Authors :
Presenting Author: Jonathan Horsley, BSc – Newcastle University
Rhys Thomas, MD, PhD – Newcastle University; Fahmida Chowdhury, MD, PhD – UCL; Beate Diehl, MD, PhD – UCL; Andrew McEvoy, MD – UCL; Anna Miserocchi, MD – UCL; Jane de Tisi, BA – UCL; Sjoerd Vos, PhD – UCL; Matthew Walker, MD, PhD – UCL; Gavin Winston, MD – Queen's University; John Duncan, MD – UCL; Yujiang Wang, PhD – Newcastle University; Peter Taylor, PhD – Newcastle University
Rationale: When investigating suitability for epilepsy surgery, people with drug-refractory focal epilepsy may have intracranial EEG (iEEG) electrodes implanted to localise sites of seizure onset. Diffusion-weighted magnetic resonance imaging (dMRI) may be acquired to identify key white matter tracts for surgical avoidance. Here, we investigate whether structural connectivity abnormalities, inferred from dMRI, may be used in conjunction with functional iEEG abnormalities to aid localisation and resection of the epileptogenic zone (EZ), and improve surgical outcomes in epilepsy.
Methods:
We retrospectively investigated data from 43 patients with epilepsy who had surgery following iEEG. Twenty five patients (58%) were free from disabling seizures (ILAE 1 or 2) at one year. For all patients, T1-weighted and diffusion-weighted MRIs were acquired prior to iEEG implantation. Interictal iEEG functional, and dMRI structural connectivity abnormalities were quantified by comparison to a normative map and healthy controls respectively.
First, we explored the relationship between structural connectivity and functional iEEG abnormalities and whether the resection of maximal abnormalities related to improved surgical outcomes. Second, we investigated whether the modalities provided complementary information and concurrent use of both modalities improved the prediction of surgical outcome. Third, we suggest how connectivity abnormalities may be useful to inform the placement of iEEG electrodes as part of the pre-surgical evaluation using a patient case study.
Results:
Seizure freedom was 15 times more likely in those patients with resection of maximal connectivity and iEEG abnormalities (p=0.008). Both modalities were separately able to distinguish patient outcome groups and when used simultaneously, a decision tree correctly separated 36 out of 43 (84%) patients based on surgical outcome.
Conclusions:
Structural dMRI could be used in pre-surgical evaluations, particularly when localisation of the EZ is uncertain and iEEG implantation is being considered. Regions with the greatest structural connectivity reductions should be strongly considered for sampling by iEEG electrodes. Our approach allows for the proposal of a personalised iEEG implantation and resection which may lead to improved surgical outcome for an individual patient.
Funding:
B.D. receives support from the NIH National Institute of Neurological Disorders and Stroke U01-NS090407 (Center for SUDEP Research) and Epilepsy Research UK. Y.W. gratefully acknowledges funding from Wellcome Trust (208940/Z/17/Z) and is supported by a UKRI Future Leaders Fellowship (MR/V026569/1). G.P.W. was supported by the MRC (G0802012, MR/M00841X/1). P.N.T. is supported by a UKRI Future Leaders Fellowship (MR/T04294X/1). J.J.H. and T.W.O are supported by the Centre for Doctoral Training in Cloud Computing for Big Data (EP/L015358/1). JD is grateful to Wellcome Trust (WT106882) and Epilepsy Research UK. We are grateful to the Epilepsy Society for supporting the Epilepsy Society MRI scanner. This work was supported by the National Institute for Health Research University College London Hospitals Biomedical Research Centre.