RESUMEN

AIMS: We aimed to investigate mesial temporal lobe abnormalities in mesial temporal lobe epilepsy (MTLE) patients with hypersynchronous (HYP) and low-voltage fast rhythms (LVF) onset identified by stereotactic electroencephalography (SEEG) and evaluate their diagnostic and prognostic value. METHODS: Fifty-one MTLE patients were categorized as HYP or LVF by SEEG. High-resolution MRI volume-based analysis and 18F-FDG-PET standard uptake values of hippocampal and amygdala subfields were quantified and compared with 57 matched controls. Further analyses were conducted to delineate the distinct pathological characteristics differentiating the two groups. Diagnostic and prognostic prediction performance of these biomarkers were assessed using receiver operating characteristic curves. RESULTS: LVF-onset individuals demonstrated ipsilateral amygdala enlargement (p = 0.048) and contralateral hippocampus hypermetabolism (p = 0.042), pathological results often accompany abnormalities in the temporal lobe cortex, while HYP-onset subjects had significant atrophy (p < 0.001) and hypometabolism (p = 0.013) in ipsilateral hippocampus and its subfields, as well as amygdala atrophy (p < 0.001), pathological results are highly correlated with hippocampal sclerosis. Severe fimbria atrophy was observed in cases of HYP-onset MTLE with poor prognosis (AUC = 0.874). CONCLUSION: Individuals with different seizure-onset patterns display specific morphological and metabolic abnormalities in the amygdala and hippocampus. Identifying these subfield abnormalities can improve diagnostic and prognostic precision, guiding surgical strategies for MTLE.

Asunto(s)

Amígdala del Cerebelo , Electroencefalografía , Epilepsia del Lóbulo Temporal , Hipocampo , Imagen por Resonancia Magnética , Tomografía de Emisión de Positrones , Técnicas Estereotáxicas , Humanos , Femenino , Masculino , Amígdala del Cerebelo/diagnóstico por imagen , Amígdala del Cerebelo/metabolismo , Amígdala del Cerebelo/patología , Adulto , Hipocampo/diagnóstico por imagen , Hipocampo/patología , Hipocampo/metabolismo , Electroencefalografía/métodos , Epilepsia del Lóbulo Temporal/diagnóstico por imagen , Epilepsia del Lóbulo Temporal/metabolismo , Epilepsia del Lóbulo Temporal/cirugía , Epilepsia del Lóbulo Temporal/patología , Persona de Mediana Edad , Imagen por Resonancia Magnética/métodos , Adulto Joven , Convulsiones/diagnóstico por imagen , Convulsiones/metabolismo , Fluorodesoxiglucosa F18

RESUMEN

BACKGROUND: Ictal brain perfusion SPECT provides higher sensitivity for the identification of the epileptic seizure onset zone (SOZ) than interictal SPECT. However, ictal SPECT is demanding due to the unpredictable waiting period for the next seizure to allow for ictal tracer injection. Thus, starting with an interictal scan and skipping the ictal scan if the interictal scan provides a SOZ candidate with high confidence could be an efficient approach. The current study estimated the rate of high-confidence SOZ candidates and the false lateralization rate among them for interictal and ictal SPECT. METHODS: 177 patients (48% females, median age 38y, interquartile range 27-48y) with ictal and interictal SPECT acquired with 99mTc-HMPAO (n = 141) or -ECD (n = 36) were included retrospectively. The vast majority of the patients was suspected to have temporal lobe epilepsy. Visual interpretation of the SPECT data was performed independently by 3 readers in 3 settings: "interictal only" (interictal SPECT and statistical hypoperfusion map), "ictal only" (ictal SPECT and hyperperfusion map), and "full" setting (side-by-side interpretation of ictal and interictal SPECT including statistical maps and SISCOM analysis). The readers lateralized the SOZ (right, left, none) and characterized their confidence using a 5-score. A case was considered "lateralizing with high confidence" if all readers lateralized to the same hemisphere with at least 4 of 5 confidence points. Lateralization of the SOZ in the "full" setting was used as reference standard. RESULTS: The proportion of "lateralizing with high confidence" cases was 4.5/31.6/38.4% in the "interictal only"/"ictal only"/"full" setting. One (12.5%) of the 8 cases that were "lateralizing with high confidence" in the "interictal only" setting lateralized to the wrong hemisphere. Among the 56 cases that were "lateralizing with high confidence" in the "ictal only" setting, 54 (96.4%) were also lateralizing in the "full" setting, all to the same hemisphere. CONCLUSIONS: Starting brain perfusion SPECT in the presurgical evaluation of epilepsy with an interictal scan to skip the ictal scan in case of a high-confidence interictal SOZ candidate is not a useful approach. In contrast, starting with an ictal scan to skip the interictal scan in case of a high-confidence ictal SOZ candidate can be recommended.

