Convolutional neural network-aided tuber segmentation in tuberous sclerosis complex patients correlates with electroencephalogram.

OBJECTIVE: One of the clinical hallmarks of tuberous sclerosis complex (TSC) is radiologically identified cortical tubers, which are present in most patients. Intractable epilepsy may require surgery, often involving invasive diagnostic procedures such as intracranial electroencephalography (EEG). Identifying the location of the dominant tuber responsible for generating epileptic activities is a critical issue. However, the link between cortical tubers and epileptogenesis is poorly understood. Given this, we hypothesized that tuber voxel intensity may be an indicator of the dominant epileptogenic tuber. Also, via tuber segmentation based on deep learning, we explored whether an automatic quantification of the tuber burden is feasible. METHODS: We annotated tubers from structural magnetic resonance images across 29 TSC subjects, summarized tuber statistics in eight brain lobes, and determined suspected epileptogenic lobes from the same group using EEG monitoring data. Then, logistic regression analyses were performed to demonstrate the linkage between the statistics of cortical tuber and the epileptogenic zones. Furthermore, we tested the ability of a neural network to identify and quantify tuber burden. RESULTS: Logistic regression analyses showed that the volume and count of tubers per lobe, not the mean or variance of tuber voxel intensity, were positively correlated with electrophysiological data. In 47.6% of subjects, the lobe with the largest tuber volume concurred with the epileptic brain activity. A neural network model on the test dataset showed a sensitivity of .83 for localizing individual tubers. The predicted masks from the model correlated highly with the neurologist labels, and thus may be a useful tool for determining tuber burden and searching for the epileptogenic zone. SIGNIFICANCE: We have proven the feasibility of an automatic segmentation of tubers and a derivation of tuber burden across brain lobes. Our method may provide crucial insights regarding the treatment and outcome of TSC patients.

The role of stereo-electroencephalography to localize the epileptogenic zone in children with nonlesional brain magnetic resonance imaging.

OBJECTIVE: This study aimed to assess the clinical outcome and outcome predictive factors in pediatric epilepsy patients evaluated with stereo-electroencephalography (SEEG). METHODS: Thirty-eight patients who underwent SEEG implantation at the Pediatric Epilepsy Center in New York Presbyterian Hospital between June 2014 and December 2019 were enrolled for retrospective chart review. Postoperative seizure outcomes were evaluated in patients with at least 12-months follow up. Meta-analysis was conducted via electronic literature search of data reported from 2000 to 2020 to evaluate significant surgical outcome predictors for SEEG evaluation in the pediatric population. RESULTS: In the current case series of 25 postsurgical patients with long-term follow up, 16 patients (64.0%) were seizure free. An additional 7 patients (28.0%) showed significant seizure improvement and 2 patients (8.0%) showed no change in seizure activity. Patients with nonlesional magnetic resonance imaging (MRI) achieved seizure freedom in 50% (5/10) of cases. By comparison, 73% (11/15) of patients with lesional MRI achieved seizure freedom. Out of 12 studies, 158 pediatric patients were identified for inclusion in a meta-analysis of the effectiveness of SEEG. Seizure freedom was reported 54.4% (n = 86/158) of patients at last follow up. Among patients with nonlesional MRI, 45% (n = 24) achieved seizure freedom compared with patients with lesional MRI findings (61.2%, n:= 60) (p = 0.02). The risk for seizure recurrence was 2.15 times higher [95% confidence interval [CI] 1.06-4.37, p = 0.033] in patients diagnosed with nonlesional focal epilepsy compared to those with lesional epilepsy [ 1.49 (95% CI 1.06-2.114, p = 0.021]. CONCLUSION: Evaluation by SEEG implantation in pediatric epilepsy is effective in localizing the epileptogenic zone with favorable outcome. Presence of a non-lesional brain MRI was associated with lower chances of seizure freedom. Further research is warranted to improve the efficacy of SEEG in localizing the epileptogenic zone in pediatric patients with non-lesional brain MRI.