Katrien Jansen

Cardiac changes in epilepsy

Epilepsy and seizures can have a dramatic effect on the autonomic nervous system by involvement of the central autonomic control centers. The peri-ictal changes can lead to short-term alteration of cardiac functions in patients with seizures, and are partially hemispheric specific. Changes in heart rhythm, conduction and even subtle signs of ischemia have been reported. Ictal asystole and the lock-step phenomenon during seizures play an important role in the pathophysiology of SUDEP. In patients with longlasting epilepsy and multiple seizures, there are now convincing arguments for a chronic dysfunction of the autonomic nervous system. In this sense, heart rate variability can be considered as a biomarker of autonomic dysfunction in epilepsy. Early recognition of these short- and long-term cardiac effects will become useful in predicting seizures and in guiding more individualized treatment in the near future.

Non-EEG seizure-detection systems and potential SUDEP prevention: state of the art.

PURPOSE There is a need for a seizure-detection system that can be used long-term and in home situations for early intervention and prevention of seizure related side effects including SUDEP (sudden unexpected death in epileptic patients). The gold standard for monitoring epileptic seizures involves video/EEG (electro-encephalography), which is uncomfortable for the patient, as EEG electrodes are attached to the scalp. EEG analysis is also labour-intensive and has yet to be automated and adapted for real-time monitoring. It is therefore usually performed in a hospital setting, for a few days at the most. The goal of this article is to provide an overview of body signals that can be measured, along with corresponding methods, state-of-art research, and commercially available systems, as well as to stress the importance of a good detection system. METHOD Narrative literature review. RESULTS A range of body signals can be monitored for the purpose of seizure detection. It is particularly interesting to include monitoring of autonomic dysfunction, as this may be an important patho-physiological mechanism of SUDEP, and of movement, as many seizures have a motor component. CONCLUSION The most effective seizure detection systems are multimodal. Such systems should also be comfortable and low-power. The body signals and modalities on which a system is based should take account of the users seizure types and personal preferences.

Peri-ictal ECG changes in childhood epilepsy: implications for detection systems.

Early detection of seizures could reduce associated morbidity and mortality and improve the quality of life of patients with epilepsy. In this study, the aim was to investigate whether ictal tachycardia is present in focal and generalized epileptic seizures in children. We sought to predict in which type of seizures tachycardia can be identified before actual seizure onset. Electrocardiogram segments in 80 seizures were analyzed in time and frequency domains before and after the onset of epileptic seizures on EEG. These ECG parameters were analyzed to find the most informative ones that can be used for seizure detection. The algorithm of Leutmezer et al. was used to find the temporal relationship between the change in heart rate and seizure onset. In the time domain, the mean RR shows a significant difference before compared to after onset of the seizure in focal seizures. This can be observed in temporal lobe seizures as well as frontal lobe seizures. Calculation of mean RR interval has a high specificity for detection of ictal heart rate changes. Preictal heart rate changes are observed in 70% of the partial seizures. Ictal heart rate changes are present only in partial seizures in this childhood epilepsy study. The changes can be observed in temporal lobe seizures as well as in frontal lobe seizures. Heart rate changes precede seizure onset in 70% of the focal seizures, making seizure detection and closed-loop systems a possible therapeutic alternative in the population of children with refractory epilepsy.

Non-EEG seizure detection systems and potential SUDEP prevention: State of the art: Review and update

PURPOSE Detection of, and alarming for epileptic seizures is increasingly demanded and researched. Our previous review article provided an overview of non-invasive, non-EEG (electro-encephalography) body signals that can be measured, along with corresponding methods, state of the art research, and commercially available systems. Three years later, many more studies and devices have emerged. Moreover, the boom of smart phones and tablets created a new market for seizure detection applications. METHOD We performed a thorough literature review and had contact with manufacturers of commercially available devices. RESULTS This review article gives an updated overview of body signals and methods for seizure detection, international research and (commercially) available systems and applications. Reported results of non-EEG based detection devices vary between 2.2% and 100% sensitivity and between 0 and 3.23 false detections per hour compared to the gold standard video-EEG, for seizures ranging from generalized to convulsive or non-convulsive focal seizures with or without loss of consciousness. It is particularly interesting to include monitoring of autonomic dysfunction, as this may be an important pathophysiological mechanism of SUDEP (sudden unexpected death in epilepsy), and of movement, as many seizures have a motor component. CONCLUSION Comparison of research results is difficult as studies focus on different seizure types, timing (night versus day) and patients (adult versus pediatric patients). Nevertheless, we are convinced that the most effective seizure detection systems are multimodal, combining for example detection methods for movement and heart rate, and that devices should especially take into account the users seizure types and personal preferences.

