Faculty Bibliography

Rationale: Resective surgical treatment can be curative in a large subset of patients with treatment resistant epilepsy. There is a need for a simple surgical grading tool which can be employed by the referring neurologist, ideally utilizing information obtained prior to diagnostic hospitalization. Our hypothesis was that a model using interictal EEG, brain MRI, seizure semiology and IQ could stratify patients with treatment resistant epilepsy with respect to their likelihood of achieving seizure freedom following assessment for resective epilepsy surgery. Methods: A prospectively identified cohort of 211 patients from the University of Alabama was combined with a retrospectively identified cohort of 193 consecutive patients at New York University presented in surgical multidisciplinary conference and either proceeded to surgery or were excluded as surgical candidates. All met inclusion criteria: age e18, focal epilepsy diagnosis e2 years, failed e1 medication, e1 seizure 3 months prior to admission, follow-up>6 months. Patients were classified as seizure free following resective surgery or not seizure free following resective surgery/no surgery. Pre-operative EEG, MRI, seizure semiology and IQ data were reviewed, systematically categorized (Table 1) and were utilized in a decision tree algorithm to predict seizure freedom. When p<0.05 was utilized, a simplistic dichotomous algorithm resulted. Therefore, to further explore, a relaxed, exploratory statistical significance level of p<0.25 was used. Nodes resulting in >50% of patients becoming seizure free were considered predictive of seizure freedom. Results: The overall seizure freedom rate was 46.8%. The exploratory decision tree analysis (Figure 1) resulted in two EEG groups: F, G, H (bilateral temporal, bilateral extra-temporal, bisynchronous; node 2; N=97) versus all others (node 3; N=307). For node 3, MRI was employed for further stratification: b (unilateral mesial temporal sclerosis (MTS); node 4; N=75) versus all others (node 7; N=232). Node 4 was further stratified based upon IQ: below 70 (node 5; N=11), above 70 (node 6; N=64). Semiology had no statistically significant impact. The model correctly predicts outcome in 62% of patients, yielding a positive predictive value of 55%, and a negative predictive value of 71%, with sensitivity of 74% and specificity of 51%. Conclusions: The relatively low overall seizure freedom rate is due to the fact that patients considered for, but ultimately not undergoing, surgery were included in the analysis, which better reflects the actual decision process for patients and neurologists. Of interest, the model fails to identify the commonly considered "best surgical" group of unilateral MTS with concordant interictal activity as a unique node. Notably, the main predictive factor was interictal EEG; other factors were only statistically viable with a more exploratory statistical approach. The positive and negative predictive values in this model are probably not sufficient for clinical use

Rationale: Resective surgery is an important consideration for patients with treatment resistant epilepsy as it may offer the best chance for seizure freedom. Initial patient counseling and the decision to refer a patient to an epilepsy surgery center is usually based on the history and physical exam, routine electroencephalogram (EEG), and brain MRI. The aim of this review is to summarize the literature and identify factors typically available in the general office setting that are reliable predictors of epilepsy surgery outcome. Methods: A literature search was performed using Pubmed and Embase. Inclusion criteria included: English language, sample size e20 patients, MRI performed on e90% of patients, a median age e16 years, average of e1 year follow-up, and predictive value assessment of clinical factors, routine EEG and/or MRI brain for outcome in epilepsy surgical resections. Articles were independently reviewed by at least 2 authors and data on study design and predictive factors were abstracted. Results: Of the 2,248 articles related to predictors of epilepsy surgical outcome identified, 123 met all inclusion criteria. Only 12 articles had a prospective study design. Study populations varied in size and epilepsy characteristics with the majority focusing on mesial temporal lobe epilepsy or lesional epilepsies. The studies focused almost exclusively on patients that had undergone resection rather than all patients considered for surgery or undergoing invasive procedures (intention-to-treat analysis). Predictive factors were not uniformly assessed in most studies, nor were they uniformly defined across studies. For example, in various studies, unilateral routine EEG epileptiform activity was variably categorized as "only ipsilateral spikes", ">70% ipsilateral", ">80% ipsilateral", or ">90% ipsilateral". Although many studies used the Engel or modified Engel classification systems, many utilized non-standardized outcome determinations (e.g. "good"). Only 6 studies had a masked assessment of seizure outcome following surgery. Conclusions: The heterogeneous patient populations, methodologies and outcome determinations significantly limit the existing literature's ability to predict the likelihood of a patient achieving seizure freedom from resective surgery based upon pre-operative data, especially in patients with extra-temporal non-mesial epilepsy. Prospective multicenter studies based upon intention to treat (i.e. enrolling patients prior to invasive procedures to determine the number of patients that are considered for epilepsy surgery that do not progress to a resective procedure) are necessary to better facilitate and encourage early referral to comprehensive epilepsy centers, counsel patients and families and identify new strategies for improving outcomes. By establishing and utilizing accepted, standardized definitions (e.g. treatment resistant epilepsy), one can improve the generalizability of findings across patients and centers

