Search

Objective. This study aims to develop and validate an end-to-end software platform, PyHFO, that streamlines the application of deep learning (DL) methodologies in detecting neurophysiological biomarkers for epileptogenic zones from EEG recordings.Approach. We introduced PyHFO, which enables time-efficient high-frequency oscillation (HFO) detection algorithms like short-term energy and Montreal Neurological Institute and Hospital detectors. It incorporates DL models for artifact and HFO with spike classification, designed to operate efficiently on standard computer hardware.Main results. The validation of PyHFO was conducted on three separate datasets: the first comprised solely of grid/strip electrodes, the second a combination of grid/strip and depth electrodes, and the third derived from rodent studies, which sampled the neocortex and hippocampus using depth electrodes. PyHFO demonstrated an ability to handle datasets efficiently, with optimization techniques enabling it to achieve speeds up to 50 times faster than traditional HFO detection applications. Users have the flexibility to employ our pre-trained DL model or use their EEG data for custom model training.Significance. PyHFO successfully bridges the computational challenge faced in applying DL techniques to EEG data analysis in epilepsy studies, presenting a feasible solution for both clinical and research settings. By offering a user-friendly and computationally efficient platform, PyHFO paves the way for broader adoption of advanced EEG data analysis tools in clinical practice and fosters potential for large-scale research collaborations.

OBJECTIVE: Identification of EEG waveforms is critical for diagnosing Lennox-Gastaut Syndrome (LGS) but is complicated by the progressive nature of the disease. Here, we assess the interrater reliability (IRR) among pediatric epileptologists for classifying EEG waveforms associated with LGS. METHODS: A novel automated algorithm was used to objectively identify epochs of EEG with transient high power, which were termed events of interest (EOIs). The algorithm was applied to EEG from 20 LGS subjects and 20 healthy controls during NREM sleep, and 1350 EOIs were identified. Three raters independently reviewed the EOIs within isolated 15-second EEG segments in a randomized, blinded fashion. For each EOI, the raters assigned a waveform label (spike and slow wave, generalized paroxysmal fast activity, seizure, spindle, vertex, muscle, artifact, nothing, or other) and indicated the perceived subject type (LGS or control). RESULTS: Labeling of subject type had 85% accuracy across all EOIs and an IRR of κ =0.790, suggesting that brief segments of EEG containing high-power waveforms can be reliably classified as pathological or normal. Waveform labels were less consistent, with κ =0.558, and the results were highly variable for different categories of waveforms. Label mismatches typically occurred when one reviewer selected nothing, suggesting that reviewers had different thresholds for applying named labels. SIGNIFICANCE: Classification of EEG waveforms associated with LGS has weak IRR, due in part to varying thresholds applied during visual review. Computational methods to objectively define EEG biomarkers of LGS may improve IRR and aid clinical decision-making.

OBJECTIVE: This study aimed to explore sensitive detection methods for pathological high-frequency oscillations (HFOs) to improve seizure outcomes in epilepsy surgery. METHODS: We analyzed interictal HFOs (80-500 Hz) in 15 children with medication-resistant focal epilepsy who underwent chronic intracranial electroencephalogram via subdural grids. The HFOs were assessed using the short-term energy (STE) and Montreal Neurological Institute (MNI) detectors and examined for spike association and time-frequency plot characteristics. A deep learning (DL)-based classification was applied to purify pathological HFOs. Postoperative seizure outcomes were correlated with HFO-resection ratios to determine the optimal HFO detection method. RESULTS: The MNI detector identified a higher percentage of pathological HFOs than the STE detector, but some pathological HFOs were detected only by the STE detector. HFOs detected by both detectors had the highest spike association rate. The Union detector, which detects HFOs identified by either the MNI or STE detector, outperformed other detectors in predicting postoperative seizure outcomes using HFO-resection ratios before and after DL-based purification. CONCLUSIONS: HFOs detected by standard automated detectors displayed different signal and morphological characteristics. DL-based classification effectively purified pathological HFOs. SIGNIFICANCE: Enhancing the detection and classification methods of HFOs will improve their utility in predicting postoperative seizure outcomes.

