Stereo-EEG propagating source reconstruction identifies new surgical targets for epilepsy patients.

Epilepsy surgery can eliminate seizures in patients with drug-resistant focal epilepsy. Surgical intervention requires proper identification of the epileptic network and often involves implanting stereo-EEG electrodes in patients where non-invasive methods are insufficient. However, only ∼60% of patients achieve seizure-freedom following surgery. Quantitative methods have been developed to help improve surgical outcomes. However, previous quantitative methods that localized interictal spike and seizure activity using stereo-EEG recordings did not account for the propagation path encoded by the temporal dynamics of stereo-EEG recordings. Reconstructing the seizure propagation path can aid in determining whether a signal originated from the seizure onset or propagation zone, which directly informs treatment decisions. We developed a novel source reconstruction algorithm, Temporally Dependent Iterative Expansion (TEDIE), that accurately reconstructs propagating and expanding neural sources over time. TEDIE iteratively optimizes the number, location and size of neural sources to minimize the differences between the reconstructed and recorded stereo-EEG signals using temporal information to refine the reconstructions. The TEDIE output comprises a movie of seizure activity projected onto patient-specific brain anatomy. We analysed data from 46 epilepsy patients implanted with stereo-EEG electrodes at Duke Hospital (12 patients) and the Hospital of the University of Pennsylvania (34 patients). We reconstructed seizure recordings and found that TEDIE's seizure onset zone reconstructions were closer to the resected brain region for Engel 1 compared to Engel 2-4 patients, retrospectively validating the clinical utility of TEDIE. We also demonstrated that TEDIE has prospective clinical value, whereby metrics that can be determined presurgically accurately predict whether a patient would achieve seizure-freedom following surgery. Furthermore, we used TEDIE to delineate new potential surgical targets in 12/23 patients who are currently Engel 2-4. We validated TEDIE by accurately reconstructing various dynamic synthetic neural sources with known locations and sizes. TEDIE generated more accurate, focal and interpretable dynamic reconstructions of seizures compared to other algorithms (sLORETA and IRES). Our findings demonstrate that TEDIE is a promising clinical tool that can greatly improve epileptogenic zone localization and epilepsy surgery outcomes.

Duke Scholars

Author Warren M. Grill Biomedical Engineering