RESUMEN

OBJECTIVE: This study was undertaken to investigate the potential of interictal electroencephalographic (EEG) findings and electrically stimulated seizures during stereo-EEG (SEEG) as surrogate markers for the spontaneous seizure onset zone (spSOZ). We hypothesized that combining the localizing information of these markers would allow clinically meaningful estimation of the spSOZ. METHODS: We included all patients (n = 63) who underwent SEEG between January 2013 and March 2020 at Helsinki University Hospital and had spontaneous seizures during the recording. We scored spikes, gamma activity, and background abnormality on each channel visually during a 12-h epoch containing waking state and sleep. Based on semiology, we classified stimulated seizures as typical or atypical/unclassifiable and estimated the stimulated SOZ (stimSOZ) for typical seizures. To assess which markers increased the odds of channel inclusion in the spSOZ, we fitted mixed effects logistic regression models. RESULTS: A combined regression model including the stimSOZ and interictal markers scored during sleep performed better in estimating which channels were part of the spSOZ than models based on stimSOZ (p < .001) or interictal markers (p < .001) alone. Of the individual markers, the effect sizes were greatest for inclusion of a channel in the stimSOZ (odds ratio [OR] = 60, 95% confidence interval [CI] = 37-97, p < .001) and for continuous (OR = 25, 95% CI = 12-55, p < .001) and subcontinuous (OR = 36, 95% CI = 21-64, p < .001) interictal spiking. At the individual level, the model's accuracy to predict spSOZ inclusion varied markedly (median accuracy = 85.7, range = 54.4-100), which was not explained by etiology (p > .05). SIGNIFICANCE: Compared to either marker alone, combining visually rated interictal SEEG markers and stimulated seizures improved prediction of which SEEG channels belonged to the spSOZ. Inclusion in the stimSOZ and continuous or subcontinuous spikes increased the odds of spSOZ inclusion the most. Future studies should investigate whether suboptimal sampling of the true epileptogenic zone can explain the model's poor performance in certain patients.

RESUMEN

The mesial temporal lobe epilepsy (MTLE) seizures are believed to originate from medial temporal structures, including the amygdala, hippocampus, and temporal cortex. Thus, the seizures onset zones (SOZs) of MTLE locate in these regions. However, whether the neural features of SOZs are specific to different medial temporal structures are still unclear and need more investigation. To address this question, the present study tracked the features of two different high frequency oscillations (HFOs) in the SOZs of these regions during MTLE seizures from 10 drug-resistant MTLE patients, who received the stereo electroencephalography (SEEG) electrodes implantation surgery in the medial temporal structures. Remarkable difference of HFOs features, including the proportions of HFOs contacts, percentages of HFOs contacts with significant coupling and firing rates of HFOs, could be observed in the SOZs among three medial temporal structures during seizures. Specifically, we found that the amygdala might contribute to the generation of MTLE seizures, while the hippocampus plays a critical role for the propagation of MTLE seizures. In addition, the HFOs firing rates in SOZ regions were significantly larger than those in NonSOZ regions, suggesting the potential biomarkers of HFOs for MTLE seizure. Moreover, there existed higher percentages of SOZs contacts in the HFOs contacts than in all SEEG contacts, especially those with significant coupling to slow oscillations, implying that specific HFOs features would help identify the SOZ regions. Taken together, our results displayed the features of HFOs in different medial temporal structures during MTLE seizures, and could deepen our understanding concerning the neural mechanism of MTLE.

