Development of a stereo-EEG based seizure matching system for clinical decision making in epilepsy surgery.

Objective.The proportion of patients becoming seizure-free after epilepsy surgery has stagnated. Large multi-center stereo-electroencephalography (SEEG) datasets can allow comparing new patients to past similar cases and making clinical decisions with the knowledge of how cases were treated in the past. However, the complexity of these evaluations makes the manual search for similar patients impractical. We aim to develop an automated system that electrographically and anatomically matches seizures to those in a database. Additionally, since features that define seizure similarity are unknown, we evaluate the agreement and features among experts in classifying similarity.Approach.We utilized 320 SEEG seizures from 95 consecutive patients who underwent epilepsy surgery. Eight international experts evaluated seizure-pair similarity using a four-level similarity score. As our primary outcome, we developed and validated an automated seizure matching system by employing patient data marked by independent experts. Secondary outcomes included the inter-rater agreement (IRA) and features for classifying seizure similarity.Main results.The seizure matching system achieved a median area-under-the-curve of 0.76 (interquartile range, 0.1), indicating its feasibility. Six distinct seizure similarity features were identified and proved effective: onset region, onset pattern, propagation region, duration, extent of spread, and propagation speed. Among these features, the onset region showed the strongest correlation with expert scores (Spearman's rho = 0.75,p< 0.001). Additionally, the moderate IRA confirmed the practicality of our approach with an agreement of 73.9% (7%), and Gwet's kappa of 0.45 (0.16). Further, the interoperability of the system was validated on seizures from five centers.Significance.We demonstrated the feasibility and validity of a SEEG seizure matching system across patients, effectively mirroring the expertise of epileptologists. This novel system can identify patients with seizures similar to that of a patient being evaluated, thus optimizing the treatment plan by considering the results of treating similar patients in the past, potentially improving surgery outcome.

Intracerebral Dynamics of Sleep Arousals: A Combined Scalp-Intracranial EEG Study.

As an intrinsic component of sleep architecture, sleep arousals represent an intermediate state between sleep and wakefulness and are important for sleep-wake regulation. They are defined in an all-or-none manner, whereas they actually present a wide range of scalp-electroencephalography (EEG) activity patterns. It is poorly understood how these arousals differ in their mechanisms. Stereo-EEG (SEEG) provides the unique opportunity to record intracranial activities in superficial and deep structures in humans. Using combined polysomnography and SEEG, we quantitatively categorized arousals during nonrapid eye movement sleep into slow wave (SW) and non-SW arousals based on whether they co-occurred with a scalp-EEG SW event. We then investigated their intracranial correlates in up to 26 brain regions from 26 patients (12 females). Across both arousal types, intracranial theta, alpha, sigma, and beta activities increased in up to 25 regions (p < 0.05; d = 0.06-0.63), while gamma and high-frequency (HF) activities decreased in up to 18 regions across the five brain lobes (p < 0.05; d = 0.06-0.44). Intracranial delta power widely increased across five lobes during SW arousals (p < 0.05 in 22 regions; d = 0.10-0.39), while it widely decreased during non-SW arousals (p < 0.05 in 19 regions; d = 0.10-0.30). Despite these main patterns, unique activities were observed locally in some regions such as the hippocampus and middle cingulate cortex, indicating spatial heterogeneity of arousal responses. Our results suggest that non-SW arousals correspond to a higher level of brain activation than SW arousals. The decrease in HF activities could potentially explain the absence of awareness and recollection during arousals.

Timing matters for accurate identification of the epileptogenic zone.

