Pitfalls in scalp EEG: Current obstacles and future directions.

Although electroencephalography (EEG) serves a critical role in the evaluation and management of seizure disorders, it is commonly misinterpreted, resulting in avoidable medical, social, and financial burdens to patients and health care systems. Overinterpretation of sharply contoured transient waveforms as being representative of interictal epileptiform abnormalities lies at the core of this problem. However, the magnitude of these errors is amplified by the high prevalence of paroxysmal events exhibited in clinical practice that compel investigation with EEG. Neurology training programs, which vary considerably both in the degree of exposure to EEG and the composition of EEG didactics, have not effectively addressed this widespread issue. Implementation of competency-based curricula in lieu of traditional educational approaches may enhance proficiency in EEG interpretation amongst general neurologists in the absence of formal subspecialty training. Efforts in this regard have led to the development of a systematic, high-fidelity approach to the interpretation of epileptiform discharges that is readily employable across medical centers. Additionally, machine learning techniques hold promise for accelerating accurate and reliable EEG interpretation, particularly in settings where subspecialty interpretive EEG services are not readily available. This review highlights common diagnostic errors in EEG interpretation, limitations in current educational paradigms, and initiatives aimed at resolving these challenges.

Quantifying interictal intracranial EEG to predict focal epilepsy.

Introduction: Intracranial EEG (IEEG) is used for 2 main purposes, to determine: (1) if epileptic networks are amenable to focal treatment and (2) where to intervene. Currently these questions are answered qualitatively and sometimes differently across centers. There is a need for objective, standardized methods to guide surgical decision making and to enable large scale data analysis across centers and prospective clinical trials. Methods: We analyzed interictal data from 101 patients with drug resistant epilepsy who underwent presurgical evaluation with IEEG. We chose interictal data because of its potential to reduce the morbidity and cost associated with ictal recording. 65 patients had unifocal seizure onset on IEEG, and 36 were non-focal or multi-focal. We quantified the spatial dispersion of implanted electrodes and interictal IEEG abnormalities for each patient. We compared these measures against the "5 Sense Score (5SS)," a pre-implant estimate of the likelihood of focal seizure onset, and assessed their ability to predict the clinicians' choice of therapeutic intervention and the patient outcome. Results: The spatial dispersion of IEEG electrodes predicted network focality with precision similar to the 5SS (AUC = 0.67), indicating that electrode placement accurately reflected pre-implant information. A cross-validated model combining the 5SS and the spatial dispersion of interictal IEEG abnormalities significantly improved this prediction (AUC = 0.79; p<0.05). The combined model predicted ultimate treatment strategy (surgery vs. device) with an AUC of 0.81 and post-surgical outcome at 2 years with an AUC of 0.70. The 5SS, interictal IEEG, and electrode placement were not correlated and provided complementary information. Conclusions: Quantitative, interictal IEEG significantly improved upon pre-implant estimates of network focality and predicted treatment with precision approaching that of clinical experts. We present this study as an important step in building standardized, quantitative tools to guide epilepsy surgery.

Seizure onset patterns predict outcome after stereo-electroencephalography-guided laser amygdalohippocampotomy.

OBJECTIVE: Stereotactic laser amygdalohippocampotomy (SLAH) is an appealing option for patients with temporal lobe epilepsy, who often require intracranial monitoring to confirm mesial temporal seizure onset. However, given limited spatial sampling, it is possible that stereotactic electroencephalography (stereo-EEG) may miss seizure onset elsewhere. We hypothesized that stereo-EEG seizure onset patterns (SOPs) may differentiate between primary onset and secondary spread and predict postoperative seizure control. In this study, we characterized the 2-year outcomes of patients who underwent single-fiber SLAH after stereo-EEG and evaluated whether stereo-EEG SOPs predict postoperative seizure freedom. METHODS: This retrospective five-center study included patients with or without mesial temporal sclerosis (MTS) who underwent stereo-EEG followed by single-fiber SLAH between August 2014 and January 2022. Patients with causative hippocampal lesions apart from MTS or for whom the SLAH was considered palliative were excluded. An SOP catalogue was developed based on literature review. The dominant pattern for each patient was used for survival analysis. The primary outcome was 2-year Engel I classification or recurrent seizures before then, stratified by SOP category. RESULTS: Fifty-eight patients were included, with a mean follow-up duration of 39 ± 12 months after SLAH. Overall 1-, 2-, and 3-year Engel I seizure freedom probability was 54%, 36%, and 33%, respectively. Patients with SOPs, including low-voltage fast activity or low-frequency repetitive spiking, had a 46% 2-year seizure freedom probability, compared to 0% for patients with alpha or theta frequency repetitive spiking or theta or delta frequency rhythmic slowing (log-rank test, p = .00015). SIGNIFICANCE: Patients who underwent SLAH after stereo-EEG had a low probability of seizure freedom at 2 years, but SOPs successfully predicted seizure recurrence in a subset of patients. This study provides proof of concept that SOPs distinguish between hippocampal seizure onset and spread and supports using SOPs to improve selection of SLAH candidates.

