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Structural brain network architecture and personalized medicine in epilepsy

ABSTRACT Introduction: Over the past decade, the field of epilepsy has witnessed growing efforts to identify objective biological measurements capable of predicting, among other issues, epileptogenesis, clinical trajectories, and response to treatment. Recent advances in computational algorithms and enhanced neuroimaging techniques have opened new and exciting windows for the development of in vivo non-invasive biomarkers based on structural network information with the potential to change the way we diagnose and manage epilepsy. Areas covered: The authors review data derived from diffusion weighted MRI and structural connectomics, the study of the physical connections that link different brain regions, as potential predictors of clinical presentation and outcomes of epilepsy. Expert commentary: There are promising results identifying diagnostic and prognostic biomarkers for epilepsy. More studies with a longitudinal approach are needed, especially specifically for biomarkers of epileptogenesis in humans. The enhancement of imaging techniques, the more widespread availability of high resolution MRI, and the improvement in computational algorithms will make processing of structural network information more efficient and cost-effective, and thus, a viable source of biomarkers for precision medicine in epilepsy.