RESUMEN

OBJECTIVE: Stereoelectroencephalography (SEEG) is increasingly utilized worldwide in epilepsy surgery planning. International guidelines for SEEG terminology and interpretation are yet to be proposed. There are worldwide differences in SEEG definitions, application of features in epilepsy surgery planning, and interpretation of surgical outcomes. This hinders the clinical interpretation of SEEG findings and collaborative research. We aimed to assess the global perspectives on SEEG terminology, differences in the application of presurgical features, and variability in the interpretation of surgery outcome scores, and analyze how clinical expert demographics influenced these opinions. METHODS: We assessed the practices and opinions of epileptologists with specialized training in SEEG using a survey. Data were qualitatively analyzed, and subgroups were examined based on geographical regions and years of experience. Primary outcomes included opinions on SEEG terminology, features used for epilepsy surgery, and interpretation of outcome scores. Additionally, we conducted a multilevel regression and poststratification analysis to characterize the nonresponders. RESULTS: A total of 321 expert responses from 39 countries were analyzed. We observed substantial differences in terminology, practices, and use of presurgical features across geographical regions and SEEG expertise levels. The majority of experts (220, 68.5%) favored the Lüders epileptogenic zone definition. Experts were divided regarding the seizure onset zone definition, with 179 (55.8%) favoring onset alone and 135 (42.1%) supporting onset and early propagation. In terms of presurgical SEEG features, a clear preference was found for ictal features over interictal features. Seizure onset patterns were identified as the most important features by 265 experts (82.5%). We found similar trends after correcting for nonresponders using regression analysis. SIGNIFICANCE: This study underscores the need for standardized terminology, interpretation, and outcome assessment in SEEG-informed epilepsy surgery. By highlighting the diverse perspectives and practices in SEEG, this research lays a solid foundation for developing globally accepted terminology and guidelines, advancing the field toward improved communication and standardization in epilepsy surgery.

RESUMEN

BACKGROUND: Ictal stereo-encephalography (sEEG) biomarkers for seizure onset zone (SOZ) localization can be classified depending on whether they target abnormalities in signal power or functional connectivity between signals, and they may depend on the frequency band and time window at which they are estimated. NEW METHOD: This work aimed to compare and optimize the performance of a power and a connectivity-based biomarker to identify SOZ contacts from ictal sEEG recordings. To do so, we used a previously introduced power-based measure, the normalized mean activation (nMA), which quantifies the ictal average power activation. Similarly, we defined the normalized mean strength (nMS), to quantify the ictal mean functional connectivity of every contact with the rest. The optimal frequency bands and time windows were selected based on optimizing AUC and F2-score. RESULTS: The analysis was performed on a dataset of 67 seizures from 10 patients with pharmacoresistant temporal lobe epilepsy. Our results suggest that the power-based biomarker generally performs better for the detection of SOZ than the connectivity-based one. However, an equivalent performance level can be achieved when both biomarkers are independently optimized. Optimal performance was achieved in the beta and lower-gamma range for the power biomarker and in the lower- and higher-gamma range for connectivity, both using a 20 or 30 s period after seizure onset. CONCLUSIONS: The results of this study highlight the importance of this optimization step over frequency and time windows when comparing different SOZ discrimination biomarkers. This information should be considered when training SOZ classifiers on retrospective patients' data for clinical applications.

Asunto(s)

Epilepsia del Lóbulo Temporal , Humanos , Epilepsia del Lóbulo Temporal/fisiopatología , Epilepsia del Lóbulo Temporal/diagnóstico , Adulto , Masculino , Femenino , Electroencefalografía/métodos , Convulsiones/fisiopatología , Convulsiones/diagnóstico , Procesamiento de Señales Asistido por Computador , Persona de Mediana Edad , Adulto Joven , Biomarcadores , Técnicas Estereotáxicas , Epilepsia Refractaria/fisiopatología , Epilepsia Refractaria/diagnóstico , Encéfalo/fisiopatología , Ondas Encefálicas/fisiología

RESUMEN

Methods to quantify cortical hyperexcitability are of enormous interest for mapping epileptic networks in patients with focal epilepsy. We hypothesize that, in the resting state, cortical hyperexcitability increases firing-rate correlations between neuronal populations within seizure onset zones (SOZs). This hypothesis predicts that in the gamma frequency band (40-200 Hz), amplitude envelope correlations (AECs), a relatively straightforward measure of functional connectivity, should be elevated within SOZs compared to other areas. To test this prediction, we analyzed archived samples of interictal electrocorticographic (ECoG) signals recorded from patients who became seizure-free after surgery targeting SOZs identified by multiday intracranial recordings. We show that in the gamma band, AECs between nodes within SOZs are markedly elevated relative to those elsewhere. AEC-based node strength, eigencentrality, and clustering coefficient are also robustly increased within the SOZ with maxima in the low-gamma band (permutation test Z-scores > 8) and yield moderate discriminability of the SOZ using ROC analysis (maximal mean AUC ~ 0.73). By contrast to AECs, phase locking values (PLVs), a measure of narrow-band phase coupling across sites, and PLV-based graph metrics discriminate the seizure onset nodes weakly. Our results suggest that gamma band AECs may provide a clinically useful marker of cortical hyperexcitability in focal epilepsy.