Quantifying trial-by-trial variability during cortico-cortical evoked potential mapping of epileptogenic tissue.

OBJECTIVE: Measuring cortico-cortical evoked potentials (CCEPs) is a promising tool for mapping epileptic networks, but it is not known how variability in brain state and stimulation technique might impact the use of CCEPs for epilepsy localization. We test the hypotheses that (1) CCEPs demonstrate systematic variability across trials and (2) CCEP amplitudes depend on the timing of stimulation with respect to endogenous, low-frequency oscillations. METHODS: We studied 11 patients who underwent CCEP mapping after stereo-electroencephalography electrode implantation for surgical evaluation of drug-resistant epilepsy. Evoked potentials were measured from all electrodes after each pulse of a 30 s, 1 Hz bipolar stimulation train. We quantified monotonic trends, phase dependence, and standard deviation (SD) of N1 (15-50 ms post-stimulation) and N2 (50-300 ms post-stimulation) amplitudes across the 30 stimulation trials for each patient. We used linear regression to quantify the relationship between measures of CCEP variability and the clinical seizure-onset zone (SOZ) or interictal spike rates. RESULTS: We found that N1 and N2 waveforms exhibited both positive and negative monotonic trends in amplitude across trials. SOZ electrodes and electrodes with high interictal spike rates had lower N1 and N2 amplitudes with higher SD across trials. Monotonic trends of N1 and N2 amplitude were more positive when stimulating from an area with higher interictal spike rate. We also found intermittent synchronization of trial-level N1 amplitude with low-frequency phase in the hippocampus, which did not localize the SOZ. SIGNIFICANCE: These findings suggest that standard approaches for CCEP mapping, which involve computing a trial-averaged response over a .2-1 Hz stimulation train, may be masking inter-trial variability that localizes to epileptogenic tissue. We also found that CCEP N1 amplitudes synchronize with ongoing low-frequency oscillations in the hippocampus. Further targeted experiments are needed to determine whether phase-locked stimulation could have a role in localizing epileptogenic tissue.

Spike patterns surrounding sleep and seizures localize the seizure-onset zone in focal epilepsy.

OBJECTIVE: Interictal spikes help localize seizure generators as part of surgical planning for drug-resistant epilepsy. However, there are often multiple spike populations whose frequencies change over time, influenced by brain state. Understanding state changes in spike rates will improve our ability to use spikes for surgical planning. Our goal was to determine the effect of sleep and seizures on interictal spikes, and to use sleep and seizure-related changes in spikes to localize the seizure-onset zone (SOZ). METHODS: We performed a retrospective analysis of intracranial electroencephalography (EEG) data from patients with focal epilepsy. We automatically detected interictal spikes and we classified different time periods as awake or asleep based on the ratio of alpha to delta power, with a secondary analysis using the recently published SleepSEEG algorithm. We analyzed spike rates surrounding sleep and seizures. We developed a model to localize the SOZ using state-dependent spike rates. RESULTS: We analyzed data from 101 patients (54 women, age range 16-69). The normalized alpha-delta power ratio accurately classified wake from sleep periods (area under the curve = .90). Spikes were more frequent in sleep than wakefulness and in the post-ictal compared to the pre-ictal state. Patients with temporal lobe epilepsy had a greater wake-to-sleep and pre- to post-ictal spike rate increase compared to patients with extra-temporal epilepsy. A machine-learning classifier incorporating state-dependent spike rates accurately identified the SOZ (area under the curve = .83). Spike rates tended to be higher and better localize the seizure-onset zone in non-rapid eye movement (NREM) sleep than in wake or REM sleep. SIGNIFICANCE: The change in spike rates surrounding sleep and seizures differs between temporal and extra-temporal lobe epilepsy. Spikes are more frequent and better localize the SOZ in sleep, particularly in NREM sleep. Quantitative analysis of spikes may provide useful ancillary data to localize the SOZ and improve surgical planning.

Interictal intracranial EEG asymmetry lateralizes temporal lobe epilepsy.

