Role of comorbidities in epilepsy surgery outcomes of older adults.

We lack knowledge about prognostic factors of resective epilepsy surgery (RES) in older adults (≥60 years), especially the role of comorbidities, which are a major consideration in managing the care of people with epilepsy (PWE). We analyzed a single-center cohort of 94 older adults (median age = 63.5 years, 52% females) who underwent RES between 2000 and 2021 with at least 6 months of postsurgical follow-up. Three fourths of the study cohort had lesional magnetic resonance imaging and underwent temporal lobectomy. Fifty-four (57%) PWE remained seizure-free during a median follow-up of 3.5 years. Cox proportional hazard multivariable analysis showed that aura (hazard ratio [HR] = .52, 95% confidence interval [CI] = .27-1.00), single ictal electroencephalographic pattern (HR = .33, 95% CI = .17-.660), and Elixhauser Comorbidity Index (HR = 1.05, 95% CI = 1.00-1.10) were independently associated with seizure recurrence at last follow-up. A sensitivity analysis using the Charlson Combined Score (HR = 1.38, 95% CI = 1.03-1.84, p = .027) confirmed the association of comorbidities with worse seizure outcome. Our findings provide a framework for a better informed discussion about RES prognosis in older adults. More extensive, multicenter cohort studies are needed to validate our findings and reduce hesitancy in pursuing RES in suitable older adults.

Exit Strategy: Balancing the Risks and Rewards of Antiseizure Medication Withdrawal.

The majority of people with epilepsy achieves long-term seizure-freedom and may consider withdrawal of their anti-seizure medications (ASMs). Withdrawal of ASMs can yield substantial benefits but may be associated with potential risks. This review critically examines the existing literature on ASM withdrawal, emphasizing evidence-based recommendations, where available. Our focus encompasses deprescribing strategies for individuals who have attained seizure freedom through medical treatment, those who have undergone successful epilepsy surgery, and individuals initiated on ASMs following acute symptomatic seizures. We explore state-of-the-art prognostic models in these scenarios that could guide the decision-making process. The review underscores the importance of a collaborative shared-decision approach between patients, caregivers, and physicians. We describe the subjective and objective factors influencing these decisions and illustrate how trade-offs may be effectively managed in practice.

Predictive models of epilepsy outcomes.

PURPOSE OF REVIEW: Multiple complex medical decisions are necessary in the course of a chronic disease like epilepsy. Predictive tools to assist physicians and patients in navigating this complexity have emerged as a necessity and are summarized in this review. RECENT FINDINGS: Nomograms and online risk calculators are user-friendly and offer individualized predictions for outcomes ranging from safety of antiseizure medication withdrawal (accuracy 65-73%) to seizure-freedom, naming, mood, and language outcomes of resective epilepsy surgery (accuracy 72-81%). Improving their predictive performance is limited by the nomograms' inability to ingest complex data inputs. Conversely, machine learning offers the potential of multimodal and expansive model inputs achieving human-expert level accuracy in automated scalp electroencephalogram (EEG) interpretation but lagging in predictive performance or requiring validation for other applications. SUMMARY: Good to excellent predictive models are now available to guide medical and surgical epilepsy decision-making with nomograms offering individualized predictions and user-friendly tools, and machine learning approaches offering the potential of improved performance. Future research is necessary to bridge the two approaches for optimal translation to clinical care.

Prediction tools and risk stratification in epilepsy surgery.

OBJECTIVE: This study was undertaken to conduct external validation of previously published epilepsy surgery prediction tools using a large independent multicenter dataset and to assess whether these tools can stratify patients for being operated on and for becoming free of disabling seizures (International League Against Epilepsy stage 1 and 2). METHODS: We analyzed a dataset of 1562 patients, not used for tool development. We applied two scales: Epilepsy Surgery Grading Scale (ESGS) and Seizure Freedom Score (SFS); and two versions of Epilepsy Surgery Nomogram (ESN): the original version and the modified version, which included electroencephalographic data. For the ESNs, we used calibration curves and concordance indexes. We stratified the patients into three tiers for assessing the chances of attaining freedom from disabling seizures after surgery: high (ESGS = 1, SFS = 3-4, ESNs > 70%), moderate (ESGS = 2, SFS = 2, ESNs = 40%-70%), and low (ESGS = 2, SFS = 0-1, ESNs < 40%). We compared the three tiers as stratified by these tools, concerning the proportion of patients who were operated on, and for the proportion of patients who became free of disabling seizures. RESULTS: The concordance indexes for the various versions of the nomograms were between .56 and .69. Both scales (ESGS, SFS) and nomograms accurately stratified the patients for becoming free of disabling seizures, with significant differences among the three tiers (p < .05). In addition, ESGS and the modified ESN accurately stratified the patients for having been offered surgery, with significant difference among the three tiers (p < .05). SIGNIFICANCE: ESGS and the modified ESN (at thresholds of 40% and 70%) stratify patients undergoing presurgical evaluation into three tiers, with high, moderate, and low chance for favorable outcome, with significant differences between the groups concerning having surgery and becoming free of disabling seizures. Stratifying patients for epilepsy surgery has the potential to help select the optimal candidates in underprivileged areas and better allocate resources in developed countries.

