Abstract
Intracranial EEG is used for two main purposes: to determine (i) if epileptic networks are amenable to focal treatment and (ii) where to intervene. Currently, these questions are answered qualitatively and differently across centres. There is a need to quantify the focality of epileptic networks systematically, which may guide surgical decision-making, enable large-scale data analysis and facilitate multi-centre prospective clinical trials. We analysed interictal data from 101 patients with drug-resistant epilepsy who underwent pre-surgical evaluation with intracranial EEG at a single centre. We chose interictal data because of its potential to reduce the morbidity and cost associated with ictal recording. Sixty-five patients had unifocal seizure onset on intracranial EEG, and 36 were non-focal or multi-focal. We quantified the spatial dispersion of implanted electrodes and interictal intracranial EEG abnormalities for each patient. We compared these measures against the '5 Sense Score,' a pre-implant prediction of the likelihood of focal seizure onset, assessed the ability to predict unifocal seizure onset by combining these metrics and evaluated how predicted focality relates to subsequent treatment and outcomes. The spatial dispersion of intracranial EEG electrodes predicted network focality with similar performance to the 5-SENSE score [area under the receiver operating characteristic curve = 0.68 (95% confidence interval 0.57, 0.78)], indicating that electrode placement accurately reflected pre-implant information. A cross-validated model combining the 5-SENSE score and the spatial dispersion of interictal intracranial EEG abnormalities significantly improved this prediction [area under the receiver operating characteristic curve = 0.79 (95% confidence interval 0.70, 0.88); P < 0.05]. Predictions from this combined model differed between surgical- from device-treated patients with an area under the receiver operating characteristic curve of 0.81 (95% confidence interval 0.68, 0.85) and between patients with good and poor post-surgical outcome at 2 years with an area under the receiver operating characteristic curve of 0.70 (95% confidence interval 0.56, 0.85). Spatial measures of interictal intracranial EEG abnormality significantly improved upon pre-implant predictions of network focality by area under the receiver operating characteristic curve and increased sensitivity in a single-centre study. Quantified focality predictions related to ultimate treatment strategy and surgical outcomes. While the 5-SENSE score weighed for specificity in their multi-centre validation to prevent unnecessary implantation, sensitivity improvement found in our single-centre study by including intracranial EEG may aid the decision on whom to perform the focal intervention. We present this study as an important step in building standardized, quantitative tools to guide epilepsy surgery.