Predictors of seizure outcomes in children with tuberous sclerosis complex and intractable epilepsy undergoing resective epilepsy surgery: an individual participant data meta-analysis.

ObjectiveTo perform a systematic review and individual participant data meta-analysis to identify preoperative factors associated with a good seizure outcome in children with Tuberous Sclerosis Complex undergoing resective epilepsy surgery.Data sourcesElectronic databases (MEDLINE, EMBASE, CINAHL and Web of Science), archives of major epilepsy and neurosurgery meetings, and bibliographies of relevant articles, with no language or date restrictions.Study selectionWe included case-control or cohort studies of consecutive participants undergoing resective epilepsy surgery that reported seizure outcomes. We performed title and abstract and full text screening independently and in duplicate. We resolved disagreements through discussion.Data extractionOne author performed data extraction which was verified by a second author using predefined data fields including study quality assessment using a risk of bias instrument we developed. We recorded all preoperative factors that may plausibly predict seizure outcomes.Data synthesisTo identify predictors of a good seizure outcome (i.e. Engel Class I or II) we used logistic regression adjusting for length of follow-up for each preoperative variable.ResultsOf 9863 citations, 20 articles reporting on 181 participants were eligible. Good seizure outcomes were observed in 126 (69%) participants (Engel Class I: 102(56%); Engel class II: 24(13%)). In univariable analyses, absence of generalized seizure semiology (OR = 3.1, 95%CI = 1.2-8.2, p = 0.022), no or mild developmental delay (OR = 7.3, 95%CI = 2.1-24.7, p = 0.001), unifocal ictal scalp electroencephalographic (EEG) abnormality (OR = 3.2, 95%CI = 1.4-7.6, p = 0.008) and EEG/Magnetic resonance imaging concordance (OR = 4.9, 95%CI = 1.8-13.5, p = 0.002) were associated with a good postoperative seizure outcome.ConclusionsSmall retrospective cohort studies are inherently prone to bias, some of which are overcome using individual participant data. The best available evidence suggests four preoperative factors predictive of good seizure outcomes following resective epilepsy surgery. Large long-term prospective multicenter observational studies are required to further evaluate the risk factors identified in this review

Lennox-Gastaut Syndrome: A State of the Art Review.

Lennox-Gastaut syndrome (LGS) is a severe age-dependent epileptic encephalopathy usually with onset between 1 and 8 years of age. Functional neuroimaging studies recently introduced the concept of Lennox-Gastaut as "secondary network epilepsy" resulting from dysfunctions of a complex system involving both cortical and subcortical structures (default-mode network, corticoreticular connections, and thalamus). These dysfunctions are produced by different disorders including hypoxic-ischemic encephalopathies, meningoencephalitis, cortical malformations, neurocutaneous disorders, or tumors. The list of etiologies was expanded to pathogenic copy number variants at whole-genome array comparative genomic hybridization associated with late-onset cases or pathogenic mutations involving genes, such as GABRB3, ALG13, SCN8A, STXBP1, DNM1, FOXG1, or CHD2. Various clinical trials demonstrated the usefulness of different drugs (including rufinamide, clobazam, lamotrigine, topiramate, or felbamate), ketogenic diet, resective surgery, corpus callosotomy, and vagus nerve stimulation in the treatment of epileptic manifestations. The outcome of LGS often remains disappointing regarding seizure control or cognitive functioning. The realization of animal models, which are still lacking, and the full comprehension of molecular mechanisms involved in epileptogenesis and cognitive impairment would give a relevant support to further improvements in therapeutic strategies for LGS patients

Is early limited surgery associated with a more benign disease course in Crohn’s disease?

AIM: To analyze the difference in disease course and need for surgery in patients with Crohn's disease (CD). METHODS: Data of 506 patients with incident CD were analyzed (age at diagnosis: 31.5 ± 13.8 years). Both hospital and outpatient records were collected prospectively with a complete clinical follow-up and comprehensively reviewed in the population-based Veszprem province database, which includes incident CD patients diagnosed between January 1, 1977 and December 31, 2008. Follow-up data were collected until December 31, 2009. All patients included had at least 1 year of follow-up available. Patients with indeterminate colitis at diagnosis were excluded from the analysis. RESULTS: Overall, 73 patients (14.4%) required resective surgery within 1 year of diagnosis. Steroid exposure and need for biological therapy were lower in patients with early limited surgery (P < 0.001 and P = 0.09). In addition, surgery rates during follow-up in patients with and without early surgery differed significantly after matching on propensity scores (P < 0.001, HR = 0.23). The need for reoperation was also lower in patients with early limited resective surgery (P = 0.038, HR = 0.42) in a Kaplan-Meier and multivariate Cox regression (P = 0.04) analysis. However, this advantage was not observed after matching on propensity scores (P(Logrank) = 0.656, P(Breslow) = 0.498). CONCLUSION: Long-term surgery rates and overall exposure to steroids and biological agents were lower in patients with early limited resective surgery, but reoperation rates did not differ

Influence of metallic artifact filtering on MEG signals for source localization during interictal epileptiform activity

Objective. Medical intractable epilepsy is a common condition that affects 40% of epileptic patients that generally have to undergo resective surgery. Magnetoencephalography (MEG) has been increasingly used to identify the epileptogenic foci through equivalent current dipole (ECD) modeling, one of the most accepted methods to obtain an accurate localization of interictal epileptiform discharges (IEDs). Modeling requires that MEG signals are adequately preprocessed to reduce interferences, a task that has been greatly improved by the use of blind source separation (BSS) methods. MEG recordings are highly sensitive to metallic interferences originated inside the head by implanted intracranial electrodes, dental prosthesis, etc and also coming from external sources such as pacemakers or vagal stimulators. To reduce these artifacts, a BSS-based fully automatic procedure was recently developed and validated, showing an effective reduction of metallic artifacts in simulated and real signals (Migliorelli et al 2015 J. Neural Eng. 12 046001). The main objective of this study was to evaluate its effects in the detection of IEDs and ECD modeling of patients with focal epilepsy and metallic interference. Approach. A comparison between the resulting positions of ECDs was performed: without removing metallic interference; rejecting only channels with large metallic artifacts; and after BSS-based reduction. Measures of dispersion and distance of ECDs were defined to analyze the results. Main results. The relationship between the artifact-to-signal ratio and ECD fitting showed that higher values of metallic interference produced highly scattered dipoles. Results revealed a significant reduction on dispersion using the BSS-based reduction procedure, yielding feasible locations of ECDs in contrast to the other two approaches. Significance. The automatic BSS-based method can be applied to MEG datasets affected by metallic artifacts as a processing step to improve the localization of epileptic foci.Postprint (published version

Seizure-onset mapping based on time-variant multivariate functional connectivity analysis of high-dimensional intracranial EEG : a Kalman filter approach

The visual interpretation of intracranial EEG (iEEG) is the standard method used in complex epilepsy surgery cases to map the regions of seizure onset targeted for resection. Still, visual iEEG analysis is labor-intensive and biased due to interpreter dependency. Multivariate parametric functional connectivity measures using adaptive autoregressive (AR) modeling of the iEEG signals based on the Kalman filter algorithm have been used successfully to localize the electrographic seizure onsets. Due to their high computational cost, these methods have been applied to a limited number of iEEG time-series (< 60). The aim of this study was to test two Kalman filter implementations, a well-known multivariate adaptive AR model (Arnold et al. 1998) and a simplified, computationally efficient derivation of it, for their potential application to connectivity analysis of high-dimensional (up to 192 channels) iEEG data. When used on simulated seizures together with a multivariate connectivity estimator, the partial directed coherence, the two AR models were compared for their ability to reconstitute the designed seizure signal connections from noisy data. Next, focal seizures from iEEG recordings (73-113 channels) in three patients rendered seizure-free after surgery were mapped with the outdegree, a graph-theory index of outward directed connectivity. Simulation results indicated high levels of mapping accuracy for the two models in the presence of low-to-moderate noise cross-correlation. Accordingly, both AR models correctly mapped the real seizure onset to the resection volume. This study supports the possibility of conducting fully data-driven multivariate connectivity estimations on high-dimensional iEEG datasets using the Kalman filter approach

