The repertoire of seizure onset patterns in human focal epilepsies: Determinants and prognostic values

Lagarde, Stanislas; Buzori, Sinziana; Trébuchon, Agnès; Carron, Romain; Scavarda, Didier; Milh, Mathieu; McGonigal, Aileen; Bartolomei, Fabricē

doi:10.1111/epi.14604

Cited by 137 publications

(172 citation statements)

References 49 publications

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“…Visual Analysis of SEEG Seizure onset zone (SOZ) was visually defined as the first clear SEEG change occurring prior to, or concomitant with, clinical seizure onset. Seizure onset patterns (SOPs) were classified according to Lagarde et al 21 The first "tonic" or fast activity at onset and within 1 second was analyzed in relation to intrainsular anatomical location of involved contacts. Mean values for seizure duration, intrainsular and extrainsular propagation, and first subjective and objective signs were calculated.…”

Section: Discussionmentioning

confidence: 99%

“…SOPs are heterogenous and similar to other brain regions. Only 2 of 12 patients (17%) had onset with LVFA, compared with 43% 32 to 46% 21 in SEEG cohorts of mixed etiology and lobar onset. Reduction in low frequencies and increase in fast activities occurs at seizure onset, 33 seen on time frequency analysis as an "epileptic fingerprint," 25 but this fingerprint also occurs at distant but closely connected functional areas, for instance pre-SMA and contralateral insula in some anterior insula seizures; therefore, this is not a biomarker for only the SOZ or "what to resect area."…”

Section: Insular Seizures Start Focally With Limited Intrainsular Spreadmentioning

confidence: 93%

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Mapping the Insula with Stereo‐Electroencephalography: The Emergence of Semiology in Insula Lobe Seizures

Singh

Príncipe

Tadel

et al. 2020

Annals of Neurology

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Objective Insula epilepsy is rare and can be evaluated effectively by Stereotactic intracerebral EEG (SEEG). Many previous studies of insulo‐opercular seizures have been unable to separate insular and opercular onset. With adequate sampling of the insula, this study shows this is possible. Methods We analyzed intrainsular dynamics and extrainsular propagation in 12 patients with “pure” insula epilepsy (n = 9) or insular and only deepest opercular involvement (n = 3) at seizure onset. Review of semiology defined clinical groups, agglomerative cluster, and principal component analysis of semiological features were performed. Quantitative epileptogenicity, and intrainsular and extrainsular propagation were computed via time frequency analysis and epileptogenicity mapping. Results Seizure onset patterns were heterogeneous; the seizure onset zone was focal. Seizure onset and first ictal change within insula functional subdivision correlated with aura and reflex component. No paninsular spread occurred; contralateral insular spread was very early. While the discharge was intrainsular, clinical signs related to aura or vegetative signs. Extrainsular propagation was early and related to the emergence of the majority of clinical signs. Cluster analysis found an anterior, intermediate, and posterior insula seizure onset group. The largest principal component separated anterior insula manifestations, including early hypermotor signs, early recovery, and no aura from posterior insula features of early dystonia, early tonic motor features, and sensorimotor aura. Interpretation Aura is vital to identifying seizure onset and relates to insula functional subdivision. Seizures are heterogenous; extrainsular propagation occurs early, accounting for most of the semiology. With adequate sampling, "pure" insula epilepsy can be identified and focal curative resection is possible. ANN NEUROL 2020;88:477–488

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Section: Discussionmentioning

confidence: 99%

Section: Insular Seizures Start Focally With Limited Intrainsular Spreadmentioning

confidence: 93%

Mapping the Insula with Stereo‐Electroencephalography: The Emergence of Semiology in Insula Lobe Seizures

Singh

Príncipe

Tadel

et al. 2020

Annals of Neurology

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“…For patients with >10 captured seizures, we reviewed all seizures, then analyzed 10 representative seizures, so as to keep the same proportion of each distinct electroclinical seizure type. Seizure onset was defined as the first unequivocal SEEG signal change from the background in the setting of a sustained rhythmic discharge …”

Section: Methodsmentioning

confidence: 99%

“…In a range of malformative pathologies, it is well established that the EZ can extend beyond visible lesions . Additionally, over the past decade, two types of spatial organizations of the EZ have been observed in various epilepsies: (1) a focal EZ limited to a lesional/restrained cortical area and (2) a more widespread network involving lesion and/or multiple distant structures. We propose that distinct EZ spatial organizations may also be observed in TSC.…”