Objective.Intracranially-recorded interictal high-frequency oscillations (HFOs) have been proposed as a promising spatial biomarker of the epileptogenic zone. However, HFOs can also be recorded in the healthy brain regions, which complicates the interpretation of HFOs. The present study aimed to characterize salient features of physiological HFOs using deep learning (DL).Approach.We studied children with neocortical epilepsy who underwent intracranial strip/grid evaluation. Time-series EEG data were transformed into DL training inputs. The eloquent cortex (EC) was defined by functional cortical mapping and used as a DL label. Morphological characteristics of HFOs obtained from EC (ecHFOs) were distilled and interpreted through a novel weakly supervised DL model.Main results.A total of 63 379 interictal intracranially-recorded HFOs from 18 children were analyzed. The ecHFOs had lower amplitude throughout the 80-500 Hz frequency band around the HFO onset and also had a lower signal amplitude in the low frequency band throughout a one-second time window than non-ecHFOs, resembling a bell-shaped template in the time-frequency map. A minority of ecHFOs were HFOs with spikes (22.9%). Such morphological characteristics were confirmed to influence DL model prediction via perturbation analyses. Using the resection ratio (removed HFOs/detected HFOs) of non-ecHFOs, the prediction of postoperative seizure outcomes improved compared to using uncorrected HFOs (area under the ROC curve of 0.82, increased from 0.76).Significance.We characterized salient features of physiological HFOs using a DL algorithm. Our results suggested that this DL-based HFO classification, once trained, might help separate physiological from pathological HFOs, and efficiently guide surgical resection using HFOs.

Background and objectivesStandard therapies (adrenocorticotropic hormone [ACTH], oral steroids, or vigabatrin) fail to control infantile spasms in almost half of children. Early identification of nonresponders could enable rapid initiation of sequential therapy. We aimed to determine the time to clinical remission after appropriate infantile spasms treatment initiation and identify predictors of the time to infantile spasms treatment response.MethodsThe National Infantile Spasms Consortium prospectively followed children aged 2-24 months with new-onset infantile spasms at 23 US centers (2012-2018). We included children treated with standard therapy (ACTH, oral steroids, or vigabatrin). Sustained treatment response was defined as having the last clinically recognized infantile spasms on or before treatment day 14, absence of hypsarrhythmia on EEG 2-4 weeks after treatment, and persistence of remission to day 30. We analyzed the time to treatment response and assessed clinical characteristics to predict sustained treatment response.ResultsAmong 395 infants, clinical infantile spasms remission occurred in 43% (n = 171) within the first 2 weeks of treatment, of which 81% (138/171) responded within the first week of treatment. There was no difference in the median time to response across standard therapies (ACTH: median 4 days, interquartile range [IQR] 3-7; oral steroids: median 3 days, IQR 2-5; vigabatrin: median 3 days, IQR 1-6). Individuals without hypsarrhythmia on the pretreatment EEG (i.e., abnormal but not hypsarrhythmia) were more likely to have early treatment response than infants with hypsarrhythmia at infantile spasms onset (hazard ratio 2.23, 95% CI 1.39-3.57). No other clinical factors predicted early responders to therapy.DiscussionRemission after first infantile spasms treatment can be identified by treatment day 7 in most children. Given the importance of early and effective treatment, these data suggest that children who do not respond to standard infantile spasms therapy within 1 week should be reassessed immediately for additional standard treatment. This approach could optimize outcomes by facilitating early sequential therapy for children with infantile spasms.

