Successful epilepsy surgery in two cases with multiple sclerosis.

Brain surgery is the only curative treatment for people with focal epilepsy, but it is unclear whether this induces active disease in multiple sclerosis (MS). This creates a barrier to evaluate MS patients for epilepsy surgery. We present two cases of successful epilepsy surgery in patients with pharmacoresistant epilepsy and stable MS and give an overview of the existing literature. (1) a 28-year-old woman with seizures arising from a right basal temporo-occipital ganglioglioma was seizure-free after surgery, without MS relapse but with one new MS lesion postsurgically. (2) a 46-year-old woman with seizures arising from a natalizumab-associated progressive multifocal leukoencephalopathy (PML) lesion in the right frontal lobe was seizure-free after surgery preceded by extraoperative subdural electrocorticography, with new subclinical MS lesions. We are the first to report brain surgery in a PML survivor. Both patients stabilized radiologically after initiating second-line therapies. Successful epilepsy surgery can substantially increase the quality of life in patients with pharmacoresistant epilepsy and MS. With increasing survival rates of brain tumors and PML, the risk-benefit ratio of epilepsy surgery compared to a potential MS relapse after surgery becomes critically important. Shared decision-making is valuable for balancing the risks related to both diseases.

Predictive value of functional MRI and EEG in epilepsy diagnosis after a first seizure.

It is often difficult to predict seizure recurrence in subjects who have suffered a first-ever epileptic seizure. In this study, the predictive value of physiological signals measured using Electroencephalography (EEG) and functional MRI (fMRI) is assessed. In particular those patients developing epilepsy (i.e. a second unprovoked seizure) that were initially evaluated as having a low risk of seizure recurrence are of interest. In total, 26 epilepsy patients, of which 8 were initially evaluated as having a low risk of seizure recurrence (i.e. converters), and 17 subjects with only a single seizure were included. All subjects underwent routine EEG as well as fMRI measurements. For diagnostic classification, features related to the temporal dynamics were determined for both the processed EEG and fMRI data. Subsequently, a logistic regression classifier was trained on epilepsy and first-seizure subjects. The trained model was tested using the clinically relevant converters group. The sensitivity, specificity, and AUC (mean ±â€¯SD) of the regression model including metrics from both modalities were 74 ±â€¯19%, 82 ±â€¯18%, and 0.75 ±â€¯0.12, respectively. Positive and negative predictive values (mean ±â€¯SD) of the regression model with both EEG and fMRI features are 84 ±â€¯14% and 78 ±â€¯12%. Moreover, this EEG/fMRI model showed significant improvements compared to the clinical diagnosis, whereas the models using metrics from either EEG or fMRI do not reach significance (p > 0.05). Temporal metrics computationally derived from EEG and fMRI time signals may clinically aid and synergistically improve the predictive value in a first-seizure sample.

Cardiometabolic risk factors as determinants of peripheral nerve function: the Maastricht Study.

AIMS/HYPOTHESIS: We aimed to examine associations of cardiometabolic risk factors, and (pre)diabetes, with (sensorimotor) peripheral nerve function. METHODS: In 2401 adults (aged 40-75 years) we previously determined fasting glucose, HbA1c, triacylglycerol, HDL- and LDL-cholesterol, inflammation, waist circumference, blood pressure, smoking, glucose metabolism status (by OGTT) and medication use. Using nerve conduction tests, we measured compound muscle action potential, sensory nerve action potential amplitudes and nerve conduction velocities (NCVs) of the peroneal, tibial and sural nerves. In addition, we measured vibration perception threshold (VPT) of the hallux and assessed neuropathic pain using the DN4 interview. We assessed cross-sectional associations of risk factors with nerve function (using linear regression) and neuropathic pain (using logistic regression). Associations were adjusted for potential confounders and for each other risk factor. Associations from linear regression were presented as standardised regression coefficients (ß) and 95% CIs in order to compare the magnitudes of observed associations between all risk factors and outcomes. RESULTS: Hyperglycaemia (fasting glucose or HbA1c) was associated with worse sensorimotor nerve function for all six outcome measures, with associations of strongest magnitude for motor peroneal and tibial NCV, ßfasting glucose = -0.17 SD (-0.21, -0.13) and ßfasting glucose = -0.18 SD (-0.23, -0.14), respectively. Hyperglycaemia was also associated with higher VPT and neuropathic pain. Larger waist circumference was associated with worse sural nerve function and higher VPT. Triacylglycerol, HDL- and LDL-cholesterol, and blood pressure were not associated with worse nerve function; however, antihypertensive medication usage (suggestive of history of exposure to hypertension) was associated with worse peroneal compound muscle action potential amplitude and NCV. Smoking was associated with worse nerve function, higher VPT and higher risk for neuropathic pain. Inflammation was associated with worse nerve function and higher VPT, but only in those with type 2 diabetes. Type 2 diabetes and, to a lesser extent, prediabetes (impaired fasting glucose and/or impaired glucose tolerance) were associated with worse nerve function, higher VPT and neuropathic pain (p for trend <0.01 for all outcomes). CONCLUSIONS/INTERPRETATION: Hyperglycaemia (including the non-diabetic range) was most consistently associated with early-stage nerve damage. Nonetheless, larger waist circumference, inflammation, history of hypertension and smoking may also independently contribute to worse nerve function.

