A Randomized Trial for the Treatment of Refractory Status Epilepticus

Background: Refractory status epilepticus (RSE) has a mortality of 16-39%; coma induction is advocated for its management, but no comparative study has been performed. We aimed to assess the effectiveness (RSE control, adverse events) of the first course of propofol versus barbiturates in the treatment of RSE. Methods: In this randomized, single blind, multi-center trial studying adults with RSE not due to cerebral anoxia, medications were titrated toward EEG burst-suppression for 36-48h and then progressively weaned. The primary endpoint was the proportion of patients with RSE controlled after a first course of study medication; secondary endpoints included tolerability measures. Results: The trial was terminated after 3years, with only 24 patients recruited of the 150 needed; 14 subjects received propofol, 9 barbiturates. The primary endpoint was reached in 43% in the propofol versus 22% in the barbiturates arm (P=0.40). Mortality (43 vs. 34%; P=1.00) and return to baseline clinical conditions at 3months (36 vs. 44%; P=1.00) were similar. While infections and arterial hypotension did not differ between groups, barbiturate use was associated with a significantly longer mechanical ventilation (P=0.03). A non-fatal propofol infusion syndrome was detected in one patient, while one subject died of bowel ischemia after barbiturates. Discussion: Although undersampled, this trial shows significantly longer mechanical ventilation with barbiturates and the occurrence of severe treatment-related complications in both arms. We describe practical issues necessary for the success of future studies needed to improve the current unsatisfactory state of evidenc

Influence of time-series normalization, number of nodes, connectivity and graph measure selection on seizure-onset zone localization from intracranial EEG

We investigated the influence of processing steps in the estimation of multivariate directed functional connectivity during seizures recorded with intracranial EEG (iEEG) on seizure-onset zone (SOZ) localization. We studied the effect of (i) the number of nodes, (ii) time-series normalization, (iii) the choice of multivariate time-varying connectivity measure: Adaptive Directed Transfer Function (ADTF) or Adaptive Partial Directed Coherence (APDC) and (iv) graph theory measure: outdegree or shortest path length. First, simulations were performed to quantify the influence of the various processing steps on the accuracy to localize the SOZ. Afterwards, the SOZ was estimated from a 113-electrodes iEEG seizure recording and compared with the resection that rendered the patient seizure-free. The simulations revealed that ADTF is preferred over APDC to localize the SOZ from ictal iEEG recordings. Normalizing the time series before analysis resulted in an increase of 25-35% of correctly localized SOZ, while adding more nodes to the connectivity analysis led to a moderate decrease of 10%, when comparing 128 with 32 input nodes. The real-seizure connectivity estimates localized the SOZ inside the resection area using the ADTF coupled to outdegree or shortest path length. Our study showed that normalizing the time-series is an important pre-processing step, while adding nodes to the analysis did only marginally affect the SOZ localization. The study shows that directed multivariate Granger-based connectivity analysis is feasible with many input nodes (> 100) and that normalization of the time-series before connectivity analysis is preferred

Electrical source imaging and connectivity analysis to localize the seizure-onset zone based on high-density ictal scalp EEG recordings

Functional connectivity analysis of ictal intracranial EEG (icEEG) recordings can help with seizure-onset zone (SOZ) localization in patients with focal epilepsy1. However, it would be of high clinical value to be able to localize the SOZ based on non-invasive ictal EEG recordings to better target or avoid icEEG and improve surgical outcome. In this work, we propose an approach to localize the SOZ based on non-invasive ictal high- density EEG (hd-EEG) recordings. We considered retrospective ictal hd-EEG recordings of two patients who were rendered seizure free after surgery. Furthermore, we simulated 1000 ictal hd-EEG epochs of 10s with an underlying network consisting of 3 randomly placed epileptic patches in the brain. EEG source imaging (ESI) was performed in CARTOOL using an individual head model (LSMAC) to calculate the forward model2. We considered dipoles uniformly distributed in the brain with a spacing of 5mm. LORETA3 was used as inverse solution method. Center dipoles of clusters with high activation were determined as dipoles for which there was no higher power in their neighborhood. The time-varying connectivity pattern between the time series of these dipoles was calculated using the integrated, full-frequency, and spectrum-weighted Adaptive Directed Transfer Function4. This was done in the frequency band containing the seizure information, 3-30Hz. The outdegree of each selected dipole was determined as the sum over time of all outgoing connections. Around the dipole with the highest outdegree, we determined a region of dipoles that had a power that was at least 90% of the power of the center dipole. This region was then considered as the SOZ. We were able to successfully localize the driver in the resected zone for both patients. For the simulation data, the results can be quantified: in 71% of the simulations, the localization error remained below 25mm. If the selection of the dipole would be solely based on the highest power, the error would be more than 82mm. ESI in combination with connectivity analysis can successfully localize the SOZ in non- invasive ictal hd-EEG recordings and outperforms localization based on power. This could have important clinical relevance for the presurgical evaluation in focal epilepsy. References: 1. van Mierlo, P et al. (2014) Prog Neurobiol. 121:19-35. 2. Brunet, D. et al. (2011) Comput. Intell. Neurosci. 2. 3. Pascal-Marqui, R.D., et al. (1994) Int. J. Psychophysiol. 18(1):49-65. 4. van Mierlo, P. et al. (2013) Epilepsia 54.8:1409-1418