OBJECTIVE: The aim of this study was to determine whether selection of treatment for children with infantile spasms (IS) varies by race/ethnicity. METHODS: The prospective US National Infantile Spasms Consortium database includes children with IS treated from 2012 to 2018. We examined the relationship between race/ethnicity and receipt of standard IS therapy (prednisolone, adrenocorticotropic hormone, vigabatrin), adjusting for demographic and clinical variables using logistic regression. Our primary outcome was treatment course, which considered therapy prescribed for the first and, when needed, the second IS treatment together. RESULTS: Of 555 children, 324 (58%) were non-Hispanic white, 55 (10%) non-Hispanic Black, 24 (4%) non-Hispanic Asian, 80 (14%) Hispanic, and 72 (13%) other/unknown. Most (398, 72%) received a standard treatment course. Insurance type, geographic location, history of prematurity, prior seizures, developmental delay or regression, abnormal head circumference, hypsarrhythmia, and IS etiologies were associated with standard therapy. In adjusted models, non-Hispanic Black children had lower odds of receiving a standard treatment course compared with non-Hispanic white children (odds ratio [OR], 0.42; 95% confidence interval [CI], 0.20-0.89; p = 0.02). Adjusted models also showed that children with public (vs. private) insurance had lower odds of receiving standard therapy for treatment 1 (OR, 0.42; CI, 0.21-0.84; p = 0.01). INTERPRETATION: Non-Hispanic Black children were more often treated with non-standard IS therapies than non-Hispanic white children. Likewise, children with public (vs. private) insurance were less likely to receive standard therapies. Investigating drivers of inequities, and understanding the impact of racism on treatment decisions, are critical next steps to improve care for patients with IS. ANN NEUROL 2022;92:32-44.

Intracranially recorded interictal high-frequency oscillations have been proposed as a promising spatial biomarker of the epileptogenic zone. However, its visual verification is time-consuming and exhibits poor inter-rater reliability. Furthermore, no method is currently available to distinguish high-frequency oscillations generated from the epileptogenic zone (epileptogenic high-frequency oscillations) from those generated from other areas (non-epileptogenic high-frequency oscillations). To address these issues, we constructed a deep learning-based algorithm using chronic intracranial EEG data via subdural grids from 19 children with medication-resistant neocortical epilepsy to: (i) replicate human expert annotation of artefacts and high-frequency oscillations with or without spikes, and (ii) discover epileptogenic high-frequency oscillations by designing a novel weakly supervised model. The 'purification power' of deep learning is then used to automatically relabel the high-frequency oscillations to distill epileptogenic high-frequency oscillations. Using 12 958 annotated high-frequency oscillation events from 19 patients, the model achieved 96.3% accuracy on artefact detection (F1 score = 96.8%) and 86.5% accuracy on classifying high-frequency oscillations with or without spikes (F1 score = 80.8%) using patient-wise cross-validation. Based on the algorithm trained from 84 602 high-frequency oscillation events from nine patients who achieved seizure-freedom after resection, the majority of such discovered epileptogenic high-frequency oscillations were found to be ones with spikes (78.6%, P

During normal childhood development, functional brain networks evolve over time in parallel with changes in neuronal oscillations. Previous studies have demonstrated differences in network topology with age, particularly in neonates and in cohorts spanning from birth to early adulthood. Here, we evaluate the developmental changes in EEG functional connectivity with a specific focus on the first 2 years of life. Functional connectivity networks (FCNs) were calculated from the EEGs of 240 healthy infants aged 0-2 years during wakefulness and sleep using a cross-correlation-based measure and the weighted phase lag index. Topological features were assessed via network strength, global clustering coefficient, characteristic path length, and small world measures. We found that cross-correlation FCNs maintained a consistent small-world structure, and the connection strengths increased after the first 3 months of infancy. The strongest connections in these networks were consistently located in the frontal and occipital regions across age groups. In the delta and theta bands, weighted phase lag index networks decreased in strength after the first 3 months in both wakefulness and sleep, and a similar result was found in the alpha and beta bands during wakefulness. However, in the alpha band during sleep, FCNs exhibited a significant increase in strength with age, particularly in the 21-24 months age group. During this period, a majority of the strongest connections in the networks were located in frontocentral regions, and a qualitatively similar distribution was seen in the beta band during sleep for subjects older than 3 months. Graph theory analysis suggested a small world structure for weighted phase lag index networks, but to a lesser degree than those calculated using cross-correlation. In general, graph theory metrics showed little change over time, with no significant differences between age groups for the clustering coefficient (wakefulness and sleep), characteristics path length (sleep), and small world measure (sleep). These results suggest that infant FCNs evolve during the first 2 years with more significant changes to network strength than features of the network structure. This study quantifies normal brain networks during infant development and can serve as a baseline for future investigations in health and neurological disease.