Asunto(s)

Electrocorticografía , Epilepsias Parciales , Humanos , Epilepsias Parciales/fisiopatología , Masculino , Femenino , Ritmo Gamma/fisiología , Red Nerviosa/fisiopatología , Adulto , Adolescente , Electroencefalografía , Adulto Joven , Mapeo Encefálico/métodos

RESUMEN

INTRODUCTION: Patients with medication-resistant disabling epilepsy should be considered for potential epilepsy surgery. If noninvasive techniques are unable to identify the location of the seizure onset zone (SOZ), it becomes necessary to consider intracranial investigations. Stereo-electroencephalography (SEEG) is currently the preferred method for such monitoring, however foramen ovale (FO) electrodes offer a less invasive alternative that may be suitable in certain situations. Previous studies have demonstrated the effectiveness of FO electrodes in suspected mesial temporal epilepsy, nevertheless, increased experience with FO electrode use could further enhance their safety and efficacy. Therefore, we conducted an analysis of recent FO electrode investigations to assess their utility in surgical decision making, post resection outcomes, and complication rates. METHODS: We conducted a retrospective analysis of 61 patients who underwent FO placement at Mass General Brigham between 2009 and 2020. Patient and seizure characteristics, preoperative investigation data, and seizures outcomes were collected. In addition, identified predictors of FO utility using logistic regression. RESULTS: A total of 61 patients were identified. FO evaluation localized the SOZ in 56 % of patients. Complications were encountered in 1.6 % of patients. Subsequent surgical resection was pursued by 49 % of patients, with 56 % becoming seizure free, and 67 % having favorable seizure outcomes at last follow-up. Multivariate analysis identified younger patients with a higher number of preoperative ASMs as more likely to undergo subsequent treatment, however, these features were not predictive features of SOZ localization, seizure freedom, or favorable seizure outcomes. In patients with bitemporal or cross-over onsets on scalp EEG, FO was able to identify the SOZ in 79 %, whereas in patients with discordant or unclear onset, the rates were 71 % and 45 %, respectively. CONCLUSION: In a contemporary cohort, FO electrode placement had a low complication rate and a high utility primarily in cases of unclear laterality of mesial temporal onsets or discordance between scalp EEG and other pre-FO investigation data in cases of suspected mesial temporal onsets.

Asunto(s)

Epilepsia Refractaria , Electroencefalografía , Foramen Oval , Humanos , Femenino , Masculino , Adulto , Estudios Retrospectivos , Foramen Oval/cirugía , Electroencefalografía/métodos , Persona de Mediana Edad , Epilepsia Refractaria/cirugía , Epilepsia Refractaria/fisiopatología , Epilepsia Refractaria/diagnóstico , Adulto Joven , Convulsiones/cirugía , Convulsiones/fisiopatología , Convulsiones/diagnóstico , Electrodos Implantados , Técnicas Estereotáxicas , Adolescente , Electrodos

RESUMEN

OBJECTIVE: Emerging evidence supports that brain dysfunction may be attributable to environmental factors. This study aims to examine associations of ambient temperature and temperature variability (TV) with seizure incidence in children, which has not been explored. MATERIAL AND METHODS: Data on 2718 outpatient visits due to seizure were collected in Shanghai, China, from 2018 to 2023. Exposure to ambient temperature was estimated at children's residential addresses using spatial-temporal models. A time-stratified case-crossover design with a distributed lag non-linear model (DLNM) was conducted to assess the association between seizure incidence and daily average of ambient temperature over a period of 21 days prior to a case date of disease onset. For a given case date, we selected all dates falling on the same day of the week within the same month as control dates. We calculated a composite index of intra-day and inter-day TV, which was the standard deviation of the daily minimum and maximum temperatures, respectively, over 7 days preceding a case date. We then assessed the association between TV and seizure incidence. Stratified analyses were conducted by age (73.51% < 5 years old and 26.49 % ≥ 5 years old), sex (41.83% female), presence of fever (69.72%), and diagnosis of epilepsy (27.63%). RESULTS: We observed inversed J-shaped temperature-response curves. Lower temperatures had a significant and prolonged effect than higher temperatures. Using 20 °C (with the minimum effect) as the reference, the cumulative odds ratios (ORs) for over 0-21 days preceding the onset at the 5th percentile of the temperature (3 °C) and at the 95th percentile (29 °C) were 3.17 (95% CI: 1.77, 5.68) and 1.54 (95% CI: 0.97, 2.44), respectively. In addition, per 1 °C increases in TV0-7 was associated with OR of 1.08 (95% CI: 1.01, 1.15). Older children and those experiencing seizure with fever exhibited a higher risk of seizure onset at both lower and higher ambient temperatures. CONCLUSION: Both low and high temperatures can contribute to the morbidity related to pediatric seizure. Lower temperatures, however, exerted a longer period of effect prior to seizure onset than higher temperatures. An increased risk for incident seizure was significantly associated with temperature variability during preceding 7 days.

