High-performance prediction of epilepsy surgical outcomes based on the genetic neural networks and hybrid iEEG marker

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.

Localizing seizure onset zone by a cortico-cortical evoked potentials-based machine learning approach in focal epilepsy

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.

Electromagnetic source imaging predicts surgical outcome in children with focal cortical dysplasia

OBJECTIVE

To evaluate the diagnostic accuracy of electromagnetic source imaging (EMSI) in localizing spikes and predict surgical outcome in children with drug resistant epilepsy (DRE) due to focal cortical dysplasia (FCD).

METHODS

We retrospectively analyzed magnetoencephalography (MEG) and high-density (HD-EEG) data from 23 children with FCD-associated DRE who underwent intracranial EEG and surgery. We localized spikes using equivalent current dipole (ECD) fitting, dipole clustering, and dynamical statistical parametric mapping (dSPM) on EMSI, electric source imaging (ESI), and magnetic source imaging (MSI). We calculated the distance from the seizure onset zone (DSOZ) and resection (DRES). We estimated receiver operating characteristic (ROC) curves with Youden's index (J) to predict outcome.

RESULTS

EMSI presented shorter DSOZ (15.18 ± 9.06 mm) and DRES (8.56 ± 6.24 mm) compared to ESI (DSOZ: 25.04 ± 16.20 mm, p < 0.009; DRES: 18.88 ± 17.30 mm, p < 0.03) and MSI (DSOZ: 23.37 ± 8.98 mm, p < 0.03; DRES: 15.51 ± 10.11 mm, p < 0.02) for clustering in patients with good outcome. Clustering showed shorter DSOZ and DRES compared to ECD fitting and dSPM (p < 0.05). EMSI had higher performance as outcome predictor (J = 70.63%) compared to ESI (J = 41.27%) and MSI (J = 33.33%) for clustering.

CONCLUSIONS

EMSI provides superior localization and improved predictive performance than individual modalities.

SIGNIFICANCE

EMSI can help the surgical planning and facilitate the localization of epileptogenic foci.

Ipsilateral preictal alpha rhythm attenuation (IPARA): An EEG sign of side of seizure onset in temporal lobe epilepsy

PURPOSE

Identification of the seizure onset zone is critically important for outlining the surgical plan in the treatment of pharmacoresistant focal epilepsy. In patients with temporal lobe epilepsy (TLE), bilateral ictal scalp EEG changes frequently occur and can make lateralization of the seizure onset zone difficult. We investigated the incidence and clinical utility of unilateral preictal alpha rhythm attenuation as a lateralizing sign of seizure onset in TLE.

METHODS

Scalp EEG recordings of the seizures acquired during presurgical video-EEG monitoring of 57 consecutive patients with TLE were reviewed retrospectively. Included patients had interictal baseline recordings demonstrating symmetrical posterior alpha rhythm and seizures occurring during wakefulness.

RESULTS

We identified a total of 649 seizures in the 57 patients, of which 448 seizures in 53 patients fulfilled the inclusion criteria. Among the 53 included patients, 7 patients (13.2%) exhibited a distinct attenuation of the posterior alpha rhythm prior to the first ictal EEG changes, in 26 of 112 (23.2%) included seizures. Preictal alpha rhythm attenuation in these seizures was ipsilateral to the ultimately determined side of seizure onset (based on video-EEG or intracranial EEG findings) in 22 (84.6%) of these seizures and bilateral in 4 (15.4%), and occurred on average 5.9 ± 2.6 s prior to ictal EEG onsets.

CONCLUSION

Our findings suggest that in some patients with TLE lateralized preictal attenuation of the posterior alpha rhythm may be a useful indicator of side of seizure onset, presumably due to early disruption of thalamo-temporo-occipital network function, likely mediated through the thalamus.

An application of dynamical directed connectivity of ictal intracranial EEG recordings in seizure onset zone localization

BACKGROUND

Identification of the seizure onset zone (SOZ) is a challenging task in epilepsy surgery. Patients with epilepsy have an altered brain network, allowing connectivity-based analyses to have a great potential in SOZ identification. We investigated a dynamical directed connectivity analysis utilizing ictal intracranial electroencephalographic (iEEG) recordings and proposed an algorithm for SOZ identification based on grouping iEEG contacts.

NEW METHODS

Granger Causality was used for directed connectivity analysis in this study. The intracranial contacts were grouped into visually detected contacts (VDCs), which were identified as SOZ by epileptologists, and non-resected contacts (NRCs). The intragroup and intergroup directed connectivity for VDCs and NRCs were calculated around seizure onset. We then proposed an algorithm for SOZ identification based on the cross-correlation of intragroup outflow and inflow of SOZ candidate contacts.

RESULTS

Our results revealed that the intragroup connectivity of VDCs (VDC→VDC) was significantly larger than the intragroup connectivity of NRCs (NRC→NRC) and the intergroup connectivity between NRCs and VDCs (NRC→VDC) around seizure onset. We found that the proposed algorithm had 90.1 % accuracy for SOZ identification in the seizure-free patients.

COMPARISON WITH EXISTING METHODS

The existing connectivity-based methods for SOZ identification often use either outflow or inflow. In this study, SOZ contacts were identified by integrating outflow and inflow based on the cross correlation between these two measures.

CONCLUSIONS

The proposed group-based dynamical connectivity analysis in this study can aid our understanding of underlying seizure network and may be used to assist in identifying the SOZ contacts before epilepsy surgery.

