trauma and during the chronic stage. It makes proposals for a simple cognitive screening test for acute injuries (soccer-related in particular) and more extensive testing for the detection and follow-up of chronic cerebral injuries (boxing-related in particular). Neuropsychological testing may be an important additional diagnostic tool. Professional boxing should be banned if the measures suggested fail to prevent chronic cognitive dysfunction. A dedicated knowledge centre for soccer and boxing would enhance the epidemiology and knowledge of brain injuries, and could help to develop more evidence-based guidelines in the future.

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To assess whether electrophysiological tests are of use in differentiating between patients with asymptomatic cervical stenosis and patients with clinical evidence of myelopathy, we studied motor evoked potentials (MEPs) to magnetic brain stimulation and somatosensory evoked potentials (SEPs) in patients with asymptomatic cervical cord compression and compared the results to healthy age-matched controls. The MEPs were normal in 23 of 25 patients and SEPs in 22 of 23 patients. Thus, MEPs and SEPs are normal in most cases of asymptomatic cervical stenosis. As previous studies have shown MEPs, and to a lesser extent SEPs, to be sensitive in the detection of spondylotic myelopathy, our data indicate that MEP and SEP may be clinically useful for differentiating patients with cervical stenosis who have myelopathy from those who have not.

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In carotid artery disease (CAD) the basilar artery (BA) may act as an important intracranial collateral to supply hypoperfused middle cerebral artery (MCA) territories. Transcranial Doppler studies were performed to study the dependency between BA hemodynamics in relation to the MCA perfusion status. BA and MCA blood flow velocities (BFV), pulsatility indices (API) and cerebrovascular reactivity (CVR) were assessed in 40 patients with a progressive MCA hypoperfusion due to progressive CAD. All patients had patent cervical segments of their vertebral arteries with an antegrade vertebral flow profile. Duplex studies were performed to diagnose the severity of CAD. Hypoperfusion of the MCA was diagnosed by the degree of vasoparalysis assessed by a Diamox procedure. Analysis showed that the basilar BFV significantly increased in cases of progressive CAD, the basilar PI decreased but the basilar CVR remained unchanged. However, in cases of bilateral hemodynamic significant CAD and bilateral exhausted CVR in the MCA territory, the basilar artery did not exhibit an increase of BFVs or a decrease of the basilar PI, but the basilar CVR showed a significant decrease. Basilar artery CVR is not impaired if this artery has a function as intracranial collateral in CAD. However in cases of bilateral hypoperfused MCA territories the basilar artery does not function as a collateral pathway. The basilar CVR declines under these circumstances which merely reflects the exhausted hemodynamics in the anterior/posterior borderzones. This situation might lead to an increased stroke risk in the distal basilar supply zones.

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BACKGROUND AND PURPOSE: Most algorithms used for automatic detection of microembolic signals (MES) are based on power spectral analysis of the Doppler shift. However, controversies exist as to whether these algorithms can replace the human expert. Therefore, a different algorithm was applied that takes advantage of the periodicity of the MES. This so-called nonlinear forecasting (NLF) is able to detect periodicity in a time series, and it is hypothesized that this technique has the potential to detect MES. Moreover, because of the lack of prominent periodicity in both the normal Doppler signals (DS) and movement artifacts (MA), the NLF has a potential to differentiate MES from normal blood flow variations and MA. METHODS: Twenty single MES and 100 MA were selected by 2 human experts. NLF was applied to MES and MA and compared with 200 randomly chosen DS. NLF resulted in a so-called prediction value that ranges from + 1 in signals with prominent periodicity to 0 in signals that lack periodicity. RESULTS: NLF revealed that MES are more predictable than the normal Doppler signals (prediction [MES]=0.829+/-0.084 versus prediction [DS]= -0.060+/-0.228; P<0.0001). Moreover, MES are more predictable than the MA (prediction [MA]=-0.034+/-0.223; P<0.0001). No difference in prediction could be found between DS and MA. CONCLUSIONS: This preliminary report shows that MES can be separated from DS and MA by NLF. Research is needed as to whether this technology can be further developed for automatic detection of MES.