Asunto(s)

Estudios Cruzados , Convulsiones , Temperatura , Humanos , Convulsiones/epidemiología , Femenino , Masculino , Preescolar , China/epidemiología , Niño , Incidencia , Dinámicas no Lineales , Lactante , Exposición a Riesgos Ambientales/efectos adversos

RESUMEN

OBJECTIVE: High frequency oscillations (HFOs) are a biomarker of the seizure onset zone (SOZ) and can be visually or automatically detected. In theory, one can optimize an automated algorithm's parameters to maximize SOZ localization accuracy; however, there is no consensus on whether or how this should be done. Therefore, we optimized an automated detector using visually identified HFOs and evaluated the impact on SOZ localization accuracy. METHODS: We detected HFOs in intracranial EEG from 20 patients with refractory epilepsy from two centers using (1) unoptimized automated detection, (2) visual identification, and (3) automated detection optimized to match visually detected HFOs. RESULTS: SOZ localization accuracy based on HFO rate was not significantly different between the three methods. Across patients, visually optimized detector settings varied, and no single set of settings produced universally accurate SOZ localization. Exploratory analysis suggests that, for many patients, detection settings exist that would improve SOZ localization. CONCLUSIONS: SOZ localization accuracy was similar for all three methods, was not improved by visually optimizing detector settings, and may benefit from patient-specific parameter optimization. SIGNIFICANCE: Visual HFO marking is laborious, and optimizing automated detection using visual markings does not improve localization accuracy. New patient-specific detector optimization methods are needed.

Asunto(s)

Epilepsia Refractaria , Humanos , Femenino , Masculino , Adulto , Epilepsia Refractaria/fisiopatología , Epilepsia Refractaria/diagnóstico , Electroencefalografía/métodos , Persona de Mediana Edad , Electrocorticografía/métodos , Electrocorticografía/normas , Convulsiones/fisiopatología , Convulsiones/diagnóstico , Ondas Encefálicas/fisiología , Algoritmos , Adulto Joven , Adolescente , Epilepsia/fisiopatología , Epilepsia/diagnóstico

RESUMEN

Objective. To demonstrate the capability of utilizing graph feature-based supervised machine learning (ML) algorithm on intracranial electroencephalogram recordings for the identification of seizure onset zones (SOZs) in individuals with drug-resistant epilepsy.Approach. Utilizing three model-free measures of effective connectivity (EC)-directed information, mutual information-guided Granger causality index (MI-GCI), and frequency-domain convergent cross-mapping (FD-CCM) - directed graphs are generated. Graph centrality measures at different sparsity are used as the classifier's features.Main results. The centrality features achieve high accuracies exceeding 90% in distinguishing SOZ electrodes from non-SOZ electrodes. Notably, a sparse graph representation with just ten features and simple ML models effectively achieves such performance. The study identifies FD-CCM centrality measures as particularly significant, with a mean AUC of 0.93, outperforming prior literature. The FD-CCM-based graph modeling also highlights elevated centrality measures among SOZ electrodes, emphasizing heightened activity relative to non-SOZ electrodes during ictogenesis.Significance. This research not only underscores the efficacy of automated SOZ identification but also illuminates the potential of specific EC measures in enhancing discriminative power within the context of epilepsy research.

Asunto(s)

Encéfalo , Electrocorticografía , Convulsiones , Humanos , Convulsiones/fisiopatología , Convulsiones/diagnóstico , Electrocorticografía/métodos , Encéfalo/fisiopatología , Encéfalo/fisiología , Red Nerviosa/fisiopatología , Epilepsia Refractaria/fisiopatología , Masculino , Femenino , Electroencefalografía/métodos , Adulto , Aprendizaje Automático Supervisado , Adulto Joven , Algoritmos , Adolescente