Patients with drug-resistant temporal lobe epilepsy often undergo intracranial EEG recording to capture multiple seizures in order to lateralize the seizure onset zone. This process is associated with morbidity and often ends in postoperative seizure recurrence. Abundant interictal (between-seizure) data is captured during this process, but these data currently play a small role in surgical planning. Our objective was to predict the laterality of the seizure onset zone using interictal (between-seizure) intracranial EEG data in patients with temporal lobe epilepsy. We performed a retrospective cohort study (single-center study for model development; two-center study for model validation). We studied patients with temporal lobe epilepsy undergoing intracranial EEG at the University of Pennsylvania (internal cohort) and the Medical University of South Carolina (external cohort) between 2015 and 2022. We developed a logistic regression model to predict seizure onset zone laterality using interictal EEG. We compared the concordance between the model-predicted seizure onset zone laterality and the side of surgery between patients with good and poor surgical outcomes. 47 patients (30 women; ages 20-69; 20 left-sided, 10 right-sided, and 17 bilateral seizure onsets) were analyzed for model development and internal validation. 19 patients (10 women; ages 23-73; 5 left-sided, 10 right-sided, 4 bilateral) were analyzed for external validation. The internal cohort cross-validated area under the curve for a model trained using spike rates was 0.83 for a model predicting left-sided seizure onset and 0.68 for a model predicting right-sided seizure onset. Balanced accuracies in the external cohort were 79.3% and 78.9% for the left- and right-sided predictions, respectively. The predicted concordance between the laterality of the seizure onset zone and the side of surgery was higher in patients with good surgical outcome. In conclusion, interictal EEG signatures are distinct across seizure onset zone lateralities. Left-sided seizure onsets are easier to distinguish than right-sided onsets. A model trained on spike rates accurately identifies patients with left-sided seizure onset zones and predicts surgical outcome.

Extracting seizure frequency from epilepsy clinic notes: a machine reading approach to natural language processing.

OBJECTIVE: Seizure frequency and seizure freedom are among the most important outcome measures for patients with epilepsy. In this study, we aimed to automatically extract this clinical information from unstructured text in clinical notes. If successful, this could improve clinical decision-making in epilepsy patients and allow for rapid, large-scale retrospective research. MATERIALS AND METHODS: We developed a finetuning pipeline for pretrained neural models to classify patients as being seizure-free and to extract text containing their seizure frequency and date of last seizure from clinical notes. We annotated 1000 notes for use as training and testing data and determined how well 3 pretrained neural models, BERT, RoBERTa, and Bio_ClinicalBERT, could identify and extract the desired information after finetuning. RESULTS: The finetuned models (BERTFT, Bio_ClinicalBERTFT, and RoBERTaFT) achieved near-human performance when classifying patients as seizure free, with BERTFT and Bio_ClinicalBERTFT achieving accuracy scores over 80%. All 3 models also achieved human performance when extracting seizure frequency and date of last seizure, with overall F1 scores over 0.80. The best combination of models was Bio_ClinicalBERTFT for classification, and RoBERTaFT for text extraction. Most of the gains in performance due to finetuning required roughly 70 annotated notes. DISCUSSION AND CONCLUSION: Our novel machine reading approach to extracting important clinical outcomes performed at or near human performance on several tasks. This approach opens new possibilities to support clinical practice and conduct large-scale retrospective clinical research. Future studies can use our finetuning pipeline with minimal training annotations to answer new clinical questions.

Patterns of seizure spread in temporal lobe epilepsy are associated with distinct white matter tracts.

OBJECTIVE: It is commonly hypothesized that seizure spread patterns in patients with focal epilepsy are associated with structural brain pathways. However, this relationship is poorly understood and has not been fully demonstrated in patients with temporal lobe epilepsy. Here, we sought to determine whether directionality of seizure spread (DSS) is associated with specific cerebral white matter tracts in patients with temporal lobe epilepsy. METHODS: Thirty-three adult patients with temporal lobe epilepsy who underwent stereoelectroencephalography (sEEG) and magnetic resonance diffusion tensor imaging (MR-DTI) as part of their standard-of-care clinical evaluation were included in the study. DSS was defined as anterior-posterior (AP) or medial-lateral (ML) spread based upon sEEG evaluation by two independent specialists who demonstrated excellent inter-rater agreement (Cohen's kappa = .92). DTI connectometry was used to assess differences between seizure spread pattern groups along major fiber pathways regarding fractional anisotropy (FA). RESULTS: Twenty-four participants showed seizures with AP spread and nine participants showed seizures with ML spread. There were no significant differences between the groups on their demographic and clinical profile. Patients with ML seizures had higher FA along the corpus callosum and, to a lesser degree, some portions of the bilateral cingulate tracts. In contrast, patients with AP seizures had higher FA along several anterior-posterior white matter projections bundles, including the cingulate fasciculus and the inferior longitudinal, with significantly less involvement of the corpus callosum compared with ML seizures. SIGNIFICANCE: This study confirms the hypothesis that the anatomical pattern of electrophysiological ictal propagation is associated with the structural reinforcement of supporting pathways in temporal lobe epilepsy. This observation can help elucidate mechanisms of ictal propagation and may guide future translational approaches to curtail seizure spread.