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The objective of this study is to find out which mathematical model best explains the temporal fluctuations of the axial blood flow velocity waveforms in the basal arteries of the brain. Blood flow velocity time series were sampled by transcranial Doppler (TCD) examination of the middle cerebral arteries in 10 healthy volunteers. A recently developed mathematical test (surrogate data analysis) was used to examine whether the spectral Doppler maximum waveform consistent with some prespecified model (null hypothesis). We tested four different null hypothesis. 1. Uncorrelated white noise. 2. Linearly filtered noise. 3. Linearly filtered noise with a static nonlinear amplitude transformation. 4. Noisy nonlinear limit cycle. All null hypotheses except the last one could be rejected. We conclude that the TCD waveforms are best described as nonlinear limit cycle with some percentage of noise, either dynamical and/or observational, which is uncorrelated from one single oscillation to the next. These results are a strong argument to perform nonlinear analysis in future TCD studies in order to obtain a better understanding of the cerebral hemodynamics.

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Nonlinear time series analysis can be used to investigate the dynamics underlying the generation of EEG signal. In the present study we used this approach to study the pathophysiology of PLEDs. We calculated the correlation dimension D2 of an EEG with typical PLEDs, and compared the results with those obtained for surrogate data. These surrogate data have the same power spectrum and amplitude distribution as the original EEG data, but are otherwise random. By construction, such surrogate data can be described by a linear model. Our results showed that D2 estimations for PLEDs were low, on the order of one, and that the results for EEG and the surrogate data were clearly different, indicating that the EEG with PLEDs reflects nonlinear dynamics of the underlying neural networks.

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Electroencephalograms (EEG) were recorded in fourteen patients who experienced a severe septic encephalopathy (SE). EEG analysis included visual inspection, spectral analysis and a recently developed nonlinear analysis (the Kaplan test). All EEGs showed decreased fast activity and an increase of slow wave activity on visual inspection. There was a nonsignificant trend of negative correlation between the spectral EEG analysis and the severity of the acute systemic illness (based on the sum score of 14 variables known as APACHE II score) (standard coefficient = -0.43, p = 0.118). However, a much more pronounced and significant negative correlation was observed between the Kaplan test and the APACHE II score (standard coefficient = -0.94, p = 0.005). The EEG abnormalities seen in these patients were independent of the sedation level. Neither the EEG parameters, nor the APACHE II score, predicted outcome. Nonlinear analysis is more powerful than spectral analysis to extract clinical relevant information from EEGs in patients who experience a severe SE. The nonlinear EEG analysis suggest that brain dynamics in SE may be characterized by a shift into a fundamentally different level of cortical information exchange which can be summarized in nonlinear terminology as a loss of deterministic structure in the EEG.

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Creutzfeldt-Jakob disease is a rare, neurological, dementing disorder characterised by periodic sharp waves in the electroencephalogram (EEG). Non-linear analysis of these EEG changes may provide insight into the abnormal dynamics of cortical neural networks in this disorder. Babloyantz et al. have suggested that the periodic sharp waves reflect low-dimensional chaotic dynamics in the brain. In the present study this hypothesis was re-examined using newly developed techniques for non-linear time series analysis. We analysed the EEG of a patient with autopsy-proven Creutzfeldt-Jakob disease using the method of non-linear forecasting as introduced by Sugihara and May, and we tested for non-linearity with amplitude-adjusted, phase-randomised surrogate data. Two epochs with generalised periodic sharp waves showed clear evidence for non-linearity. These epochs could be predicted better and further ahead in time than most of the irregular background activity. Testing against cycle-randomised surrogate data and close inspection of the periodograms showed that the non-linearity of the periodic sharp waves may be better explained by quasi-periodicity than by low-dimensional chaos. The EEG further displayed at least one example of a sudden, large qualitative change in the dynamics, highly suggestive of a bifurcation. The presence of quasi-periodicity and bifurcations strongly argues for the use of a non-linear model to describe the EEG in Creutzfeldt-Jakob disease.

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In 1942 Gibbs and Reid described a slowing of the electroencephalogram (EEG) at the end of a normal pregnancy. To the best of our knowledge this is the only report that addresses the modification of the EEG in normal pregnancy. We performed a spectral multichannel EEG analysis and revealed no differences during third trimester pregnancy and six months postpartum. Therefore EEG changes seen during pregnancy, which were previously regarded as 'subtle changes of pregnancy', may turn out to be clinically relevant changes which indicate either pre-existing EEG dysfunction or EEG abnormalities in the context of a pregnancy-related disorder.

