Surface and deep EEG correlates of surgical outcome in temporal lobe epilepsy.

Abstract

Interictal and ictal EEG characteristics derived from limited surface montages and medial temporal lobe sites were compared with long-term seizure relief following anterior temporal lobectomy in 52 epileptics. Patients were classified into one of four surgical outcome groups, ranging from seizure free to no clinical improvement. For each patient, interictal records were analyzed according to deep and surface spike characteristics and background activity. Ictal records were analyzed according to the proportion of episodes initiated in a unilateral or bilaterally synchronous fashion, the proportion of surface or deep onsets, the variability of onset location, and the morphology of seizures onsets. Interictal EEG variables that correlates with surgical outcome included: (a) various types of bilaterally synchronous surface/deep spikes; (b) diffuse background slowing; (c) sharp waves; and (d) the presence of multiple independent deep spike patterns in the lobe chosen for resection. Relevant ictal EEG variables included: (a) episodes initiated in a bilaterally synchronous fashion; (b) variability in seizure onset location; (c) the proportion of precisely focal onsets from deep sites; (d) the proportion of surface onsets; and (e) the proportion of onsets from the side chosen for resection. Multivariate analysis of these data with linear, stepwise, discriminate analysis and adaptive, nonlinear, distribution-free pattern recognition demonstrated that: (a) both interictal and ictal EEG characteristics can independently predict surgical outcome at levels significantly better than chance; (b) ictal and interictal EEG data contain nonredundant information for making such predictions; and (c) nonlinear pattern recognition techniques are capable of deriving the most accurate rules for predicting the effects of surgery.