GP.04 Network connectivity following a single unprovoked seizure using 7 Tesla resting-state fMRI. (June 2017)

• Record Type: Journal Article
• Authors: Ikeda, KM; Mirsattari, SM; Khan, AR; Johnsrude, I; Burneo, JG; Peters, TM
• Is Part Of: Canadian journal of neurological sciences. Volume 44(2017)Supplement 2
• Page Start: S8
• Page End: S8
• Publication Date: 2017-06
• Subjects: Neurology -- Periodicals; Nervous system -- Surgery -- Periodicals; Electronic journals; 616.8
• DOI: 10.1017/cjn.2017.63
• Languages: English
• ISSNs: 0317-1671

Abstract

Abstract : Background: Predicting epilepsy following a first seizure is difficult. Network abnormalities are observed in patients with epilepsy using resting-state functional MRI (rs-fMRI), which worsen with duration of epilepsy. We use rs-fMRI to identify network abnormalities in patients after a first seizure that can be used as a biomarker to predict development of epilepsy.Methods: Patients after a single, unprovoked seizure and age/sex matched healthy controls underwent 7 Tesla structural and resting-state functional MRI. Data were analyzed using graph theory measures. Patients were followed for development of epilepsy.Results: Nine patients and nine control subjects were analyzed. There were no differences in baseline characteristics. No patients developed epilepsy (average follow-up 3 months). No differences between groups occurred on a whole-brain network level. At a 20% threshold, significant differences occurred in the default mode network (DMN). Patients demonstrated an increased local efficiency (p=0.02) and clustering coefficient (p=0.04), and decreased path length (p=0.02) and betweenness centrality (p=0.02).Conclusions: No whole-brain network changes occur after a single unprovoked seizure. No patient has developed epilepsy suggesting this group does not have network alterations after a single seizure. In the DMN, the alterations noted indicate increased segregation of network function.