OBJECTIVE: We aimed to analyze seizure outcomes and define ictal onset with intracranial electroencephalography (ICEEG) in patients with polymicrogyria (PMG)-related drug-resistant epilepsy (DRE), considering surrounding cortex and extent of surgical resection.
METHODS: Retrospective study of PMG-diagnosed patients (2001 to June 2018) at a single epilepsy center was performed. Primary outcome was complete seizure freedom (SF), based on Engel classification with follow-up of ≥ 1 year. Univariate analyses identified predictive clinical variables, later integrated into multivariate Cox proportional hazards models.
RESULTS: Thirty-five patients with PMG-related DRE (19 adults/16 pediatric: 20 unilateral/15 bilateral) were studied. In surgical group (n = 23), 52 % achieved SF (mean follow-up:47 months), whereas none in non-resective treatment group (n = 12) attained SF (mean follow-up:39.3 months) (p = 0.002). In surgical group, there were no significant differences in SF, based on the laterality of the PMG [uni or bilateral,p = 0.35], involvement of perisylvian region(p = 0.714), and extent of the PMG resection [total vs. partial,p = 0.159]. Patients with ictal ICEEG onset in both PMG and non-PMG cortices, and those limited to non- PMG cortices had a greater chance of achieving SF compared to those limited to the PMG cortices.
CONCLUSIONS: Resective surgery guided by ICEEG for defining the epileptogenic zone (EZ), in DRE patients with PMG, leads to favorable seizure outcomes. ICEEG-guided focal surgical resection(s) may lead to SF in patients with bilateral or extensive unilateral PMG. ICEEG aids in EZ localization within and/or outside the MRI-identified PMG. Complete removal of PMG identified on MRI does not guarantee SF. Hence, developing preimplantation hypotheses based on epileptogenic networks evaluation during presurgical assessment is crucial in this patient population.

OBJECTIVE: To investigate post-operative seizure outcomes, and predictors of surgical outcomes of the malformation of cortical development (MCD) in children with drug-resistant epilepsy (DRE) and age-specific characteristics.
METHODS: We retrospectively analyzed clinical data from 428 children with MCD-related DRE who underwent curative surgical treatment. Statistical analyses were conducted to identify correlative characteristics, prognostic predictors, and differences among various age groups.
RESULTS: After more than 3 years of follow-up, 81.3% of patients achieved Engel I outcomes. Prognosis was correlated with factors such as age at surgery, MRI findings, invasive EEG, pathology, acute postoperative seizures (APOS), and the number of preoperative and postoperative anti-seizure medications (AEDs). Age at surgery and the number of preoperative AEDs (p < 0.001) were significant predictors of seizure recurrence. Distinct clinical characteristics were observed among different age groups.
CONCLUSIONS: Surgery is effective in terminating MCD-related DRE. Younger age at surgery and fewer preoperative AEDs are associated with better prognoses. Clinical characteristics vary significantly with age.

Among patients with epilepsy, 30-40% experience recurrent seizures even after adequate antiseizure medications therapies, making them refractory. The early identification of refractory epilepsy is important to provide timely surgical treatment for these patients. In this study, we analyze interictal electroencephalography (EEG) data to predict drug refractoriness in patients with temporal lobe epilepsy (TLE) who were treated with monotherapy at the time of the first EEG acquisition. Various EEG features were extracted, including statistical measurements and interchannel coherence. Feature selection was performed to identify the optimal features, and classification was conducted using different classifiers. Functional connectivity and graph theory measurements were calculated to identify characteristics of refractory TLE. Among the 48 participants, 34 (70.8%) were responsive, while 14 (29.2%) were refractory over a mean follow-up duration of 38.5 months. Coherence feature within the gamma frequency band exhibited the most favorable performance. The light gradient boosting model, employing the mutual information filter-based feature selection method, demonstrated the highest performance (AUROC = 0.821). Compared to the responsive group, interchannel coherence displayed higher values in the refractory group. Interestingly, graph theory measurements using EEG coherence exhibited higher values in the refractory group than in the responsive group. Our study has demonstrated a promising method for the early identification of refractory TLE utilizing machine learning algorithms.

