Interictal SEEG Resting-State Connectivity Localizes the Seizure Onset Zone and Predicts Seizure Outcome.
Haiteng JiangVasileios KokkinosShuai YeAlexandra UrbanAnto BagićMark RichardsonBin HePublished in: Advanced science (Weinheim, Baden-Wurttemberg, Germany) (2022)
Localization of epileptogenic zone currently requires prolonged intracranial recordings to capture seizure, which may take days to weeks. The authors developed a novel method to identify the seizure onset zone (SOZ) and predict seizure outcome using short-time resting-state stereotacticelectroencephalography (SEEG) data. In a cohort of 27 drug-resistant epilepsy patients, the authors estimated the information flow via directional connectivity and inferred the excitation-inhibition ratio from the 1/f power slope. They hypothesized that the antagonism of information flow at multiple frequencies between SOZ and non-SOZ underlying the relatively stable epilepsy resting state could be related to the disrupted excitation-inhibition balance. They found flatter 1/f power slope in non-SOZ regions compared to the SOZ, with dominant information flow from non-SOZ to SOZ regions. Greater differences in resting-state information flow between SOZ and non-SOZ regions are associated with favorable seizure outcome. By integrating a balanced random forest model with resting-state connectivity, their method localized the SOZ with an accuracy of 88% and predicted the seizure outcome with an accuracy of 92% using clinically determined SOZ. Overall, this study suggests that brief resting-state SEEG data can significantly facilitate the identification of SOZ and may eventually predict seizure outcomes without requiring long-term ictal recordings.
Keyphrases
- resting state
- functional connectivity
- temporal lobe epilepsy
- drug resistant
- end stage renal disease
- multidrug resistant
- chronic kidney disease
- health information
- healthcare
- newly diagnosed
- ejection fraction
- electronic health record
- acinetobacter baumannii
- type diabetes
- prognostic factors
- metabolic syndrome
- social media
- peritoneal dialysis
- patient reported outcomes
- quantum dots