Drug-refractory Epilepsy Research Articles

Comparison of robotic and manual implantation of intracerebral electrodes: a single-centre, single-blinded, randomised controlled trial

There has been a significant rise in robotic trajectory guidance devices that have been utilised for stereotactic neurosurgical procedures. These devices have significant costs and associated learning curves. Previous studies reporting devices usage have not undertaken prospective parallel-group comparisons before their introduction, so the comparative differences are unknown. We study the difference in stereoelectroencephalography electrode implantation time between a robotic trajectory guidance device (iSYS1) and manual frameless implantation (PAD) in patients with drug-refractory focal epilepsy through a single-blinded randomised control parallel-group investigation of SEEG electrode implantation, concordant with CONSORT statement. Thirty-two patients (18 male) completed the trial. The iSYS1 returned significantly shorter median operative time for intracranial bolt insertion, 6.36 min (95% CI 5.72–7.07) versus 9.06 min (95% CI 8.16–10.06), p = 0.0001. The PAD group had a better median target point accuracy 1.58 mm (95% CI 1.38–1.82) versus 1.16 mm (95% CI 1.01–1.33), p = 0.004. The mean electrode implantation angle error was 2.13° for the iSYS1 group and 1.71° for the PAD groups (p = 0.023). There was no statistically significant difference for any other outcome. Health policy and hospital commissioners should consider these differences in the context of the opportunity cost of introducing robotic devices.Trial registration: ISRCTN17209025 (https://doi.org/10.1186/ISRCTN17209025).

Advances in Brain Imaging Techniques for Patients With Intractable Epilepsy.

Intractable epilepsy, also known as drug resistance or refractory epilepsy, is a major problem affecting nearly one-third of epilepsy patients. Surgical intervention could be an option to treat these patients. Correct identification and localization of epileptogenic foci is a crucial preoperative step. Some of these patients, however, have no abnormality on routine magnetic resonance imaging (MRI) of the brain. Advanced imaging techniques, therefore, can be helpful to identify the area of concern. Moreover, a clear delineation of certain anatomical brain structures and their relation to the surgical lesion or the surgical approach is essential to avoid postoperative complications, and advanced imaging techniques can be very helpful. In this review, we discuss and highlight the use of advanced imaging techniques, particularly positron emission tomography (PET)–MRI, single-photon emission computed tomography, functional MRI, and diffusion tensor imaging–tractography for the preoperative assessment of epileptic patients.

An integrative prediction algorithm of drug-refractory epilepsy based on combined clinical-EEG functional connectivity features

Although the use of antiepileptic drugs (AEDs) is routine, 30-40% of patients with epilepsy (PWEs) experience drug resistance. Thus, early identification of AED resistance will help optimize treatment regimens and improve patients' prognoses. However, there have been few studies on this topic to date. Here, we try to establish an integrative prediction model of AED resistance for drug-naive PWEs, and to identify the clinical and Electroencephalogram (EEG) factors that affect their outcomes. One hundred sixty-four PWEs naive to AEDs treated at a tertiary care center from January 2014 to June 2020 were retrospectively analyzed. A total of 113 of these patients were well controlled and 53 were drug refractory with regular AED treatment for more than oneyear. Eighty clinical characteristics and 684 EEG functional connectivity variables based on phase lag index before drug initiation were identified. Overall, 80% of each group was chosen to establish a support vector machine (SVM) model with ten-fold cross validation, and the other 20% were used to evaluate the model's performance. Absolute weight value was used to rank the features that had impacts on classification. An integrative algorithm was modeled to predict AED resistance for drug-naive PWEs by SVM based on clinical characteristics and EEG functional connectivity values. The model had an accuracy of 94% [95% confidence interval (CI) 0.85-1.0], sensitivity of 95% [95% CI 0.82-1.0], specificity of 93% [95% CI 0.77-1.0], and an area under the curve (AUC) of 0.98 [95% CI 0.91-1.0]. The p values of accuracy, sensitivity specificity and AUC were calculated as 0.001, 0.001, 0.01 and 0.001, respectively. The δ band fromT4-FZ and T3-PZ, α band from T3-T6 and β band from F7-CZ and FP2-F3 were the top five EEG features that impacted the SVM classifier. We constructed an integrative prediction algorithm of AED resistance for drug-naive PWEs. Its utility in clinical settings should be evaluated in the future.

Efficacy, Retention and Tolerability of Everolimus in Patients with Tuberous Sclerosis Complex: A Survey-Based Study on Patients' Perspectives.

BackgroundThe approval of everolimus (EVE) for the treatment of angiomyolipoma (2013), subependymal giant cell astrocytoma (2013) and drug-refractory epilepsy (2017) in patients with tuberous sclerosis complex (TSC) represents the first disease-modifying treatment option available for this rare and complex genetic disorder.ObjectiveThe objective of this study was to analyse the use, efficacy, tolerability and treatment retention of EVE in patients with TSC in Germany from the patient’s perspective.MethodsA structured cross-age survey was conducted at 26 specialised TSC centres in Germany and by the German TSC patient advocacy group between February and July 2019, enrolling children, adolescents and adult patients with TSC.ResultsOf 365 participants, 36.7% (n = 134) reported the current or past intake of EVE, including 31.5% (n = 115) who were taking EVE at study entry. The mean EVE dosage was 6.1 ± 2.9 mg/m2 (median: 5.6 mg/m2, range 2.0–15.1 mg/m2) in children and adolescents and 4 ± 2.1 mg/m2 (median: 3.7 mg/m2, range 0.8–10.1 mg/m2) in adult patients. An early diagnosis of TSC, the presence of angiomyolipoma, drug-refractory epilepsy, neuropsychiatric manifestations, subependymal giant cell astrocytoma, cardiac rhabdomyoma and overall multi-organ involvement were associated with the use of EVE as a disease-modifying treatment. The reported efficacy was 64.0% for angiomyolipoma (75% in adult patients), 66.2% for drug-refractory epilepsy, and 54.4% for subependymal giant cell astrocytoma. The overall retention rate for EVE was 85.8%. The retention rates after 12 months of EVE therapy were higher among adults (93.7%) than among children and adolescents (88.7%; 90.5% vs 77.4% after 24 months; 87.3% vs 77.4% after 36 months). Tolerability was acceptable, with 70.9% of patients overall reporting adverse events, including stomatitis (47.0%), acne-like rash (7.7%), increased susceptibility to common infections and lymphoedema (each 6.0%), which were the most frequently reported symptoms. With a total score of 41.7 compared with 36.8 among patients not taking EVE, patients currently being treated with EVE showed an increased Liverpool Adverse Event Profile. Noticeable deviations in the sub-items ‘tiredness’, ‘skin problems’ and ‘mouth/gum problems’, which are likely related to EVE-typical adverse effects, were more frequently reported among patients taking EVE.ConclusionsFrom the patients’ perspective, EVE is an effective and relatively well-tolerated disease-modifying treatment option for children, adolescents and adults with TSC, associated with a high long-term retention rate that can be individually considered for each patient. Everolimus therapy should ideally be supervised by a centre experienced in the use of mechanistic target of rapamycin inhibitors, and adverse effects should be monitored on a regular basis.

Translational potential of the ghrelin receptor agonist macimorelin for seizure suppression in pharmacoresistant epilepsy.

Current drugs for epilepsy affect seizures, but no antiepileptogenic or disease-modifying drugs are available that prevent or slow down epileptogenesis, which is characterized by neuronal cell loss, inflammation and aberrant network formation. Ghrelin and ghrelin receptor (ghrelin-R) agonists were previously found to exert anticonvulsant, neuroprotective and anti-inflammatory effects in seizure models and immediately after status epilepticus (SE). Therefore, the aim of this study was to assess whether the ghrelin-R agonist macimorelin is antiepileptogenic in the pharmacoresistant intrahippocampal kainic acid (IHKA) mouse model. SE was induced in C57BL/6mice by unilateral IHKA injection. Starting 24h after SE, mice were treated intraperitoneally with macimorelin (5mg/kg) or saline twice daily for 2weeks, followed by a 2-week wash-out. Mice were continuously electroencephalogram-monitored, and at the end of the experiment neuroprotection and gliosis were assessed. Macimorelin significantly decreased the number and duration of seizures during the treatment period, but had no antiepileptogenic or disease-modifying effect in this dose regimen. While macimorelin did not significantly affect food intake or body weight over a 2-week treatment period, its acute orexigenic effect was preserved in epileptic mice but not in sham mice. While the full ghrelin-R agonist macimorelin was not significantly antiepileptogenic nor disease-modifying, this is the first study to demonstrate its anticonvulsant effects in the IHKA model of drug-refractory temporal lobe epilepsy. These findings highlight the potential use of macimorelin as a novel treatment option for seizure suppression in pharmacoresistant epilepsy.

Targeting Neuroinflammation via Purinergic P2 Receptors for Disease Modification in Drug-Refractory Epilepsy.

Treatment of epilepsy remains a clinical challenge, with >30% of patients not responding to current antiseizure drugs (ASDs). Moreover, currently available ASDs are merely symptomatic without altering significantly the progression of the disease. Inflammation is increasingly recognized as playing an important role during the generation of hyperexcitable networks in the brain. Accordingly, the suppression of chronic inflammation has been suggested as a promising therapeutic strategy to prevent epileptogenesis and to treat drug-refractory epilepsy. As a consequence, a strong focus of ongoing research is identification of the mechanisms that contribute to sustained inflammation in the brain during epilepsy and whether these can be targeted. ATP is released in response to several pathological stimuli, including increased neuronal activity within the central nervous system, where it functions as a neuro- and gliotransmitter. Once released, ATP activates purinergic P2 receptors, which are divided into metabotropic P2Y and ionotropic P2X receptors, driving inflammatory processes. Evidence from experimental models and patients demonstrates widespread expression changes of both P2Y and P2X receptors during epilepsy, and critically, drugs targeting both receptor subtypes, in particular the P2Y1 and P2X7 subtypes, have been shown to possess both anticonvulsive and antiepileptic potential. This review provides a detailed summary of the current evidence suggesting ATP-gated receptors as novel drug targets for epilepsy and discusses how P2 receptor–driven inflammation may contribute to the generation of seizures and the development of epilepsy.

Quality of life and its predictors in adults with tuberous sclerosis complex (TSC): a multicentre cohort study from Germany

BackgroundTuberous sclerosis complex (TSC) is a monogenetic, multisystemic disease characterised by the formation of benign tumours that can affect almost all organs, caused by pathogenic variations in TSC1 or TSC2. In this multicentre study from Germany, we investigated the influence of sociodemographic, clinical, and therapeutic factors on quality of life (QoL) among individuals with TSC.MethodsWe assessed sociodemographic and clinical characteristics and QoL among adults with TSC throughout Germany using a validated, three-month, retrospective questionnaire. We examined predictors of health-related QoL (HRQoL) using multiple linear regression analysis and compared the QoL among patients with TSC with QoL among patients with other chronic neurological disorders.ResultsWe enrolled 121 adults with TSC (mean age: 31.0 ± 10.5 years; range: 18–61 years, 45.5% [n = 55] women). Unemployment, a higher grade of disability, a higher number of organ manifestations, the presence of neuropsychiatric manifestations or active epilepsy, and a higher burden of therapy-related adverse events were associated with worse QoL, as measured by two QoL instruments (EuroQoL-5 dimensions [EQ-5D] and Quality of Life in Epilepsy Patients [QOLIE-31]). Neuropsychiatric and structural nervous system manifestations, the number of affected organs, and therapy-related adverse events were also associated with higher depression, as measured by the Neurological Disorders Depression Inventory for Epilepsy (NDDI-E). In multiple regression analysis, more severe therapy-related adverse events (large effect, p < 0.001), active epilepsy (large effect, p < 0.001), and neuropsychiatric manifestations (medium effect, p = 0.003) were independently associated with worse HRQoL, explaining 65% of the variance (p < 0.001). The HRQoL among patients with active TSC-associated epilepsy was worse than that among patients with drug-refractory mesial temporal lobe epilepsy (p < 0.001), and the generic QoL among patients with more than three TSC organ manifestations was similar to those of patients with severe migraine and uncontrolled asthma.ConclusionsActive epilepsy, neuropsychiatric manifestations (such as anxiety and depression), and therapy-related adverse events are important independent predictors of worse quality of life among adults with TSC. Generic quality of life in TSC with several manifestations is similar to uncontrolled severe chronic diseases and significantly negatively correlates with TSC severity.Trial registrationDRKS, DRKS00016045. Registered 01 March 2019.

Transitional pattern as a potential marker of epileptogenic zone in focal epilepsy - Clinical observations from intracerebral recordings

ObjectivesTo investigate the characteristics of transition from interictal to ictal phase in intracranial recordings and further to determine the potential marker of epileptogenic zone. MethodsEighteen patients with drug-refractory epilepsy who underwent stereo-electroencephalography (SEEG) evaluation and subsequent resective surgery were included. All patients were seizure-free post-operatively. The recorded seizures were retrospectively reviewed and time episodes including 5 min before electrographic onset were selected for further analysis to verify the presence of a transitional pattern in the transitional phase, which was distinct from interictal background and ictal onset. Besides, the components of transitional patterns which characterized by different pathological waveforms were identified by visual analysis and time-frequency analysis. The prevalence of transitional patterns between resection and non-resection, lesion and non-lesion sites were compared. In addition, the association between transitional patterns and types of epilepsy was explored. ResultsSix transitional patterns characterized by different combinations of multiple pathological waveforms by visual analysis combined with time-frequency analysis were identified: spike/spike-waves/polyspikes; spike superimposed by HFOs; spike superimposed by gamma oscillations; spike followed by suppression; spike superimposed by HFOs and followed by suppression; and spike superimposed by gamma oscillations and followed by suppression. A higher prevalence of transitional patterns in resection than non-resection (p < 0.001) and in lesion than non-lesion contacts (p < 0.001). The pattern characterized by spike superimposed by HFOs and followed by suppression was more prevalent in resection than non-resection sites (p = 0.004). Further, there was an association between the complexity of transitional patterns and the location of contacts. Patterns with higher degree of complexity were more likely to be inside the resection area (p = 0.035). Besides, we found the pattern with spike superimposed by HFOs was associated more with limbic epilepsy than neocortical epilepsy (p < 0.001), whereas another 3 patterns, spike superimposed by gamma oscillation, spike followed by suppression and spike combined with HFOs and suppression, were observed more frequently in neocortical epilepsy than limbic epilepsy (p = 0.018, 0.011 and < 0.001, respectively). ConclusionTransitional patterns from interictal to ictal state were characterized by different combinations of multiple pathological waveforms, which may be a potential marker of epileptogenic zone. Our findings support that the interaction of different neuronal oscillations or waveforms generated by different neuronal populations may be the potential mechanism of seizure generation.

Computer-Aided Intracranial EEG Signal Identification Method Based on a Multi-Branch Deep Learning Fusion Model and Clinical Validation.

Surgical intervention or the control of drug-refractory epilepsy requires accurate analysis of invasive inspection intracranial EEG (iEEG) data. A multi-branch deep learning fusion model is proposed to identify epileptogenic signals from the epileptogenic area of the brain. The classical approach extracts multi-domain signal wave features to construct a time-series feature sequence and then abstracts it through the bi-directional long short-term memory attention machine (Bi-LSTM-AM) classifier. The deep learning approach uses raw time-series signals to build a one-dimensional convolutional neural network (1D-CNN) to achieve end-to-end deep feature extraction and signal detection. These two branches are integrated to obtain deep fusion features and results. Resampling is employed to split the imbalanced epileptogenic and non-epileptogenic samples into balanced subsets for clinical validation. The model is validated over two publicly available benchmark iEEG databases to verify its effectiveness on a private, large-scale, clinical stereo EEG database. The model achieves high sensitivity (97.78%), accuracy (97.60%), and specificity (97.42%) on the Bern–Barcelona database, surpassing the performance of existing state-of-the-art techniques. It is then demonstrated on a clinical dataset with an average intra-subject accuracy of 92.53% and cross-subject accuracy of 88.03%. The results suggest that the proposed method is a valuable and extremely robust approach to help researchers and clinicians develop an automated method to identify the source of iEEG signals.