Fully automatic segmentation of brain lacunas resulting from resective surgery using a 3D deep learning model.

The rapid and constant development of deep learning (DL) strategies is pushing forward the quality of object segmentation in images from diverse fields of interest. In particular, these algorithms can be very helpful in delineating brain abnormalities (lesions, tumors, lacunas, etc), enabling the extraction of information such as volume and location, that can inform doctors or feed predictive models. In this study, we describe ResectVol DL, a fully automatic tool developed to segment resective lacunas in brain images of patients with epilepsy. ResectVol DL relies on the nnU-Net framework that leverages the 3D U-Net deep learning architecture. T1-weighted MRI datasets from 120 patients (57 women; 31.5 ± 15.9 years old at surgery) were used to train (n=78) and test (n=48) our tool. Manual segmentations were carried out by five different raters and were considered as ground truth for performance assessment. We compared ResectVol DL with two other fully automatic methods: ResectVol 1.1.2 and DeepResection, using the Dice similarity coefficient (DSC), Pearson's correlation coefficient, and relative difference to manual segmentation. ResectVol DL presented the highest median DSC (0.92 vs. 0.78 and 0.90), the highest correlation coefficient (0.99 vs. 0.63 and 0.94) and the lowest median relative difference (9 vs. 44 and 12 %). Overall, we demonstrate that ResectVol DL accurately segments brain lacunas, which has the potential to assist in the development of predictive models for postoperative cognitive and seizure outcomes.

Molecular subtypes of epilepsy associated with post-surgical seizure recurrence.

Approximately 50% of individuals who undergo resective epilepsy surgery experience seizure recurrence. The heterogenous post-operative outcomes are not fully explained by clinical, imaging and electrophysiological variables. We hypothesized that molecular features may be useful in understanding surgical response, and that individuals with epilepsy can be classified into molecular subtypes that are associated with seizure freedom or recurrence after surgical resection. Pre-operative blood samples, brain tissue and post-operative seizure outcomes were collected from a cohort of 40 individuals with temporal lobe epilepsy, 23 of whom experienced post-operative seizure recurrence. Messenger RNA and microRNA extracted from the blood and tissue samples were sequenced. The messenger RNA and microRNA expression levels from the blood and brain were each subjected to a novel clustering approach combined with multiple logistic regression to separate individuals into genetic clusters that identify novel subtypes associated with post-operative seizure outcomes. We then compared the microRNAs and messenger RNAs from patient blood and brain tissue that were significantly associated with each subtype to identify signatures that are similarly over- or under-represented for an outcome and more likely to represent endophenotypes with common molecular aetiology. These target microRNAs and messenger RNAs were further characterized by pathway analysis to assess their functional role in epilepsy. Using blood-derived microRNA and messenger RNA expression levels, we identified two subtypes of epilepsy that were significantly associated with seizure recurrence (clusters A1 and B4) (adjusted P < 0.20). A total of 551 microRNAs and 2486 messenger RNAs were associated with clusters A1 and B4, respectively (adjusted P < 0.05). Clustering of brain-tissue messenger RNA expression levels revealed an additional subtype (C2) associated with seizure recurrence that had high overlap of dysregulated messenger RNA transcripts with cluster B4. Clusters A1, B4 and C2 also shared significant overlap of subjects, which altogether suggests a coordinated mechanism by which microRNA and messenger RNA transcripts may be related to seizure recurrence. Epileptic subtypes A1, B4 and C2 reveal both known and novel microRNA and messenger RNA targets in seizure recurrence. Furthermore, targets identified in A1 and B4 are quantifiable in pre-operative blood samples and could potentially serve as biomarkers for surgical resection outcomes.