Hemispherotomy is an effective surgery for treating refractory epilepsy from diffuse unihemispheric lesions. To date, postsurgery neuroplastic changes supporting behavioral recovery after left or right hemispherotomy remain unclear. In the present study, we systematically investigated changes in gray matter volume (GMV) before and after surgery and further analyzed their relationships with behavioral scores in two large groups of pediatric patients with left and right hemispherotomy (29 left and 28 right). To control for the dramatic developmental effect during this stage, age-adjusted GMV within unaffected brain regions was derived voxel by voxel using a normative modeling approach with an age-matched reference cohort of 2115 healthy children. Widespread GMV increases in the contralateral cerebrum and ipsilateral cerebellum and GMV decreases in the contralateral cerebellum were consistently observed in both patient groups, but only the left hemispherotomy patients showed GMV decreases in the contralateral cingulate gyrus. Intriguingly, the GMV decrease in the contralateral cerebellum was significantly correlated with improvement in behavioral scores in the right but not the left hemispherotomy patients. Importantly, the preoperative voxelwise GMV features can be used to significantly predict postoperative behavioral scores in both patient groups. These findings indicate an important role of the contralateral cerebellum in the behavioral recovery following right hemispherotomy and highlight the predictive potential of preoperative imaging features in postoperative behavioral performance.

BACKGROUND: Epilepsy surgery has been shown to significantly improve the quality of life of patients with drug resistant epilepsy. Despite this, epilepsy surgery remains remarkably underutilized in Nigeria. There are high misconceptions about epilepsy and its management among physicians and trainees.
METHODS: This study aims to identify knowledge gaps in epilepsy surgery among medical doctors in Nigeria and factors associated with their level of knowledge of the procedure. A cross-sectional study was carried out among 566 medical doctors in Nigeria, at different levels of post-graduate training (House officers, Medical officers, Resident doctors and Consultants). An online survey with a 24-item questionnaire adapted from a standardized pro forma was utilized. Binary and multiple logistic regression were used to identify associations between the independent variable and outcome variable (good or poor knowledge) RESULTS: Majority of the respondents were medical officers (post-intern physicians) comprising 65.7 % of the participants. Significant predictors of poor knowledge included being a medical officer [P=0.006], working in north-central [P=0.017] and north-western Nigeria [P=0.045], seeing less than 20 epilepsy patients per month [1-10 patients, P=0.015; 11-20 patients, P=0.011], and enrolment in online epilepsy course [P=0.004].
CONCLUSIONS: Comprehensive education and awareness about epilepsy surgery are important in overcoming the knowledge gap and improving access to care.

MR-guided Laser Interstitial Thermal Therapy (MRgLITT) is a minimally invasive neurosurgical technique increasingly used for the treatment of drug-resistant epilepsy and brain tumors. Utilizing near-infrared light energy delivery guided by real-time MRI thermometry, MRgLITT enables precise ablation of targeted brain tissues, resulting in limited corridor-related morbidity and expedited postoperative recovery. Since receiving CE marking in 2018, the adoption of MRgLITT has expanded to more than 40 neurosurgical centers across Europe. In epilepsy treatment, MRgLITT can be applied to various types of focal lesional epilepsy, including mesial temporal lobe epilepsy, hypothalamic hamartoma, focal cortical dysplasias, periventricular heterotopias, cavernous malformations, dysembryoplastic neuroepithelial tumors (DNET), low-grade gliomas, tuberous sclerosis, and in disconnective surgeries. In neuro-oncology, MRgLITT is used for treating newly diagnosed and recurrent primary brain tumors, brain metastases, and radiation necrosis. This comprehensive review presents an overview of the current evidence and technical considerations for the use of MRgLITT in treating various pathologies associated with drug-resistant epilepsy and brain tumors.

Objective.For medically-refractory epilepsy patients, stereoelectroencephalography (sEEG) is a surgical method using intracranial electrode recordings to identify brain networks participating in early seizure organization and propagation (i.e. the epileptogenic zone, EZ). If identified, surgical EZ treatment via resection, ablation or neuromodulation can lead to seizure-freedom. To date, quantification of sEEG data, including its visualization and interpretation, remains a clinical and computational challenge. Given elusiveness of physical laws or governing equations modelling complex brain dynamics, data science offers unique insight into identifying unknown patterns within high-dimensional sEEG data. We apply here an unsupervised data-driven algorithm, dynamic mode decomposition (DMD), to sEEG recordings from five focal epilepsy patients (three with temporal lobe, and two with cingulate epilepsy), who underwent subsequent resective or ablative surgery and became seizure free.Approach.DMD obtains a linear approximation of nonlinear data dynamics, generating coherent structures (\'modes\') defining important signal features, used to extract frequencies, growth rates and spatial structures. DMD was adapted to produce dynamic modal maps (DMMs) across frequency sub-bands, capturing onset and evolution of epileptiform dynamics in sEEG data. Additionally, we developed a static estimate of EZ-localized electrode contacts, termed the higher-frequency mode-based norm index (MNI). DMM and MNI maps for representative patient seizures were validated against clinical sEEG results and seizure-free outcomes following surgery.Main results.DMD was most informative at higher frequencies, i.e. gamma (including high-gamma) and beta range, successfully identifying EZ contacts. Combined interpretation of DMM/MNI plots best identified spatiotemporal evolution of mode-specific network changes, with strong concordance to sEEG results and outcomes across all five patients. The method identified network attenuation in other contacts not implicated in the EZ.Significance.This is the first application of DMD to sEEG data analysis, supporting integration of neuroengineering, mathematical and machine learning methods into traditional workflows for sEEG review and epilepsy surgical decision-making.

