OBJECTIVE: The study investigated metabolic connectivity (MC) differences between patients with unilateral drug-resistant mesial temporal lobe epilepsy (MTLE) with hippocampal sclerosis (HS) and healthy controls (HCs), based on [18 F]-fluorodeoxyglucose (FDG)-PET data. We focused on the MC changes dependent on the lateralization of the epileptogenic lobe and on correlations with postoperative outcomes. METHODS: FDG-PET scans of 47 patients with unilateral MTLE with histopathologically proven HS and 25 HC were included in the study. All the patients underwent a standard anterior temporal lobectomy and were more than 2 years after the surgery. MC changes were compared between the two HS groups (left HS, right HS) and HC. Differences between the metabolic network of seizure-free and non-seizure-free patients after surgery were depicted afterward. Network changes were correlated with clinical characteristics. RESULTS: The study showed widespread metabolic network changes in the HS patients as compared to HC. The changes were more extensive in the right HS than in the left HS. Unfavorable surgical outcomes were found in patients with decreased MC within the network including both the lesional and contralesional hippocampus, ipsilesional frontal operculum, and contralesional insula. Favorable outcomes correlated with decreased MC within the network involving both orbitofrontal cortices and the ipsilesional temporal lobe. SIGNIFICANCE: There are major differences in the metabolic networks of left and right HS, with more extensive changes in right HS. The changes within the metabolic network could help predict surgical outcomes in patients with HS. MC may identify patients with potentially unfavorable outcomes and direct them to a more detailed presurgical evaluation. PLAIN LANGUAGE SUMMARY: Metabolic connectivity is a promising method for metabolic network mapping. Metabolic networks in mesial temporal lobe epilepsy are dependent on lateralization of the epileptogenic lobe and could predict surgical outcomes.

• Klíčová slova
• mesial temporal lobe epilepsy, metabolic connectivity, positron emission tomography,
• MeSH
• epilepsie temporálního laloku * diagnostické zobrazování   chirurgie   MeSH
• fluorodeoxyglukosa F18 metabolismus   MeSH
• hipokampus chirurgie   metabolismus   MeSH
• lidé MeSH
• refrakterní epilepsie * MeSH
• spánkový lalok metabolismus   MeSH
• výsledek terapie MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• Názvy látek
• fluorodeoxyglukosa F18 MeSH

OBJECTIVE: When considering all patients with focal drug-resistant epilepsy, as high as 40-50% of patients suffer seizure recurrence after surgery. To achieve seizure freedom without side effects, accurate localization of the epileptogenic tissue is crucial before its resection. We investigate an automated, fast, objective mapping process that uses only interictal data. METHODS: We propose a novel approach based on multiple iEEG features, which are used to train a support vector machine (SVM) model for classification of iEEG electrodes as normal or pathologic using 30 min of inter-ictal recording. RESULTS: The tissue under the iEEG electrodes, classified as epileptogenic, was removed in 17/18 excellent outcome patients and was not entirely resected in 8/10 poor outcome patients. The overall best result was achieved in a subset of 9 excellent outcome patients with the area under the receiver operating curve = 0.95. CONCLUSION: SVM models combining multiple iEEG features show better performance than algorithms using a single iEEG marker. Multiple iEEG and connectivity features in presurgical evaluation could improve epileptogenic tissue localization, which may improve surgical outcome and minimize risk of side effects. SIGNIFICANCE: In this study, promising results were achieved in localization of epileptogenic regions by SVM models that combine multiple features from 30 min of inter-ictal iEEG recordings.

• Klíčová slova
• Connectivity, Drug resistant epilepsy, Epileptogenic zone localization, High frequency oscillations, Machine learning, Multi-feature approach,
• MeSH
• dospělí MeSH
• elektroencefalografie přístrojové vybavení   metody   MeSH
• epilepsie parciální diagnóza   patofyziologie   MeSH
• implantované elektrody MeSH
• lidé středního věku MeSH
• lidé MeSH
• mladý dospělý MeSH
• retrospektivní studie MeSH
• senioři MeSH
• Check Tag
• dospělí MeSH
• lidé středního věku MeSH
• lidé MeSH
• mladý dospělý MeSH
• mužské pohlaví MeSH
• senioři MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Research Support, N.I.H., Extramural MeSH