Faculty Bibliography

OBJECTIVE:The association between postictal electroencephalogram (EEG) suppression (PES), autonomic dysfunction, and Sudden Unexpected Death in Epilepsy (SUDEP) remains poorly understood. We compared PES on simultaneous intracranial and scalp-EEG and evaluated the association of PES with postictal heart rate variability (HRV) and SUDEP outcome. METHODS:Convulsive seizures were analyzed in patients with drug-resistant epilepsy at 5 centers. Intracranial PES was quantified using the Hilbert transform. HRV was quantified using root mean square of successive differences of interbeat intervals, low-frequency to high-frequency power ratio, and RR-intervals. RESULTS:There were 64 seizures from 63 patients without SUDEP and 11 seizures from 6 SUDEP patients. PES occurred in 99% and 87% of seizures on intracranial-EEG and scalp-EEG, respectively. Mean PES duration in intracranial and scalp-EEG was similar. Intracranial PES was regional (<90% of channels) in 46% of seizures; scalp PES was generalized in all seizures. Generalized PES showed greater decrease in postictal parasympathetic activity than regional PES. PES duration and extent were similar between patients with and without SUDEP. CONCLUSIONS:Regional intracranial PES can be present despite scalp-EEG demonstrating generalized or no PES. Postictal autonomic dysfunction correlates with the extent of PES. SIGNIFICANCE/CONCLUSIONS:Intracranial-EEG demonstrates changes in autonomic regulatory networks not seen on scalp-EEG.

OBJECTIVE:Accreditation Council for Graduate Medical Education (ACGME)-accredited epilepsy fellowships, like other ACGME accredited training programs, use Milestones to establish learning objectives and to evaluate how well trainees are achieving these goals. The ACGME began developing the second iteration of the Milestones 6 years ago, and these are now being adapted to all specialties. Here, we describe the process by which Epilepsy Milestones 2.0 were developed and summarize them. METHODS:A work group of nine board-certified, adult and pediatric epileptologists reviewed Epilepsy Milestones 1.0 and revised them using a modified Delphi approach. RESULTS:The new Milestones share structural changes with all other specialties, including a clearer stepwise progression in professional development and the harmonized Milestones that address competencies common to all medical fields. Much of the epilepsy-specific content remains the same, although a major addition is a set of Milestones focused on reading and interpreting electroencephalograms (EEGs), which the old Milestones lacked. Epilepsy Milestones 2.0 includes a Supplemental Guide to help program directors implement the new Milestones. Together, Epilepsy Milestones 2.0 and the Supplemental Guide recognize advances in epilepsy, including stereo-EEG, neurostimulation, genetics, and safety in epilepsy monitoring units. SIGNIFICANCE:Epilepsy Milestones 2.0 address the shortcomings of the old Milestones and should facilitate the assessment of epilepsy fellowships and fellows by program directors, faculty, and fellows themselves.

BACKGROUND AND OBJECTIVES:The aim of this study was to identify predictors of a resective surgery and subsequent seizure freedom following intracranial EEG (ICEEG) for seizure-onset localization. METHODS:This is a retrospective chart review of 178 consecutive patients with medically refractory epilepsy who underwent ICEEG monitoring from 2002 to 2015. Univariable and multivariable regression analysis identified independent predictors of resection vs other options. Stepwise Akaike information criteria with the aid of clinical consideration were used to select the best multivariable model for predicting resection and outcome. Discrete time survival analysis was used to analyze the factors predicting seizure-free outcome. Cumulative probability of seizure freedom was analyzed using Kaplan-Meier curves and compared between resection and nonresection groups. Additional univariate analysis was performed on 8 select clinical scenarios commonly encountered during epilepsy surgical evaluations. RESULTS:< 0.0001, hazard ratio 0.16, 95% CI 0.09-0.28). Even patients thought to have unfavorable predictors (nonlesional MRI or extratemporal lobe hypothesis or dominant hemisphere implant) had ≥50% chance of seizure freedom at 5 years if they underwent resection. DISCUSSION:Unfavorable predictors, including having nonlesional extratemporal epilepsy, should not deter a thorough presurgical evaluation, including with invasive recordings in many cases. Resective surgery without functional impairment offers the best chance for sustained seizure freedom and should always be considered first. CLASSIFICATION OF EVIDENCE:This study provides Class II evidence that the presence of a lesional MRI, presurgical hypothesis suggesting temporal lobe onset, and a nondominant hemisphere implant are independent predictors of resection. Focal ICEEG onset and undergoing resection are independent predictors of 5-year seizure freedom.