Altered ripple density inside seizure onset zone in patients with focal cortical dysplasia-associated epilepsy.

PurposeTo evaluate the clinical and stereoelectroencephalography (SEEG) features and postsurgical outcome in a uniform series of patients who underwent epilepsy surgery and had pathologically confirmation of focal cortical dysplasia (FCD).MethodsWe studied consecutive patients with drug‐refractory epilepsy who underwent SEEG recording. The high‐frequency oscillations (HFOs) features of SEEG, clinical characteristics, and surgical outcome were evaluated.ResultsSixty patients (31 FCD type I, 13 II, and 16 III) were analyzed retrospectively. Patients with type II tended to have their seizures at an earlier age than those with I and III (p < .01). Six different ictal onset patterns (IOPs) were identified. In patients with temporal lobe epilepsy (TLE), the most common patterns were rhythmic spikes or spike waves and LFRS, and in patients with extratemporal epilepsy, the most common patterns were low‐voltage fast activity (LVFA) and rhythmic spikes or spike waves. In addition, ripple density was found to increase significantly from the interictal to ictal onset sections and from the ictal onset to ictal evolution sections in patients with FCD I (p < .001). Regarding the distinct IOPs, ripple density continued to increase significantly between the interictal and ictal onset sections in LVFA, rhythmic spikes or spike waves, and burst of high‐amplitude polyspikes (p < .05). Ripple density decreased between ictal onset and ictal evolution sections in patterns of LVFA and rhythmic spikes or spike waves (p < .05). The mean follow‐up duration was 2.7 years (range 1–4.2), and 66.7% (n = 40) were class I. Patients with subtypes III and II had favorable surgical outcome than those with I.ConclusionThe clinical expression of seizure may depend on the pathological types with FCD II patients exhibiting their seizures at an earlier age. Distinct IOPs may demonstrate different ripple features and distinguishing the IOPs is very necessary to have an insight into the electrophysiological characteristics.

Gut flora and metabolism are altered in epilepsy and partially restored after ketogenic diets

ObjectiveThe aim of this study was to investigate the composition of the intestinal microbiota and its association with fecal short chain fatty acids (SCFAs) in children with drug refractory epilepsy (DRE) before and after treatment with a ketogenic diet (KD). MethodsHerein, we conducted a cross-sectional study of 12 children with DRE and 12 matched healthy controls to compare the changes in fecal microbiomes and SCFAs. Disease cohort also underwent analysis before and after 6 months of KD treatment. ResultsA higher microbial alpha diversity and a significant increase in Actinobacteria at the phylum level and Enterococcus, Anaerostipes, Bifidobacterium, Bacteroides, and Blautia at the genus level were observed in the children with DRE. The abundance of the eight epileptic-associated genera was reversed after six months of KD treatment with decreases in Bifidobacterium, Akkermansia, Enterococcaceae and Actinomyces and increases in Subdoligranulum, Dialister, Alloprevotella (p < 0.05). In particular, we identified some taxa that were more prevalent in patients with an inadequate response to KD than in those with an adequate response. Further, a significant correlation was observed between the change in the microbiome genera after KD treatment. The SCFA content in the fecal after 6 months of KD treatment increased and was highly correlated with the gut bacteria. SignificancesDysbiosis of the microbiome could be involved in the pathogenesis of DRE in children, which can be relieved by a KD to a large extent. Gut microbiota and microbial metabolism could contribute to the antiseizure effect of KD.

Clinical Spectrum and Comorbidities among Children with West Syndrome with Drug Refractory Epilepsy (3026)

Clinical Spectrum and Comorbidities among Children with West Syndrome with Drug Refractory Epilepsy (3026)

Epilepsy surgery in COVID times-a unique conundrum.