Seizure onset zone localization from ictal high-density EEG in five patients

Rationale Because epilepsy is a network disease, localization of the exact seizure onset zone (SOZ) is difficult because the epileptic activity can spread to other regions within milliseconds. Functional connectivity metrics quantify how the activity in different brain regions is interrelated. In the past, it has been shown that functional connectivity analysis of ictal intracranial EEG (icEEG) recordings can help with SOZ localization in patients with focal epilepsy (van Mierlo et al., 2014). However, it would be of high clinical value to be able to localize the SOZ based on non-invasive ictal EEG recordings to optimize the icEEG implantation scheme or to avoid invasive monitoring and improve surgical outcome. In this work, we propose an approach to localize the SOZ based on non-invasive ictal high-density EEG (hd-EEG) recordings. Methods We considered retrospective ictal epochs of 2.4 s up to 10 s recorded with hd-EEG (256 electrodes) in five patients who were rendered seizure free after surgery. From the 256 electrodes, the facial electrodes were removed, resulting in a subset of 204 electrodes. A 28-channel subset was constructed to mimic a low-density (ld) electrode setup used in clinical practice. EEG source imaging (ESI) was performed in the CARTOOL software using an individual head model (LSMAC) to calculate the forward model (Brunet et al., 2011). We considered sources uniformly distributed in the brain with a spacing of 5 mm. LORETA (Pascal-Marqui et al., 1994) was used as inverse solution method. In each cluster of activity, we determined a central source based on the criterion that there was no higher power in its neighborhood. The time-varying connectivity pattern between the time series of these sources was calculated using Granger causality (van Mierlo et al., 2013). This was done in the frequency band containing the fundamental seizure frequency, 3-30Hz. The outdegree of each selected dipole was determined as the sum over time of all outgoing connections. Around the dipole with the highest outdegree, we determined a region of dipoles that had a power that was at least 90% of the power of the center dipole. This region was then considered as the SOZ. Results We were able to successfully localize the driver in the resected zone for all patients based on ESI followed by connectivity analysis of the hd-EEG (mean localization error (LE) = 0 mm). If we chose the cluster with the highest power as driver, the mean LE was 59.69 mm. For the ld-EEG, ESI followed by connectivity analysis resulted in a mean LE of 23.30 mm and when selecting the cluster with the highest power as driver, the mean LE was 31.21 mm. Conclusions ESI in combination with connectivity analysis can successfully localize the SOZ in non-invasive ictal hd-EEG recordings and greatly outperforms localization based on power. For ld-EEG recordings, the localization error remains significant but still outperforms localization based on power. This could have important clinical relevance for the presurgical evaluation in focal epilepsy

EEG source connectivity to localize the seizure onset zone in patients with drug resistant epilepsy

Visual inspection of the EEG to determine the seizure onset zone (SOZ) in the context of the presurgical evaluation in epilepsy is time-consuming and often challenging or impossible. We offer an approach that uses EEG source imaging (ESI) in combination with functional connectivity analysis (FC) to localize the SOZ from ictal EEG. Ictal low-density-scalp EEG from 111 seizures in 27 patients who were rendered-seizure free after surgery was analyzed. For every seizure, ESI (LORETA) was applied on an artifact-free epoch selected around the seizure onset. Additionally, FC was applied on the reconstructed sources. We estimated the SOZ in two ways: (i)the source with highest power after ESI and (ii)the source with the most outgoing connections after ESI and FC. For both approaches, the distance between the estimated SOZ and the resected zone (RZ) of the patient were calculated. Using ESI alone, the SOZ was estimated inside the RZ in 31% of the seizures and within 10mm from the border of the RZ in 42%. For 18.5% of the patients, all seizures were estimated within 10mm of the RZ. Using ESI and FC, 72% of the seizures were estimated inside the RZ, and 94% within 10mm. For 85% of the patients, all seizures were estimated within 10mm of the RZ. FC provided a significant added value to ESI alone (p<0.001). ESI combined with subsequent FC is able to localize the SOZ in a non-invasive way with high accuracy. Therefore it could be a valuable tool in the presurgical evaluation of epilepsy

