Purpose: Magnetic resonance imaging (MRI) and positron emission tomography (PET) with 18F-fluorodeoxyglucose (18FDG) are valuable tools for evaluating hippocampal sclerosis (HS); however, bias may arise during visual analyses. The aim of this study was to evaluate and compare MRI and PET post-processing techniques, automated quantitative hippocampal volume (Q-volume), and fluid-attenuated inversion-recovery (FLAIR) signal (Q-FLAIR) and glucose metabolism (Q-PET) analyses in patients with HS.Methods: We collected MRI and 18FDG-PET images from 54 patients with HS and 22 healthy controls and independently performed conventional visual analyses (CVA) of PET (CVA-PET) and MRI (CVA-MRI) images. During the subsequent quantitative analyses, the hippocampus was segmented from the 3D T1 image, and the mean volumetric, FLAIR intensity and standardized uptake value ratio (SUVR) values of the left and right hippocampus were assessed in each subject. Threshold confidence levels calculated from the mean volumetric, FLAIR intensity and SUVR values of the controls were used to identify healthy subjects or subjects with HS. The performance of the three methods was assessed using receiver operating characteristic (ROC) curves, and the detection rates of CVA-MRI, CVA-PET, Q-volume, Q-FLAIR, and Q-PET were statistically compared.Results: The areas under the curves (AUCs) for the Q-volume, Q-FLAIR, and Q-PET ROC analyses were 0.88, 0.41, and 0.98, which suggested a diagnostic method with moderate, poor, and high accuracy, respectively. Although Q-PET had the highest detection rate among the two CVA methods and three quantitative methods, the difference between Q-volume and Q-PET did not reach statistical significance. Regarding the HS subtypes, CVA-MRI, CVA-PET, Q-volume, and Q-PET had similar detection rates for type 1 HS, and Q-PET was the most sensitive method for detecting types 2 and 3 HS.Conclusions: In MRI or 18FDG-PET images that have been visually assessed by experts, the quantification of hippocampal volume or glucose uptake can increase the detection of HS and appear to be additional valuable diagnostic tools for evaluating patients with epilepsy who are suspected of having HS.

Objective Focal cortical dysplasia (FCD) represents an essential cause of drug‐resistant epilepsy with surgery as an effective treatment option. This study aimed to identify the important predictors of favorable surgical outcomes and the impact of the interictal scalp electroencephalogram (EEG) patterns in predicting postsurgical seizure outcomes. Methods We retrospectively evaluated 210 consecutive patients between 2015 and 2019. They were diagnosed with FCD by pathology, underwent resection, and had at least one year of postsurgical follow‐up. Predictors of seizure freedom were analyzed. Results Based on the information at the latest follow‐up, seizure outcome was classified as Engel Class I (seizure‐free) in 81.4% and Engel Class II‐IV (non‐seizure‐free) in 18.6% of patients. There were 43, 105, and 62 cases of FCD type I, type II, and type III, respectively. The interictal EEG showed a repetitive discharge pattern (REDP) in 87 (41.4%) patients, polyspike discharge pattern (PDP) in 41 (19.5%), and the coexistence of REDP and PDP in the same location in 32 (15.2%) patients. The analyzed patterns in order of frequency were repetitive discharges lasting 5 seconds or more (32.4%); polyspikes (16.7%); RED type 1 (11.4%); continuous epileptiform discharges occupying >80% of the recording (11.4%); RED type 2 (6.2%); brushes (3.3%); focal, fast, continuous spikes (2.4%); focal fast rhythmic epileptiform discharges (1.43%); and frequent rhythmic bursting epileptiform activity (1.4%). The coexistence of REDP and PDP in the same location on scalp EEG and complete resection of the assumed epileptogenic zone (EZ) was independently associated with favorable postsurgical prognosis. Significance Resective epilepsy surgery for intractable epilepsy caused by FCD has favorable outcomes. Interictal scalp EEG patterns were revealed to be predictive of excellent surgical outcomes and may help clinical decision‐making and enable better presurgical evaluation.