Source localization of ictal SEEG to predict postoperative seizure outcome

OBJECTIVE

Stereo-electroencephalography (SEEG) is inherently-three-dimensional and can be modeled using source localization. This study aimed to assess the validity of ictal SEEG source localization.

METHODS

The dominant frequency at ictal onset was used for source localization in the time and frequency domains using rotating dipoles and current density maps. Validity was assessed by concordance with the epileptologist-defined seizure onset zone (conventional SOZ) and the surgical treatment volume (TV) of seizure-free versus non-seizure-free patients.

RESULTS

Source localization was performed on 68 seizures from 27 patients. Median distance to nearest contact in the conventional SOZ was 7 (IQR 6-12) mm for time-domain dipoles. Current density predicted ictal activity with up to 86 % (60-87 %) accuracy. Distance from time-domain dipoles to the TV was smaller (P = 0.045) in seizure-free (2 [0-4] mm) versus non-seizure-free (12 [2-17] mm) patients, and predicted surgical outcome with 91 % sensitivity and 63 % specificity. Removing near-field data from contacts within the TV negated outcome prediction (P = 0.51).

CONCLUSIONS

Source localization of SEEG accurately mapped ictal onset compared with conventional interpretation. Proximity of dipoles to the TV predicted seizure outcome when near-field recordings were analyzed.

SIGNIFICANCE

Ictal SEEG source localization is useful in corroborating the epileptogenic zone, assuming near-field recordings are obtained.

Presurgical video-EEG monitoring with foramen ovale and epidural peg electrodes: a 25-year perspective

Background

Epilepsy surgery cases are becoming more complex and increasingly require invasive video-EEG monitoring (VEM) with intracranial subdural or intracerebral electrodes, exposing patients to substantial risks. We assessed the utility and safety of using foramen ovale (FO) and epidural peg electrodes (FOP) as a next step diagnostic approach following scalp VEM.

Methods

We analyzed clinical, electrophysiological, and imaging characteristics of 180 consecutive patients that underwent FOP VEM between 1996 and 2021. Multivariate logistic regression was used to assess predictors of clinical and electrophysiological outcomes.

Results

FOP VEM allowed for immediate resection recommendation in 36 patients (20.0%) and excluded this option in 85 (47.2%). Fifty-nine (32.8%) patients required additional invasive EEG investigations; however, only eight with bilateral recordings. FOP VEM identified the ictal onset in 137 patients, compared to 96 during prior scalp VEM, p = .004. Predictors for determination of ictal onset were temporal lobe epilepsy (OR 2.9, p = .03) and lesional imaging (OR 3.1, p = .01). Predictors for surgery recommendation were temporal lobe epilepsy (OR 6.8, p < .001), FO seizure onset (OR 6.1, p = .002), and unilateral interictal epileptic activity (OR 3.8, p = .02). One-year postsurgical seizure freedom (53.3% of patients) was predicted by FO ictal onset (OR 5.8, p = .01). Two patients experienced intracerebral bleeding without persisting neurologic sequelae.

Conclusion

FOP VEM adds clinically significant electrophysiological information leading to treatment decisions in two-thirds of cases with a good benefit–risk profile. Predictors identified for electrophysiological and clinical outcome can assist in optimally selecting patients for this safe diagnostic approach.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00415-022-11208-6.

Estimation of seizure onset zone from ictal scalp EEG using independent component analysis in extratemporal lobe epilepsy

OBJECTIVE

The purpose of this study is to localize the seizure onset zone of patients suffering from drug-resistant epilepsy. During the last two decades, multiple studies proposed the use of Independent Component Analysis (ICA) to analyze ictal electroencephalogram (EEG) recordings. This study aims at evaluating ICA potential with quantitative measurements. In particular, we address the challenging step where the components extracted by ICA of an ictal nature must be selected.

APPROACH

We considered a cohort of 10 patients suffering from extratemporal lobe epilepsy who were rendered seizure-free after surgery. Different sets of pre-processing parameters were compared and component features were explored to help distinguish ictal components from others. Quantitative measurements were implemented to determine whether some of the components returned by ICA were located within the resection zone and thus likely to be ictal. Finally, an assistance to the component selection was proposed based on the implemented features.

MAIN RESULTS

For every seizure, at least one component returned by ICA was localized within the resection zone, with the optimal pre-processing parameters. Three features were found to distinguish components localized within the resection zone: the dispersion of their active brain sources, the ictal rhythm power and the contribution to the EEG variance. Using the implemented component selection assistance based on the features, the probability that the first proposed component yields an accurate estimation reaches 51.43% (without assistance: 24.74%). The accuracy reaches 80% when considering the best result within the first five components.

SIGNIFICANCE

This study confirms the utility of ICA for ictal EEG analysis in extratemporal lobe epilepsy, and suggests relevant features to analyze the components returned by ICA. A component selection assistance is proposed to guide clinicians in their choice for ictal components.

Epileptogenic networks in drug-resistant epilepsy with amygdala enlargement: Assessment with stereo-EEG and 7 T MRI

OBJECTIVE

Amygdala enlargement is increasingly described in association with temporal lobe epilepsies. Its significance, however, remains uncertain both in terms of etiology and its link with psychiatric disorders and of its involvement in the epileptogenic zone. We assessed the epileptogenic networks underlying drug-resistant epilepsy with amygdala enlargement and investigated correlations between clinical features, epileptogenicity and morphovolumetric amygdala characteristics.

METHODS

We identified 12 consecutive patients suffering from drug-resistant epilepsy with visually suspected amygdala enlargement and available stereoelectroencephalographic recording. The epileptogenic zone was defined using the Connectivity Epileptogenicity Index. Morphovolumetric measurements were performed using automatic segmentation and co-registration on the 7TAMIbrain Amygdala atlas.

RESULTS

The epileptogenic zone involved the enlarged amygdala in all but three cases and corresponded to distributed, temporal-insular, temporal-insular-prefrontal or prefrontal-temporal networks in ten cases, while only two were temporo-mesial networks. Morphovolumetrically, amygdala enlargement was bilateral in 75% of patients. Most patients presented psychiatric comorbidities (anxiety, depression, posttraumatic stress disorder). The level of depression defined by screening questionnaire was positively correlated with the extent of amygdala enlargement.

CONCLUSIONS

Drug-resistant epilepsy with amygdala enlargement is heterogeneous; most cases implied "temporal plus" networks.

SIGNIFICANCE

The enlarged amygdala could reflect an interaction of stress-mediated limbic network alterations and mechanisms of epileptogenesis.

Ictal gamma-band interactions localize ictogenic nodes of the epileptic network in focal cortical dysplasia

OBJECTIVE

Epilepsy surgery fails in > 30% of patients with focal cortical dysplasia (FCD). The seizure persistence after surgery can be attributed to the inability to precisely localize the tissue with an endogenous potential to generate seizures. In this study, we aimed to identify the critical components of the epileptic network that were actively involved in seizure genesis.

METHODS

The directed transfer function was applied to intracranial EEG recordings and the effective connectivity was determined with a high temporal and frequency resolution. Pre-ictal network properties were compared with ictal epochs to identify regions actively generating ictal activity and discriminate them from the areas of propagation.

RESULTS

Analysis of 276 seizures from 30 patients revealed the existence of a seizure-related network reconfiguration in the gamma-band (25-170 Hz; p < 0.005) - ictogenic nodes. Unlike seizure onset zone, resecting the majority of ictogenic nodes correlated with favorable outcomes (p < 0.012).

CONCLUSION

The prerequisite to successful epilepsy surgery is the accurate identification of brain areas from which seizures arise. We show that in FCD-related epilepsy, gamma-band network markers can reliably identify and distinguish ictogenic areas in macroelectrode recordings, improve intracranial EEG interpretation and better delineate the epileptogenic zone.

SIGNIFICANCE

Ictogenic nodes localize the critical parts of the epileptogenic tissue and increase the diagnostic yield of intracranial evaluation.

Characterizing the seizure onset zone and epileptic network using EEG-fMRI in a rat seizure model

Accurate epileptogenic zone (EZ) or seizure onset zone (SOZ) localization is crucial for epilepsy surgery optimization. Previous animal and human studies on epilepsy have reported that changes in blood oxygen level-dependent (BOLD) signals induced by epileptic events could be used as diagnostic markers for EZ or SOZ localization. Simultaneous electroencephalography and functional magnetic resonance imaging (EEG-fMRI) recording is gaining interest as a non-invasive tool for preoperative epilepsy evaluation. However, EEG-fMRI studies have reported inconsistent and ambiguous findings. Therefore, it remains unclear whether BOLD responses can be used for accurate EZ or SOZ localization. In this study, we used simultaneous EEG-fMRI recording in a rat model of 4-aminopyridine-induced acute focal seizures to assess the spatial concordance between individual BOLD responses and the SOZ. This was to determine the optimal use of simultaneous EEG-fMRI recording in the SOZ localization. We observed a high spatial consistency between BOLD responses and the SOZ. Further, dynamic BOLD responses were consistent with the regions where the seizures were propagated. These results suggested that simultaneous EEG-fMRI recording could be used as a noninvasive clinical diagnostic technique for localizing the EZ or SOZ and could be an effective tool for mapping epileptic networks.

Injection of prophylactic lorazepam versus antiseizure drugs on the localization value of ictal SPECT studies and treatment-emergent adverse events: A single-center prospective study

OBJECTIVE

We aimed to examine the impact of resumption of home antiseizure drugs alone (ASD-) compared with adjunct administration of scheduled intravenous (IV) lorazepam 2 mg every 6 h (ASD+) following ictal single-photon emission computed tomography (SPECT) injection on the localization value of SPECT studies and treatment-emergent adverse events (TEAEs).

METHODS

We conducted a prospective study at Mayo Clinic inpatient epilepsy monitoring unit (EMU) between January 2018 and May 2020 in Jacksonville, Florida. The ASD- and ASD+ groups were compared for concordance of SPECT studies with the epilepsy surgical conference (ESC) consensus or intracranial electroencephalography (icEEG) findings as reference. Treatment-emergent adverse events, obtained from surveys at 24 h and one week postictal SPECT injection, were also compared between both groups.

RESULTS

Twenty-two consecutive patients with temporal (eight patients, 36%) and extratemporal (14 patients, 64%) epilepsy were included: 12 ASD+ and 10 ASD-. The two groups were well matched with regard to clinical and ictal SPECT injection characteristics including the occurrence of seizure between ictal and interictal SPECT injections. The localization value of SPECT studies was similar in the two groups. Patients in the ASD+ group reported higher rates of dizziness and excessive sedation at 24 h (p-value = 0.008). Fourteen patients (64%) underwent icEEG monitoring. For the entire cohort, the localization concordance of SPECT analysis by statistical parametric mapping (SPM) was superior to raw ictal SPECT (p-value = 0.003) and subtraction ictal SPECT coregistered to magnetic resonance imaging (MRI) (SISCOM; p-value = 0.021). Eventually, seven patients (31.8%) underwent resective brain surgery of whom four (57.1%) became seizure-free (median follow-up = 22 months).