Automatic Focal Cortical Dysplasiav(FCD) detection by Magnetic Resonance Image (MRI)

Nowadays, approximately 50 million people are suffering from epilepsy all over the world, of whom 30% have Focal Cortical Dysplasia (FCD), a malformation that occurs during brain cortical development. In clinical treatments, FCD lesions often have to be removed by resective surgery. Magnetic Resonance Imaging (MRI) is the most important clinical tool for identifying FCD lesions, and has allowed the diagnostic detection of FCD lesions in an increasing number of patients, leading to increased rates of successful resective surgery. However, detection of FCD lesions is still a challenging task because of various factors such as extremely subtle FCD malformations, complex convolutions of human cerebral cortex and partial volume effect due to imaging. Previous works develop MRI features of FCD lesions to highlight FCD regions. However, these MRI features also exist in Healthy Controls. We developed a new MRI features of FCD lesions, and use a multi-feature based method to perform automatic FCD detection. As a results, we improve the similarity index than the previous method. Sensitivity and specificity are also improved by proposed work. The proposed work can be a useful clinical tool to assist FCD detection

Drug-resistant focal epilepsy in children is associated with increased modal controllability of the whole brain and epileptogenic regions

Network control theory provides a framework by which neurophysiological dynamics of the brain can be modelled as a function of the structural connectome constructed from diffusion MRI. Average controllability describes the ability of a region to drive the brain to easy-to-reach neurophysiological states whilst modal controllability describes the ability of a region to drive the brain to difficult-to-reach states. In this study, we identify increases in mean average and modal controllability in children with drug-resistant epilepsy compared to healthy controls. Using simulations, we purport that these changes may be a result of increased thalamocortical connectivity. At the node level, we demonstrate decreased modal controllability in the thalamus and posterior cingulate regions. In those undergoing resective surgery, we also demonstrate increased modal controllability of the resected parcels, a finding specific to patients who were rendered seizure free following surgery. Changes in controllability are a manifestation of brain network dysfunction in epilepsy and may be a useful construct to understand the pathophysiology of this archetypical network disease. Understanding the mechanisms underlying these controllability changes may also facilitate the design of network-focussed interventions that seek to normalise network structure and function

Optimal management of seizures associated with tuberous sclerosis complex: current and emerging options.

Seizures are clinically significant manifestations associated with 79%-90% of patients with tuberous sclerosis complex. Often occurring within the first year of life in the form of infantile spasms, seizures interfere with neuropsychiatric, social, and cognitive development and carry significant individual and societal consequences. Prompt identification and treatment of seizures is an important focus in the overall management of tuberous sclerosis complex patients. Medical management, either after seizure onset or prophylactically in infants with electroencephalographic abnormalities, is considered first-line therapy. Vigabatrin and adrenocorticotropic hormone have emerged over the past few decades as mainstay pharmacologic modalities. Furthermore, emerging research on mammalian target of rapamycin inhibitors demonstrated promise for the management of seizures and subependymal giant cell astrocytoma. For appropriate surgical candidates with an epileptogenic zone associated with one or more glioneuronal hamartomas, ideally in noneloquent cortex, resective surgery can be considered, which provides a cure in 56% of patients. For medically refractory patients who do not meet criteria for curative surgery, palliative surgical approaches focused on reducing seizure burden, in the form of corpus callosotomy and vagus nerve stimulation, are alternative management options. Lastly, the ketogenic diet, a reemerging therapy based on the anticonvulsant effects of ketone bodies, can be utilized independently or in conjunction with other treatment modalities for the management of difficult-to-treat seizures