OBJECTIVE: Interictal biomarkers of the epileptogenic zone (EZ) and their use in machine learning models open promising avenues for improvement of epilepsy surgery evaluation. Currently, most studies restrict their analysis to short segments of intracranial EEG (iEEG). METHODS: We used 2381 hours of iEEG data from 25 patients to systematically select 5-minute segments across various interictal conditions. Then, we tested machine learning models for EZ localization using iEEG features calculated within these individual segments or across them and evaluated the performance by the area under the precision-recall curve (PRAUC). RESULTS: On average, models achieved a score of 0.421 (the result of the chance classifier was 0.062). However, the PRAUC varied significantly across the segments (0.323-0.493). Overall, NREM sleep achieved the highest scores, with the best results of 0.493 in N2. When using data from all segments, the model performed significantly better than single segments, except NREM sleep segments. CONCLUSIONS: The model based on a short segment of iEEG recording can achieve similar results as a model based on prolonged recordings. The analyzed segment should, however, be carefully and systematically selected, preferably from NREM sleep. SIGNIFICANCE: Random selection of short iEEG segments may give rise to inaccurate localization of the EZ.

Four Atypical Cases of Subclinical Rhythmic Electroencephalogram Discharge of Adults: Case Series and Review.

SUMMARY: Subclinical rhythmic EEG discharge of adults is an uncommon variant that represents a diagnostic challenge in the clinical practice because it can be mistaken for an electrographic seizure. We present a case series of four patients who underwent EEG because of suspicious events or an unclear medical history of epilepsy. In all cases, the EEG revealed atypical features including focal and asymmetric distribution, presentation during NREM and REM sleep, rhythmic activity in the delta range with a notched appearance and blocked by eyes opening.

mTOR Pathway Somatic Pathogenic Variants in Focal Malformations of Cortical Development: Novel Variants, Topographic Mapping, and Clinical Outcomes.

Background and Objectives: Somatic and germline pathogenic variants in genes of the mammalian target of rapamycin (mTOR) signaling pathway are a common mechanism underlying a subset of focal malformations of cortical development (FMCDs) referred to as mTORopathies, which include focal cortical dysplasia (FCD) type II, subtypes of polymicrogyria, and hemimegalencephaly. Our objective is to screen resected FMCD specimens with mTORopathy features on histology for causal somatic variants in mTOR pathway genes, describe novel pathogenic variants, and examine the variant distribution in relation to neuroimaging, histopathologic classification, and clinical outcomes. Methods: We performed ultra-deep sequencing using a custom HaloPlexHS Target Enrichment kit in DNA from 21 resected fresh-frozen histologically confirmed FCD type II, tuberous sclerosis complex, or hemimegalencephaly specimens. We mapped the variant alternative allele frequency (AAF) across the resected brain using targeted ultra-deep sequencing in multiple formalin-fixed paraffin-embedded tissue blocks. We also functionally validated 2 candidate somatic MTOR variants and performed targeted RNA sequencing to validate a splicing defect associated with a novel DEPDC5 variant. Results: We identified causal mTOR pathway gene variants in 66.7% (14/21) of patients, of which 13 were somatic with AAF ranging between 0.6% and 12.0%. Moreover, the AAF did not predict balloon cell presence. Favorable seizure outcomes were associated with genetically clear resection borders. Individuals in whom a causal somatic variant was undetected had excellent postsurgical outcomes. In addition, we demonstrate pathogenicity of the novel c.4373_4375dupATG and candidate c.7499T>A MTOR variants in vitro. We also identified a novel germline aberrant splice site variant in DEPDC5 (c.2802-1G>C). Discussion: The AAF of somatic pathogenic variants correlated with the topographic distribution, histopathology, and postsurgical outcomes. Moreover, cortical regions with absent histologic FCD features had negligible or undetectable pathogenic variant loads. By contrast, specimens with frank histologic abnormalities had detectable pathogenic variant loads, which raises important questions as to whether there is a tolerable variant threshold and whether surgical margins should be clean, as performed in tumor resections. In addition, we describe 2 novel pathogenic variants, expanding the mTORopathy genetic spectrum. Although most pathogenic somatic variants are located at mutation hotspots, screening the full-coding gene sequence remains necessary in a subset of patients.

Estimation of fMRI responses related to epileptic discharges using Bayesian hierarchical modeling.