CONCLUSIONS

Our findings suggest that resuming home ASDs without the addition of scheduled IV lorazepam following inpatient ictal SPECT injection is equally efficacious for seizure onset zone (SOZ) localization on SPECT studies, especially SPM. This approach is also associated with fewer transient TEAEs and lower financial cost with no difference in preventing seizure between ictal and interictal SPECT injections.

Auras in intractable frontal lobe epilepsy: Clinical characteristics, values, and limitations

Auras are essential in preoperative evaluation and can provide valuable information for delineating seizure onset zones. Frontal lobe epilepsy (FLE) is the second most common focal epilepsy, while a few studies have focused on auras in FLE. To better understand FLE, we analyzed the clinical characteristics, values, and limitations of auras in FLE. The incidence rate of aura in FLE was 37.9% in our study. We included 54 patients and 76 auras in 11 categories were reported. The rate of auras in the decreasing order are as follows: autonomic aura; emotional aura; somatosensory aura; psychic aura; cephalic aura; abdominal aura; whole-body sensory aura, visual aura; auditory aura; and vestibular and unclassified aura. A significant number of aura types can be reported by FLE patients; autonomic aura was the most frequent category and somatosensory auras are most likely associated with the contralateral motor areas.

Prediction of seizure freedom after epilepsy surgery - Critical reappraisal of significance of intracranial EEG parameters

OBJECTIVE

To analyze the significance of intracranial electroencephalography (iEEG) parameters such as seizure onset patterns (SOP) and size of seizure onset zone (SOZ) with respect to prediction of seizure freedom after resective epilepsy surgery.

METHODS

All patients who underwent iEEG with subdural electrodes between January 2006 and December 2015 in our epilepsy-center were included. Various iEEG parameters were retrospectively analyzed regarding their predictive value to post-operative seizure freedom. Furthermore, associations of specific SOPs with underlying histopathology and brain regions of the SOZ were examined.

RESULTS

Eighty-one patients (34 female) with 324 seizures were assessed. Low-voltage fast activity (37%) and sharp activity <13 Hz (30%) were the most frequent SOPs. Focal SOZ (≤2 cm) was the only iEEG parameter independently associated with 1-year post-operative seizure freedom (OR 4.1, 95% CI 1.433-11.679). While no SOP was linked to specific histopathologies, some associations between SOPs and anatomical regions of SOZ were found.

CONCLUSIONS

A circumscribed SOZ, but no specific SOP was predictive for seizure freedom after epilepsy surgery.

SIGNIFICANCE

Intracranial EEG may be helpful to predict post-operative seizure freedom. Multicenter studies with larger numbers of patients are required to reliably assess the significance of specific SOPs for successful resective epilepsy surgery.

Ictal EEG source localization in focal epilepsy: Review and future perspectives

Electroencephalographic (EEG) source imaging localizes the generators of neural activity in the brain. During presurgical epilepsy evaluation, EEG source imaging of interictal epileptiform discharges is an established tool to estimate the irritative zone. However, the origin of interictal activity can be partly or fully discordant with the origin of seizures. Therefore, source imaging based on ictal EEG data to determine the seizure onset zone can provide precious clinical information. In this descriptive review, we address the importance of localizing the seizure onset zone based on noninvasive EEG recordings as a complementary analysis that might reduce the burden of the presurgical evaluation. We identify three major challenges (low signal-to-noise ratio of the ictal EEG data, spread of ictal activity in the brain, and validation of the developed methods) and discuss practical solutions. We provide an extensive overview of the existing clinical studies to illustrate the potential clinical utility of EEG-based localization of the seizure onset zone. Finally, we conclude with future perspectives and the needs for translating ictal EEG source imaging into clinical practice.

Enhanced Regional Functional Connectivity Indicates Seizure Onset Zone

This project aims to explore if stronger functional connectivity (FC) exists in the maximal BOLD response of EEG/fMRI analysis when it is concordant with seizure-onset-zone (SOZ). Twenty-six patients with drug-resistant focal epilepsy who had an EEG/fMRI and later underwent stereo-EEG implantation were included. Different types of IEDs were labeled in scalp EEG and IED-related maximal BOLD responses were evaluated separately, each constituting one study. After evaluating concordance between maximal BOLD and SOZ, twenty-seven studies were placed in the concordant group and eight in the discordant group. We evaluated the local connectivity and ipsilaterally distant connectivity difference between the maximal BOLD and the contralateral homotopic region. Significantly stronger local FC was found for the maximal BOLD in the concordant group (p < 0.05, Bonferroni corrected). 52% of the studies in the concordant group and 13% in the discordant group had a significant difference compared to healthy subjects (p < 0.05, uncorrected). The finding suggests that, when concordant with the SOZ, the maximal BOLD is more likely to have stronger local FC compared to its contralateral counterpart. This asymmetry in functional connectivity may help to noninvasively improve the specificity of EEG/fMRI analysis.

Epileptogenicity Mapping: A Quantitative Approach to Identify the Seizure Onset

During the presurgical evaluation of patients with focal refractory epilepsies, the spatial mapping of the seizure onset zone (SOZ) and seizure propagation networks critically depends on the use of different features extracted from the intracranial electroencephalogram (IEEG). The identification of the SOZ is usually based on visual inspection by highly qualified neurophysiologists. However, quantitative IEEG analyses have recently been developed by exploiting signal and image characteristics in order to improve and expedite the SOZ detection. Here, the authors briefly review some of the latest methods proposed by different research groups and then present the recent implementation in Brainstorm software.