BackgroundDespite the well-documented utility of responsive neurostimulation (RNS, NeuroPace) in adult epilepsy patients, literature on the use of RNS in children is limited.ObjectiveTo determine the real-world efficacy and safety of RNS in pediatric epilepsy patients.MethodsPatients with childhood-onset drug-resistant epilepsy treated with RNS were retrospectively identified at 5 pediatric centers. Reduction of disabling seizures and complications were evaluated for children (18 yr) and compared with prior literature pertaining to adult patients.ResultsOf 35 patients identified, 17 were

ObjectiveTo compare the effectiveness of initial treatment for infantile spasms.MethodsThe National Infantile Spasms Consortium prospectively followed up children with new-onset infantile spasms that began at age 2 to 24 months at 23 US centers (2012-2018). Freedom from treatment failure at 60 days required no second treatment for infantile spasms and no clinical spasms after 30 days of treatment initiation. We managed treatment selection bias with propensity score weighting and within-center correlation with generalized estimating equations.ResultsFreedom from treatment failure rates were as follows: adrenocorticotropic hormone (ACTH) 88 of 190 (46%), oral steroids 42 of 95 (44%), vigabatrin 32 of 87 (37%), and nonstandard therapy 4 of 51 (8%). Changing from oral steroids to ACTH was not estimated to affect response (observed 44% estimated to change to 44% [95% confidence interval 34%-54%]). Changing from nonstandard therapy to ACTH would improve response from 8% to 39% (17%-67%), and changing to oral steroids would improve response from 8% to 38% (15%-68%). There were large but not statistically significant estimated effects of changing from vigabatrin to ACTH (29% to 42% [15%-75%]), from vigabatrin to oral steroids (29% to 42% [28%-57%]), and from nonstandard therapy to vigabatrin (8% to 20% [6%-50%]). Among children treated with vigabatrin, those with tuberous sclerosis complex (TSC) responded more often than others (62% vs 29%; p < 0.05).DiscussionCompared to nonstandard therapy, ACTH and oral steroids are superior for initial treatment of infantile spasms. The estimated effectiveness of vigabatrin is between that of ACTH/oral steroids and nonstandard therapy, although the sample was underpowered for statistical confidence. When used, vigabatrin worked best for TSC.Classification of evidenceThis study provides Class III evidence that for children with new-onset infantile spasms, ACTH or oral steroids were superior to nonstandard therapies.

BackgroundSleep disturbances in autism spectrum disorder (ASD) represent a common and vexing comorbidity. Clinical heterogeneity amongst these warrants studies of the mechanisms associated with specific genetic etiologies. Duplications of 15q11.2-13.1 (Dup15q syndrome) are highly penetrant for neurodevelopmental disorders (NDDs) such as intellectual disability and ASD, as well as sleep disturbances. Genes in the 15q region, particularly UBE3A and a cluster of GABAA receptor genes, are critical for neural development, synaptic protein synthesis and degradation, and inhibitory neurotransmission. During awake electroencephalography (EEG), children with Dup15q syndrome demonstrate increased beta band oscillations (12-30 Hz) that likely reflect aberrant GABAergic neurotransmission. Healthy sleep rhythms, necessary for robust cognitive development, are also highly dependent on GABAergic neurotransmission. We therefore hypothesized that sleep physiology would be abnormal in children with Dup15q syndrome.MethodsTo test the hypothesis that elevated beta oscillations persist in sleep in Dup15q syndrome and that NREM sleep rhythms would be disrupted, we computed: (1) beta power, (2) spindle density, and (3) percentage of slow-wave sleep (SWS) in overnight sleep EEG recordings from a cohort of children with Dup15q syndrome (n = 15) and compared them to age-matched neurotypical children (n = 12).ResultsChildren with Dup15q syndrome showed abnormal sleep physiology with elevated beta power, reduced spindle density, and reduced or absent SWS compared to age-matched neurotypical controls.LimitationsThis study relied on clinical EEG where sleep staging was not available. However, considering that clinical polysomnograms are challenging to collect in this population, the ability to quantify these biomarkers on clinical EEG-routinely ordered for epilepsy monitoring-opens the door for larger-scale studies. While comparable to other human studies in rare genetic disorders, a larger sample would allow for examination of the role of seizure severity, medications, and developmental age that may impact sleep physiology.ConclusionsWe have identified three quantitative EEG biomarkers of sleep disruption in Dup15q syndrome, a genetic condition highly penetrant for ASD. Insights from this study not only promote a greater mechanistic understanding of the pathophysiology defining Dup15q syndrome, but also lay the foundation for studies that investigate the association between sleep and cognition. Abnormal sleep physiology may undermine healthy cognitive development and may serve as a quantifiable and modifiable target for behavioral and pharmacological interventions.