Simultaneous electroencephalography-functional MRI (EEG-fMRI) is a unique and noninvasive method for epilepsy presurgical evaluation. When selecting voxels by null-hypothesis tests, the conventional analysis may overestimate fMRI response amplitudes related to interictal epileptic discharges (IEDs), especially when IEDs are rare. We aimed to estimate fMRI response amplitudes represented by blood oxygen level dependent (BOLD) percentage changes related to IEDs using a hierarchical model. It involves the local and distributed hemodynamic response homogeneity to regularize estimations. Bayesian inference was applied to fit the model. Eighty-two epilepsy patients who underwent EEG-fMRI and subsequent surgery were included in this study. A conventional voxel-wise general linear model was compared to the hierarchical model on estimated fMRI response amplitudes and on the concordance between the highest response cluster and the surgical cavity. The voxel-wise model overestimated fMRI responses compared to the hierarchical model, evidenced by a practically and statistically significant difference between the estimated BOLD percentage changes. Only the hierarchical model differentiated brief and long-lasting IEDs with significantly different BOLD percentage changes. Overall, the hierarchical model outperformed the voxel-wise model on presurgical evaluation, measured by higher prediction performance. When compared with a previous study, the hierarchical model showed higher performance metric values, but the same or lower sensitivity. Our results demonstrated the capability of the hierarchical model of providing more physiologically reasonable and more accurate estimations of fMRI response amplitudes induced by IEDs. To enhance the sensitivity of EEG-fMRI for presurgical evaluation, it may be necessary to incorporate more appropriate spatial priors and bespoke decision strategies.

Rapid eye movement sleep affects interictal epileptic activity differently in mesiotemporal and neocortical areas.

OBJECTIVE: Rapid eye movement (REM) sleep reduces the rate and extent of interictal epileptiform discharges (IEDs). Breakthrough epileptic activity during REM sleep is therefore thought to best localize the seizure onset zone (SOZ). We utilized polysomnography combined with direct cortical recordings to investigate the influences of anatomical locations and the time of night on the suppressive effect of REM sleep on IEDs. METHODS: Forty consecutive patients with drug-resistant focal epilepsy underwent combined polysomnography and stereo-electroencephalography during presurgical evaluation. Ten-minute interictal epochs were selected 2 h prior to sleep onset (wakefulness), and from the first and second half of the night during non-REM (NREM) sleep and REM sleep. IEDs were detected automatically across all channels. Anatomic localization, time of night, and channel type (within or outside the SOZ) were tested as modulating factors. RESULTS: Relative to wakefulness, there was a suppression of IEDs by REM sleep in neocortical regions (median = -27.6%), whereas mesiotemporal regions showed an increase in IEDs (19.1%, p = .01, d = .39). This effect was reversed when comparing the regional suppression of IEDs by REM sleep relative to NREM sleep (-35.1% in neocortical, -58.7% in mesiotemporal, p < .001, d = .39). Across all patients, no clinically relevant novel IED regions were observed in REM sleep versus NREM or wakefulness based on our predetermined thresholds (4 IEDs/min in REM, 0 IEDs/min in NREM and wakefulness). Finally, there was a reduction in IEDs in late (NREM: 1.08/min, REM: .61/min) compared to early sleep (NREM: 1.22/min, REM: .69/min) for both NREM (p < .001, d = .21) and REM (p = .04, d = .14). SIGNIFICANCE: Our results demonstrate a spatiotemporal effect of IED suppression by REM sleep relative to wakefulness in neocortical but not mesiotemporal regions, and in late versus early sleep. This suggests the importance of considering sleep stage interactions and the potential influences of anatomical locations when using IEDs to define the epileptic focus.

Interictal high-frequency oscillations, spikes, and connectivity profiles: A fingerprint of epileptogenic brain pathologies.

