Epilepsy Surgery Outcome Prediction

In drug-resistant epilepsy, where medications fail to control seizures, surgical resection of the epileptogenic zone can offer a potential cure. However, surgical success depends critically on accurately identifying the brain regions generating seizures and understanding their network-level interactions. Advances in electrophysiology and neuroimaging have revealed that epilepsy is not merely a focal phenomenon but involves distributed pathological networks. Quantitative biomarkers derived from EEG or intracranial recordings—such as connectivity measures, network topology, and source activation patterns—are increasingly used to predict surgical outcomes. By modeling how resection overlaps with pathological networks, researchers aim to forecast whether surgery will result in seizure freedom. Integrating these approaches with artificial intelligence and machine learning enables personalized, data-driven predictions, supporting more precise surgical planning and improved prognostic accuracy.

People

Silvia Francesca Storti

silviafrancesca.storti@univr.it

Edoardo Paolini

edoardo.paolini@univr.it