Jehi, Lara

Abstract Objective Anterior temporal lobectomy (ATL) is a widely performed and successful intervention for drug‐resistant temporal lobe epilepsy (TLE). However, up to one third of patients experience seizure recurrence within 1 year after ATL. Despite the extensive literature on presurgical electroencephalography (EEG) and magnetic resonance imaging (MRI) abnormalities to prognosticate seizure freedom following ATL, the value of quantitative analysis of visually reviewed normal interictal EEG in such prognostication remains unclear. In this retrospective multicenter study, we investigate whether machine learning analysis of normal interictal scalp EEG studies can inform the prediction of postoperative seizure freedom outcomes in patients who have undergone ATL. Methods We analyzed normal presurgical scalp EEG recordings from 41 Mayo Clinic (MC) and 23 Cleveland Clinic (CC) patients. We used an unbiased automated algorithm to extract eyes closed awake epochs from scalp EEG studies that were free of any epileptiform activity and then extracted spectral EEG features representing (a) spectral power and (b) interhemispheric spectral coherence in frequencies between 1 and 25 Hz across several brain regions. We analyzed the differences between the seizure‐free and non–seizure‐free patients and employed a Naïve Bayes classifier using multiple spectral features to predict surgery outcomes. We trained the classifier using a leave‐one‐patient‐out cross‐validation scheme within the MC data set and then tested using the out‐of‐sample CC data set. Finally, we compared the predictive performance of normal scalp EEG‐derived features against MRI abnormalities. Results We found that several spectral power and coherence features showed significant differences correlated with surgical outcomes and that they were most pronounced in the 10–25 Hz range. The Naïve Bayes classification based on those features predicted 1‐year seizure freedom following ATL with area under the curve (AUC) values of 0.78 and 0.76 for the MC and CC data sets, respectively. Subsequent analyses revealed that (a) interhemispheric spectral coherence features in the 10–25 Hz range provided better predictability than other combinations and (b) normal scalp EEG‐derived features provided superior and potentially distinct predictive value when compared with MRI abnormalities (>10% higher F1 score). Significance These results support that quantitative analysis of even a normal presurgical scalp EEG may help prognosticate seizure freedom following ATL in patients with drug‐resistant TLE. Although the mechanism for this result is not known, the scalp EEG spectral and coherence properties predicting seizure freedom may represent activity arising from the neocortex or the networks responsible for temporal lobe seizure generation within vs outside the margins of an ATL.

AbstractObjectiveSummarize the current evidence on efficacy and tolerability of vagus nerve stimulation (VNS), responsive neurostimulation (RNS), and deep brain stimulation (DBS) through a systematic review and meta‐analysis.MethodsWe followed the Preferred Reporting Items of Systematic reviews and Meta‐Analyses reporting standards and searched Ovid Medline, Ovid Embase, and the Cochrane Central Register of Controlled Trials. We included published randomized controlled trials (RCTs) and their corresponding open‐label extension studies, as well as prospective case series, with ≥20 participants (excluding studies limited to children). Our primary outcome was the mean (or median, when unavailable) percentage decrease in frequency, as compared to baseline, of all epileptic seizures at last follow‐up. Secondary outcomes included the proportion of treatment responders and proportion with seizure freedom.ResultsWe identified 30 eligible studies, six of which were RCTs. At long‐term follow‐up (mean 1.3 years), five observational studies for VNS reported a pooled mean percentage decrease in seizure frequency of 34.7% (95% confidence interval [CI]: −5.1, 74.5). In the open‐label extension studies for RNS, the median seizure reduction was 53%, 66%, and 75% at 2, 5, and 9 years of follow‐up, respectively. For DBS, the median reduction was 56%, 65%, and 75% at 2, 5, and 7 years, respectively. The proportion of individuals with seizure freedom at last follow‐up increased significantly over time for DBS and RNS, whereas a positive trend was observed for VNS. Quality of life was improved in all modalities. The most common complications included hoarseness, and cough and throat pain for VNS and implant site pain, headache, and dysesthesia for DBS and RNS.SignificanceNeurostimulation modalities are an effective treatment option for drug‐resistant epilepsy, with improving outcomes over time and few major complications. Seizure‐reduction rates among the three therapies were similar during the initial blinded phase. Recent long‐term follow‐up studies are encouraging for RNS and DBS but are lacking for VNS.