OBJECTIVE: Focal cortical dysplasia (FCD), hippocampal sclerosis (HS), nonspecific gliosis (NG), and normal tissue (NT) comprise the majority of histopathological results of surgically treated drug-resistant epilepsy patients. Epileptic spikes, high-frequency oscillations (HFOs), and connectivity measures are valuable biomarkers of epileptogenicity. The question remains whether they could also be utilized for preresective differentiation of the underlying brain pathology. This study explored spikes and HFOs together with functional connectivity in various epileptogenic pathologies. METHODS: Interictal awake stereoelectroencephalographic recordings of 33 patients with focal drug-resistant epilepsy with seizure-free postoperative outcomes were analyzed (15 FCD, 8 HS, 6 NT, and 4 NG). Interictal spikes and HFOs were automatically identified in the channels contained in the overlap of seizure onset zone and resected tissue. Functional connectivity measures (relative entropy, linear correlation, cross-correlation, and phase consistency) were computed for neighboring electrode pairs. RESULTS: Statistically significant differences were found between the individual pathologies in HFO rates, spikes, and their characteristics, together with functional connectivity measures, with the highest values in the case of HS and NG/NT. A model to predict brain pathology based on all interictal measures achieved up to 84.0% prediction accuracy. SIGNIFICANCE: The electrophysiological profile of the various epileptogenic lesions in epilepsy surgery patients was analyzed. Based on this profile, a predictive model was developed. This model offers excellent potential to identify the nature of the underlying lesion prior to resection. If validated, this model may be particularly valuable for counseling patients, as depending on the lesion type, different outcomes are achieved after epilepsy surgery.

Regional variability in intracerebral properties of NREM to REM sleep transitions in humans.

Transitions between wake and sleep states show a progressive pattern underpinned by local sleep regulation. In contrast, little evidence is available on non-rapid eye movement (NREM) to rapid eye movement (REM) sleep boundaries, considered as mainly reflecting subcortical regulation. Using polysomnography (PSG) combined with stereoelectroencephalography (SEEG) in humans undergoing epilepsy presurgical evaluation, we explored the dynamics of NREM-to-REM transitions. PSG was used to visually score transitions and identify REM sleep features. SEEG-based local transitions were determined automatically with a machine learning algorithm using features validated for automatic intra-cranial sleep scoring (10.5281/zenodo.7410501). We analyzed 2988 channel-transitions from 29 patients. The average transition time from all intracerebral channels to the first visually marked REM sleep epoch was 8 s ± 1 min 58 s, with a great heterogeneity between brain areas. Transitions were observed first in the lateral occipital cortex, preceding scalp transition by 1 min 57 s ± 2 min 14 s (d = -0.83), and close to the first sawtooth wave marker. Regions with late transitions were the inferior frontal and orbital gyri (1 min 1 s ± 2 min 1 s, d = 0.43, and 1 min 1 s ± 2 min 5 s, d = 0.43, after scalp transition). Intracranial transitions were earlier than scalp transitions as the night advanced (last sleep cycle, d = -0.81). We show a reproducible gradual pattern of REM sleep initiation, suggesting the involvement of cortical mechanisms of regulation. This provides clues for understanding oneiric experiences occurring at the NREM/REM boundary.

The phenotypic spectrum of epilepsy associated with periventricular nodular heterotopia.