Clinical and genetic features of five unrelated patients with de novo pathogenic variants in the synaptic vesicle-associated membrane protein 2 (VAMP2) reveal common features of global developmental delay, autistic tendencies, behavioral disturbances, and a higher propensity to develop epilepsy. For one patient, a cognitively impaired adolescent with a de novo stop-gain VAMP2 mutation, we tested a potential treatment strategy, enhancing neurotransmission by prolonging action potentials with the aminopyridine family of potassium channel blockers, 4-aminopyridine and 3,4-diaminopyridine, in vitro and in vivo. Synaptic vesicle recycling and neurotransmission were assayed in neurons expressing three VAMP2 variants by live-cell imaging and electrophysiology. In cellular models, two variants decrease both the rate of exocytosis and the number of synaptic vesicles released from the recycling pool, compared with wild-type. Aminopyridine treatment increases the rate and extent of exocytosis and total synaptic charge transfer and desynchronizes GABA release. The clinical response of the patient to 2 years of off-label aminopyridine treatment includes improved emotional and behavioral regulation by parental report, and objective improvement in standardized cognitive measures. Aminopyridine treatment may extend to patients with pathogenic variants in VAMP2 and other genes influencing presynaptic function or GABAergic tone, and tested in vitro before treatment.

ObjectiveTo investigate the diagnostic utility of high frequency oscillations (HFOs) via scalp electroencephalogram (EEG) in infantile spasms.MethodsWe retrospectively analyzed interictal slow-wave sleep EEGs sampled at 2,000 Hz recorded from 30 consecutive patients who were suspected of having infantile spasms. We measured the rate of HFOs (80-500 Hz) and the strength of the cross-frequency coupling between HFOs and slow-wave activity (SWA) at 3-4 Hz and 0.5-1 Hz as quantified with modulation indices (MIs).ResultsTwenty-three patients (77%) exhibited active spasms during the overnight EEG recording. Although the HFOs were detected in all children, increased HFO rate and MIs correlated with the presence of active spasms (p

High-frequency oscillations (HFOs), including ripples (Rs) and fast ripples (FRs), are promising biomarkers of epileptogenesis, but their clinical utility is limited by the lack of a standardized approach to identification. We set out to determine whether electroencephalographers experienced in HFO analysis can reliably identify and quantify interictal HFOs. Two blinded raters independently reviewed 10 intraoperative electrocorticography (ECoG) samples from epilepsy surgery cases, and 10 scalp EEG samples from epilepsy monitoring unit evaluations. HFOs were visually marked using bandpass filters (R, 80-250 Hz; FR, 250-500 Hz) with a sampling frequency of 2,000 Hz. There was agreement as to the presence or absence of epileptiform discharges (EDs), Rs, and FRs, in 17, 18, and 18 cases, respectively. Interrater reliability (IRR) was favorable with κ = 0.70, 0.80, and 0.80, respectively, and similar for ECoG and scalp electroencephalography (EEG). Furthermore, interclass correlation for rates of Rs (0.99, 95% confidence interval [CI] 0.96-0.99) and FRs (0.77, 95% CI 0.41-0.91) were superior in comparison to EDs (0.37, 95% CI -0.60 to 0.75). Our data suggest that HFO identification and quantification are reliable among experienced electroencephalographers. Our findings support the reliability of utilizing HFO data in both research and clinical arenas.

