Identifying a structural brain lesion on MRI is the most important factor that correlates with seizure freedom after surgery in patients suffering from drug-resistant focal epilepsy. By providing better image contrast and higher spatial resolution, structural MRI at 7 Tesla (7T) can lead to lesion detection in about 25% of patients presenting with negative MRI at lower fields. In addition to a better detection/delineation/phenotyping of epileptogenic lesions, higher signal at ultra-high field also facilitates more detailed analyses of several functional and molecular alterations of tissues, susceptible to detect epileptogenic properties even in absence of visible lesions. These advantages but also the technical challenges of 7T MRI in practice will be presented and discussed.

Epilepsy surgery is a safe but underutilised treatment for drug-resistant focal epilepsy. One challenge in the presurgical evaluation of patients with drug-resistant epilepsy are patients considered “MRI negative”, i.e. where a structural brain abnormality has not been identified on MRI. A major pathology in “MRI negative” patients is focal cortical dysplasia (FCD), where lesions are often small or subtle and easily missed by visual inspection. In recent years, there has been an explosion in artificial intelligence (AI) research in the field of healthcare. Automated FCD detection is an area where the application of AI may translate into significant improvements in the presurgical evaluation of patients with focal epilepsy. I will provide an overview of our automated FCD detection work, the Multicentre Epilepsy Lesion Detection (MELD) project and how AI algorithms are beginning to be integrated into epilepsy presurgical planning at Great Ormond Street Hospital and elsewhere around the world. Finally, I will discuss the challenges and future work required to bring AI to the forefront of care for patients with epilepsy.