Ictal and interictal source imaging on intracranial EEG predicts epilepsy surgery outcome in children with focal cortical dysplasia

OBJECTIVE

To localize the seizure onset zone (SOZ) and irritative zone (IZ) using electric source imaging (ESI) on intracranial EEG (iEEG) and assess their clinical value in predicting epilepsy surgery outcome in children with focal cortical dysplasia (FCD).

METHODS

We analyzed iEEG data from 25 children with FCD-associated medically refractory epilepsy (MRE) who underwent surgery. We performed ESI on ictal onset to localize SOZ (ESI-SOZ) and on interictal discharges to localize IZ (ESI-IZ). We tested whether resection of ESI-SOZ and ESI-IZ predicted good surgical outcome (Engel 1). We further compared the prediction performance of ESI-SOZ and ESI-IZ to those of SOZ and IZ defined using conventional methods, i.e. by identifying iEEG-contacts showing ictal onsets (conventional-SOZ) or being the most interictally active (conventional-IZ).

RESULTS

The proximity of ESI-SOZ (p = 0.043, odds-ratio = 3.9) and ESI-IZ (p = 0.011, odds-ratio = 7.04) to resection has higher effect on patients' outcome than proximity of conventional-SOZ (p = 0.17, odds-ratio = 1.7) and conventional-IZ (p = 0.038, odds-ratio = 2.6). Resection of ESI-SOZ and ESI-IZ presented higher discriminative power in predicting outcome (68% and 60%) than conventional-SOZ and conventional-IZ (48% and 53%).

CONCLUSIONS

Localizing SOZ and IZ via ESI on iEEG offers higher predictive value compared to conventional-iEEG interpretation.

SIGNIFICANCE

iEEG-ESI may help surgical planning and facilitate prognostic assessment of children with FCD-associated MRE.

Low entropy map of brain oscillatory activity identifies spatially localized events: A new method for automated epilepsy focus prediction

The spatial mapping of localized events in brain activity critically depends on the correct identification of the pattern signatures associated with those events. For instance, in the context of epilepsy research, a number of different electrophysiological patterns have been associated with epileptogenic activity. Motivated by the need to define automated seizure focus detectors, we propose a novel data-driven algorithm for the spatial identification of localized events that is based on the following rationale: the distribution of emerging oscillations during confined events across all recording sites is highly non-uniform and can be mapped using a spatial entropy function. By applying this principle to EEG recording obtained from 67 distinct seizure epochs, our method successfully identified the seizure focus on a group of ten drug-resistant temporal lobe epilepsy patients (average sensitivity: 0.94, average specificity: 0.90) together with its characteristic electrophysiological pattern signature. Cross-validation of the method outputs with postresective information revealed the consistency of our findings in long follow-up seizure-free patients. Overall, our methodology provides a reliable computational procedure that might be used as in both experimental and clinical domains to identify the neural populations undergoing an emerging functional or pathological transition.

Quantitative Analysis of [18F]FFMZ and [18F]FDG PET Studies in the Localization of Seizure Onset Zone in Drug-Resistant Temporal Lobe Epilepsy

BACKGROUND

Positron emission tomography (PET) imaging in epilepsy is an in vivo technique that allows the localization of a possible seizure onset zone (SOZ) during the interictal period. Stereo-electro-encephalography (SEEG) is the gold standard to define the SOZ. The objective of this research was to evaluate the accuracy of PET imaging in localizing the site of SOZ compared with SEEG.

METHODS

Seven patients with refractory temporal lobe epilepsy (Ep) and 2 healthy controls (HC) underwent 2 PET scans, one with 2-[18F]-fluoro-2-deoxy-D-glucose (FDG) and another with 2'-[18F]fluoroflumazenil (FFMZ), acquired 1 day apart. FDG was acquired for 10 min (static scan) 1 h after administration. An FFMZ scan was acquired for 60 min from radiopharmaceutical administration in a dynamic mode. Each brain PET image was segmented using a standard template implemented in PMOD 3.8. The pons was used as the reference region for modeling of the nondisplaceable binding potential (BPND)for FFMZ, and to obtain uptake ratios for FDG. SEEG studies of patients were performed as a part of their surgical evaluation to define the SOZ.

RESULTS

Well-defined differences between HC and Ep were found with both radiopharmaceuticals, showing the utility to identify abnormal brain regions using quantitative PET imaging. Lateralization of the SOZ findings by PET (lower uptake/binding in a specific brain hemisphere) matched in 86% for FFMZ and 71% for FDG with SEEG data.

CONCLUSION

Quantitative PET imaging is an excellent complementary tool that matches reasonably well with SEEG to define SOZ in presurgical evaluation.

Low entropy of interictal gamma oscillations is a biomarker of the seizure onset zone in focal cortical dysplasia type II

OBJECTIVE

Dynamic changes in the regularity of interictal gamma oscillations (GOs, 30-70 Hz) on intracranial electroencephalography (EEG) reflect focal ictogenesis with epileptogenic neuronal synchronization in focal cortical dysplasia (FCD). We investigated whether the regularity of interictal GOs is a biomarker of the seizure onset zone (SOZ) using multiscale entropy analysis.

METHODS

We quantified the regularity of interictal GOs using intracranial EEG data from 1164 electrodes in 13 patients with FCD who were seizure-free postoperatively. The regularity of interictal GOs was quantified as entropy values. Low entropy represents high regularity. We standardized entropy values using Z values for each SOZ, resection area (RA), and the region outside the RA. The cutoff Z values, sensitivity, and specificity for detecting each area were calculated using area under the receiver operating characteristics curves (AUCs).

