Abstract

Paediatric patients with drug-resistant focal epilepsy (DRFE) who have no clear focal lesion identified on conventional structural magnetic resonance imaging (MRI) are a particularly challenging cohort to treat and form an increasing part of epilepsy surgery programs. A recently developed deep-learning-based MRI lesion detection algorithm, the Multicentre Lesion Detection (MELD) algorithm, has been shown to aid detection of focal cortical dysplasia (FCD). We applied this algorithm retrospectively to a cohort of MRI-negative children with refractory focal epilepsy who underwent stereoelectroencephalography (SEEG) to determine its accuracy in identifying unseen epileptic lesions, seizure onset zones and clinical outcomes.