Localizing the Ictal Onset: Visualizing the Epileptogenic Target.
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ABSTRACT:
SUBMITTER: Rossi MA
PROVIDER: S-EPMC5706357 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:ObjectiveTo determine whether seizure onset zone (SOZ) can be localized accurately prior to surgical planning in patients with focal epilepsy, we performed noninvasive EEG recordings and source localization analyses on 39 patients.MethodsIn 39 patients with focal epilepsy, we recorded and extracted 138 seizures and 1,325 interictal epileptic discharges using high-density EEG. We investigated a novel approach for directly imaging sources of seizures and interictal spikes from high-density EEG recordings, and rigorously validated it for noninvasive localization of SOZ determined from intracranial EEG findings and surgical resection volume. Conventional source imaging analyses were also performed for comparison.ResultsIctal source imaging showed a concordance rate of 95% when compared to intracranial EEG or resection results. The average distance from estimation to seizure onset (intracranial) electrodes is 1.35 cm in patients with concordant results, and 0.74 cm to surgical resection boundary in patients with successful surgery. About 41% of the patients were found to have multiple types of interictal activities; coincidentally, a lower concordance rate and a significantly worse performance in localizing SOZ were observed in these patients.ConclusionNoninvasive ictal source imaging with high-density EEG recording can provide highly concordant results with clinical decisions obtained by invasive monitoring or confirmed by resective surgery. By means of direct seizure imaging using high-density scalp EEG recordings, the added value of ictal source imaging is particularly high in patients with complex interictal activity patterns, who may represent the most challenging cases with poor prognosis.
| S-EPMC7884986 | biostudies-literature
Project description:The neuronal synchronous discharging may cause an epileptic seizure. Currently, most of the studies conducted to investigate the mechanism of epilepsy are based on EEGs or functional magnetic resonance imaging (fMRI) recorded during the ictal discharging or the resting-state, and few studies have probed into the dynamic patterns during the inter-ictal discharging that are much easier to record in clinical applications. Here, we propose a time-varying network analysis based on adaptive directed transfer function to uncover the dynamic brain network patterns during the inter-ictal discharging. In addition, an algorithm based on the time-varying outflow of information derived from the network analysis is developed to detect the epileptogenic zone. The analysis performed revealed the time-varying network patterns during different stages of inter-ictal discharging; the epileptogenic zone was activated prior to the discharge onset then worked as the source to propagate the activity to other brain regions. Consistence between the epileptogenic zones detected by our proposed approach and the actual epileptogenic zones proved that time-varying network analysis could not only reveal the underlying neural mechanism of epilepsy, but also function as a useful tool in detecting the epileptogenic zone based on the EEGs in the inter-ictal discharging.
| S-EPMC5563307 | biostudies-literature
Project description:The focal and network concepts of epilepsy present different aspects of electroclinical phenomenon of seizures. Here, we present a 23-year-old man undergoing surgical evaluation with left fronto-temporal electrocorticography (ECoG) and microelectrode-array (MEA) in the middle temporal gyrus (MTG). We compare action-potential (AP) and local field potentials (LFP) recorded from MEA with ECoG. Seizure onset in the mesial-temporal lobe was characterized by changes in the pattern of AP-firing without clear changes in LFP or ECoG in MTG. This suggests simultaneous analysis of neuronal activity in differing spatial scales and frequency ranges provide complementary insights into how focal and network neurophysiological activity contribute to ictal activity.
| S-EPMC5707213 | biostudies-literature
Project description:Objective:To assess feasibility and efficacy of subtraction ictal SPECT coregistered to MRI (SISCOM) for epilepsy localization in children who are candidates for resective surgery. Methods:We retrospectively reviewed all patients ?16 years with drug-resistant epilepsy screened for epilepsy surgery in the University Hospital of Leuven from January 2009 to January 2018. Fifty-eight hospitalizations for ictal SPECT and 51 SISCOM analyses in 44 patients were included. Mean age was 9.1 years. Hospitalizations for SISCOM were analyzed in terms of multiple variables affecting feasibility and efficacy. The localization of SISCOM was compared with the localization of the presumed epileptogenic zone (PEZ) as determined by video-EEG. Results:SISCOM was feasible in terms of chronic medication management, rescue antiepileptic therapy during hospitalization, and operative timings. Radiotracer injection occurred within 30 seconds from seizure onset in 91.4% of the patients. ictal SPECT imaging was performed within two hours from injection in 100% of the patients (mean: 40 minutes). SISCOM was able to localize the PEZ in 51.0% (26/51) and to additionally lateralize the PEZ in 17.6% (9/51), achieving better localizations than ictal SPECT, FDG-PET, and MRI (P < .01). SISCOM was useful to localize the PEZ in 25% of patients with poorly localizing video-EEG and in 27.8% of MRI-negative cases. The occurrence of habitual seizures during injection for ictal SPECT and the temporal localization of the PEZ both correlated with a better SISCOM localization (P < .05). 36.4% (16/44) patients were finally selected for resective surgery, with a 87.5% seizure-free rate at 12 months. A localizing SISCOM was associated with seizure freedom in 66.7% and with a Engel I-II in 75.0% of our patients. Significance:SISCOM is a reliable tool to localize the epileptogenic zone in clinical practice and is both feasible and useful in children, adding precious presurgical information especially in patients with noninformative MRI or a poorly localizing video-EEG.