RESULTS

Low Z values represent higher regularity of GOs. The cutoff Z value of ≤-2.09 for the SOZ had a sensitivity of 100% and specificity of 97.1% (AUC = 0.992 ± 0.002). The cutoff Z value of ≤-0.12 for the RA had a sensitivity of 54.2% and specificity of 73.8% (AUC = 0.673 ± 0.019). The cutoff Z value of ≥-0.11 for the region outside the RA had a sensitivity of 73.8% and specificity of 54.2% (AUC = 0.673 ± 0.019).

CONCLUSIONS

Low entropy of interictal GOs was a reliable biomarker for the SOZ. Maintained high entropy of interictal GOs may be an auxiliary biomarker for nonepileptogenic regions.

SIGNIFICANCE

Low entropy of interictal GOs may be a biomarker for the SOZ in FCD type II.

The predictive value of hypometabolism in focal epilepsy: a prospective study in surgical candidates

PURPOSE

FDG PET is an established tool in presurgical epilepsy evaluation, but it is most often used selectively in patients with discordant MRI and EEG results. Interpretation is complicated by the presence of remote or multiple areas of hypometabolism, which leads to doubt as to the true location of the seizure onset zone (SOZ) and might have implications for predicting the surgical outcome. In the current study, we determined the sensitivity and specificity of PET localization prospectively in a consecutive unselected cohort of patients with focal epilepsy undergoing in-depth presurgical evaluation.

METHODS

A total of 130 patients who underwent PET imaging between 2006 and 2015 matched our inclusion criteria, and of these, 86 were operated on (72% with a favourable surgical outcome, Engel class I). Areas of focal hypometabolism were identified using statistical parametric mapping and concordance with MRI, EEG and intracranial EEG was evaluated. In the surgically treated patients, postsurgical outcome was used as the gold standard for correctness of localization (minimum follow-up 12 months).

RESULTS

PET sensitivity and specificity were both 95% in 86 patients with temporal lobe epilepsy (TLE) and 80% and 95%, respectively, in 44 patients with extratemporal epilepsy (ETLE). Significant extratemporal hypometabolism was observed in 17 TLE patients (20%). Temporal hypometabolism was observed in eight ETLE patients (18%). Among the 86 surgically treated patients, 26 (30%) had hypometabolism extending beyond the SOZ. The presence of unilobar hypometabolism, included in the resection, was predictive of complete seizure control (p = 0.007), with an odds ratio of 5.4.

CONCLUSION

Additional hypometabolic areas were found in one of five of this group of nonselected patients with focal epilepsy, including patients with "simple" lesional epilepsy, and this finding should prompt further in-depth evaluation of the correlation between EEG findings, semiology and PET. Hypometabolism confined to the epileptogenic zone as defined by EEG and MRI is associated with a favourable postoperative outcome in both TLE and ETLE patients.

DC shifts, high frequency oscillations, ripples and fast ripples in relation to the seizure onset zone

Efforts to improve epilepsy surgery outcomes have led to increased interest in the study of electroencephalographic oscillations outside the conventional EEG bands. These include fast activity above the gamma band, known as high frequency oscillations (HFOs), and infraslow activity (ISA) below the delta band, sometimes referred to as direct current (DC) or ictal baseline shifts (IBS). HFOs in particular have been extensively studied as potential biomarkers for epileptogenic tissue in light of evidence showing that resection of brain tissue containing HFOs is associated with good surgical outcomes. Not all HFOs are conclusively pathological, however, as they can be recorded in nonepileptic tissue and induced by cognitive, visual, or motor tasks. Consequently, efforts to distinguish between pathological and physiological HFOs have identified several traits specific to pathological HFOs, such as coupling with interictal spikes, association with delta waves, and stereotypical morphologies. On the opposite end of the EEG spectrum, sub-delta oscillations have been shown to co-localize with the seizure onset zones (SOZ) and appear in a narrower spatial distribution than activity in the conventional EEG frequency bands. In this report, we review studies that implicate HFOs and ISA in ictogenesis and discuss current limitations such as inter-observer variability and poor standardization of recording techniques. Furthermore, we propose that HFOs and ISA should be analyzed in addition to activity in the conventional EEG band during intracranial presurgical EEG monitoring to identify the best possible surgical margin.

Widespread interictal epileptic discharge more likely than focal discharges to unveil the seizure onset zone in EEG-fMRI

OBJECTIVE

We hypothesized that the number of interictal epileptic discharges (IEDs) during scan and their spatial extent are contributing factors in obtaining appropriate activations that reveal the seizure onset zone (SOZ) in EEG-fMRI.

METHODS

157 IED types, each corresponding to one EEG scalp distribution, in 64 consecutive EEG-fMRI studies from 64 patients with refractory localization-related epilepsy were reviewed. To determine reliable activation, we used the threshold corresponding to corrected whole-brain topological false discovery rate (FDR). The location with maximum activation was compared to the presumed SOZ as defined by a comprehensive evaluation for each patient.

RESULTS

The number of IEDs was significantly higher in the types with t-value above FDR than with t-value below FDR. The presumed SOZ could be delineated in 30 of the 64 patients. Among these patients, the types of IED concordant with the SOZ had significantly larger extent on scalp EEG than the IED types discordant with the SOZ.

CONCLUSIONS

The number of IEDs is important factor in obtaining reliable activations in EEG-fMRI. IEDs with larger spatial extent are more likely to reveal, on maximum BOLD, accurate location of the SOZ.

SIGNIFICANCE

Widespread discharges are more likely to yield a reliable activation for SOZ in EEG-fMRI.