Determinants of epileptogenic zone identification and seizure outcome in children with refractory epilepsy undergoing stereoelectroencephalography.

OBJECTIVE: The objective of this paper was to investigate the factors associated with successful epileptogenic zone (EZ) identification and postsurgical seizure freedom in pediatric patients with drug-resistant epilepsy who underwent first-time stereoelectroencephalography (SEEG). METHODS: The authors conducted a retrospective cohort study of all consecutive patients younger than 18 years of age at the time of recommendation for invasive evaluation with SEEG who were treated from July 2009 to June 2020. The authors excluded patients who had undergone failed prior resective epilepsy surgery or prior intracranial electrode evaluation for seizure localization. For their primary outcome, the authors evaluated the relationship between clinical and radiographic factors and successful identification of a putative EZ. For their secondary outcome, the authors investigated whether these factors had a significant relationship with seizure freedom (according to the Engel classification) at last follow-up. RESULTS: The authors included 101 patients in this study. SEEG was safe, with no major morbidity or mortality experienced. The population was complex, with an MRI lesion present in less than 40% of patients and patients as young as 2.9 years included. A proposed EZ was identified in 88 (87%) patients. Patients with an older onset of epilepsy (OR 1.20/year, p = 0.04) or epilepsy etiology suspected to be due to a developmental lesion (OR 8.38, p = 0.02) were more likely to have proposed EZ identification. Patients with a preimplantation bilateral seizure-onset hypothesis (OR 0.29, p = 0.047) and those who underwent longer periods of monitoring (OR 0.86/day, p = 0.006) were somewhat less likely to have proposed EZ identification. The presence of an MRI lesion was a positive factor on secondary analyses (OR 4.18, p = 0.049; 1-tailed test). Fifty percent of patients who underwent surgical treatment with resection or laser ablation achieved Engel class I outcomes, in contrast to 0% of patients who underwent neuromodulation. Patients with a preimplantation hypothesis in the frontal/parietal lobes had increased odds of seizure freedom compared with patients with a hypothesis in other locations (OR 3.64, p = 0.01). CONCLUSIONS: Pediatric SEEG is safe and often identifies a proposed resectable EZ. These results suggest that SEEG is effective in patients with frontal/parietal preimplantation hypothesis, with or without identified lesions on MRI.

Machine Learning for Precision Epilepsy Surgery.

Brain surgery offers the best chance of seizure-freedom for patients with focal drug-resistant epilepsy, but only 50% achieve sustained seizure-freedom. With the explosion of data collected during routine presurgical evaluations and recent advances in computational science, we now have a tremendous potential to achieve precision epilepsy surgery: a data-driven tailoring of surgical planning. This review highlights the clinical need, the relevant computational science focusing on machine learning, and discusses some specific applications in epilepsy surgery.

Beyond seizure freedom: Dissecting long-term seizure control after surgical resection for drug-resistant epilepsy.

OBJECTIVE: This study was undertaken to better understand the long-term palliative and disease-modifying effects of surgical resection beyond seizure freedom, including frequency reduction and both late recurrence and remission, in patients with drug-resistant epilepsy. METHODS: This retrospective database-driven cohort study included all patients with >9 years of follow-up at a single high-volume epilepsy center. We included patients who underwent lobectomy, multilobar resection, or lesionectomies for drug-resistant epilepsy; we excluded patients who underwent hemispherectomies. Our main outcomes were (1) reduction in frequency of disabling seizures (at 6 months, each year up to 9 years postoperatively, and at last follow-up), (2) achievement of seizure remission (>6 months, >1 year, and longest duration), and (3) seizure freedom at last follow-up. RESULTS: We included 251 patients; 234 (93.2%) achieved 6 months and 232 (92.4%) experienced 1 year of seizure freedom. Of these, the average period of seizure freedom was 10.3 years. A total of 182 (72.5%) patients were seizure-free at last follow-up (defined as >1 year without seizures), with a median 11.9 years since remission. For patients not completely seizure-free, the mean seizure frequency reduction at each time point was 76.2%, and ranged from 66.6% to 85.0%. Patients decreased their number of antiseizure medications on average by .58, and 53 (21.2%) patients were on no antiseizure medication at last follow-up. Nearly half (47.1%) of those seizure-free at last follow-up were not seizure-free immediately postoperatively. SIGNIFICANCE: Patients who continue to have seizures after resection often have considerable reductions in seizure frequency, and many are able to achieve seizure freedom in a delayed manner.