In childhood drug-resistant focal epilepsy, the identification of a magnetic resonance imaging lesion significantly affects the management and prognosis, although it is often challenging. Herein we report the preliminary results of a modified MR sequence, in which both magnetization transfer and chemical shift selective preparation pulses are added to a 3D fast spin echo T1-weighted sequence to recognize focal cortical dysplasia. The scan time is short, and the images have expected uniform suppression of the background normal gray and white matter. We report four children with focal epilepsy, in whom the focal cortical and subcortical lesions are superiorly conspicuous on the aforementioned MR sequence compared to the high-resolution fluid-attenuated inversion recovery images obtained with typical epilepsy MR protocols.

BACKGROUND: Children with tuberous sclerosis complex (TSC) are at high risk for drug-resistant epilepsy (DRE). The ability to stratify those at highest risk for DRE is important for counseling and prompt, aggressive management, necessary to optimize neurocognitive outcomes. Using the extensively phenotyped PREVeNT cohort, we aimed to characterize whether the TSC genotype was associated with DRE.
METHODS: The study group (N = 70) comprised participants with TSC enrolled at age less than or equal to six months with detailed epilepsy and other phenotypic and genotypic data, prospectively collected as part of the PREVeNT trial. Genotype-phenotype correlations of DRE, time to first abnormal electroencephalography, and time to epilepsy onset were compared using Fisher exact test and regression models.
RESULTS: Presence of a TSC2 pathogenic variant was significantly associated with DRE, compared with TSC1 and participants with no pathogenic mutation identified. In fact, all participants with DRE had a TSC2 pathogenic variant. Furthermore, TSC2 variants expected to result in no protein product were associated with higher risk for DRE. Finally, TSC1 pathogenic variants were associated with later-onset epilepsy, on average 21.2 months later than those with other genotypes.
CONCLUSIONS: Using a comprehensively phenotyped cohort followed from infancy, this study is the first to delineate genotype-phenotype correlations for epilepsy severity and onset in children with TSC. Patients with TSC2 pathogenic variants, especially TSC2 pathogenic variants predicted to result in lack of TSC2 protein, are at highest risk for DRE, and are likely to have earlier epilepsy onset than those with TSC1. Clinically, these insights can inform counseling, surveillance, and management.

BACKGROUND: Drug-resistant epilepsy is defined as failure of seizure control in spite of using 2 or 3 proper antiepileptic drugs in appropriate time. Mineral elements play important roles in neuronal function; it is believed that mineral deficiency may lead to complications through seizure management. In the present study, serum levels of zinc (Zn), copper (Cu), magnesium (Mg), calcium (Ca), and 25-hydroxy vitamin D (Vit D) in drug-resistant-epilepsy (DRE) patients were evaluated and compared with the controlled patients.
METHODS: In this cross-sectional study, epileptic patients were included and categorized into two groups of DRE and well-controlled patients. Patients\' serum samples were analysed to evaluate Zn, Cu, Mg, Ca, and Vit D levels. The primary objective was comparison of serum levels of different trace elements between the groups.
RESULTS: Sixty-four epileptic children including 33 DRE and 31 well-controlled children entered the study. The DRE children showed a significantly earlier onset of disease compared to the other group (p = 0.014). Comparing the frequency of developmental delay between the groups, the results showed this complication was significantly more frequent in the DRE group (p < 0.001). Concerning serum elements, the results showed a significantly higher concentration of Zn in the well-controlled group than the DRE group (p = 0.007). On the other hand, no significant differences were observed between the groups regarding the means of Vit D, Ca, Cu, and Mg levels (p > 0.05).
CONCLUSIONS: The results of the present study delineated that drug-resistant epilepsy patients had earlier onset of disease and were at higher risk of neurodevelopmental delay compared with well-controlled-epilepsy patients. A significant lower serum levels of Zn were also observed in drug-resistant-epilepsy patients. This finding may suggest the role of zinc supplementation in help to better control of drug-resistant seizures, as well as, the importance of serum zinc monitoring in epileptic patients.