Mapping interictal discharges using intracranial EEG-fMRI to predict postsurgical outcomes
Notice bibliographique
Résumé
Various subjective and objective methods have been proposed to identify which interictal epileptiform discharge (IED)-related EEG-functional MRI (fMRI) results are more likely to delineate seizure-generating tissue in patients with drug-resistant focal epilepsy for the purposes of surgical planning. In this intracranial EEG-fMRI study, we evaluated the utility of these methods to localize clinically relevant regions preoperatively and compared the extent of resection of these areas to postoperative outcome. Seventy patients admitted for intracranial video-EEG monitoring were recruited for a simultaneous intracranial EEG-fMRI study. For all analyses of blood oxygen level-dependent responses associated with IEDs, an experienced epileptologist identified the most clinically relevant brain activation cluster using available clinical information. The maximum cluster (the cluster with the highest z-score) was also identified for all analyses and assigned to one of three confidence levels (low, medium or high) based on the difference of the peak z-scores between the maximum and second maximum cluster (the cluster with the second highest peak z-value). The distance was measured and compared between the peak voxel of the aforementioned clusters and the electrode contacts where the interictal discharge and seizure onset were recorded. In patients who subsequently underwent epilepsy surgery, the spatial concordance between the aforementioned clusters and the area of resection was determined and compared to postoperative outcome. We evaluated 106 different IEDs in 70 patients. Both subjective (identification of the clinically relevant cluster) and objective (maximum cluster much more significant than the second maximum cluster) methods of culling non-localizing EEG-fMRI activation maps increased the spatial concordance between these clusters and the corresponding IED or seizure onset zone contacts. However, only the objective methods of identifying medium and high confidence maps resulted in a significant association between resection of the peak voxel of the maximum cluster and postoperative outcome. Resection of this area was associated with good postoperative outcomes but was not sufficient for seizure freedom. On the other hand, we found that failure to resect the medium and high confidence maximum clusters was associated with a poor post-surgical outcome (negative predictive value = 1.0, sensitivity = 1.0). Methods to identify higher confidence EEG-fMRI results are needed to localize areas necessary for good postoperative outcomes. However, resection of the peak voxel within higher confidence maximum clusters is not sufficient for good outcomes. Conversely, failure to resect the peak voxel in these clusters is associated with a poor post-surgical outcome.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| 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 | 0,000 |
| 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 ».