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The present study outlines the relationship between cerebral and systemic hemodynamics in patients with septic shock. Sepsis is an immune mediated systemic disease in which the systemic vascular resistance (SVR) often decreases as a result of a Gram negative sepsis. The result is a hyperdynamic systemic circulation with redistribution phenomena in different organ systems. In order to study the effect of sepsis on cerebral vessels 20 patients with septic shock (12 men, 8 women, mean age 57.9 years) were subjected to both pulmonary artery catheter and transcranial Doppler (TCD) monitoring. The data were correlated to the APACHE II score and outcome. The study showed that cerebral mean and end-diastolic blood flow velocities (BFV) in the middle cerebral arteries significantly enhanced if the SVR-index decreases. In some patients a severely reduced SVRI (below 500 dynes.s/cm5.m2) was observed in combination with a downstroke latent steal phenomenon. TCD abnormalities were strongly related to disease severity and outcome. The increased BFV are explained by a mild vasospasm of the basal cerebral arteries. TCD appears to be a valuable tool to monitor the cerebral hemodynamics in these patients. They are particularly at risk for ischemic brain damage if they are subjected to therapeutic or spontaneous hyperventilation, which can potentially be detected by TCD.

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Until the last few years the correlation dimension (D2) or the Lyapunow exponent were the two dominant mathematical methods which were applied to identify possible chaotic behavior in biological systems. Detection of deterministic chaos is important, because it suggests that a relatively simple nonlinear model might explain the data. It was however discovered that these methods could give rise to an erroneous detection of chaos. For this reason a new method was proposed in which the originally measured data set was directly compared with a computer generated 'surrogate' data set with exactly the same linear correlations as the original. The basic idea is then to compute a nonlinear statistic for the original data and for each of the surrogate data sets. In principle any statistic can be used. We used the correlation dimension (D2), which measures the complexity of a time series. In this study we applied this surrogate method to estimate whether the variability of the transcranial Doppler (TCD) waveforms is the result of nonlinearity or not. From 10 healthy volunteers, left middle cerebral artery (MCA) blood flow velocities were measured by TCD examinations. An artifact free epoch of each TCD was used for analysis. From each original data set 50 surrogate data sets were constructed using the Gaussian-scaled phase-randomized Fourier transform. For both the original and the surrogate data sets the D2 was measured. The D2 values of the original TCD waveforms differed significantly from the mean D2 of the surrogate data sets. Therefore the null hypothesis, which stated that the original TCD time series arise from filtered noise, is rejected and nonlinearity is detected. The clinical significance and implications are discussed.

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We studied the age- and gender-related changes in complexity of arterial blood flow by analyzing the maximum velocity waveforms. Data were collected by insonation of the middle cerebral artery blood flow by a 2-MHz transcranial pulsed Doppler system. Following the paradigm of nonlinear dynamical systems or "chaos" theory, complexity is best evaluated by estimating the correlation dimension (D2) and the largest Lyapunov exponent (lambda 1). Forty healthy persons (male/female ratio: 1/1; mean age 48.6 y; range 19-86 y) were studied. No gender-related differences were observed. The age-effect showed a diminishing lambda 1 [df(1, 36) = 5.687; p < 0.022] and an increasing D2 at higher age [df(1, 36) = 4.997; p < 0.032]. The age-related decline of the lambda 1 implies a more prominent periodicity, explained by reduced fluctuations in R-R intervals and an altered gain of the baroreceptor reflex. The increased D2 might be related to more prominent vessel wall oscillations due to the increased vessel wall stiffness at higher age.

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Many recent studies based on the surrogate data method failed to identify significant non-linearity in the EEG. In this study we examine whether the use of a different embedding method (spatial instead of time delay), and calculation of Kolmogorov entropy (K2) and the largest Lyapunov exponent (L1) in addition to the correlation dimension (D2), can distinguish the EEG form linearly filtered noise. We have calculated D2, L1 and K2 of original EEG epochs and surrogate (phase randomized) data in 9 control subjects, 9 demented patients and 13 Parkinson patients. The correlation dimension D2 and the largest Lyapunov exponent L1 could distinguish between the EEG tracings and the surrogate data. Demented patients had significantly lower D2 and L1 compared to controls. L1 was higher in Parkinson patients than in demented patients. Contrary to other studies that have used the Theiler surrogate data method, we find evidence for non-linearity in normal and abnormal EEG during the awake/eyes closed state. Apparently it is the spatial structure in the EEG that exhibits much of the non-linear structure. Furthermore, non-linear EEG measures show more or less specific patterns of dysfunction in dementia and Parkinson's disease.