BACKGROUND: Periventricular nodular heterotopia (PVNH) is a congenital brain malformation often associated with seizures. We aimed to clarify the spectrum of epilepsy phenotypes in PVNH and the significance of specific brain malformation patterns. METHODS: In this retrospective cohort study, we recruited people with PVNH and a history of seizures, and collected data via medical record review and a standardized questionnaire. RESULTS: One hundred individuals were included, aged 1 month to 61 years. Mean seizure onset age was 7.9 years. Ten patients had a self-limited epilepsy course and 35 more were pharmacoresponsive. Fifty-five had ongoing seizures, of whom 23 met criteria for drug resistance. Patients were subdivided as follows: isolated PVNH ("PVNH-Only") single nodule (18) or multiple nodules (21) and PVNH with additional brain malformations ("PVNH-Plus") single nodule (8) or multiple nodules (53). Of PVNH-Only single nodule, none had drug-resistant seizures. Amongst PVNH-Plus, 55% with multiple unilateral nodules were pharmacoresponsive, compared to only 21% with bilateral nodules. PVNH-Plus with bilateral nodules demonstrated the highest proportion of drug resistance (39%). A review of genetic testing results revealed eight patients with pathogenic or likely pathogenic single-gene variants, two of which were FLNA. Five had copy number variants, two of which were pathogenic. CONCLUSIONS: The spectrum of epilepsy phenotypes in PVNH is broad, and seizure patterns are variable; however, epilepsy course may be predicted to an extent by the pattern of malformation. Overall, drug-resistant epilepsy occurs in approximately one quarter of affected individuals. When identified, genetic etiologies are very heterogeneous.

Relative entropy is an easy-to-use invasive electroencephalographic biomarker of the epileptogenic zone.

OBJECTIVE: High-frequency oscillations are considered among the most promising interictal biomarkers of the epileptogenic zone in patients suffering from pharmacoresistant focal epilepsy. However, there is no clear definition of pathological high-frequency oscillations, and the existing detectors vary in methodology, performance, and computational costs. This study proposes relative entropy as an easy-to-use novel interictal biomarker of the epileptic tissue. METHODS: We evaluated relative entropy and high-frequency oscillation biomarkers on intracranial electroencephalographic data from 39 patients with seizure-free postoperative outcome (Engel Ia) from three institutions. We tested their capability to localize the epileptogenic zone, defined as resected contacts located in the seizure onset zone. The performance was compared using areas under the receiver operating curves (AUROCs) and precision-recall curves. Then we tested whether a universal threshold can be used to delineate the epileptogenic zone across patients from different institutions. RESULTS: Relative entropy in the ripple band (80-250 Hz) achieved an average AUROC of .85. The normalized high-frequency oscillation rate in the ripple band showed an identical AUROC of .85. In contrast to high-frequency oscillations, relative entropy did not require any patient-level normalization and was easy and fast to calculate due to its clear and straightforward definition. One threshold could be set across different patients and institutions, because relative entropy is independent of signal amplitude and sampling frequency. SIGNIFICANCE: Although both relative entropy and high-frequency oscillations have a similar performance, relative entropy has significant advantages such as straightforward definition, computational speed, and universal interpatient threshold, making it an easy-to-use promising biomarker of the epileptogenic zone.

A Subpopulation of Spikes Predicts Successful Epilepsy Surgery Outcome.

OBJECTIVE: Epileptic spikes are the traditional interictal electroencephalographic (EEG) biomarker for epilepsy. Given their low specificity for identifying the epileptogenic zone (EZ), they are given only moderate attention in presurgical evaluation. This study aims to demonstrate that it is possible to identify specific spike features in intracranial EEG that optimally define the EZ and predict surgical outcome. METHODS: We analyzed spike features on stereo-EEG segments from 83 operated patients from 2 epilepsy centers (37 Engel IA) in wakefulness, non-rapid eye movement sleep, and rapid eye movement sleep. After automated spike detection, we investigated 135 spike features based on rate, morphology, propagation, and energy to determine the best feature or feature combination to discriminate the EZ in seizure-free and non-seizure-free patients by applying 4-fold cross-validation. RESULTS: The rate of spikes with preceding gamma activity in wakefulness performed better for surgical outcome classification (4-fold area under receiver operating characteristics curve [AUC] = 0.755 ± 0.07) than the seizure onset zone, the current gold standard (AUC = 0.563 ± 0.05, p = 0.015) and the ripple rate, an emerging seizure-independent biomarker (AUC = 0.537 ± 0.07, p = 0.006). Channels with a spike-gamma rate exceeding 1.9/min had an 80% probability of being in the EZ. Combining features did not improve the results. INTERPRETATION: Resection of brain regions with high spike-gamma rates in wakefulness is associated with a high probability of achieving seizure freedom. This rate could be applied to determine the minimal number of spiking channels requiring resection. In addition to quantitative analysis, this feature is easily accessible to visual analysis, which could aid clinicians during presurgical evaluation. ANN NEUROL 2023;93:522-535.