The COVID-19 pandemic has forced hospitals to prioritize admissions. Epilepsy surgeries have been postponed at most centers. As the pandemic continues with no definite end in sight in the near future, the question arises until when such patients should be denied appropriate treatment. A 12-year-old child with left-sided Rasmussen’s encephalitis with drug refractory epilepsy (DRE) presented at the height of the pandemic, with worsening of seizure frequency from 4–5/day to 20/day, with new-onset epilepsia partialis continua. She demonstrated features of progressive cognitive decline. The pros and cons of operating during the pandemic were discussed with the parents by a multidisciplinary team. She underwent endoscopic left hemispherotomy. Postoperatively she became seizure free but developed hospital-acquired mild COVID infection for which she was treated accordingly. Chosen cases of severe DRE, as the one illustrated above, who are deemed to benefit from surgery by a multidisciplinary team of physicians, should be re-categorized into the most severe class of patients and scheduled for surgery as soon as possible. The risk benefit ratio of the seizures being mitigated by surgery on one hand and possibility of acquiring COVID infection during hospital stay has to be balanced and a decision made accordingly.

Efficient automated localization of ECoG electrodes in CT images via shape analysis

PurposePeople with drug-refractory epilepsy are potential candidates for surgery. In many cases, epileptogenic zone localization requires intracranial investigations, e.g., via ElectroCorticoGraphy (ECoG), which uses subdural electrodes to map eloquent areas of large cortical regions. Precise electrodes localization on cortical surface is mandatory to delineate the seizure onset zone. Simple thresholding operations performed on patients’ computed tomography (CT) volumes recognize electrodes but also other metal objects (e.g., wires, stitches), which need to be manually removed. A new automated method based on shape analysis is proposed, which provides substantially improved performances in ECoG electrodes recognition.MethodsThe proposed method was retrospectively tested on 24 CT volumes of subjects with drug-refractory focal epilepsy, presenting a large number (> 1700) of round platinum electrodes. After CT volume thresholding, six geometric features of voxel clusters (volume, symmetry axes lengths, circularity and cylinder similarity) were used to recognize the actual electrodes among all metal objects via a Gaussian support vector machine (G-SVM). The proposed method was further tested on seven CT volumes from a public repository. Simultaneous recognition of depth and ECoG electrodes was also investigated on three additional CT volumes, containing penetrating depth electrodes.ResultsThe G-SVM provided a 99.74% mean classification accuracy across all 24 single-patient datasets, as well as on the combined dataset. High accuracies were obtained also on the CT volumes from public repository (98.27% across all patients, 99.68% on combined dataset). An overall accuracy of 99.34% was achieved for the recognition of depth and ECoG electrodes.ConclusionsThe proposed method accomplishes automated ECoG electrodes localization with unprecedented accuracy and can be easily implemented into existing software for preoperative analysis process. The preliminary yet surprisingly good results achieved for the simultaneous depth and ECoG electrodes recognition are encouraging.Ethical approval n°NCT04479410 by “IRCCS Neuromed” (Pozzilli, Italy), 30th July 2020.

Two Concomitant Cases with Febrile Infection-Related Epilepsy Syndrome (FIRES) treated with andldquo;3-Dimensional Combination Treatment Protocolandrdquo;

Objective: Febrile Infection-Related Epilepsy Syndrome (FIRES) is an immun-mediated epileptic encephalopathy presents as a febrile infection related super refractory status epilepticus with mortality rate of up to 30% in intensive care unit in spite of pharmacologically induced coma and immunotherapies. Early interventional ketogenic diet and cannabinoids are suggested for treatment with unknown mechanisms. Case presentation: Here we report two concomitant FIRES cases treated with a “3 dimensional combined treatment protocol“ for FIRES including (1); super refractory status epilepticus treatment protocol with intravenous infusion of antiepileptic and anesthetic drugs, (2) immunomodulatory therapies and (3) early interventional anti-epileptogenic therapy (ketogenic diet plus cannabinoids). The therapeutic intensity of the treatment protocol was monitored with serial EEG monitoring and Functional Independence Scores-WeeFIM. Two previously healthy school children manifesting super refractory status epilepticus were treated with moderate success. Both patients recovered with drug refractory epilepsy and neurocognitive impairments (patient 1; WeeFIM Scores were: self-care: 17, motor: 24, cognition: 10 and patient 2; WeeFIM score remained totally dependent: self-care: 8, motor: 5, cognition: 5) at the 12 months of follow-up. Conclusion: Febrile infection-related epilepsy syndrome is a devasting catastrophic epileptic encephalopathy. Early interventional treatment protocols should be applied in the early period of super refractory status epilepticus.

