Geometric representations of brain networks can predict the surgery outcome in temporal lobe epilepsy.

ABSTRACT: Epilepsy surgery, particularly for temporal lobe epilepsy (TLE), remains a vital treatment option for patients with drug-resistant seizures. However, accurately predicting surgical outcomes remains a significant challenge. This study introduces a novel biomarker derived from brain connectivity, analyzed using non-Euclidean network geometry, to predict the surgery outcome in TLE. Using structural and diffusion magnetic resonance imaging (MRI) data from 51 patients, we examined differences in structural connectivity networks associated with surgical outcomes. Our approach uniquely utilized hyperbolic embeddings of pre- and post-surgery brain networks, successfully distinguishing patients with favorable outcomes from those with poor outcomes. Notably, the method identified regions in the cont

SUBMITTER: Guillemaud M 

PROVIDER: S-EPMC12267629 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature