P.035 Correlation of thalamic connectivity with the duration of epilepsy in patients with temporal lobe epilepsy. (2nd June 2017)

• Record Type: Journal Article
• Authors: Santyr, B; Lau, JC; Mirsattari, SM; Burneo, JG; de Ribaupierre, S; Steven, DA; Parrent, AG; MacDougall, KW; Peters, TM; Khan, AR
• Is Part Of: Canadian journal of neurological sciences. Volume 44(2017)Supplement 2
• Page Start: S22
• Page End: S22
• Publication Date: 2017-06-02
• Subjects: Neurology -- Periodicals; Nervous system -- Surgery -- Periodicals; Electronic journals; 616.8
• DOI: 10.1017/cjn.2017.120
• Languages: English
• ISSNs: 0317-1671

Abstract

Abstract : Background: Morphometry and connectivity studies targeting the thalamus have revealed specific patterns of atrophy and deafferentiation in patients with temporal lobe epilepsy (TLE). We used probabilistic tractography to investigate thalamic connectivity with respect to duration of epilepsy and surgical outcomes in TLE.Methods: Patients (N=20) with drug-resistant TLE (10 short duration (<15 years), 10 long duration (>15 years)) were scanned with multi-parametric 3T MRI and compared with 34 healthy controls. The Harvard-Oxford atlas was modified to create 14 target regions in the temporal lobes. Probabilistic tractography (FSL) was used to delineate thalamic sub-regions most connected to each target. The volume, mean T1, T2, FA and MD of each thalamic sub-region was quantified. Surgical success was quantified using Engel outcome scores.Results: Significant decreases in thalamic connected volumes to the hippocampus in patients with longer duration of TLE were revealed. Likewise, when stratified based on surgical success, significant differences in diffusion metrics to the hippocampus, parahippocampal gyrus, and temporal neocortex were found. Significant differences did not withstand false discovery rate (FDR) correction.Conclusions: These findings suggest ongoing connectivity changes dependent on epilepsy duration and promote further investigation into the use of thalamic connectivity data as biomarkers for predicting surgical outcomes in TLE patients.