OBJECTIVE:Temporal lobe encephaloceles (TLENs) are a significant cause of medically refractory epilepsy, but there is little consensus regarding their workup and treatment. This study characterizes these lesions and their role in seizures and aims to standardize preoperative evaluation and surgical management. METHODS:Patients with TLEN who had undergone resective epilepsy surgery from December 2015 to August 2020 at a single institution were included in the study. Medical records were reviewed for each patient to collect relevant seizure workup information including demographics, radiological findings, surgical data, and neuropsychological evaluation. RESULTS:For patients who presented to the authors' program with suspected medically intractable temporal lobe epilepsy (219 patients), TLEN was considered to be the epileptogenic focus in 5.5%. Ten patients with TLEN had undergone resection and were included in this study. Concordance between ictal scalp electroencephalography (EEG) lateralization and TLEN was found in 9/10 patients (90%), and 4/10 patients (40%) had signs suggestive of idiopathic intracranial hypertension (IIH). Surgical outcome was reported in patients with at least 12 months of follow-up (9/10). Patients with scalp EEG findings concordant with the TLEN side had a good outcome (Engel class I: 7 patients, class II: 1 patient). One patient with discordant EEG findings had a bad outcome (Engel class III). No significant neuropsychological deficits were observed after the surgery. CONCLUSIONS:TLENs are epileptogenic lesions that should be screened for in patients with medically refractory epilepsy who have signs of IIH and no other lesions on MRI. Restricted resection is safe and effective in patients with scalp EEG findings concordant with TLEN.

OBJECTIVE:To evaluate the role of intracranial electroencephalography monitoring in diagnosing and directing the appropriate therapy for MRI-negative epilepsy and to present the surgical outcomes of patients following treatment. METHODS:Retrospective chart review between 2015-2021 at a single institution identified 48 patients with no lesion on MRI, who received surgical intervention for their epilepsy. The outcomes assessed were the surgical treatment performed and the International League Against Epilepsy seizure outcomes at 1 year of follow-up. RESULTS:Eleven patients underwent surgery without invasive monitoring, including vagus nerve stimulation (10%), deep brain stimulation (8%), laser interstitial thermal therapy (2%), and callosotomy (2%). The remaining 37 patients received invasive monitoring followed by resection (35%), responsive neurostimulation (21%), and deep brain stimulation (15%) or no treatment (6%). At 1 year postoperatively, 39% were Class 1-2, 36% were Class 3-4 and 24% were Class 5. More patients with Class 1-2 or 3-4 outcomes underwent invasive monitoring (100% and 83% respectively) compared with those with poor outcomes (25%, P < .001). Patients with Class 1-2 outcomes more commonly underwent resection or responsive neurostimulation: 69% and 31%, respectively (P < .001). SIGNIFICANCE:The optimal management of MRI-negative focal epilepsy may involve invasive monitoring followed by resection or responsive neurostimulation in most cases, as these treatments were associated with the best seizure outcomes in our cohort. Unless multifocal onset is clear from the noninvasive evaluation, invasive monitoring is preferred before pursuing deep brain stimulation or vagal nerve stimulation directly.

Objective/UNASSIGNED:Sudden unexpected death in epilepsy (SUDEP) is the leading cause of epilepsy-related mortality. Although lots of effort has been made in identifying clinical risk factors for SUDEP in the literature, there are few validated methods to predict individual SUDEP risk. Prolonged postictal EEG suppression (PGES) is a potential SUDEP biomarker, but its occurrence is infrequent and requires epilepsy monitoring unit admission. We use machine learning methods to examine SUDEP risk using interictal EEG and ECG recordings from SUDEP cases and matched living epilepsy controls. Methods/UNASSIGNED:This multicenter, retrospective, cohort study examined interictal EEG and ECG recordings from 30 SUDEP cases and 58 age-matched living epilepsy patient controls. We trained machine learning models with interictal EEG and ECG features to predict the retrospective SUDEP risk for each patient. We assessed cross-validated classification accuracy and the area under the receiver operating characteristic (AUC) curve. Results/UNASSIGNED:The logistic regression (LR) classifier produced the overall best performance, outperforming the support vector machine (SVM), random forest (RF), and convolutional neural network (CNN). Among the 30 patients with SUDEP [14 females; mean age (SD), 31 (8.47) years] and 58 living epilepsy controls [26 females (43%); mean age (SD) 31 (8.5) years], the LR model achieved the median AUC of 0.77 [interquartile range (IQR), 0.73-0.80] in five-fold cross-validation using interictal alpha and low gamma power ratio of the EEG and heart rate variability (HRV) features extracted from the ECG. The LR model achieved the mean AUC of 0.79 in leave-one-center-out prediction. Conclusions/UNASSIGNED:Our results support that machine learning-driven models may quantify SUDEP risk for epilepsy patients, future refinements in our model may help predict individualized SUDEP risk and help clinicians correlate predictive scores with the clinical data. Low-cost and noninvasive interictal biomarkers of SUDEP risk may help clinicians to identify high-risk patients and initiate preventive strategies.