Estimation of local aortic elastic properties with MRI

Aortic compliance and pulse wave velocity (PWV) are important determiners of heart load, and are clinically useful indices of cardiovascular risk. Most direct methods to derive them require invasive pressure measurement. In this work a noninvasive technique to evaluate aortic compliance and PWV using MRI is proposed. MRI magnitude and phase images to measure area and flow in the ascending aorta were acquired in a group of 13 young healthy subjects. Assuming that the early systolic part of the wave was unidirectional and reflectionless, PWV was determined as the ratio between flow and area variations at early systole. Our results were compared to pulse wave velocities derived from a direct transit time, and to one using ascending aortic area and peripheral brachial pulse pressure. The new method proved to be accurate and in good agreement with the transit time method, as well as with previously published results

Blinded study: prospectively defined high-frequency oscillations predict seizure outcome in individual patients

Interictal high-frequency oscillations are discussed as biomarkers for epileptogenic brain tissue that should be resected in epilepsy surgery to achieve seizure freedom. The prospective classification of tissue sampled by individual electrode contacts remains a challenge. We have developed an automated, prospective definition of clinically relevant high-frequency oscillations in intracranial EEG from Montreal and tested it in recordings from Zurich. We here validated the algorithm on intracranial EEG that was recorded in an independent epilepsy centre so that the analysis was blinded to seizure outcome. We selected consecutive patients who underwent resective epilepsy surgery in Geneva with post-surgical follow-up > 12 months. We analysed long-term recordings during sleep that we segmented into intervals of 5 min. High-frequency oscillations were defined in the ripple (80-250 Hz) and the fast ripple (250-500 Hz) frequency bands. Contacts with the highest rate of ripples co-occurring with fast ripples designated the relevant area. As a validity criterion, we calculated the test-retest reliability of the high-frequency oscillations area between the 5 min intervals (dwell time ≥50%). If the area was not fully resected and the patient suffered from recurrent seizures, this was classified as a true positive prediction. We included recordings from 16 patients (median age 32 years, range 18-53 years) with stereotactic depth electrodes and/or with subdural electrode grids (median follow-up 27 months, range 12-55 months). For each patient, we included several 5 min intervals (median 17 intervals). The relevant area had high test-retest reliability across intervals (median dwell time 95%). In two patients, the test-retest reliability was too low (dwell time < 50%) so that outcome prediction was not possible. The area was fully included in the resected volume in 2/4 patients who achieved post-operative seizure freedom (specificity 50%) and was not fully included in 9/10 patients with recurrent seizures (sensitivity 90%), leading to an accuracy of 79%. An additional exploratory analysis suggested that high-frequency oscillations were associated with interictal epileptic discharges only in channels within the relevant area and not associated in channels outside the area. We thereby validated the automated procedure to delineate the clinically relevant area in each individual patient of an independently recorded dataset and achieved the same good accuracy as in our previous studies. The reproducibility of our results across datasets is promising for a multicentre study to test the clinical application of high-frequency oscillations to guide epilepsy surgery

Connectivity and tissue microstructural alterations in right and left temporal lobe epilepsy revealed by diffusion spectrum imaging

Focal epilepsy is increasingly recognized as the result of an altered brain network, both on the structural and functional levels and the characterization of these widespread brain alterations is crucial for our understanding of the clinical manifestation of seizure and cognitive deficits as well as for the management of candidates to epilepsy surgery. Tractography based on Diffusion Tensor Imaging allows non-invasive mapping of white matter tracts in vivo. Recently, diffusion spectrum imaging (DSI), based on an increased number of diffusion directions and intensities, has improved the sensitivity of tractography, notably with respect to the problem of fiber crossing and recent developments allow acquisition times compatible with clinical application. We used DSI and parcellation of the gray matter in regions of interest to build whole-brain connectivity matrices describing the mutual connections between cortical and subcortical regions in patients with focal epilepsy and healthy controls. In addition, the high angular and radial resolution of DSI allowed us to evaluate also some of the biophysical compartment models, to better understand the cause of the changes in diffusion anisotropy. Global connectivity, hub architecture and regional connectivity patterns were altered in TLE patients and showed different characteristics in RTLE vs LTLE with stronger abnormalities in RTLE. The microstructural analysis suggested that disturbed axonal density contributed more than fiber orientation to the connectivity changes affecting the temporal lobes whereas fiber orientation changes were more involved in extratemporal lobe changes. Our study provides further structural evidence that RTLE and LTLE are not symmetrical entities and DSI-based imaging could help investigate the microstructural correlate of these imaging abnormalities