Case report: PLPHP deficiency, a rare but important cause of B6-responsive disorders: A report of three novel individuals and review of 51 cases.

PLPHP (pyridoxal-phosphate homeostasis protein) deficiency is caused by biallelic pathogenic variants in PLPBP and is a rare cause of pyridoxine-responsive disorders. We describe three French-Canadian individuals with PLPHP deficiency, including one with unusual paroxysmal episodes lacking EEG correlation with a suspicious movement disorder, rarely reported in B6RDs. In addition, we review the clinical features and treatment responses of all 51 previously published individuals with PLPHP deficiency. Our case series underlines the importance of considering PLPBP mutations in individuals with partially B6-responsive seizures and highlights the presence of a founder effect in the French-Canadian population.

Surgically Remediable Secondary Network Epileptic Encephalopathies With Continuous Spike Wave in Sleep: Lesions May Not Be Visible on Brain Magnetic Resonance Imaging (MRI).

BACKGROUND: Continuous spike wave in sleep (CSWS) is an electroencephalogram (EEG) pattern associated with developmental and epileptic encephalopathy with spike-and-wave activation in sleep (DEE-SWAS). This etiologically heterogeneous syndrome may occur because of genetic factors and congenital or acquired brain lesions. We studied the pattern of clinical presentation and underlying etiologies in patients with DEE-SWAS that respond to resective surgery. METHODS: We reviewed our clinical and research databases for patients who had resolution of CSWS following surgical resection of a focal lesion. RESULTS: We identified 5 patients meeting inclusion criteria. In 3 of 5, an epileptogenic structural abnormality was not apparent on brain magnetic resonance imaging (MRI). In all 3 patients, focal cortical dysplasia was identified through intracranial EEG monitoring. SIGNIFICANCE: DEE-SWAS may be a secondary bilateral network epilepsy syndrome, which can be treated with resection of the inciting focal lesion. In patients with drug-resistant CSWS, clinicians should consider a complete epilepsy presurgical workup, including intracranial EEG monitoring.

"Generalized-to-focal" epilepsy: stereotactic EEG and high-frequency oscillation patterns

Objective: We aimed to clarify the pathophysiology of epilepsy involving seizures with apparently generalized onset, progressing to focal ictal rhythm through stereotactic EEG (SEEG) implantation, recording, stimulation and high-frequency oscillation (HFO) analysis. Methods: We identified two patients with seizures with bilateral electrographic onset evolving to focal ictal rhythm, who underwent SEEG implantation. Patients had pre-surgical epilepsy work-up, including prolonged video scalp EEG, brain MRI, PET, ictal/interictal SPECT, MEG, and EEG-fMRI prior to SEEG implantation. Results: Both patients had childhood-onset seizures involving behavioural arrest and left versive head and eye deviation, evolving to bilateral tonic-clonic convulsions. Seizures were electrographically preceded by diffuse, bilateral 3-Hz activity resembling absence seizures. Both had suspected focal lesions based on neuroimaging, including 3T MRI and voxel-based post-processing in one patient. Electrode stimulation did not elicit any habitual electroclinical seizures. HFO analysis showed bilateral focal regions with high fast-ripple rates. Significance: "Generalized-to-focal" seizures may occur due to a diffuse, bilateral epileptic network, however, both patients showed ictal evolution from a generalized pattern to a single dominant focus which may explain why the focal aspect of their seizures had a consistent clinical semiology. Patients such as these may have a unique form of generalized epilepsy, but focal/multifocal cerebral abnormalities are also a possibility.