RESUMEN

OBJECTIVE: The increased amplitude of ictal activity is a common feature of epileptic seizures, but the determinants of this amplitude have not been identified. Clinically, ictal amplitudes are measured electrographically (using, e.g., electroencephalography, electrocorticography, and depth electrodes), but these methods do not enable the assessment of the activity of individual neurons. Population signal may increase from three potential sources: (1) increased synchrony (i.e., more coactive neurons); (2) altered active state, from bursts of action potentials and/or paroxysmal depolarizing shifts in membrane potential; and (3) altered subthreshold state, which includes all lower levels of activity. Here, we quantify the fraction of ictal signal from each source. METHODS: To identify the cellular determinants of the ictal signal, we measured single cell and population electrical activity and neuronal calcium levels via optical imaging of the genetically encoded calcium indicator (GECI) GCaMP. Spontaneous seizure activity was assessed with microendoscopy in an APP/PS1 mouse with focal cortical injury and via widefield imaging in the organotypic hippocampal slice cultures (OHSCs) model of posttraumatic epilepsy. Single cell calcium signals were linked to a range of electrical activities by performing simultaneous GECI-based calcium imaging and whole-cell patch-clamp recordings in spontaneously seizing OHSCs. Neuronal resolution calcium imaging of spontaneous seizures was then used to quantify the cellular contributions to population-level ictal signal. RESULTS: The seizure onset signal was primarily driven by increased subthreshold activity, consistent with either barrages of excitatory postsynaptic potentials or sustained membrane depolarization. Unsurprisingly, more neurons entered the active state as seizure activity progressed. However, the increasing fraction of active cells was primarily driven by synchronous reactivation and not from continued recruitment of new populations of neurons into the seizure. SIGNIFICANCE: This work provides a critical link between single neuron activity and population measures of seizure activity.

Asunto(s)

Hipocampo , Neuronas , Animales , Ratones , Neuronas/fisiología , Hipocampo/fisiopatología , Potenciales de Acción/fisiología , Ratones Transgénicos , Ratones Endogámicos C57BL , Electroencefalografía/métodos , Convulsiones/fisiopatología , Epilepsia/fisiopatología , Masculino , Calcio/metabolismo

RESUMEN

Determining the laterality of the seizure onset zone is challenging in frontal lobe epilepsy (FLE) due to the rapid propagation of epileptic discharges to the contralateral hemisphere. There is hemispheric lateralization of autonomic control, and heart rate is modulated by interactions between the sympathetic and parasympathetic nervous systems. Based on this notion, the laterality of seizure foci in FLE might be determined using heart rate variability (HRV) parameters. We explored preictal markers for differentiating the laterality of seizure foci in FLE using HRV parameters. Twelve patients with FLE (6 right FLE and 6 left FLE) were included in the analyzes. A total of 551 (460 left FLE and 91 right FLE) 1-min epoch electrocardiography data were used for HRV analysis. We found that most HRV parameters differed between the left and right FLE groups. Among the machine learning algorithms applied in this study, the light gradient boosting machine was the most accurate, with an AUC value of 0.983 and a classification accuracy of 0.961. Our findings suggest that HRV parameter-based laterality determination models can be convenient and effective tools in clinical settings. Considering that heart rate can be easily measured in real time with a wearable device, our proposed method can be applied to a closed-loop device as a real-time monitoring tool for determining the side of stimulation.

RESUMEN

In medication-resistant epilepsy, the goal of epilepsy surgery is to make a patient seizure free with a resection/ablation that is as small as possible to minimize morbidity. The standard of care in planning the margins of epilepsy surgery involves electroclinical delineation of the seizure onset zone (SOZ) and incorporation of neuroimaging findings from MRI, PET, SPECT, and MEG modalities. Resecting cortical tissue generating high-frequency oscillations (HFOs) has been investigated as a more efficacious alternative to targeting the SOZ. In this study, we used a support vector machine (SVM), with four distinct fast ripple (FR: 350-600 Hz on oscillations, 200-600 Hz on spikes) metrics as factors. These metrics included the FR resection ratio (RR), a spatial FR network measure, and two temporal FR network measures. The SVM was trained by the value of these four factors with respect to the actual resection boundaries and actual seizure free labels of 18 patients with medically refractory focal epilepsy. Leave one out cross-validation of the trained SVM in this training set had an accuracy of 0.78. We next used a simulated iterative virtual resection targeting the FR sites that were highest rate and showed most temporal autonomy. The trained SVM utilized the four virtual FR metrics to predict virtual seizure freedom. In all but one of the nine patients seizure free after surgery, we found that the virtual resections sufficient for virtual seizure freedom were larger in volume (p<0.05). In nine patients who were not seizure free, a larger virtual resection made five virtually seizure free. We also examined 10 medically refractory focal epilepsy patients implanted with the responsive neurostimulator system (RNS) and virtually targeted the RNS stimulation contacts proximal to sites generating FR at highest rates to determine if the simulated value of the stimulated SOZ and stimulated FR metrics would trend toward those patients with a better seizure outcome. Our results suggest: 1) FR measures can accurately predict whether a resection, defined by the standard of care, will result in seizure freedom; 2) utilizing FR alone for planning an efficacious surgery can be associated with larger resections; 3) when FR metrics predict the standard of care resection will fail, amending the boundaries of the planned resection with certain FR generating sites may improve outcome; and 4) more work is required to determine if targeting RNS stimulation contact proximal to FR generating sites will improve seizure outcome.