The insula is well established as an epileptogenic area.1 Insular epilepsy surgery demands precise anatomic knowledge2-4 and tailored removal of the epileptic zone with careful neuromonitoring.5 We present an operative video illustrating an intracranial electroencephalogram (EEG) depth electrode guided anterior insulectomy.  We report a 17-yr-old right-handed woman with a 4-yr history of medically refractory epilepsy. The patient reported daily nocturnal ictal vocalization preceded by an indescribable feeling. Preoperative evaluation was suggestive of a right frontal-temporal onset, but the noninvasive results were discordant. She underwent a combined intracranial EEG study with a frontal-parietal grid, with strips and depth electrodes covering the entire right hemisphere. Epileptiform activity was observed in contact 6 of the anterior insula electrode. The patient consented to the procedure and to the publication of her images.  A right anterior insulectomy was performed. First, a portion of the frontal operculum was resected and neuronavigation was used for the initial insula localization. However, due to unreliable neuronavigation (ie, brain shift), the medial and anterior borders of the insular resection were guided by the depth electrode reference. The patient was discharged 3 d after surgery with no neurological deficits and remains seizure free.  We demonstrate that depth electrode guided insular surgery is a safe and precise technique, leading to an optimal outcome.

The term 'implantation effect' is used to describe an immediate and transient improvement in seizure frequency following an intracranial study for seizure onset localization. We conducted a retrospective analysis of 190 consecutive patients undergoing intracranial electroencephalogram (EEG) monitoring, of whom 41 had no subsequent resection/ablation/stimulation; 33 had adequate data and follow-up time available for analysis. Analysis of seizure frequency following an intracranial study showed 36% (12/33) responder rate (>50% seizure reduction) at one year, decreasing and stabilizing at 20% from year 4 onwards. In addition, we describe three patients (9%) who had long term seizure freedom of more than five years following electrode implantation alone, two of whom had thalamic depth electrodes. Electrode implantation perhaps leads to a neuromodulatory effect sufficient enough to disrupt epileptogenic networks. Rarely, this may be significant enough to even result in long term seizure freedom, as seen in our three patients.

OBJECTIVE:Generalized epileptiform discharges (GEDs) can occur during seizures or without obvious clinical accompaniment. Motor vehicle driving risk during apparently subclinical GEDs is uncertain. Our goals were to develop a feasible, realistic test to evaluate driving safety during GEDs, and to begin evaluating electroencephalographic (EEG) features in relation to driving safety. METHODS:Subjects were aged ≥15 years with generalized epilepsy, GEDs on EEG, and no clinical seizures. Using a high-fidelity driving simulator (miniSim) with simultaneous EEG, a red oval visual stimulus was presented every 5 minutes for baseline testing, and with each GED. Participants were instructed to pull over as quickly and safely as possible with each stimulus. We analyzed driving and EEG signals during GEDs. RESULTS:Nine subjects were tested, and five experienced 88 GEDs total with mean duration 2.31 ± 1.89 (SD) seconds. Of these five subjects, three responded appropriately to all stimuli, one failed to respond to 75% of stimuli, and one stopped driving immediately during GEDs. GEDs with no response to stimuli were significantly longer than those with appropriate responses (8.47 ± 3.10 vs 1.85 ± 0.69 seconds, P < .001). Reaction times to stimuli during GEDs were significantly correlated with GED duration (r = 0.30, P = .04). In addition, EEG amplitude was greater for GEDs with no response to stimuli than GEDs with responses, both for overall root mean square voltage amplitude (66.14 μV vs 52.99 μV, P = .02) and for fractional power changes in the frequency range of waves (P < .05) and spikes (P < .001). SIGNIFICANCE:High-fidelity driving simulation is feasible for investigating driving behavior during GEDs. GEDs with longer duration and greater EEG amplitude showed more driving impairment. Future work with a large sample size may ultimately enable classification of GED EEG features to predict individual driving risk.