After initially successful treatment of infantile spasms, the long-term cumulative risk of relapse approaches 50%, and there is no established protocol to mitigate this risk. Although vigabatrin may be an effective means to prevent relapse, there is little guidance as to ideal duration and dosage. Using a cohort of children with infantile spasms and tuberous sclerosis complex (TSC), we evaluated the potential association of post-response VGB treatment and the rate of infantile spasms relapse. Patients with infantile spasms and clinical response to vigabatrin were identified among a multicenter prospective observational cohort of children with TSC. For each patient we recorded dates of infantile spasms onset, response to vigabatrin, relapse (if any), and quantified duration and dosage of vigabatrin after response. Time to relapse as a function of vigabatrin exposure was evaluated using survival analyses. We identified 50 children who responded to VGB. During a median follow-up of 16.6 months (IQR 10.3-22.9), 12 (24%) patients subsequently relapsed after a median of 7.8 months (IQR 3.1-9.6). Relapse occurred after VGB discontinuation in four patients, and during continued VGB treatment in the remaining eight cases. In survival analyses, risk of relapse was unaffected by the presence or absence of VGB treatment (HR 0.31, 95%CI 0.01-28.4, P =  0.61), but weighted-average dosage was associated with marked reduction in relapse risk: Each 50 mg/kg/d increment in dosage was associated with 61% reduction in risk (HR 0.39, 95%CI 0.17 - 0.90, P =  0.026). This study suggests that the risk of infantile spasms relapse in TSC may be reduced by high-dose vigabatrin treatment.

OBJECTIVE:Epileptic spasms (ES) are associated with pathological neuronal networks, which may underlie characteristic EEG patterns such as hypsarrhythmia. Here we evaluate EEG functional connectivity as a quantitative marker of treatment response, in comparison to classic visual EEG features. METHODS:We retrospectively identified 21 ES patients and 21 healthy controls. EEG data recorded before treatment and after ≥10 days of treatment underwent blinded visual assessment, and functional connectivity was measured using cross-correlation techniques. Short-term treatment response and long-term outcome data were collected. RESULTS:Subjects with ES had stronger, more stable functional networks than controls. After treatment initiation, all responders (defined by cessation of spasms) exhibited decreases in functional connectivity strength, while an increase in connectivity strength occurred only in non-responders. There were six subjects with unusually strong pre-treatment functional connectivity, and all were responders. Visually assessed EEG features were not predictive of treatment response. CONCLUSIONS:Changes in network connectivity and stability correlate to treatment response for ES, and high pre-treatment connectivity may predict favorable short-term treatment response. Quantitative measures outperform visual analysis of the EEG. SIGNIFICANCE:Functional networks may have value as objective markers of treatment response in ES, with potential to facilitate rapid identification of personalized, effective treatments.

We present the case of a child with long-standing, super-refractory status epilepticus (SRSE) who manifested prompt and complete resolution of SRSE upon exposure to pure cannabidiol. SRSE emerged in the context of remote suspected encephalitis with previously well-controlled epilepsy. We discuss the extent to which response may be specifically attributed to cannabidiol, with consideration and discussion of multiple potential drug-drug interactions. Based on this case, we propose that adjunctive cannabidiol be considered in the treatment of SRSE.

Infantile spasms syndrome is an epileptic encephalopathy in which prompt diagnosis and treatment initiation are critical to therapeutic response. Diagnosis of the disease heavily depends on the identification of characteristic electroencephalographic (EEG) patterns, including hypsarrhythmia. However, visual assessment of the presence and characteristics of hypsarrhythmia is challenging because multiple variants of the pattern exist, leading to poor inter-rater reliability. We investigated whether a quantitative measurement of the control of neural synchrony in the EEGs of infantile spasms patients could be used to reliably distinguish the presence of hypsarrhythmia and indicate successful treatment outcomes. We used autocorrelation and Detrended Fluctuation Analysis (DFA) to measure the strength of long-range temporal correlations in 21 infantile spasms patients before and after treatment and 21 control subjects. The strength of long-range temporal correlations was significantly lower in patients with hypsarrhythmia than control patients, indicating decreased control of neural synchrony. There was no difference between patients without hypsarrhythmia and control patients. Further, the presence of hypsarrhythmia could be classified based on the DFA exponent and intercept with 92% accuracy using a support vector machine. Successful treatment was marked by a larger increase in the DFA exponent compared to those in which spasms persisted. These results suggest that the strength of long-range temporal correlations is a marker of pathological cortical activity that correlates with treatment response. Combined with current clinical measures, this quantitative tool has the potential to aid objective identification of hypsarrhythmia and assessment of treatment efficacy to inform clinical decision-making.