A brain atlas of axonal and synaptic delays based on modelling of cortico-cortical evoked potentials.

Epilepsy presurgical investigation may include focal intracortical single-pulse electrical stimulations with depth electrodes, which induce cortico-cortical evoked potentials at distant sites because of white matter connectivity. Cortico-cortical evoked potentials provide a unique window on functional brain networks because they contain sufficient information to infer dynamical properties of large-scale brain connectivity, such as preferred directionality and propagation latencies. Here, we developed a biologically informed modelling approach to estimate the neural physiological parameters of brain functional networks from the cortico-cortical evoked potentials recorded in a large multicentric database. Specifically, we considered each cortico-cortical evoked potential as the output of a transient stimulus entering the stimulated region, which directly propagated to the recording region. Both regions were modelled as coupled neural mass models, the parameters of which were estimated from the first cortico-cortical evoked potential component, occurring before 80 ms, using dynamic causal modelling and Bayesian model inversion. This methodology was applied to the data of 780 patients with epilepsy from the F-TRACT database, providing a total of 34 354 bipolar stimulations and 774 445 cortico-cortical evoked potentials. The cortical mapping of the local excitatory and inhibitory synaptic time constants and of the axonal conduction delays between cortical regions was obtained at the population level using anatomy-based averaging procedures, based on the Lausanne2008 and the HCP-MMP1 parcellation schemes, containing 130 and 360 parcels, respectively. To rule out brain maturation effects, a separate analysis was performed for older (>15 years) and younger patients (<15 years). In the group of older subjects, we found that the cortico-cortical axonal conduction delays between parcels were globally short (median = 10.2 ms) and only 16% were larger than 20 ms. This was associated to a median velocity of 3.9 m/s. Although a general lengthening of these delays with the distance between the stimulating and recording contacts was observed across the cortex, some regions were less affected by this rule, such as the insula for which almost all efferent and afferent connections were faster than 10 ms. Synaptic time constants were found to be shorter in the sensorimotor, medial occipital and latero-temporal regions, than in other cortical areas. Finally, we found that axonal conduction delays were significantly larger in the group of subjects younger than 15 years, which corroborates that brain maturation increases the speed of brain dynamics. To our knowledge, this study is the first to provide a local estimation of axonal conduction delays and synaptic time constants across the whole human cortex in vivo, based on intracerebral electrophysiological recordings.

Clinical Yield of Electromagnetic Source Imaging and Hemodynamic Responses in Epilepsy: Validation With Intracerebral Data.

OBJECTIVES: Accurate delineation of the seizure-onset zone (SOZ) in focal drug-resistant epilepsy often requires stereo-electroencephalography (SEEG) recordings. We aimed at: (1) proposing a truly objective and quantitative comparison between electro-encephalography/magnetoencephalography (EEG/MEG) source-imaging (EMSI), EEG/functional MRI (EEG/fMRI) responses for similar spikes with primary-irritative zone (PIZ) and SOZ defined by SEEG and (2) evaluating the value of EMSI and EEG/fMRI to predict postsurgical outcome. METHODS: We identified patients with drug-resistant epilepsy who underwent EEG/MEG, EEG/fMRI, and subsequent SEEG at the Epilepsy Service from the Montreal Neurological Institute and Hospital. We quantified multimodal concordance within the SEEG channel-space, as spatial overlap with PIZ/SOZ and distances to the Spike-onset, Spike-maximum-amplitude and Seizure-core intracerebral channels, by applying a new methodology consisting of converting EMSI results into SEEG electrical potentials (EMSIe-SEEG) and projecting the most significant fMRI response on the SEEG channels (fMRIp-SEEG). Spatial overlaps with PIZ/SOZ (AUCPIZ, AUCSOZ) were assessed by using the area under the receiver operating characteristic curve (AUC). Here, AUC represents the probability that a randomly picked active contact exhibited higher amplitude when located inside the spatial reference than outside. RESULTS: Seventeen patients were included. Mean spatial overlaps with the primary-irritative zone and seizure-onset zone were 0.71 and 0.65 for EMSIe-SEEG, and 0.57 and 0.62 for fMRIp-SEEG. Good EMSIe-SEEG  spatial overlap with the primary-irritative zone was associated with smaller distance from the maximum EMSIe-SEEG contact to the Spike-maximum-amplitude channel (median distance 14 mm). Conversely, good fMRIp-SEEG spatial overlap with the seizure-onset zone was associated with smaller distances from the maximum  fMRIp-SEEG contact to the Spike-onset and Seizure-core channels (median distances 10 mm and 5mm respectively). Surgical outcomes were correctly predicted by EEG/MEG in 12/15 (80%) patients and EEG/fMRI in 6/11(54%) patients. CONCLUSIONS: Using a unique quantitative approach estimating EMSI and fMRI results in the reference SEEG channel-space, EEG/MEG and EEG/fMRI accurately localized the seizure-onset zone as well as the primary-irritative zone. Precisely, EEG/MEG more accurately localized the primary-irritative zone, whereas EEG/fMRI was more sensitive to the seizure-onset zone. Both neuro-imaging techniques provide complementary localization that can help guiding SEEG implantation and selecting good candidates for surgery.

