Epilepsy neuroimaging is important for detecting the seizure onset zone, predicting and preventing deficits from surgery and illuminating mechanisms of epileptogenesis. An aspiration is to integrate imaging and genetic biomarkers to enable personalized epilepsy treatments.
The ability to detect lesions, particularly focal cortical dysplasia and hippocampal sclerosis, is increased using ultra high-field imaging and postprocessing techniques such as automated volumetry, T2 relaxometry, voxel-based morphometry and surface-based techniques. Statistical analysis of PET and single photon emission computer tomography (STATISCOM) are superior to qualitative analysis alone in identifying focal abnormalities in MRI-negative patients. These methods have also been used to study mechanisms of epileptogenesis and pharmacoresistance.
Recent language fMRI studies aim to localize, and also lateralize language functions. Memory fMRI has been recommended to lateralize mnemonic function and predict outcome after surgery in temporal lobe epilepsy.
Combinations of structural, functional and post-processing methods have been used in multimodal and machine learning models to improve the identification of the seizure onset zone and increase understanding of mechanisms underlying structural and functional aberrations in epilepsy.
aDepartment of Clinical and Experimental Epilepsy, National Institute for Health Research University College London Hospitals Biomedical Research Centre, Institute of Neurology, University College London, London
bChalfont Centre for Epilepsy, Chesham Lane, Chalfont St. Peter, Gerrards Cross, UK
cStichting Epilepsie Instellngen Nederland, Achterweg 5, Heemstede, The Netherlands
Correspondence to Dr Meneka Kaur Sidhu, MBChB, MRCP, PhD, Depatment of Clinical and Experimental Epilepsy, UCL, Institute of Neurology, 33 Queen Square, London WC1N 3BG, UK. Tel: +44 20 3448 8612; fax: +44 20 3448 8615; e-mail: email@example.com