Predictive models for starting antiseizure medication withdrawal following epilepsy surgery in adults.

More than half of adults with epilepsy undergoing resective epilepsy surgery achieve long-term seizure freedom and might consider withdrawing antiseizure medications. We aimed to identify predictors of seizure recurrence after starting postoperative antiseizure medication withdrawal and develop and validate predictive models. We performed an international multicentre observational cohort study in nine tertiary epilepsy referral centres. We included 850 adults who started antiseizure medication withdrawal following resective epilepsy surgery and were free of seizures other than focal non-motor aware seizures before starting antiseizure medication withdrawal. We developed a model predicting recurrent seizures, other than focal non-motor aware seizures, using Cox proportional hazards regression in a derivation cohort (n = 231). Independent predictors of seizure recurrence, other than focal non-motor aware seizures, following the start of antiseizure medication withdrawal were focal non-motor aware seizures after surgery and before withdrawal [adjusted hazard ratio (aHR) 5.5, 95% confidence interval (CI) 2.7-11.1], history of focal to bilateral tonic-clonic seizures before surgery (aHR 1.6, 95% CI 0.9-2.8), time from surgery to the start of antiseizure medication withdrawal (aHR 0.9, 95% CI 0.8-0.9) and number of antiseizure medications at time of surgery (aHR 1.2, 95% CI 0.9-1.6). Model discrimination showed a concordance statistic of 0.67 (95% CI 0.63-0.71) in the external validation cohorts (n = 500). A secondary model predicting recurrence of any seizures (including focal non-motor aware seizures) was developed and validated in a subgroup that did not have focal non-motor aware seizures before withdrawal (n = 639), showing a concordance statistic of 0.68 (95% CI 0.64-0.72). Calibration plots indicated high agreement of predicted and observed outcomes for both models. We show that simple algorithms, available as graphical nomograms and online tools (predictepilepsy.github.io), can provide probabilities of seizure outcomes after starting postoperative antiseizure medication withdrawal. These multicentre-validated models may assist clinicians when discussing antiseizure medication withdrawal after surgery with their patients.

Epilepsy Surgery Outcome of Traumatic Intradiploic Meningoencephalocele: A Case Report and Literature Review.

We highlight an under-recognized epileptic pathology in a 56-year-old left-handed female with progressive right facial numbness and weekly focal seizures characterized by episodic aphasia. She was found to have a left frontoparietal intradiploic meningoencephalocele (IDME). Her only epilepsy risk factor was minor head trauma 10 years prior to presentation. She underwent craniotomy for encephalocele resection and mesh cranioplasty without residual neurological deficits and excellent seizure outcome: at 3-year follow-up, she was still seizure-free since surgery, except for an isolated breakthrough seizure at 7 postoperative months when she discontinued her preoperative regimen of Lacosamide monotherapy. Traumatic IDME is a rare condition and rarely presents with seizures. Symptoms may arise up to decades following minor head trauma and are progressive in nature. The likely definitive treatment is cranioplasty and dural repair with or without resecting the protruding parenchyma.

Genetic and molecular features of seizure-freedom following surgical resections for focal epilepsy: A pilot study.

