Quantitative Analysis of Visually Reviewed Normal Scalp EEG Predicts Seizure Freedom Following Anterior Temporal Lobectomy



Anterior temporal lobectomy (ATL) is a widely performed and successful intervention for drug-resistant temporal lobe epilepsy (TLE). However, up to a third of patients experience seizure recurrence within one year after ATL. Despite the extensive literature on presurgical EEG and MRI abnormalities to prognosticate seizure freedom following ATL, the value of quantitative analysis of visually reviewed normal interictal EEG in such prognostication remains unclear. In this retrospective multicenter study, we investigate whether machine learning analysis of normal interictal scalp EEGs can inform the prediction of postoperative seizure freedom outcomes in patients who underwent ATL.


We analyzed normal presurgical scalp EEGs from 41 Mayo Clinic (MC) and 23 Cleveland Clinic (CC) patients. We used an unbiased automated algorithm to extract eyes closed awake epochs from scalp EEGs that were free of any epileptiform activity and then extracted spectral EEG features representing a) spectral power and b) interhemispheric spectral coherence in frequencies between 1-25 Hz across several brain regions. We analyzed the differences between the seizure-free and non-seizure-free patients and employed a Naïve Bayes classifier using multiple spectral features to predict surgery outcomes. We trained the classifier using a leave-one-patient-out cross-validation scheme within the MC dataset and then tested using the out-of-sample CC dataset. Finally, we compared the predictive performance of normal scalp EEG-derived features against MRI abnormalities.


We found that several spectral power and coherence features showed significant differences correlated with surgical outcomes and that they were most pronounced in the 10 – 25 Hz range. The Naïve Bayes classification based on those features predicted 1-year seizure freedom following ATL with AUC values of 0.78 and 0.76 for the MC and CC datasets, respectively. Subsequent analyses revealed that a) ISD features in the 10 – 25 Hz range provided better predictability than other combinations and b) normal scalp EEG-derived features provided superior and potentially distinct predictive value when compared with MRI abnormalities (>10% higher F1-score).


These results support that quantitative analysis of even a normal presurgical scalp EEG may help prognosticate seizure freedom following ATL in patients with drug-resistant TLE. While the mechanism for this result is not known, the scalp EEG spectral and coherence properties predicting seizure freedom may represent activity arising from the neocortex or the networks responsible for temporal lobe seizure generation within versus outside the margins of an ATL.