Localization of epileptic foci in children with intractable epilepsy secondary to multiple cortical tubers by using synthetic aperture magnetometry kurtosis
Notice bibliographique
Résumé
OBJECT: Magnetoencephalography (MEG) has been typically used to localize epileptic activity by modeling interictal activity as equivalent current dipoles (ECDs). Synthetic aperture magnetometry (SAM) is a recently developed adaptive spatial filtering algorithm for MEG that provides some advantages over the ECD approach. The SAM-kurtosis algorithm (also known as SAM[g2]) additionally provides automated temporal detection of spike sources by using excess kurtosis value (steepness of epileptic spike on virtual sensors). To evaluate the efficacy of the SAM(g2) method, the authors applied it to readings obtained in children with intractable epilepsy secondary to tuberous sclerosis complex (TSC), and compared them to localizations obtained with ECDs. METHODS: The authors studied 13 children with TSC (7 girls) whose ages ranged from 13 months to 16.3 years (mean 7.3 years). Video electroencephalography, MR imaging, and MEG studies were analyzed. A single ECD model was applied to localize ECD clusters. The SAM(g2) value was calculated at each SAM(g2) virtual voxel in the patient's MR imaging-defined brain volume. The authors defined the epileptic voxels of SAM(g2) (evSAM[g2]) as those with local peak kurtosis values higher than half of the maximum. A clustering of ECDs had to contain > or = 6 ECDs within 1 cm of each other, and a grouping of evSAM(g2)s had to contain > or = 3 evSAM(g2)s within 1 cm of each other. The authors then compared both ECD clusters and evSAM(g2) groups with the resection area and correlated these data with seizure outcome. RESULTS: Seizures started when patients were between 6 weeks and 8 years of age (median 6 months), and became intractable secondary to multiple tubers in all cases. Ictal onset on scalp video electroencephalography was lateralized in 8 patients (62%). The MEG studies showed multiple ECD clusters in 7 patients (54%). The SAM(g2) method showed multiple groups of epileptic voxels in 8 patients (62%). Colocalization of grouped evSAM(g2) with ECD clusters ranged from 20 to 100%, with a mean of 82%. Eight patients underwent resection of single (1 patient) and multiple (7 patients) lobes, with 6 patients achieving freedom from seizures. Of 8 patients who underwent surgery, in 7 the resection area covered ECD clusters and grouped evSAM(g2)s. In the remaining patient the resection area partially included the ECD cluster and grouped evSAM(g2)s. Six of the 7 patients became seizure free. CONCLUSIONS: The combination of SAM(g2) and ECD analyses succeeded in localizing the complex epileptic zones in children with TSC who had intractable epilepsy secondary to multiple cortical tubers. For the subset of children with TSC who present with early-onset and nonlateralized seizures, MEG studies in which SAM(g2) and ECD are used might identify suitable candidates for resection to control seizures.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».