Objective: Seizure outcomes after brain surgery for drug-resistant epilepsy (DRE) are very heterogeneous and difficult to predict with models utilizing the current clinical, imaging, and electrophysiological variables. In this pilot study, we investigated whether genetic and molecular biomarkers (e.g., genomic, transcriptomic) can provide additional insight into differential response to surgery. Methods: Post-operative seizure-outcomes were collected at last follow-up (>6 months) for 201 adult patients with DRE who underwent surgery between 2004 and 2020. Resected tissue was sent for miRNA sequencing (n = 132) and mRNA sequencing (n = 135). Following the selection of 10 genes (SCN1A, NBEA, PTEN, GABRA1, LGL1, DEPDC5, IL1A, ABCB1, C3, CALHM1), we investigated SNPs in those 10 genes from previously acquired exome sequencing data (n = 106). Logistic regression was performed to test for associations between individual features (mRNAs, miRNAs, and SNPs) and post-operative seizure-outcome with an exploratory FDR P < 0.25 as the threshold for significance. Post-operative time-to-seizure analyses were performed for each SNP using a Cox proportional hazards model. Results: The majority of patients (83%) had temporal lobe epilepsy. Mean age at surgery was 38.3 years, and 56% were female. Three SNPs (rs10276036, rs11975994, rs1128503) in multi-drug resistance gene, ABCB1, were associated with post-operative seizure outcomes. Patients with alternate alleles in ABCB1 were more likely to be seizure-free at last follow-up (52-56% reduction in seizure recurrence; FDR P = 0.24). All three SNPs were in linkage disequilibrium and highly correlated with each other. Median post-operative time-to-seizure was 63 months for patients with 2 alternate alleles, 24-33 months with 1 alternate allele, and 10-11 months with 0 alternate alleles. These SNPs improved outcome prediction beyond MRI and sex alone. No independent miRNAs or mRNAs were significantly associated with seizure-outcome (P > 0.05). However, pathway analysis identified "cancer drug resistance by drug efflux" (mir-154 and mir-379) as enriched (P = 0.02), supporting the role of drug response genes in post-operative seizure recurrence. Significance: ABCB1 may have a role in epileptogenesis and surgery outcomes independent of its drug efflux activity necessitating further investigation. SNPs in ABCB1 may serve as independent predictors of post-operative outcome.

Does Stereoelectroencephalography Add Value in Patients with Lesional Epilepsy?

OBJECTIVE: Stereoelectroencephalography (SEEG) has gained popularity as an invasive monitoring modality for epileptogenic zone (EZ) localization. The need and indications for SEEG in patients with evident brain lesions or associated abnormalities on imaging is debated. We report our experience with SEEG as a presurgical evaluation tool for patients with lesional epilepsy. METHODS: A retrospective cohort study was performed of 131 patients with lesional or magnetic resonance imaging abnormality-associated medically refractory focal epilepsy who underwent resections from 2010 to 2017. Seventy-one patients had SEEG followed by resection, and 60 had no invasive recordings. Volumetric analysis of resection cavities from 3T magnetic resonance imaging was performed. RESULTS: Mean lesion and resection volumes for SEEG and non-SEEG were 16.2 (standard deviation [SD] = 29) versus 23.7 cm3 (SD = 38.4) and 28.1 (SD = 23.2) versus 43.6 cm3 (SD = 43.5), respectively (P = 0.009). Comparing patients with seizure recurrence and patients who remained seizure free, significantly associated variables with seizure recurrence included mean number of failed antiseizure medications (6.86 [SD = 0.32] vs. 5.75 [SD = 0.32]; P = 0.01) and in SEEG patients the mean number of electrodes implanted (8.1 [SD = 0.8] vs. 5.0 [SD = 0.8]; P = 0.005). After multivariate analysis, only failed numbers of medication remained significantly associated with seizure recurrence. CONCLUSIONS: Seizure outcomes did not correlate with final resection volume after SEEG evaluation. SEEG evaluation presurgically can be used to maintain the efficacy of resection and decrease the volume and subsequent risk of extensive tissue removal. We believe that this technology allows resective surgery to proceed in a subpopulation of patients with lesional epilepsy who may otherwise not have been considered surgical candidates.

Timing of referral to evaluate for epilepsy surgery: Expert Consensus Recommendations from the Surgical Therapies Commission of the International League Against Epilepsy.