In the surgical management of epilepsy, the resection of cortex exhibiting interictal fast ripples (250-500Hz) on electrocorticography has been linked to postoperative seizure-freedom. Although fast ripples appear to accurately identify the epileptogenic zone-the minimum tissue that must be removed at surgery to achieve seizure-freedom-it has not been established that fast ripples are a superior biomarker in comparison with multimodal presurgical neuroimaging and other electrocorticography abnormalities. Hence, in the prediction of postoperative seizure-freedom, we compared the value of fast ripples with other intraoperative electocorticography abnormalities including focal slowing, paroxysmal fast activity, intermittent spike discharges, continuous epileptiform discharges, focal attenuation, and intraoperative seizures, as well as complete resection of the lesion defined by MRI and other neuroimaging. In a cohort of 60 children with lesional epilepsy and median postsurgical follow-up exceeding 4 years, who underwent resective epilepsy surgery with intraoperative electrocorticography, we evaluated the extent to which removal of each intraoperative electrocorticography abnormality impacts time to first postoperative seizure using the Kaplan-Meier method and Cox proportional hazards regression. Secondly, we contrasted the predictive value of resection of each competing electrocorticography abnormality using standard test metrics (sensitivity, specificity, positive predictive value, and negative predictive value). In contrast with all other intraoperative electrocorticography abnormalities, fast ripples demonstrated the most favorable combination of positive predictive value (100%) and negative predictive value (76%) in the prediction of postoperative seizures. Among all candidate electrocorticography features, time to first postoperative seizure was most strongly associated with incomplete resection of fast ripples (hazard ratio=19.8, p

ObjectiveAlthough the link between vigabatrin (VGB) and retinotoxicity is well known, little attention has been focused on the risk of VGB-associated brain abnormalities on magnetic resonance imaging (MRI) (VABAM), namely reversible-and largely asymptomatic-signal changes in the thalami, basal ganglia, brainstem tegmentum, and cerebellar nuclei. Using a large infantile spasms cohort, we set out to identify predictors of these phenomena.MethodsChildren with infantile spasms were retrospectively identified. Brain MRI reports were serially reviewed without knowledge of VGB exposure. Upon VABAM discovery, records were systematically reviewed to ascertain presence of symptoms attributable to VGB. Separately, progress notes were sequentially reviewed to identify and quantify VGB exposure.ResultsWe identified 507 brain MRI studies among 257 patients with infantile spasms. VGB treatment was documented in 143 children, with detailed exposure data available for 104, of whom 45 had at least one MRI study during VGB treatment. Among the limited subset of asymptomatic children who underwent MRI (n = 40), 6 exhibited VABAM. Risk of asymptomatic VABAM was dose-dependent, as peak (but not cumulative) VGB dosage was strongly associated with asymptomatic VABAM (p = 0.0028). In an exploratory analysis, we encountered 4 children with symptomatic VABAM among 104 patients with detailed VGB exposure data. Risk of symptomatic VABAM was seemingly dose-independent, and potentially associated with concomitant hormonal therapy (i.e., prednisolone and adrenocorticotropic hormone [ACTH]) (p = 0.039).SignificanceWe have demonstrated dose-dependent risk of asymptomatic VABAM and uncovered a possible association between symptomatic VABAM and concomitant hormonal therapy. Caution should be exercised in the use of high VGB dosage (i.e., >175 mg/kg/day), and further study is warranted to confirm the potential impact of hormonal therapy.