Transient seizure onset network for localization of epileptogenic zone: effective connectivity and graph theory-based analyses of ECoG data in temporal lobe epilepsy

OBJECTIVE

Abnormal and dynamic epileptogenic networks cause difficulties for clinical epileptologists in the localization of the seizure onset zone (SOZ) and the epileptogenic zone (EZ) in preoperative assessments of patients with refractory epilepsy. The aim of this study is to investigate the characteristics of time-varying effective connectivity networks in various non-seizure and seizure periods, and to propose a quantitative approach for accurate localization of SOZ and EZ.

METHODS

We used electrocorticogram recordings in the temporal lobe and hippocampus from seven patients with temporal lobe epilepsy to characterize the effective connectivity dynamics at a high temporal resolution using the full-frequency adaptive directed transfer function (ffADTF) measure and five graph metrics, i.e., the out-degree (OD), closeness centrality (CC), betweenness centrality (BC), clustering coefficient (C), and local efficiency (LE). The ffADTF effective connectivity network was calculated and described in five frequency bands (δ, θ, α, β, and γ) and five seizure periods (pre-seizure, early seizure, mid-seizure, late seizure, and post-seizure). The cortical areas with high values of graph metrics in the transient seizure onset network were compared with the SOZ and EZ identified by clinical epileptologists and the results of epilepsy resection surgeries.

RESULTS

Origination and propagation of epileptic activity were observed in the high time resolution ffADTF effective connectivity network throughout the entire seizure period. The seizure-specific transient seizure onset ffADTF network that emerged at seizure onset time remained for approximately 20-50 ms with strong connections generated from both SOZ and EZ. The values of graph metrics in the SOZ and EZ were significantly larger than that in the other cortical areas. More cortical areas with the highest mean of graph metrics were the same as the clinically determined SOZ in the low-frequency δ and θ bands and in Engel Class I patients than in higher frequency α, β, and γ bands and in Engel Class II and III patients. The OD and C were more likely to localize the SOZ and EZ than CC, BC, and LE in the transient seizure onset network.

CONCLUSION

The high temporal resolution ffADTF effective connectivity analysis combined with the graph theoretical analysis helps us to understand how epileptic activity is generated and propagated during the seizure period. The newly discovered seizure-specific transient seizure onset network could be an important biomarker and a promising tool for more precise localization of the SOZ and EZ in preoperative evaluations.

Theta band network supporting human episodic memory is not activated in the seizure onset zone

Episodic memory, everyday memory for events, is frequently impaired in patients with epilepsy. We tested patients undergoing intracranial electroencephalography (intracranial EEG) monitoring for the treatment of medically-refractory epilepsy on a well-characterized paradigm that requires episodic memory. We report that an anatomically diffuse network characterized by theta-band (4-7 Hz) coherence is activated at the time of target selection in a task that requires episodic memory. This distinct network of oscillatory activity is absent when episodic memory is not required. Further, the theta band synchronous network was absent in electrodes within the patient's seizure onset zone (SOZ). Our data provide novel empirical evidence for a set of brain areas that supports episodic memory in humans, and it provides a pathophysiologic mechanism for the memory deficits observed in patients with epilepsy.

High-frequency oscillations detected in ECoG recordings correlate with cavernous malformation and seizure-free outcome in a child with focal epilepsy: A case report

Epilepsy associated with cavernous malformation (CM) often requires surgical resection of seizure focus to achieve seizure‐free outcome. High‐frequency oscillations (HFOs) in intracranial electroencephalogram (EEG) are reported as potential biomarkers of epileptogenic regions, but to our knowledge there are no data on the existence of HFOs in CM‐caused epilepsy. Here we report our experience of the identification of the seizure focus in a 3‐year‐old pediatric patient with intractable epilepsy associated with CM. The electrocorticographic recordings were obtained from a 64‐contact grid over 2 days in the epilepsy monitoring unit (EMU). The spatial distribution of HFOs and epileptic spikes were estimated from recording segments right after the electrode placement, during sleep and awake states separately. The HFO distribution showed consistency with the perilesional region; the location of spikes varied over days and did not correlate with the lesion. The HFO spatial distribution was more compact in sleep state and pinpointed the contacts sitting on the CM border. Following the resection of the CM and the hemosiderin ring, the patient became seizure‐free. This is the first report describing HFOs in a pediatric patient with intractable epilepsy associated with CM and shows their potential in identifying the seizure focus.

Universal automated high frequency oscillation detector for real-time, long term EEG

OBJECTIVE

Interictal high frequency oscillations (HFOs) in intracranial EEG are a potential biomarker of epilepsy, but current automated HFO detectors require human review to remove artifacts. Our objective is to automatically redact false HFO detections, facilitating clinical use of interictal HFOs.

METHODS

Intracranial EEG data from 23 patients were processed with automated detectors of HFOs and artifacts. HFOs not concurrent with artifacts were labeled quality HFOs (qHFOs). Methods were validated by human review on a subset of 2000 events. The correlation of qHFO rates with the seizure onset zone (SOZ) was assessed via (1) a retrospective asymmetry measure and (2) a novel quasi-prospective algorithm to identify SOZ.

RESULTS

Human review estimated that less than 12% of qHFOs are artifacts, whereas 78.5% of redacted HFOs are artifacts. The qHFO rate was more correlated with SOZ (p=0.020, Wilcoxon signed rank test) and resected volume (p=0.0037) than baseline detections. Using qHFOs, our algorithm was able to determine SOZ in 60% of the ILAE Class I patients, with all algorithmically-determined SOZs fully within the resected volumes.