Epilepsy surgery is the treatment of choice for patients with drug-resistant seizures. A timely evaluation for surgical candidacy can be life-saving for patients who are identified as appropriate surgical candidates, and may also enhance the care of nonsurgical candidates through improvement in diagnosis, optimization of therapy, and treatment of comorbidities. Yet, referral for surgical evaluations is often delayed while palliative options are pursued, with significant adverse consequences due to increased morbidity and mortality associated with intractable epilepsy. The Surgical Therapies Commission of the International League Against Epilepsy (ILAE) sought to address these clinical gaps and clarify when to initiate a surgical evaluation. We conducted a Delphi consensus process with 61 epileptologists, epilepsy neurosurgeons, neurologists, neuropsychiatrists, and neuropsychologists with a median of 22 years in practice, from 28 countries in all six ILAE world regions. After three rounds of Delphi surveys, evaluating 51 unique scenarios, we reached the following Expert Consensus Recommendations: (1) Referral for a surgical evaluation should be offered to every patient with drug-resistant epilepsy (up to 70 years of age), as soon as drug resistance is ascertained, regardless of epilepsy duration, sex, socioeconomic status, seizure type, epilepsy type (including epileptic encephalopathies), localization, and comorbidities (including severe psychiatric comorbidity like psychogenic nonepileptic seizures [PNES] or substance abuse) if patients are cooperative with management; (2) A surgical referral should be considered for older patients with drug-resistant epilepsy who have no surgical contraindication, and for patients (adults and children) who are seizure-free on 1-2 antiseizure medications (ASMs) but have a brain lesion in noneloquent cortex; and (3) referral for surgery should not be offered to patients with active substance abuse who are noncooperative with management. We present the Delphi consensus results leading up to these Expert Consensus Recommendations and discuss the data supporting our conclusions. High level evidence will be required to permit creation of clinical practice guidelines.

Seizure Outcomes and Reoperation in Surgical Rasmussen Encephalitis Patients.

BACKGROUND: Rasmussen encephalitis (RE) is a rare inflammatory disease affecting one hemisphere, causing progressive neurological deficits and intractable seizures. OBJECTIVE: To report long-term seizure outcomes, reoperations, and functional outcomes in patients with RE who underwent hemispherectomy at our institution. METHODS: Retrospective review was performed for all patients with RE who had surgery between 1998 and 2020. We collected seizure history, postoperative outcomes, and functional data. Imaging was independently reviewed in a blinded fashion by 2 neurosurgeons and a neuroradiologist. RESULTS: We analyzed 30 patients with RE who underwent 35 hemispherectomies (5 reoperations). Using Kaplan-Meier analysis, seizure-freedom rate was 81.5%, 63.6%, and 55.6% at 1, 5, and 10 years after surgery, respectively. Patients with shorter duration of hemiparesis preoperatively were less likely to be seizure-free at follow-up (P = .011) and more likely to undergo reoperation (P = .004). Shorter duration of epilepsy (P = .026) and preoperative bilateral MRI abnormalities (P = .011) were associated with increased risk of reoperation. Complete disconnection of diseased hemisphere on postoperative MRI after the first operation improved seizure-freedom (P = .021) and resulted in fewer reoperations (P = .034), and reoperation resulted in seizure freedom in every case. CONCLUSION: Obtaining complete disconnection is critical for favorable seizure outcomes from hemispherectomy, and neurosurgeons should have a low threshold to reoperate in patients with RE with recurrent seizures. Rapid progression of motor deficits and bilateral MRI abnormalities may indicate a subpopulation of patients with RE with increased risk of needing reoperation. Overall, we believe that hemispherectomy is a curative surgery for the majority of patients with RE, with excellent long-term seizure outcome.

Quantitative analysis of visually reviewed normal scalp EEG predicts seizure freedom following anterior temporal lobectomy.

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.

The Clinical Utility of Surgical Histopathology in Predicting Seizure Outcomes in Patients with Rasmussen Encephalitis Undergoing Hemispherectomy.

OBJECTIVE: The objectives of this study were to determine the relationship between the severity of pathology and seizure outcomes in patients who underwent hemispherectomy for Rasmussen encephalitis (RE) and to investigate which clinical factors correlated with severity of pathology. METHODS: In this retrospective cohort study, we collected and reviewed pathology and clinical variables. We ascertained seizure outcomes using Engel's classification, and Pardo stages were used to grade pathology. RESULTS: We included 29 unique patients who underwent 34 hemispherectomy procedures for analysis. There was no statistically significant correlation between Pardo stage and seizure outcome (P = 1). Increasing duration of epilepsy (ß = 0.011, P = 0.02) and duration of hemiparesis (ß = 0.024, P = 0.01) were significantly associated with a more severe Pardo stage. In contrast, the presence of epilepsia partialis continua had a negative relationship with Pardo stage (ß = -0.49, P = 0.04). Twenty-six (89.75%) patients were Engel class I at the last follow-up, including all 5 patients who underwent redo hemispherectomy in our cohort. CONCLUSIONS: Consistent with the progressive nature of RE, more severe pathology was associated with a longer duration of epilepsy and longer duration of hemiparesis, while the presence of epilepsia partialis continua was associated with less severe pathology. Results from this series suggest the degree of cortical involvement with RE as assessed on surgical histopathology does not correlate with seizure outcome after hemispherectomy, which appears to be more dependent on surgical technique/complete disconnection.

