Multicentre Epilepsy Lesion Detection project: bringing AI into epilepsy presurgical planning

ICNC2024
Symposia: Big Data, Artificial Intelligence and Machine Learning In The Diagnosis and Management of Epilepsy

Multicentre Epilepsy Lesion Detection project: bringing AI into epilepsy presurgical planning
Konrad Wagstyl

Focal cortical dysplasias (FCDs) are a common cause of drug-resistant epilepsy that can be challenging to identify on MRI. However, when detected, they can often be treated effectively through surgical resection. The Multi-centre Epilepsy Lesion Detection (MELD) Project is an international collaboration dedicated to improving the detection of FCDs in patients with drug-resistant epilepsy. In this talk, I will present our work on developing and training a neural network to detect FCDs using a large cohort of 1015 MRI scans from 22 epilepsy centres worldwide. Our algorithm achieved an overall sensitivity of 67% and was able to detect 63% of lesions previously considered MRI-negative. I will also discuss how our pipeline generates individual patient reports that identify the locations of predicted lesions and their imaging features and relative saliencies to the classifier. Finally, I will share updates on how the MELD pipeline is being integrated into presurgical planning for epilepsy at Great Ormond Street Hospital (GOSH) and other centres around the world.

Other Lectures in this symposium:
Artificial Intelligence in the diagnosis of epilepsy in resource poor areas.
Generative models of brain dynamics in epilepsy
Machine Learning to improve diagnosis of epilepsy in infancy and potential solution for remote detection.