Seizures in Patients With Metastatic Brain Tumors: Prevalence, Clinical Characteristics, and Features on EEG.

INTRODUCTION: Metastases to the brain (MB) occur in up to 30% of adults with cancer; of these, 15% to 35% may have seizures. We investigated clinical and pathologic associations with seizure and EEG findings in patients with MB, given the sparse literature in this area. METHODS: We performed a retrospective chart review of adults with pathologically confirmed MB treated at a large tertiary care center between April 8, 2006, and December 14, 2018. Primary outcomes were odds of "chart-documented seizure" (CDS) in the full sample and EEG-captured seizure or any epileptiform discharges among those monitored on EEG. RESULTS: We studied 187 patients with MB, of whom 55 (28.3%) were monitored on EEG. We found an overall CDS prevalence of 29.4% and an EEG-captured seizure of 18.9% among patients monitored on EEG. Of those monitored on EEG, 47.2% had epileptiform discharges. Adenocarcinoma pathology was associated with lower odds of CDS (odds ratio [OR] 0.50, 95% CI 0.26-0.96) and EEG-captured seizure (OR 0.09, 95% CI 0.01-0.87) versus other pathologies. When modeled separately, melanoma pathology was associated with CDS (OR 4.45, 95% CI 1.58-12.57) versus other pathologies. Hemorrhagic MB were associated with any epileptiform discharges (OR 5.50, 95% CI 1.65-18.37), regardless of pathology modeled. Increasing size of the largest dimension of the largest MB was associated with lower odds of CDS (OR 0.68, 95% CI 0.52-0.89 when adenocarcinoma modeled, OR 0.69, 95% CI 0.53-0.91 when melanoma modeled). CONCLUSIONS: Seizures and epileptiform discharges are common in patients with MB. Tumor size and pathology were significantly associated with CDS. Larger studies are needed for further analysis.

Clinical characteristics, EEG findings and implications of status epilepticus in patients with brain metastases.

PURPOSE: To evaluate the clinical implications of status epilepticus in patients with metastases to the brain as well as associated demographic, clinical, EEG and radiographic features. METHODS: Retrospective chart review of 19 patients with metastases to the brain who subsequently developed status epilepticus. RESULTS: Of the patients who developed status epilepticus only 36.8% had a prior history of seizures since diagnosis of brain metastases. Status epilepticus most commonly occurred in the setting of a new structural injury to the brain such as new metastases, increase in size of metastases or hemorrhage. 57.9% of patients had either refractory or super-refractory status epilepticus. Focal non-convulsive status epilepticus was the most common subtype occurring in 42.1% of patients. 31.6% of patients died within 30 days of the onset of status epilepticus. CONCLUSION: Status epilepticus eventually resolved with treatment in all patients with brain metastases; however, it is associated with poor outcomes as nearly one-third was deceased within 30-days of onset. Nevertheless, no patients died during status epilepticus. Thus, status epilepticus may be indicative of an overall poor clinical status among patients with brain metastases.

Elite controller CD8+ T cells exhibit comparable viral inhibition capacity, but better sustained effector properties compared to chronic progressors.

Mechanisms modulating HIV-specific CD8+ T cell-mediated viral inhibition are not well defined. To delineate features of effective control, we compared the ability of CD8+ T cells from HIV ECs and CPs to inhibit HIV ex vivo. ECs showed superior inhibition compared to HAART-treated or untreated CPs in a typical VIA in which CD8+ T cells are rested 3 d before use (P = 0.025). In contrast, comparable antiviral activity was observed in freshly thawed cells. Rested CD8+ T cells underwent apoptosis with preferential loss of HIV-specific cells. EC CD8+ T cells showed greater capacity to sustain polyfunctionality ex vivo compared with those of CPs, and incubation of CD8+ T cells with IL-15 augmented inhibition. These results indicate that superior ex vivo inhibition of viral replication by CD8+ T cells from ECs is associated with enhanced retention of functional qualities and that in vitro antiviral function is enhanced by IL-15.

Rate of colonization of health care workers by carbapenem-resistant Enterobacteriaceae in an endemic hospital: A prospective study.

The role of health care workers in transmission of carbapenem-resistant Enterobacteriaceae (CRE) has not been evaluated thoroughly. We sought to determine the rate of fecal carriage of CRE among health care workers in our hospital, which is endemic for CRE (prevalence of 19 out of 800 beds and incidence of 128 out of 49,325 hospital admissions). We found no carriers among the 177 health care workers that participated in the study, suggesting that transmission does not occur through personnel gastrointestinal carriage of the bacteria.