Objective: Relapse of epileptic spasms after initial treatment of infantile epileptic spasms syndrome (IESS) is common. However, past studies of small cohorts have inconsistently linked relapse risk to etiology, treatment modality, and EEG features upon response. Using a large single‐center IESS cohort, we set out to quantify the risk of epileptic spasms relapse and identify specific risk factors. Methods: We identified all children with epileptic spasms at our center using a clinical EEG database. Using the electronic medical record, we confirmed IESS syndrome classification and ascertained treatment, response, time to relapse, etiology, EEG features, and other demographic factors. Relapse‐free survival analysis was carried out using Cox proportional hazards regression. Results: Among 599 children with IESS, 197 specifically responded to hormonal therapy and/or vigabatrin (as opposed to surgery or other second‐line treatments). In this study, 41 (21%) subjects exhibited relapse of epileptic spasms within 12 months of response. Longer duration of IESS prior to response (>3 months) was strongly associated with shorter latency to relapse (hazard ratio = 3.11; 95% CI 1.59–6.10; p = 0.001). Relapse was not associated with etiology, developmental status, or any post‐treatment EEG feature. Significance: This study suggests that long duration of IESS before response is the single largest clinical predictor of relapse risk, and therefore underscores the importance of prompt and successful initial treatment. Further study is needed to evaluate candidate biomarkers of epileptic spasms relapse and identify treatments to mitigate this risk. Plain Language Summary: Relapse of infantile spasms is common after initially successful treatment. With study of a large group of children with infantile spasms, we determined that relapse is linked to long duration of infantile spasms. In contrast, relapse was not associated with the cause of infantile spasms, developmental measures, or EEG features at the time of initial response. Further study is needed to identify tools to predict impending relapse of infantile spasms. [ABSTRACT FROM AUTHOR]

ObjectiveLovastatin has been shown to reverse learning deficits in a mouse model of Neurofibromatosis Type 1 (NF1), a common monogenic disorder caused by a mutation in the Ras-MAPK pathway and associated with learning disabilities. We conducted a randomized double-blind placebo-controlled trial to assess lovastatin's effects on cognition and behavior in patients with NF1.MethodForty-four NF1 patients (mean age 25.7+/-11.6 years; 64% female) were randomly assigned to 14 weeks of lovastatin (N = 23; maximum dose of 80 mg/day for adult participants and 40 mg/day for children) or placebo (N = 21). Based on findings in the mouse model, primary outcome measures were nonverbal learning and working memory. Secondary outcome measures included verbal memory, attention, and self/parent-reported behavioral problems, as well as tolerability of medication. Participants also underwent neuroimaging assessments at baseline and 14 weeks, to determine whether neural biomarkers were associated with treatment response. Linear mixed models assessed for differential treatment effects on outcome measures.ResultsTwelve participants dropped from the study prior to completion (8 placebo, 4 lovastatin), resulting in 32 completers (15 placebo, 17 lovastatin). Lovastatin was well-tolerated, with no serious adverse events. Differential improvement favoring lovastatin treatment was observed for one primary (working memory; effect size f (2) = 0.70, P < 0.01) and two secondary outcome measures (verbal memory, f (2) = 0.19, P = 0.02, and adult self-reported internalizing problems, f (2) = 0.26, P = 0.03). Exploratory moderator analyses revealed that higher baseline neural activity in frontal regions was associated with larger treatment effects.InterpretationThese preliminary results suggest beneficial effects of lovastatin on some learning and memory functions, as well as internalizing symptoms in patients with NF1.

PurposeThis study investigated the short-term response to a standardized hormonal therapy protocol for treatment of infantile spasms.MethodsTwenty-seven children with video electroencephalography (EEG)-confirmed infantile spasms received very high dose (8 mg/kg/day, max 60 mg/day) oral prednisolone for 2 weeks. Response (absence of both hypsarrhythmia and spasms) to prednisolone was ascertained by repeat overnight video-EEG. Responders were tapered over 2 weeks and nonresponders were immediately transitioned to high dose (150 IU/m(2)/day) intramuscular adrenocorticotropic hormone (ACTH) for two additional weeks. Response was again determined by overnight video-EEG after ACTH therapy.Key findingsSixty-three percent (17/27) of patients responded completely to prednisolone. Subsequently, 40% (4/10) of prednisolone nonresponders exhibited a complete response after an additional 2-week course with ACTH. Among 27 subjects with median follow-up of 13.5 months (interquartile range [IQR] 4.8-25.9), 12% (2/17) of prednisolone responders and 50% (2/4) of ACTH responders experienced a relapse between 2 and 9 months after initial response.SignificanceVery high dose prednisolone demonstrated significantly higher efficacy than previously reported for lower doses in prior studies. High dose ACTH may be superior to very high dose prednisolone, and in lieu of a definitive clinical trial, the choice between prednisolone and ACTH for initial treatment of infantile spasms remains controversial.