| S-EPMC7049808 | biostudies-literature
Project description:Although failure of GABAergic inhibition is a commonly hypothesized mechanism underlying seizure disorders, the series of events that precipitate a rapid shift from healthy to ictal activity remain unclear. Furthermore, the diversity of inhibitory interneuron populations poses a challenge for understanding local circuit interactions during seizure initiation. Using a combined optogenetic and electrophysiological approach, we examined the activity of identified mouse hippocampal interneuron classes during chemoconvulsant seizure induction in vivo. Surprisingly, synaptic inhibition from parvalbumin- (PV) and somatostatin-expressing (SST) interneurons remained intact throughout the preictal period and early ictal phase. However, these two sources of inhibition exhibited cell-type-specific differences in their preictal firing patterns and sensitivity to input. Our findings suggest that the onset of ictal activity is not associated with loss of firing by these interneurons or a failure of synaptic inhibition but is instead linked with disruptions of the respective roles these interneurons play in the hippocampal circuit.
| S-EPMC6245730 | biostudies-literature
Project description:Both magnetoencephalography and stereo-electroencephalography are used in presurgical epilepsy assessment, with contrasting advantages and limitations. It is not known whether simultaneous stereo-electroencephalography-magnetoencephalography recording confers an advantage over both individual modalities, in particular whether magnetoencephalography can provide spatial context to epileptiform activity seen on stereo-electroencephalography. Twenty-four adult and paediatric patients who underwent stereo-electroencephalography study for pre-surgical evaluation of drug-resistant focal epilepsy, were recorded using simultaneous stereo-electroencephalography-magnetoencephalography, of which 14 had abnormal interictal activity during recording. The 14 patients were divided into two groups; those with detected superficial (n = 7) and deep (n = 7) brain interictal activity. Interictal spikes were independently identified in stereo-electroencephalography and magnetoencephalography. Magnetoencephalography dipoles were derived using a distributed inverse method. There was no significant difference between stereo-electroencephalography and magnetoencephalography in detecting superficial spikes (P = 0.135) and stereo-electroencephalography was significantly better at detecting deep spikes (P = 0.002). Mean distance across patients between stereo-electroencephalography channel with highest average spike amplitude and magnetoencephalography dipole was 20.7 ± 4.4 mm. for superficial sources, and 17.8 ± 3.7 mm. for deep sources, even though for some of the latter (n = 4) no magnetoencephalography spikes were detected and magnetoencephalography dipole was fitted to a stereo-electroencephalography interictal activity triggered average. Removal of magnetoencephalography dipole was associated with 1 year seizure freedom in 6/7 patients with superficial source, and 5/6 patients with deep source. Although stereo-electroencephalography has greater sensitivity in identifying interictal activity from deeper sources, a magnetoencephalography source can be localized using stereo-electroencephalography information, thereby providing useful whole brain context to stereo-electroencephalography and potential role in epilepsy surgery planning.
| S-EPMC8099997 | biostudies-literature
Project description:Hypersynchronous (HYP) and low voltage fast (LVF) activity are two separate ictal depth EEG onsets patterns often recorded in presurgical patients with MTLE. Evidence suggests the mechanisms generating HYP and LVF onset seizures are distinct, including differential involvement of hippocampal and extra-hippocampal sites. Yet the extent of extra-hippocampal structural alterations, which could support these two common seizures, is not known. In the current study, preoperative MRI from 24 patients with HYP or LVF onset seizures were analyzed to determine changes in cortical thickness and relate structural changes to spatiotemporal properties of the ictal EEG. Overall, onset and initial ipsilateral spread of HYP onset seizures involved mesial temporal structures, whereas LVF onset seizures involved mesial and lateral temporal as well as orbitofrontal cortex. MRI analysis found reduced cortical thickness correlated with longer duration of epilepsy. However, in patients with HYP onsets, the most affected areas were on the medial surface of each hemisphere, including parahippocampal regions and cingulate gyrus, whereas in patients with LVF onsets, the lateral surface of the anterior temporal lobe and orbitofrontal cortex showed the greatest effect. Most patients with HYP onset seizures were seizure-free after resective surgery, while a higher proportion of patients with LVF onset seizures had only worthwhile improvement. Our findings confirm the view that recurrent seizures cause progressive changes in cortical thickness, and provide information concerning the structural basis of two different epileptogenic networks responsible for MTLE. One, identified by HYP ictal onsets, chiefly involves hippocampus and is associated with excellent outcome after standardized anteromedial temporal resection, while the other also involves lateral temporal and orbitofrontal cortex and a seizure-free surgical outcome occurs less after this procedure. These results suggest that a more extensive tailored resection may be required for patients with the second type of MTLE.