Incidence and prevalence of major epilepsy-associated brain lesions.

Epilepsy surgery is an effective treatment option for drug-resistant focal epilepsy patients with associated structural brain lesions. However, little epidemiological data are available regarding the number of patients with these lesions. We reviewed data regarding (1) the prevalence and incidence of epilepsy; (2) the proportion of epilepsy patients with focal epilepsy, drug-resistant epilepsy, and drug-resistant focal epilepsies; and (3) the number of epilepsy presurgical evaluations and surgical resections. We also assessed the relative proportion of brain lesions using post-surgical histopathological findings from 541 surgical patients from the Cleveland Clinic and 9,523 patients from a European multi-center cohort. Data were combined to generate surgical candidate incidence and prevalence estimates and the first lesion-specific estimates for hippocampal sclerosis (HS), low-grade epilepsy-associated brain tumors (LEAT), malformations of cortical development (MCD), glial scars, vascular malformations, and encephalitis. The most frequently diagnosed brain lesions were HS (incidence = 2.32 ± 0.26 in 100,000, prevalence = 19.40 ± 2.16 in 100,000) for adults and MCD (incidence = 1.15 ± 0.34 in 100,000, prevalence = 6.52 ± 1.89 in 100,000) for children. Our estimates can guide patient advocacy groups, clinicians, researchers, policymakers in education, development of health care strategy, resource allocation, and reimbursement schedules.

Neuromodulation for Refractory Epilepsy.

Three neuromodulation therapies, all using implanted device and electrodes, have been approved to treat adults with drug-resistant focal epilepsy, namely, the vagus nerve stimulation in 1995, deep brain stimulation of the anterior nucleus of the thalamus (ANT-DBS) in 2018 (2010 in Europe), and responsive neurostimulation (RNS) in 2014. Indications for VNS have more recently extended to children down to age of 4. Limited or anecdotal data are available in other epilepsy syndromes and refractory/super-refractory status epilepticus. Overall, neuromodulation therapies are palliative, with only a minority of patients achieving long-term seizure freedom, justifying favoring such treatments in patients who are not good candidates for curative epilepsy surgery. About half of patients implanted with VNS, ANT-DBS, and RNS have 50% or greater reduction in seizures, with long-term data suggesting increased efficacy over time. Besides their impact on seizure frequency, neuromodulation therapies are associated with various benefits and drawbacks in comparison to antiseizure drugs. Yet, we lack high-level evidence to best position each neuromodulation therapy in the treatment pathways of persons with difficult-to-treat epilepsy.

Aging-related cell type-specific pathophysiologic immune responses that exacerbate disease severity in aged COVID-19 patients.

Coronavirus disease 2019 (COVID-19) is especially severe in aged patients, defined as 65 years or older, for reasons that are currently unknown. To investigate the underlying basis for this vulnerability, we performed multimodal data analyses on immunity, inflammation, and COVID-19 incidence and severity as a function of age. Our analysis leveraged age-specific COVID-19 mortality and laboratory testing from a large COVID-19 registry, along with epidemiological data of ~3.4 million individuals, large-scale deep immune cell profiling data, and single-cell RNA-sequencing data from aged COVID-19 patients across diverse populations. We found that decreased lymphocyte count and elevated inflammatory markers (C-reactive protein, D-dimer, and neutrophil-lymphocyte ratio) are significantly associated with age-specific COVID-19 severities. We identified the reduced abundance of naïve CD8 T cells with decreased expression of antiviral defense genes (i.e., IFITM3 and TRIM22) in aged severe COVID-19 patients. Older individuals with severe COVID-19 displayed type I and II interferon deficiencies, which is correlated with SARS-CoV-2 viral load. Elevated expression of SARS-CoV-2 entry factors and reduced expression of antiviral defense genes (LY6E and IFNAR1) in the secretory cells are associated with critical COVID-19 in aged individuals. Mechanistically, we identified strong TGF-beta-mediated immune-epithelial cell interactions (i.e., secretory-non-resident macrophages) in aged individuals with critical COVID-19. Taken together, our findings point to immuno-inflammatory factors that could be targeted therapeutically to reduce morbidity and mortality in aged COVID-19 patients.