Rationale: Magnetic resonance imaging has revolutionized the detection of small structural abnormalities in patients with epilepsy. However, many focal abnormalities remain undetected in routine visual inspection. Here we used morphometric MRI to quantify imaging features related to epileptogenic cortical malformations to detect abnormal cortical thickness and blurred gray-white matter boundaries that went undetected by routine clinical visual inspection. Methods: Using MRI morphometry at 3T with surface-based spherical averaging techniques that precisely align anatomical structures between individual brains, we compared single patients with known lesions to a large normal control group to detect clusters of abnormal cortical thickness and gray-white matter contrast (GWC). To assess the effects of threshold and smoothing on detection sensitivity and specificity, we systematically varied these parameters with different thresholds and smoothing levels. To establish the effectiveness of the technique, we compared the detected structural abnormalities to resection margins, seizure onset zones based on intracranial EEG and pathological features using post-resection histology. Results: We report optimal parameters by which cortical thickness and GWC features detected previously occult lesions. We present sensitivity and specificity measures for each threshold and smoothing level to allow for selection of parameters based on clinical need. Conclusions: This automated approach may be a valuable additional clinical tool to improve the detection of subtle or previously occult malformations and therefore may improve identification of patients with intractable focal epilepsy who may benefit from surgery

Muscimol has potent antiepileptic efficacy after transmeningeal administration in animals. However, it is unknown whether this compound stops local neuronal firing at concentrations that prevent seizures. The purpose of this study was to test the hypothesis that epidurally administered muscimol can prevent acetylcholine (Ach)-induced focal seizures in the rat neocortex without causing cessation of multineuronal activity. Rats were chronically implanted with a modified epidural cup over the right frontal cortex, with microelectrodes positioned underneath the cup. In each postsurgical experimental day, either saline or 0.005-, 0.05-, 0.5- or 5.0-mM muscimol was delivered through the cup, followed by a 20-min monitoring of the multineuronal activity and the subsequent delivery of Ach in the same way. Saline and muscimol pretreatment in the concentration range of 0.005-0.05mM did not prevent EEG seizures. In contrast, 0.5-mM muscimol reduced the average EEG Seizure Duration Ratio value from 0.30+/-0.04 to 0. At this muscimol concentration, the average baseline multineuronal firing rate of 10.9+/-4.4spikes/s did not change significantly throughout the 20-min pretreatment. Muscimol at 5.0mM also prevented seizures, but decreased significantly the baseline multineuronal firing rate of 7.0+/-1.8 to 3.7+/-0.9spikes/s in the last 10min of pretreatment. These data indicate that transmeningeal muscimol in a submillimolar concentration range can prevent focal neocortical seizures without stopping multineuronal activity in the treated area, and thus this treatment is unlikely to interrupt local physiological functions

Periodic transmeningeal administration of muscimol into the neocortical epileptogenic zone via a subdurally implanted device has been proposed for the treatment of intractable focal neocortical epilepsy. It is unknown whether such muscimol applications induce tolerance. The purpose of this study was to determine whether daily transmeningeal (epidural) muscimol applications into the rat parietal cortex induce tolerance to the antiepileptic effect of this drug. Rats were chronically implanted with an epidural cup and adjacent epidural EEG electrodes over the right parietal cortex. After recovery 1.0mM muscimol was delivered into the implanted cortical area through the cup while the animal behaved freely, once per day for 4 consecutive days in each week, with each delivery followed within 3min by the delivery of a seizure-inducing concentration of acetylcholine (Ach) into the same area. The study lasted for 3 weeks. In each week, one day was used to test the epileptogenicity of the examined cortical site by replacing muscimol with saline prior to Ach delivery. The duration of Ach-induced EEG seizures was measured in each experimental session to assess the antiepileptic efficacy of muscimol, while the rat's behavior was also monitored. The daily epidural muscimol pretreatments prevented Ach-induced EEG and behavioral seizures in all rats. This antiepileptic action did not diminish over time and was maintained throughout the 3-week test period. When muscimol was replaced with saline, the subsequent Ach administrations induced EEG and behavioral seizures. These results suggest that periodic transmeningeal administrations of a relatively low concentration of muscimol into the neocortex over three weeks do not induce tolerance to the localized antiepileptic effects of this drug

The Common Data Element (CDE) Project was initiated in 2006 by the National Institute of Neurological Disorders and Stroke (NINDS) to develop standards for performing funded neuroscience-related clinical research. CDEs are intended to standardize aspects of data collection; decrease study start-up time; and provide more complete, comprehensive, and equivalent data across studies within a particular disease area. Therefore, CDEs will simplify data sharing and data aggregation across NINDS-funded clinical research, and where appropriate, facilitate the development of evidenced-based guidelines and recommendations. Epilepsy-specific CDEs were established in nine content areas: (1) Antiepileptic Drugs (AEDs) and Other Antiepileptic Therapies (AETs), (2) Comorbidities, (3) Electrophysiology, (4) Imaging, (5) Neurological Exam, (6) Neuropsychology, (7) Quality of Life, (8) Seizures and Syndromes, and (9) Surgery and Pathology. CDEs were developed as a dynamic resource that will accommodate recommendations based on investigator use, new technologies, and research findings documenting emerging critical disease characteristics. The epilepsy-specific CDE initiative can be viewed as part of the larger international movement toward 'harmonization' of clinical disease characterization and outcome assessment designed to promote communication and research efforts in epilepsy. It will also provide valuable guidance for CDE improvement during further development, refinement, and implementation. This article describes the NINDS CDE Initiative, the process used in developing Epilepsy CDEs, and the benefits of CDEs for the clinical investigator and NINDS