Efficacy of low glycemic index diet therapy (LGIT) in children aged 2–8 years with drug-resistant epilepsy: A randomized controlled trial

BackgroundA classic ketogenic diet, even though effective in children with drug-resistant epilepsy is not tolerated well by them and cumbersome to prepare. Low glycemic index therapy (LGIT), the least restrictive with minimal adverse effects among ketogenic dietary therapies has been proven effective in uncontrolled trials, but a placebo-controlled trial in this regard is still lacking. MethodsIn this open-label randomized controlled study, we randomized children above age two years with drug-resistant epilepsy into two groups (LGIT and control groups). Patients in the LGIT group received an add-on low glycemic index diet for 3 months along with the ongoing antiepileptic drugs and the patients in the control group did not receive any dietary intervention. Seizure frequency was assessed from the seizure diary maintained by the parents. Diet compliance was assessed using the diet diary that was maintained by the parents for three days just before the scheduled monthly visits of the patients. ResultsForty children with drug-refractory epilepsy (20 in each group) were enrolled. While 6/20 children in the LGIT arm have >50 % reduction in seizure frequency, none achieved this in the control arm (p = 0.02). The overall compliance with the low glycemic diet in the intervention group was 88.5 %. Out of six responders to LGIT, one child achieved seizure freedom and one achieved >90 % seizure reduction. Five continued LGIT further for a median duration of 8 months (range-4−12 months) successfully. The number needed to treat for more than 50 % seizure reduction was 3 and for more than 90 % seizure reduction was 10. The mean frequency of seizures for the intervention and control groups at three months of follow-up was not significantly different (p = 0.16), but the change in seizure frequency as compared to baseline was better in the intervention arm (p = 0.01). Three patients in the LGIT arm had non-serious adverse events (lethargy in two, vomiting in one). ConclusionIn children aged 2−8 years with drug-refractory epilepsy, the administration of LGIT along with ongoing anti-seizure medications (ASM) is more efficacious in reducing seizure frequency as compared to ASM alone.

Interictal spike localization for epilepsy surgery using magnetoencephalography beamforming

ObjectiveMagnetoencephalography (MEG) kurtosis beamforming is an automated localization method for focal epilepsy. Visual examination of virtual sensors, which are source activities reconstructed by beamforming, can improve performance but can be time-consuming for neurophysiologists. We propose a framework to automate the method and evaluate its effectiveness against surgical resections and outcomes. MethodsWe retrospectively analyzed MEG recordings of 13 epilepsy surgery patients who had one-year minimum post-operative follow-up. Kurtosis beamforming was applied and manual inspection was confined to morphological clusters. The region with the Maximum Interictal Spike Frequency (MISF) was validated against prospectively modelled sLORETA solutions and surgical resections linked to outcome. ResultsOur approach localized spikes in 12 out of 13 patients. In eight patients with Engel I surgical outcomes, beamforming MISF regions were concordant with surgical resection at overlap level for five patients and at lobar level for three patients. The MISF regions localized to spike onset and propagation modelled by sLORETA in two and six patients, respectively. ConclusionsAutomated beamforming using MEG can predict postoperative seizure freedom at the lobar level but tends to localize propagated MEG spikes. SignificanceMEG beamforming may contribute to non-invasive procedures to predict surgical outcome for patients with drug-refractory focal epilepsy.