Abstract Objective This study aims to evaluate the role of scalp electroencephalography (EEG; ictal and interictal patterns) in predicting resective epilepsy surgery outcomes. We use the data to further develop a nomogram to predict seizure freedom. Methods We retrospectively reviewed the scalp EEG findings and clinical data of patients who underwent surgical resection at three epilepsy centers. Using both EEG and clinical variables categorized into 13 isolated candidate predictors and 6 interaction terms, we built a multivariable Cox proportional hazards model to predict seizure freedom 2 years after surgery. Harrell's step‐down procedure was used to sequentially eliminate the least‐informative variables from the model until the change in the concordance index (c‐index) with variable removal was less than 0.01. We created a separate model using only clinical variables. Discrimination of the two models was compared to evaluate the role of scalp EEG in seizure‐freedom prediction. Results Four hundred seventy patient records were analyzed. Following internal validation, the full Clinical + EEG model achieved an optimism‐corrected c‐index of 0.65, whereas the c‐index of the model without EEG data was 0.59. The presence of focal to bilateral tonic‐clonic seizures (FBTCS), high preoperative seizure frequency, absence of hippocampal sclerosis, and presence of nonlocalizable seizures predicted worse outcome. The presence of FBTCS had the largest impact for predicting outcome. The analysis of the models’ interactions showed that in patients with unilateral interictal epileptiform discharges (IEDs), temporal lobe surgery cases had a better outcome. In cases with bilateral IEDs, abnormal magnetic resonance imaging (MRI) predicted worse outcomes, and in cases without IEDs, patients with extratemporal epilepsy and abnormal MRI had better outcomes. Significance This study highlights the value of scalp EEG, particularly the significance of IEDs, in predicting surgical outcome. The nomogram delivers an individualized prediction of postoperative outcome, and provides a unique assessment of the relationship between the outcome and preoperative findings.

Abstract Quantitative volumetric brain MRI measurement is important in research applications, but translating it into patient care is challenging. We explore the incorporation of clinical automated quantitative MRI measurements in statistical models predicting outcomes of surgery for temporal lobe epilepsy. Four hundred and thirty-five patients with drug-resistant epilepsy who underwent temporal lobe surgery at Cleveland Clinic, Mayo Clinic and University of Campinas were studied. We obtained volumetric measurements from the pre-operative T1-weighted MRI using NeuroQuant, a Food and Drug Administration approved software package. We created sets of statistical models to predict the probability of complete seizure-freedom or an Engel score of I at the last follow-up. The cohort was randomly split into training and testing sets, with a ratio of 7:3. Model discrimination was assessed using the concordance statistic (C-statistic). We compared four sets of models and selected the one with the highest concordance index. Volumetric differences in pre-surgical MRI located predominantly in the frontocentral and temporal regions were associated with poorer outcomes. The addition of volumetric measurements to the model with clinical variables alone increased the model’s C-statistic from 0.58 to 0.70 (right-sided surgery) and from 0.61 to 0.66 (left-sided surgery) for complete seizure freedom and from 0.62 to 0.67 (right-sided surgery) and from 0.68 to 0.73 (left-sided surgery) for an Engel I outcome score. 57% of patients with extra-temporal abnormalities were seizure-free at last follow-up, compared to 68% of those with no such abnormalities (P-value = 0.02). Adding quantitative MRI data increases the performance of a model developed to predict post-operative seizure outcomes. The distribution of the regions of interest included in the final model supports the notion that focal epilepsies are network disorders and that subtle cortical volume loss outside the surgical site influences seizure outcome.

Summary Objective Epilepsy surgery is the most effective treatment for select patients with drug‐resistant epilepsy. In this article, we aim to provide an accurate understanding of the current epidemiologic characteristics of this intervention, as this knowledge is critical for guiding educational, academic, and resource priorities. Methods We profile the practice of epilepsy surgery between 1991 and 2011 in nine major epilepsy surgery centers in the United States, Germany, and Australia. Clinical, imaging, surgical, and histopathologic data were derived from the surgical databases at various centers. Results Although five of the centers performed their highest number of surgeries for mesial temporal sclerosis ( MTS ) in 1991, and three had their highest number of MTS surgeries in 2001, only one center achieved its peak number of MTS surgeries in 2011. The most productive year for MTS surgeries varied then by center; overall, the nine centers surveyed performed 48% (95% confidence interval [CI] −27.3% to −67.4%) fewer such surgeries in 2011 compared to either 1991 or 2001, whichever was higher. There was a parallel increase in the performance of surgery for nonlesional epilepsy. Further analysis of 5/9 centers showed a yearly increase of 0.6 ± 0.07% in the performance of invasive electroencephalography ( EEG ) without subsequent resections. Overall, although MTS was the main surgical substrate in 1991 and 2001 (proportion of total surgeries in study centers ranging from 33.3% to 70.2%); it occupied only 33.6% of all resections in 2011 in the context of an overall stable total surgical volume. Significance These findings highlight the major aspects of the evolution of epilepsy surgery across the past two decades in a sample of well‐established epilepsy surgery centers, and the critical current challenges of this treatment option in addressing complex epilepsy cases requiring detailed evaluations. Possible causes and implications of these findings are discussed.