| S-EPMC4388829 | biostudies-literature
Project description:Background: Epilepsy affects 50 million people worldwide and a third are refractory to medication. If a discrete cerebral focus or network can be identified, neurosurgical resection can be curative. Most excisions are in the temporal-lobe, and are more likely to result in seizure-freedom than extra-temporal resections. However, less than half of patients undergoing surgery become entirely seizure-free. Localizing the epileptogenic-zone and individualized outcome predictions are difficult, requiring detailed evaluations at specialist centers. Methods: We used bespoke natural language processing to text-mine 3,800 electronic health records, from 309 epilepsy surgery patients, evaluated over a decade, of whom 126 remained entirely seizure-free. We investigated the diagnostic performances of machine learning models using set-of-semiology (SoS) with and without hippocampal sclerosis (HS) on MRI as features, using STARD criteria. Findings: Support Vector Classifiers (SVC) and Gradient Boosted (GB) decision trees were the best performing algorithms for temporal-lobe epileptogenic zone localization (cross-validated Matthews correlation coefficient (MCC) SVC 0.73 ± 0.25, balanced accuracy 0.81 ± 0.14, AUC 0.95 ± 0.05). Models that only used seizure semiology were not always better than internal benchmarks. The combination of multimodal features, however, enhanced performance metrics including MCC and normalized mutual information (NMI) compared to either alone (p < 0.0001). This combination of semiology and HS on MRI increased both cross-validated MCC and NMI by over 25% (NMI, SVC SoS: 0.35 ± 0.28 vs. SVC SoS+HS: 0.61 ± 0.27). Interpretation: Machine learning models using only the set of seizure semiology (SoS) cannot unequivocally perform better than benchmarks in temporal epileptogenic-zone localization. However, the combination of SoS with an imaging feature (HS) enhance epileptogenic lobe localization. We quantified this added NMI value to be 25% in absolute terms. Despite good performance in localization, no model was able to predict seizure-freedom better than benchmarks. The methods used are widely applicable, and the performance enhancements by combining other clinical, imaging and neurophysiological features could be similarly quantified. Multicenter studies are required to confirm generalizability. Funding: Wellcome/EPSRC Center for Interventional and Surgical Sciences (WEISS) (203145Z/16/Z).
| S-EPMC8521800 | biostudies-literature
Project description:Epilepsy is one of the most common neurological disorders affecting about 1% of the world population. For patients with focal seizures that cannot be treated with antiepileptic drugs, the common treatment is a surgical procedure for removal of the seizure onset zone (SOZ). In this work we introduce an algorithm for automatic localization of the seizure onset zone (SOZ) in epileptic patients based on electrocorticography (ECoG) recordings. The proposed algorithm builds upon the hypothesis that the abnormal excessive (or synchronous) neuronal activity in the brain leading to seizures starts in the SOZ and then spreads to other areas in the brain. Thus, when this abnormal activity starts, signals recorded at electrodes close to the SOZ should have a relatively large causal influence on the rest of the recorded signals. The SOZ localization is executed in two steps. First, the algorithm represents the set of electrodes using a directed graph in which nodes correspond to recording electrodes and the edges' weights quantify the pair-wise causal influence between the recorded signals. Then, the algorithm infers the SOZ from the estimated graph using a variant of the PageRank algorithm followed by a novel post-processing phase. Inference results for 19 patients show a close match between the SOZ inferred by the proposed approach and the SOZ estimated by expert neurologists (success rate of 17 out of 19).
| S-EPMC5806930 | biostudies-literature
Project description:ObjectiveIn drug-resistant temporal lobe epilepsy, automated tools for seizure onset zone (SOZ) localization that use brief interictal recordings could supplement presurgical evaluations and improve care. Thus, the authors sought to localize SOZs by training a multichannel convolutional neural network on stereoelectroencephalography (SEEG) cortico-cortical evoked potentials.MethodsThe authors performed single-pulse electrical stimulation in 10 drug-resistant temporal lobe epilepsy patients implanted with SEEG. Using 500,000 unique poststimulation SEEG epochs, the authors trained a multichannel 1-dimensional convolutional neural network to determine whether an SOZ had been stimulated.ResultsSOZs were classified with mean sensitivity of 78.1% and specificity of 74.6% according to leave-one-patient-out testing. To achieve maximum accuracy, the model required a 0- to 350-msec poststimulation time period. Post hoc analysis revealed that the model accurately classified unilateral versus bilateral mesial temporal lobe seizure onset, as well as neocortical SOZs.ConclusionsThis was the first demonstration, to the authors' knowledge, that a deep learning framework can be used to accurately classify SOZs with single-pulse electrical stimulation-evoked responses. These findings suggest that accurate classification of SOZs relies on a complex temporal evolution of evoked responses within 350 msec of stimulation. Validation in a larger data set could provide a practical clinical tool for the presurgical evaluation of drug-resistant epilepsy.
| S-EPMC10619627 | biostudies-literature