RESUMEN

OBJECTIVE: This study aims to detect the seizure onset, in childhood absence epilepsy, as early as possible. Indeed, interfering with absence seizures with sensory simulation has been shown to be possible on the condition that the stimulation occurs soon enough after the seizure onset. METHODS: We present four variations (two supervised, two unsupervised) of an algorithm designed to detect the onset of absence seizures from 4 scalp electrodes, and compare their performance with that of a state-of-the-art algorithm. We exploit the characteristic shape of spike-wave discharges to detect the seizure onset. Their performance is assessed on clinical electroencephalograms from 63 patients with confirmed childhood absence epilepsy. RESULTS: The proposed approaches succeed in early detection of the seizure onset, contrary to the classical detection algorithm. Indeed, the results clearly show the superiority of the proposed methods for small delays of detection, under 750 ms from the onset. CONCLUSION: The performance of the proposed unsupervised methods is equivalent to that of the supervised ones. The use of only four electrodes makes the pipeline suitable to be embedded in a wearable device. SIGNIFICANCE: The proposed pipelines perform early detection of absence seizures, which constitutes a prerequisite for a closed-loop system.

Asunto(s)

Electroencefalografía , Epilepsia Tipo Ausencia , Humanos , Epilepsia Tipo Ausencia/fisiopatología , Epilepsia Tipo Ausencia/diagnóstico , Electroencefalografía/métodos , Niño , Femenino , Masculino , Convulsiones/fisiopatología , Convulsiones/diagnóstico , Algoritmos , Preescolar , Adolescente

RESUMEN

Accurately identification of the seizure onset zone (SOZ) is pivotal for successful surgery in patients with medically refractory epilepsy. The purpose of this study is to improve the performance of model predicting the epilepsy surgery outcomes using genetic neural network (GNN) model based on a hybrid intracranial electroencephalography (iEEG) marker. We extracted 21 SOZ related markers based on iEEG data from 79 epilepsy patients. The least absolute shrinkage and selection operator (LASSO) regression was employed to integrated seven markers, selected after testing in pairs with all 21 biomarkers and 7 machine learning models, into a hybrid marker. Based on the hybrid marker, we devised a GNN model and compared its predictive performance for surgical outcomes with six other mainstream machine-learning models. Compared to the mainstream models, underpinning the GNN with the hybrid iEEG marker resulted in a better prediction of surgical outcomes, showing a significant increase of the prediction accuracy from approximately 87% to 94.3% (P = 0.0412). This study suggests that the hybrid iEEG marker can improve the performance of model predicting the epilepsy surgical outcomes, and validates the effectiveness of the GNN in characterizing and analyzing complex relationships between clinical data variables.

Asunto(s)

Epilepsia Refractaria , Epilepsia , Humanos , Electrocorticografía/métodos , Epilepsia/genética , Epilepsia/cirugía , Epilepsia Refractaria/cirugía , Aprendizaje Automático , Resultado del Tratamiento , Electroencefalografía/métodos

RESUMEN

BACKGROUND: Seizure onset pattern (SOP) represents an alteration of electroencephalography (EEG) morphology at the beginning of seizure activity in epilepsy. With stereotactic electroencephalography (SEEG), a method for intracranial EEG evaluation, many morphological SOP classifications have been reported without established consensus. These inconsistent classifications with ambiguous terminology present difficulties to communication among epileptologists. METHODS: We reviewed SOP in SEEG by searching the PubMed database. Reported morphological classifications and the ambiguous terminology used were collected. After thoroughly reviewing all reports, we reconsidered the definitions of these terms and explored a more consistent and simpler morphological SOP classification. RESULTS: Of the 536 studies initially found, 14 studies were finally included after screening and excluding irrelevant studies. We reconsidered the definitions of EEG onset, period for determining type of SOP, core electrode and other terms in SEEG. We proposed a more consistent and simpler morphological SOP classification comprising five major types with two special subtypes. CONCLUSIONS: A scoping review of SOP in SEEG was performed. Our classification may be suitable for describing SOP morphology.