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.

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.

Single-Cell Recordings to Target the Anterior Nucleus of the Thalamus in Deep Brain Stimulation for Patients with Refractory Epilepsy.

Deep brain stimulation (DBS) of the anterior nucleus of the thalamus (ANT) is a promising treatment for patients with refractory epilepsy. However, therapy response varies and precise positioning of the DBS lead is potentially essential for maximizing therapeutic efficacy. We investigate if single-cell recordings acquired by microelectrode recordings can aid targeting of the ANT during surgery and hypothesize that the neuronal firing properties of the target region relate to clinical outcome. We prospectively included 10 refractory epilepsy patients and performed microelectrode recordings under general anesthesia to identify the change in neuronal signals when approaching and transecting the ANT. The neuronal firing properties of the target region, anatomical locations of microelectrode recordings and active contact positions of the DBS lead along the recorded trajectory were compared between responders and nonresponders to DBS. We obtained 19 sets of recordings from 10 patients (five responders and five nonresponders). Amongst the 403 neurons detected, 365 (90.6%) were classified as bursty. Entry into the ANT was characterized by an increase in firing rate while exit of the ANT was characterized by a decrease in firing rate. Comparing the trajectories of responders to nonresponders, we found differences neither in the neuronal firing properties themselves nor in their locations relative to the position of the active contact. Single-cell firing rate acquired by microelectrode recordings under general anesthesia can thus aid targeting of the ANT during surgery, but is not related to clinical outcome in DBS for patients with refractory epilepsy.

Improved seizure control and regaining cognitive milestones after vagus nerve stimulation revision surgery in Lennox-Gastaut syndrome.

We report a child with Lennox-Gastaut syndrome with an increase in seizure frequency and loss of psychomotor skills due to a disintegrated cervical VNS lead, not detected during standard device monitoring. The lead was completely removed and replaced by a new 303 lead on the same nerve segment. After reinitiating VNS, side effects forced us to switch it off, resulting in immediate seizure recurrence. EEG recording demonstrated a non-convulsive status epilepticus that was halted by reinitiating VNS therapy. Thereafter, he remained seizure free for eight months, and regained psychomotor development.

Recovery of lost motor evoked potentials in open thoracoabdominal aortic aneurysm repair using intercostal artery bypass.

Ischemia of the spinal cord remains a disastrous complication in thoracoabdominal aortic aneurysm (TAAA) surgery. We report a case of open type I TAAA repair during which no motor evoked potentials were detectable for >1 hour after aortic cross-clamping. The creation of three intercostal artery bypasses restored spinal cord perfusion. As the patient showed only moderate clinical signs of spinal cord ischemia afterward, we underline the role of neuromonitoring to guide intercostal artery bypass implantation during TAAA surgery as the combined use of neuromonitoring and intercostal artery bypass implantation may prevent paraplegia in specific TAAA cases.

The Use of Continuous EEG Monitoring in Intensive Care Units in The Netherlands: A National Survey.

BACKGROUND: Currently, continuous electroencephalographic monitoring (cEEG) is the only available diagnostic tool for continuous monitoring of brain function in intensive care unit (ICU) patients. Yet, the exact relevance of routinely applied ICU cEEG remains unclear, and information on the implementation of cEEG, especially in Europe, is scarce. This study explores current practices of cEEG in adult Dutch ICU departments focusing on organizational and operational factors, development over time and factors perceived relevant for abstaining its use. METHODS: A national survey on cEEG in adults among the neurology and adult intensive care departments of all Dutch hospitals (n = 82) was performed. RESULTS: The overall institutional response rate was 78%. ICU cEEG is increasingly used in the Netherlands (in 37% of all hospitals in 2016 versus in 21% in 2008). Currently in 88% of university, 55% of teaching and 14% of general hospitals use ICU cEEG. Reasons for not performing cEEG are diverse, including perceived non-feasibility and lack of data on the effect of cEEG use on patient outcome. Mostly, ICU cEEG is used for non-convulsive seizures or status epilepticus and prognostication. However, cEEG is never or rarely used for monitoring cerebral ischemia and raised intracranial pressure in traumatic brain injury. Review and reporting practices differ considerably between hospitals. Nearly all hospitals perform non-continuous review of cEEG traces. Methods for moving toward continuous review of cEEG traces are available but infrequently used in practice. CONCLUSIONS: cEEG is increasingly used in Dutch ICUs. However, cEEG practices vastly differ between hospitals. Future research should focus on uniform cEEG practices including unambiguous EEG interpretation to facilitate collaborative research on cEEG, aiming to provide improved standard patient care and robust data on the impact of cEEG use on patient outcome.