Quantitative [18]FDG PET asymmetry features predict long-term seizure recurrence in refractory epilepsy

ObjectiveFluorodeoxyglucose-positron emission tomography (FDG-PET) is an established, independent, strong predictor of surgical outcome in refractory epilepsy. In this study, we explored the added value of quantitative [18F]FDG-PET features combined with clinical variables, including electroencephalography (EEG), [18F]FDG-PET, and magnetic resonance imaging (MRI) qualitative interpretations, to predict long-term seizure recurrence (mean post-op follow-up of 5.85 ± 3.77 years). MethodsMachine learning predictive models of surgical outcome were created using a random forest classifier trained on quantitative features in 89 patients with drug-refractory temporal lobe epilepsy evaluated at the Hospital of the University of Pennsylvania epilepsy surgery program (2003–2016). Quantitative features were calculated from asymmetry features derived from image processing using Advanced Normalization Tools (ANTs). ResultsThe best-performing model used quantification and had an out-of-bag accuracy of 0.71 in identifying patients with seizure recurrence (Engel IB or worse) which outperformed that using qualitative clinical data by 10%. This model is shared through open-source software for research use. In addition, several asymmetry features in temporal and extratemporal regions that were significantly associated with seizure freedom are identified for future study. SignificanceComplex quantitative [18F]FDG-PET imaging features can predict seizure recurrence in patients with refractory temporal lobe epilepsy. These initial retrospective results in a cohort with long-term follow-up suggest that using quantitative imaging features from regions in the epileptogenic network can inform the clinical decision-making process.

Visual field defects in temporal lobe epilepsy surgery.

Surgery can provide a robust long-standing seizure remission in drug-refractory mesial temporal lobe epilepsy (MTLE). Despite this, a significant proportion of postoperative patients are ineligible to gain a driving licence due to the size of the subsequent visual field defect (VFD). The amygdala and hippocampus are intimately related to several important white fibre association tracts and damage to the optic radiation results in a contralateral superior quadrantanopia. For this reason, several different modifications to established surgical approaches and novel techniques have recently been applied to mitigate or prevent damage to the optic radiation. There is still no consensus on which operative technique results in optimal outcomes regarding seizure remission, neuropsychological sequelae and VFD rates. We explore contemporary surgical approaches to the mesial temporal lobe and describe the intraoperative use of tractography and iMRI in preventing VFDs. Established approaches for the surgical treatment of MTLE include standardized approaches in the form of anterior temporal lobectomies, selective approaches and various modifications thereof. Recent advancements in microsurgical techniques have seen numerous modifications to these approaches to spare the optic radiation as well as the introduction of minimally invasive alternatives such as laser interstitial thermal therapy (LITT) and stereotactic radiosurgery (SRS). The intraoperative use of optic radiation tractography through overlays in the operative microscope and interventional MRI suites to correct for brain shift have been shown to reduce VFDs. VFDs following the surgical treatment of drug-refractory MTLE can have a significant impact on the quality of life. Each of the surgical techniques carries a risk to the visual pathways but the use of minimally invasive techniques as well as surgical adjuncts may reduce or prevent acquired VFDs.

Identifying Refractory Epilepsy Without Structural Abnormalities by Fusing the Common Spatial Patterns of Functional and Effective EEG Networks

Drug refractory epilepsy (RE) is believed to be associated with structural lesions, but some RE patients show no significant structural abnormalities (RE-no-SA) on conventional magnetic resonance imaging scans. Since most of the medically controlled epilepsy (MCE) patients also do not exhibit structural abnormalities, a reliable assessment needs to be developed to differentiate RE-no-SA patients and MCE patients to avoid misdiagnosis and inappropriate treatment. Using resting-state scalp electroencephalogram (EEG) datasets, we extracted the spatial pattern of network (SPN) features from the functional and effective EEG networks of both RE-no-SA patients and MCE patients. Compared to the performance of traditional resting-state EEG network properties, the SPN features exhibited remarkable superiority in classifying these two groups of epilepsy patients, and accuracy values of 90.00% and 80.00% were obtained for the SPN features of the functional and effective EEG networks, respectively. By further fusing the SPN features of functional and effective networks, we demonstrated that the highest accuracy value of 96.67% could be reached, with a sensitivity of 100% and specificity of 92.86%. Overall, these findings not only indicate that the fused functional and effective SPN features are promising as reliable measurements for distinguishing RE-no-SA patients and MCE patients but also may provide a new perspective to explore the complex neurophysiology of refractory epilepsy.