Using data from NIH Research Portfolio Online Reporting Tools (RePORT) and recently assembled prevalence estimates of 6 major neurologic diseases, we compared the relative prevalences and the annual NIH support levels for 6 major neurologic disorders: Alzheimer disease, amyotrophic lateral sclerosis (ALS), epilepsy, multiple sclerosis, Parkinson disease, and stroke. Compared to these other major neurologic disorders, epilepsy research is funded at a persistently lower rate based on relative disease prevalences. Relative NIH funding for these other disorders in 2010 adjusted for prevalence ranged from 1.7x (stroke) to 61.1x (ALS) greater than epilepsy. The disparity cannot be explained by differences in the overall impact of these diseases on US citizens. Greater transparency in the review and funding process is needed to disclose the reason for this disparity

OBJECTIVE: To evaluate the efficacy and safety of ezogabine (United States adopted name)/retigabine (international nonproprietary name) (EZG[RTG]) 1,200 mg/day as adjunctive treatment in adults with drug-resistant epilepsy with partial-onset seizures with or without secondary generalization. METHODS: RESTORE 1 was a multicenter, randomized, double-blind, parallel-group trial. Following a prospective 8-week baseline phase, patients entered an 18-week double-blind treatment period (6-week forced dose titration to EZG[RTG] 1,200 mg/day in 3 equally divided doses or placebo, followed by a 12-week maintenance phase). Results were analyzed on an intent-to-treat basis for the entire 18-week period and for patients reaching the maintenance phase. RESULTS: In 306 patients randomized, 305 received EZG(RTG) 1,200 mg/day (n = 153) or placebo (n = 152). Median percent reduction in total partial-seizure frequency was 44.3% vs 17.5% (p < 0.001) for EZG(RTG) and placebo, respectively, during the 18-week double-blind period; responder rates (>/=50% reduction in total partial-seizure frequency from baseline) were 44.4% vs 17.8% (p < 0.001). In 256 patients (EZG[RTG], 119; placebo, 137) entering the 12-week maintenance phase, median percent reduction in seizure frequency for EZG(RTG) vs placebo was 54.5% and 18.9% (p < 0.001), respectively; responder rates were 55.5% vs 22.6% (p < 0.001). The proportion of patients discontinuing due to treatment-emergent adverse events (TEAEs) was 26.8% (EZG[RTG]) vs 8.6% (placebo). Dizziness, somnolence, fatigue, confusion, dysarthria, urinary tract infection, ataxia, and blurred vision were the most common TEAEs reported by more patients treated with EZG(RTG) than placebo. CONCLUSIONS: This study demonstrates that EZG(RTG) is effective as add-on therapy for reducing seizure frequency in patients with drug-resistant partial-onset seizures. Classification of evidence: This study provides Class II evidence that EZG(RTG) 1,200 mg/day is effective as adjunctive therapy in adults with partial-onset seizures with or without secondary generalization

Magnetic resonance imaging has revolutionized the detection of structural abnormalities in patients with epilepsy. However, many focal abnormalities remain undetected in routine visual inspection. Here we use an automated, surface-based method for quantifying morphometric features related to epileptogenic cortical malformations to detect abnormal cortical thickness and blurred gray-white matter boundaries. Using MRI morphometry at 3T with surface-based spherical averaging techniques that precisely align anatomical structures between individual brains, we compared single patients with known lesions to a large normal control group to detect clusters of abnormal cortical thickness, gray-white matter contrast, local gyrification, sulcal depth, jacobian distance and curvature. To assess the effects of threshold and smoothing on detection sensitivity and specificity, we systematically varied these parameters with different thresholds and smoothing levels. To test the effectiveness of the technique to detect lesions of epileptogenic character, we compared the detected structural abnormalities to expert-tracings, intracranial EEG, pathology and surgical outcome in a homogeneous patient sample. With optimal parameters and by combining thickness and GWC, the surface-based detection method identified 92% of cortical lesions (sensitivity) with few false positives (96% specificity), successfully discriminating patients from controls 94% of the time. The detected structural abnormalities were related to the seizure onset zones, abnormal histology and positive outcome in all surgical patients. However, the method failed to adequately describe lesion extent in most cases. Automated surface-based MRI morphometry, if used with optimized parameters, may be a valuable additional clinical tool to improve the detection of subtle or previously occult malformations and therefore could improve identification of patients with intractable focal epilepsy who may benefit from surgery