Continuous electroencephalographic-monitoring in the ICU: an overview of current strengths and future challenges.

PURPOSE OF REVIEW: In ICUs, numerous physiological parameters are continuously monitored and displayed. Yet, functional monitoring of the organ of primary concern, the brain, is not routinely performed. Despite the benefits of ICU use of continuous electroencephalographic (EEG)-monitoring (cEEG) is increasingly recognized, several issues nevertheless seem to hamper its widespread clinical implementation. RECENT FINDINGS: Utilization of ICU cEEG has significantly improved detection and characterization of cerebral pathology, prognostication and clinical management in specific patient groups. Potential solutions to several remaining challenges are currently being established. Descriptive EEG-terminology is evolving, whereas logistical issues are dealt with using telemedicine and quantitative EEG trends, training of nonexpert personnel and development of specialized detection algorithms. These concerted solutions are advancing cEEG-registration towards cEEG-monitoring. Notwithstanding these advances, obstacles such as ambiguous EEG-interpretation and differences in treatment based on EEG-findings need yet to be overcome. SUMMARY: In selected critically ill patient groups, ICU cEEG has clear benefits over (repeated) standard EEG or no functional brain monitoring at all and if available, cEEG should be used. However, several issues preventing optimal ICU cEEG usage persist and should be further explored.

Towards prognostic biomarkers from BOLD fluctuations to differentiate a first epileptic seizure from new-onset epilepsy.

OBJECTIVE: The diagnosis of epilepsy cannot be reliably made prior to a patient's second seizure in most cases. Therefore, adequate diagnostic tools are needed to differentiate subjects with a first seizure from those with a seizure preceding the onset of epilepsy. The objective was to explore spontaneous blood oxygen level-dependent (BOLD) fluctuations in subjects with a first-ever seizure and patients with new-onset epilepsy (NOE), and to find characteristic biomarkers for seizure recurrence after the first seizure. METHODS: We examined 17 first-seizure subjects, 19 patients with new-onset epilepsy (NOE), and 18 healthy controls. All subjects underwent clinical investigation and received electroencephalography and resting-state functional magnetic resonance imaging (MRI). The BOLD time series were analyzed in terms of regional homogeneity (ReHo) and fractional amplitude of low-frequency fluctuations (fALFFs). RESULTS: We found significantly stronger amplitudes (higher fALFFs) in patients with NOE relative to first-seizure subjects and healthy controls. The frequency range of 73-198 mHz (slow-3 subband) appeared most useful for discriminating patients with NOE from first-seizure subjects. The ReHo measure did not show any significant differences. SIGNIFICANCE: The fALFF appears to be a noninvasive measure that characterizes spontaneous BOLD fluctuations and shows stronger amplitudes in the slow-3 subband of patients with NOE relative first-seizure subjects and healthy controls. A larger study population with follow-up is required to determine whether fALFF holds promise as a potential biomarker for identifying subjects at increased risk to develop epilepsy.

An improved qEEG index for asymmetry detection during the Wada test.

The Wada test is commonly used to evaluate language and memory lateralization in candidates for epilepsy surgery. The spatial Brain Symmetry Index (BSI) quantifies inter-hemispheric differences in the EEG. Its application has been shown to be feasible during Wada testing. We developed a method for the quantification of EEG asymmetry that matches visual assessments of the EEG better than BSI. Fifty-three patients' EEG data, with a total of 85 injections were analyzed. In a step-wise, data-driven manner, multiple electrode and frequency band combinations were evaluated. Eventually, BSI, calculated using only the frontal electrodes F3 and F4, was combined with a temporal measure of delta power in the central electrodes, C3 and C4, into a new measure: cBSI. Using the area under the ROC curve (AUC), we showed that cBSI performs significantly better relative to BSI (median AUC 0.98 versus 0.96, p=0.0015, Wilcoxon signed rank test). Our results showed that asymmetry detection was significantly improved by combining temporal with spatial qEEG measures. In the future, our combined qEEG measure could allow for a more objective way of monitoring EEG asymmetry, thereby increasing the feasibility of using EEG as a monitoring tool during the Wada test. Future studies should, however, validate our cBSI method in real time in the operating room or radiology suite.