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In order to compare the results of nonlinear analysis of hemodynamically compromised and noncompromised cerebral circulations we measured consecutive transcranial Doppler (TCD) waveforms of fourteen patients with a unilateral or bilateral occlusion of the internal carotid artery. The cerebral vasomotor reactivity (VMR) to acetazolamide in both middle cerebral artery (MCA) territories was established by using TCD. Conventional TCD data and nonlinear TCD analysis of data were compared. Nonlinear analysis of the TCD time series suggested dynamical chaos based on the fractal dimension of the TCD curve and the positive Lyapunov exponents in the compromised and noncompromised MCA territories. In the areas with the compromised circulation the positive Lyapunov exponents were significantly lower compared to the noncompromised side and in some cases with a negative VMR, the Lyapunov exponent was almost zero. The latter is suggestive for periodic behavior of the impaired cerebral circulation instead of the dynamical chaos which is found under normal conditions. The TCD time series of a hemodynamic compromised cerebral territory not only shows phenomena related to a decreased perfusion pressure (such as a 'damped waveform') but also phenomena which are related to a more prominent periodicity. We speculate that conventional and nonlinear TCD analysis could be used to determine the VMR.

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Since the introduction of transcranial Doppler sonography (TCD) several investigators have described the relationship between raised intracranial pressure (ICP) and Doppler waveform. This waveform has been expressed by several indices, such as the pulsatility index (PI) and the resistance index (RI). These indices are used to demonstrate the presence of raised ICP. In childhood hydrocephalus this information can be used to indicate the need for shunt implantation. However, PI and RI do prove to have certain disadvantages as both are strongly influenced by the heart rate. Moreover, both indices have a broad range of reference values, especially in children. Therefore, they are not very reliable for detecting insidious changes in the ICP. These drawbacks are due to the fact that these indices are composed of blood flow velocity measurements and do not embody the slope of the TCD waveform itself. An ideal TCD waveform analysis should be performed concerning the time-related changes of the velocities. We present a hydrodynamic model, with its electrical analogue, which shows the effects of raised ICP on the intracranial hemodynamic system. Based on these physical findings we define a new Doppler index, the Trans Systolic Time, reflecting specific changes in the TCD waveform induced by changes in the mean ICP. The applicability of this index, compared with PI and RI, is illustrated by consecutive simultaneous TCD and AFP measurements in three children with hydrocephalus.

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In order to establish whether or not the cerebral autoregulation is still effective at blood pressure rates in those who experience a chronic cerebral hypotension 37 patients were subjected to noninvasive CO2 enhanced transcranial Doppler (TCD) and ocular pneumoplethysmographic (OPG-GEE) studies of the middle cerebral and ophthalmic arteries. The patients demonstrating a combination of a unilateral patent internal carotid artery (ICA diameter reduction less than 49%) and a contra-lateral ICA occlusion based on duplex scan examinations were examined. The cerebral blood flow velocities at normocapnia (BFV) and pulsatility indices (PI) were measured by TCD. An equivalent of the reserve capacity of the cerebral autoregulation was estimated by quantification of the CO2 enhanced cerebral vasomotor reactivity (VMR). Cerebral blood pressure equivalents such as the OSP/BSP ratio and the ophthalmo-brachial systolic pressure (OBSP) index were estimated by measuring the ocular systolic blood pressure (OSP) and the systemic systolic blood pressure (BSP). The TCD and OPG-GEE data are both in the normal range distally to a patent ICA (n = 22). If the ICA is occluded the OPG-GEE data show a significant reduction in both OSP/BSP ratio's and OBSP indices. If the VMR was in the normal range, distally to an occluded ICA (n = 25), the pressure drop was mild and the BFV at rest was in the normal range. Nevertheless, the waveforms were more damped as seen from the reduction in pulsatility indices but the reduction did not reach statistical significance when compared to the PI values distally to a patent ICA.(ABSTRACT TRUNCATED AT 250 WORDS)

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