Section: Introductionmentioning

confidence: 99%

Epileptogenicity in tuberous sclerosis complex: A stereoelectroencephalographic study

et al. 2019

Self Cite

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Objective:In tuberous sclerosis complex (TSC)-associated drug-resistant epilepsy, the optimal invasive electroencephalographic (EEG) and operative approach remains unclear. We examined the role of stereo-EEG in TSC and used stereo-EEG data to investigate tuber and surrounding cortex epileptogenicity. Methods: We analyzed 18 patients with TSC who underwent stereo-EEG (seven adults). One hundred ten seizures were analyzed with the epileptogenicity index (EI).In 13 patients with adequate tuber sampling, five anatomical regions of interest (ROIs) were defined: dominant tuber (tuber with highest median EI), perituber cortex, secondary tuber (tuber with second highest median EI), nearby cortex (normal-appearing cortex in the same lobe as dominant tuber), and distant cortex (in other lobes). At the seizure level, epileptogenicity of ROIs was examined by comparing the highest EI recorded within each anatomical region. At the patient level, epileptogenic zone (EZ) organization was separated into focal tuber (EZ confined to dominant tuber) and complex (all other patterns). Results: The most epileptogenic ROI was the dominant tuber, with higher EI than perituber cortex, secondary tuber, nearby cortex, and distant cortex (P < .001). A focal tuber EZ organization was identified in seven patients. This group had 80% Engel IA postsurgical outcome and distinct dominant tuber characteristics: continuous interictal discharges (IEDs; 100%), fluid-attenuated inversion recovery (FLAIR) hypointense center (86%), center-to-rim EI gradient, and stimulation-induced seizures (71%). In contrast, six patients had a complex EZ organization, characterized by nearby cortex as the most epileptogenic region and 40% Engel IA outcome.At the intratuber level, the combination of FLAIR hypointense center, continuous IEDs, and stimulation-induced seizures offered 98% specificity for a focal tuber EZ organization. Significance: Tubers with focal EZ organization have a striking similarity to type II focal cortical dysplasia. The presence of distinct EZ organizations has significant implications for EZ hypothesis generation, invasive EEG approach, and resection strategy. |

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“…Contacts were considered to be within the seizure onset zone when a typical ictal pattern was seen at onset -stimulation data was also considered where appropriate as is standard practice for sEEG interpretation 17,18 .…”

Section: Evaluation Of Classifier In Lesion Positive Cohort and Controlsmentioning

confidence: 99%

Planning sEEG implantation using automated lesion detection: retrospective feasibility study

Wagstyl

Adler

Pimpel

et al. 2019

Preprint

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Objective: A retrospective, cross-sectional study to evaluate the feasibility and potential benefits of incorporating deep-learning on structural MRI into planning stereoelectroencephalography (sEEG) implantation in paediatric patients with diagnostically complex drug-resistant epilepsy. This study aims to assess the degree of co-localisation between automated lesion detection and the seizure onset zone (SOZ) as assessed by sEEG. Methods: A neural network classifier was applied to cortical features from MRI data from three cohorts. 1) The network was trained and cross-validated using 34 patients with visible focal cortical dysplasias (FCDs). 2) Specificity was assessed in 20 paediatric healthy controls. 3) Feasibility for incorporation into sEEG implantation plans was evaluated in 38 sEEG patients. Coordinates of sEEG contacts were coregistered with classifier-predicted lesions. sEEG contacts in seizure onset and irritative tissue were identified by clinical neurophysiologists. A distance of <10mm between SOZ contacts and classifier-predicted lesions was considered co-localisation. Results: In patients with radiologically-defined lesions, classifier sensitivity was 74% (25/34 lesions detected). No clusters were detected in the controls (specificity 100%). Of 34 sEEG patients, 21 patients had a focal cortical SOZ. Of these there was co-localisation between classifier output and SOZ contacts in 62%. The algorithm detected 7/8 histopathologically-confirmed FCDs (86%). Conclusions: There was a high degree of co-localisation between automated lesion detection and sEEG. We have created a framework for incorporation of deep-learning based MRI lesion detection into sEEG implantation planning. Our findings demonstrate that automated MRI analysis could be used to plan optimal electrode trajectories.

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The repertoire of seizure onset patterns in human focal epilepsies: Determinants and prognostic values

Cited by 137 publications

References 49 publications

Mapping the Insula with Stereo‐Electroencephalography: The Emergence of Semiology in Insula Lobe Seizures

Mapping the Insula with Stereo‐Electroencephalography: The Emergence of Semiology in Insula Lobe Seizures

Epileptogenicity in tuberous sclerosis complex: A stereoelectroencephalographic study

Planning sEEG implantation using automated lesion detection: retrospective feasibility study

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