CONCLUSIONS

The algorithm reduced false-positive HFO detections, improving the precision of the HFO-biomarker.

SIGNIFICANCE

These methods provide a feasible strategy for HFO detection in real-time, continuous EEG with minimal human monitoring of data quality.

Identification of seizure onset zone and preictal state based on characteristics of high frequency oscillations

OBJECTIVE

We investigate the relevance of high frequency oscillations (HFO) for biomarkers of epileptogenic tissue and indicators of preictal state before complex partial seizures in humans.

METHODS

We introduce a novel automated HFO detection method based on the amplitude and features of the HFO events. We examined intracranial recordings from 33 patients and compared HFO rates and characteristics between channels within and outside the seizure onset zone (SOZ). We analyzed changes of HFO activity from interictal to preictal and to ictal periods.

RESULTS

The average HFO rate is higher for SOZ channels compared to non-SOZ channels during all periods. Amplitudes and durations of HFO are higher for events within the SOZ in all periods compared to non-SOZ events, while their frequency is lower. All analyzed HFO features increase for the ictal period.

CONCLUSIONS

HFO may occur in all channels but their rate is significantly higher within SOZ and HFO characteristics differ from HFO outside the SOZ, but the effect size of difference is small.

SIGNIFICANCE

The present results show that based on accumulated dataset it is possible to distinguish HFO features different for SOZ and non-SOZ channels, and to show changes in HFO characteristics during the transition from interictal to preictal and to ictal periods.

Ictal propagation of high frequency activity is recapitulated in interictal recordings: effective connectivity of epileptogenic networks recorded with intracranial EEG

Seizures are increasingly understood to arise from epileptogenic networks across which ictal activity is propagated and sustained. In patients undergoing invasive monitoring for epilepsy surgery, high frequency oscillations have been observed within the seizure onset zone during both ictal and interictal intervals. We hypothesized that the patterns by which high frequency activity is propagated would help elucidate epileptogenic networks and thereby identify network nodes relevant for surgical planning. Intracranial EEG recordings were analyzed with a multivariate autoregressive modeling technique (short-time direct directed transfer function--SdDTF), based on the concept of Granger causality, to estimate the directionality and intensity of propagation of high frequency activity (70-175 Hz) during ictal and interictal recordings. These analyses revealed prominent divergence and convergence of high frequency activity propagation at sites identified by epileptologists as part of the ictal onset zone. In contrast, relatively little propagation of this activity was observed among the other analyzed sites. This pattern was observed in both subdural and depth electrode recordings of patients with focal ictal onset, but not in patients with a widely distributed ictal onset. In patients with focal ictal onsets, the patterns of propagation recorded during pre-ictal (up to 5 min immediately preceding ictal onset) and interictal (more than 24h before and after seizures) intervals were very similar to those recorded during seizures. The ability to characterize epileptogenic networks from interictal recordings could have important clinical implications for epilepsy surgery planning by reducing the need for prolonged invasive monitoring to record spontaneous seizures.

Occurrence of scalp-fast oscillations among patients with different spiking rate and their role as epileptogenicity marker

INTRODUCTION

We aim to analyze the fast oscillations in the scalp EEG of focal epilepsy patients with low-to-high rates of interictal epileptiform discharges (IEDs), in order to determine how this neurophysiological feature influences fast oscillation occurrence and their significance as markers of the seizure onset zone (SOZ).

METHODS

Thirty-two patients were studied, subdivided in four categories based on IED frequency: groups A, B and C respectively with high, intermediate and low IED rate, and group D with no IED. Thirty minutes of slow-wave sleep EEG, low-pass filtered at 300Hz and sampled at 1000Hz, were reviewed. IEDs and fast oscillations (gamma activity, 40-80Hz; and ripples, >80Hz) were marked. Each channel was classified as inside or outside the irritative zone and the SOZ. We calculated the number and rates of IEDs and fast oscillation, their co-occurrence, their frequency in the irritative zone and SOZ, and the specificity, sensitivity and accuracy to determine the SOZ in the overall population and separately for each group.

RESULTS

We analyzed 984 channels. Group A (high IED rate) showed the highest fast oscillation rate (gamma: 0.37±0.73; ripples: 0.17±0.26), followed by group B (gamma: 0.08±0.06; ripples: 0.07±0.05), group C (gamma: 0.06±0.06; ripples: 0.04±0.01), and finally group D, with very low values (gamma: 0.03±0; ripples: 0.03±0). IEDs co-occurred with gamma in 9.5% and with ripples in 3.2%; and gamma and ripples co-occurred with IEDs in 46.2% and 44.4%, respectively. The fast oscillations were more frequent inside than outside the irritative zone and the SOZ (p<0.001). Compared to the IEDs, the fast oscillations were less sensitive (sensitivity: IEDs 78%, gamma 66% and ripples 48%) but more specific (specificity: IEDs 50%, gamma 76% and ripples 83%) and accurate (accuracy: IEDs 54%, gamma 74% and ripples 77%) in identifying the SOZ; the same results were reproduced for the different groups separately.

CONCLUSIONS

This study confirms that fast oscillations can be recorded from the scalp EEG. Gamma activity and ripples are more frequent in patients with frequent IEDs and, in general, inside the irritative zone. However, compared to IEDs, gamma and ripples are less sensitive but more specific and accurate in identifying the SOZ, and this remains in patients with low fast oscillation rates. These findings suggest that IEDs and fast oscillations could share some common neuronal network, but gamma activity and ripples are a better biomarker of epileptogenicity.