Line length as a robust method to detect high-activity events: Automated burst detection in premature EEG recordings

OBJECTIVE EEG is a valuable tool for evaluation of brain maturation in preterm babies. Preterm EEG constitutes of high voltage burst activities and more suppressed episodes, called interburst intervals (IBIs). Evolution of background characteristics provides information on brain maturation and helps in prediction of neurological outcome. The aim is to develop a method for automated burst detection. METHODS Thirteen polysomnography recordings were used, collected at preterm postmenstrual age of 31.4 (26.1-34.4)weeks. We developed a burst detection algorithm based on the feature line length and compared it with manual scorings of clinical experts and other published methods. RESULTS The line length-based algorithm is robust (84.27% accuracy, 84.00% sensitivity, 85.70% specificity). It is not critically dependent on the number of measurement channels, because two channels still provide 82% accuracy. Furthermore, it approximates well clinically relevant features, such as median IBI duration 5.45 (4.00-7.11)s, maximum IBI duration 14.02 (8.73-18.80)s and burst percentage 48.89 (35.45-60.12)%, with a median deviation of respectively 0.65s, 1.96s and 6.55%. CONCLUSION Automated assessment of long-term preterm EEG is possible and its use will optimize EEG interpretation in the NICU. SIGNIFICANCE This study takes a first step towards fully automatic analysis of the preterm brain.

Autonomic effects of refractory epilepsy on heart rate variability in children: influence of intermittent vagus nerve stimulation.

Aim  Vagus nerve stimulation (VNS) is a therapeutic option for individuals with refractory epilepsy. Individuals with refractory epilepsy are prone to dysfunction of the autonomic nervous system. Reduced heart rate variability is a marker of dysfunction of the autonomic nervous system. Our goal was to study heart rate variability in children with refractory epilepsy and the influence of VNS on this parameter.

Ring chromosome 20 syndrome: Electroclinical description of six patients and review of the literature

BACKGROUND Ring chromosome 20 syndrome is a rare chromosomal disorder. METHODS In six patients, we focused on the presenting epileptic phenotype, the behavioral and mental problems and the relationship between the ratio of mosaicism and the age at onset of the epilepsy. RESULTS All patients presented with pharmacoresistant frontal lobe complex partial seizures. The earliest onset of epilepsy was seen in patients without mosaicism. There were three patients out of six with behavioral disturbances before the onset of seizures. All patients had mild to moderate cognitive impairment. Electroencephalogram recordings showed rhythmic theta waves with frontal predominance and non-convulsive status epilepticus (NCSE). CONCLUSIONS The ring chromosome 20 syndrome is characterized by childhood-onset refractory epilepsy continuing throughout adult life, mental disability, and behavioral disturbances which can originate before seizure onset. Ictal EEG reveals a unique pattern. Our findings indicate a possible link between the percentage of affected cells and the age of epilepsy onset.

Neuromyelitis optica-IgG(+) optic neuritis associated with celiac disease and dysgammaglobulinemia: A role for tacrolimus?

We present a pediatric case of recurrent optic neuritis, celiac disease, partial IgA and IgG3 deficiency in the context of anti-aquaporin-4 auto-immunity and familial IgA deficiency with celiac disease. Treatment with tacrolimus was successful in preventing disease relapses. This case stresses the relevance of central nervous system anti-aquaporin-4 auto-immunity in a broader context of immune dysregulation and neuro-immunology.

Early development of synchrony in cortical activations in the human

Highlights • We study the early development of cortical activations synchrony index (ASI).• Cortical activations become increasingly synchronized during the last trimester.• Interhemispheric synchrony increases more than intrahemispheric synchrony.• Our EEG metric ASI can be directly translated to experimental animal studies.• ASI holds promise as an early functional biomarker of brain networks.

DNA methylation analysis of Homeobox genes implicates HOXB7 hypomethylation as risk factor for neural tube defects.

Neural tube defects (NTDs) are common birth defects of complex etiology. Though family- and population-based studies have confirmed a genetic component, the responsible genes for NTDs are still largely unknown. Based on the hypothesis that folic acid prevents NTDs by stimulating methylation reactions, epigenetic factors, such as DNA methylation, are predicted to be involved in NTDs. Homeobox (HOX) genes play a role in spinal cord development and are tightly regulated in a spatiotemporal and collinear manner, partly by epigenetic modifications. We have quantified DNA methylation for the different HOX genes by subtracting values from a genome-wide methylation analysis using leukocyte DNA from 10 myelomeningocele (MMC) patients and 6 healthy controls. From the 1575 CpGs profiled for the 4 HOX clusters, 26 CpGs were differentially methylated (P-value < 0.05; β-difference > 0.05) between MMC patients and controls. Seventy-seven percent of these CpGs were located in the HOXA and HOXB clusters, with the most profound difference for 3 CpGs within the HOXB7 gene body. A validation case-control study including 83 MMC patients and 30 unrelated healthy controls confirmed a significant association between MMC and HOXB7 hypomethylation (-14.4%; 95% CI: 11.9–16.9%; P-value < 0.0001) independent of the MTHFR 667C>T genotype. Significant HOXB7 hypomethylation was also present in 12 unaffected siblings, each related to a MMC patient, suggestive of an epigenetic change induced by the mother. The inclusion of a neural tube formation model using zebrafish showed that Hoxb7a overexpression but not depletion resulted in deformed body axes with dysmorphic neural tube formation. Our results implicate HOXB7 hypomethylation as risk factor for NTDs and highlight the importance for future genome-wide DNA methylation analyses without preselecting candidate pathways.