Asunto(s)

Electroencefalografía , Convulsiones , Técnicas Estereotáxicas , Humanos , Convulsiones/clasificación , Convulsiones/fisiopatología , Convulsiones/diagnóstico , Convulsiones/patología , Electroencefalografía/métodos , Electrocorticografía/métodos

RESUMEN

Stereoelectroencephalography is a powerful intracerebral EEG recording method for the presurgical evaluation of epilepsy. It consists in implanting depth electrodes in the patient's brain to record electrical activity and map the epileptogenic zone, which should be resected to render the patient seizure-free. Stereoelectroencephalography has high spatial accuracy and signal-to-noise ratio but remains limited in the coverage of the explored brain regions. Thus, the implantation might provide a suboptimal sampling of epileptogenic regions. We investigate the potential of improving a suboptimal stereoelectroencephalography recording by performing source localization on stereoelectroencephalography signals. We propose combining independent component analysis, connectivity measures to identify components of interest, and distributed source modelling. This approach was tested on two patients with two implantations each, the first failing to characterize the epileptogenic zone and the second giving a better diagnosis. We demonstrate that ictal and interictal source localization performed on the first stereoelectroencephalography recordings matches the findings of the second stereo-EEG exploration. Our findings suggest that independent component analysis followed by source localization on the topographies of interest is a promising method for retrieving the epileptogenic zone in case of suboptimal implantation.

Asunto(s)

Epilepsia , Humanos , Epilepsia/diagnóstico , Epilepsia/cirugía , Técnicas Estereotáxicas , Electroencefalografía/métodos , Encéfalo , Electrodos Implantados

RESUMEN

Low-voltage fast (LVF) seizure-onset is one of the two frequently observed temporal lobe seizure-onset patterns. Depth electroencephalogram profile analysis illustrated that the peak amplitude of LVF onset was deep temporal areas, e.g., hippocampus. However, the specific dynamic transition mechanisms between normal hippocampal rhythmic activity and LVF seizure-onset remain unclear. Recently, the optogenetic approach to gain control over epileptic hyper-excitability both in vitro and in vivo has become a novel noninvasive modulation strategy. Here, we combined biophysical modeling to study LVF dynamics following changes in crucial physiological parameters, and investigated the potential optogenetic intervention mechanism for both excitatory and inhibitory control. In an Ammon's horn 3 (CA3) biophysical model with light-sensitive protein channelrhodopsin 2 (ChR2), we found that the cooperative effects of excessive extracellular potassium concentration of parvalbumin-positive (PV+) inhibitory interneurons and synaptic links could induce abundant types of discharges of the hippocampus, and lead to transitions from gamma oscillations to LVF seizure-onset. Simulations of optogenetic stimulation revealed that the LVF seizure-onset and morbid fast spiking could not be eliminated by targeting PV+ neurons, whereas the epileptic network was more sensitive to the excitatory control of principal neurons with strong optogenetic currents. We illustrate that in the epileptic hippocampal network, the trajectories of the normal and the seizure state are in close vicinity and optogenetic perturbations therefore may result in transitions. The network model system developed in this study represents a scientific instrument to disclose the underlying principles of LVF, to characterize the effects of optogenetic neuromodulation, and to guide future treatment for specific types of seizures.

RESUMEN

OBJECTIVE: We aimed to develop a new approach for identifying the localization of the seizure onset zone (SOZ) based on corticocortical evoked potentials (CCEPs) and to compare the connectivity patterns in patients with different clinical phenotypes. METHODS: Fifty patients who underwent stereoelectroencephalography and CCEP procedures were included. Logistic regression was used in the model, and six CCEP metrics were input as features: root mean square of the first peak (N1RMS) and second peak (N2RMS), peak latency, onset latency, width duration, and area. RESULTS: The area under the curve (AUC) for localizing the SOZ ranged from 0.88 to 0.93. The N1RMS values in the hippocampus sclerosis (HS) group were greater than that of the focal cortical dysplasia (FCD) IIa group (p < 0.001), independent of the distance between the recorded and stimulated sites. The sensitivity of localization was higher in the seizure-free group than in the non-seizure-free group (p = 0.036). CONCLUSIONS: This new method can be used to predict the SOZ localization in various focal epilepsy phenotypes. SIGNIFICANCE: This study proposed a machine-learning approach for localizing the SOZ. Moreover, we examined how clinical phenotypes impact large-scale abnormality of the epileptogenic networks.

Asunto(s)

Electroencefalografía , Epilepsias Parciales , Humanos , Electroencefalografía/métodos , Epilepsias Parciales/diagnóstico , Potenciales Evocados/fisiología , Técnicas Estereotáxicas , Convulsiones