Insular Involvement in Cases of Epilepsy Surgery Failure.

BACKGROUND: Epilepsy surgery failure is not uncommon, with several explanations having been proposed. In this series, we detail cases of epilepsy surgery failure subsequently attributed to insular involvement. METHODS: We retrospectively identified patients investigated at the epilepsy monitoring units of two Canadian tertiary care centers (2004-2020). Included patients were adults who had undergone epilepsy surgeries with recurrence of seizures post-operatively and who were subsequently determined to have an insular epileptogenic focus. Clinical, electrophysiological, neuroimaging, and surgical data were synthesized. RESULTS: We present 14 patients who demonstrated insular epileptic activity post-surgery-failure as detected by intracranial EEG, MEG, or seizure improvement after insular resection. Seven patients had manifestations evoking possible insular involvement prior to their first surgery. Most patients (8/14) had initial surgeries targeting the temporal lobe. Seizure recurrence ranged from the immediate post-operative period to one year. The main modality used to determine insular involvement was MEG (8/14). Nine patients underwent re-operations that included insular resection; seven achieved a favorable post-operative outcome (Engel I or II). CONCLUSIONS: Our series suggests that lowering the threshold for suspecting insular epilepsy may be necessary to improve epilepsy surgery outcomes. Detecting insular epilepsy post-surgery-failure may allow for re-operations which may lead to good outcomes.

Spatio-temporal spike dynamics predict surgical outcome in adult focal epilepsy.

OBJECTIVE: We hypothesized that spatio-temporal dynamics of interictal spikes reflect the extent and stability of epileptic sources and determine surgical outcome. METHODS: We studied 30 consecutive patients (14 good outcome). Spikes were detected in prolonged stereo-electroencephalography recordings. We quantified the spatio-temporal dynamics of spikes using the variance of the spike rate, line length and skewness of the spike distribution, and related these features to outcome. We built a logistic regression model, and compared its performance to traditional markers. RESULTS: Good outcome patients had more dominant and stable sources than poor outcome patients as expressed by a higher variance of spike rates, a lower variance of line length, and a lower variance of positive skewness (ps < 0.05). The outcome was correctly predicted in 80% of patients. This was better or non-inferior to predictions based on a focal lesion (p = 0.016), focal seizure-onset zone, or complete resection (ps > 0.05). In the five patients where traditional markers failed, spike distribution predicted the outcome correctly. The best results were achieved by 18-h periods or longer. CONCLUSIONS: Analysis of spike dynamics shows that surgery outcome depends on strong, single and stable sources. SIGNIFICANCE: Our quantitative method has the potential to be a reliable predictor of surgical outcome.