Structural Alterations in People with Functional Seizures
Abstract number :
2.301
Submission category :
5. Neuro Imaging / 5A. Structural Imaging
Year :
2024
Submission ID :
921
Source :
www.aesnet.org
Presentation date :
12/8/2024 12:00:00 AM
Published date :
Authors :
Presenting Author: Fenglai Xiao, MD PhD – Department of Clinical and Experimental Epilepsy, Institute of Neurology, Faculty of Brain Sciences, University College London
Nisa Kahn, BS – Department of Clinical and Experimental Epilepsy, Institute of Neurology, Faculty of Brain Sciences, University College London
Rohan Kandasamy, MD – Department of Clinical and Experimental Epilepsy, Institute of Neurology, Faculty of Brain Sciences, University College London
Lawrence Binding, PhD – Department of Clinical and Experimental Epilepsy, Institute of Neurology, Faculty of Brain Sciences, University College London
Marine Fleury, PhD – Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology,University College London
Davide Giampiccolo, MD – Department of Clinical and Experimental Epilepsy, Institute of Neurology, Faculty of Brain Sciences, University College London
John Duncan, MD – University College London
Matthias J Koepp, MD PhD – Department of Clinical & Experimental Epilepsy, UCL Queen Square Institute of Neurology, London WC1N 3BG & Chalfont Centre for Epilepsy, Chalfont St Peter SL9 0RJ, United Kingdom
Mahinda Yogarajah, MD PhD – Department of Clinical and Experimental Epilepsy, Institute of Neurology, Faculty of Brain Sciences, University College London
Rationale: Functional seizures (FSs) are episodes that resemble epileptic seizures but are not caused by epileptic discharges in the brain. Dissociation is recognized as a key factor in the occurrence of FSs.
Methods: We retrospectively analysed high-resolution T1-weighted MRI scans from 60 people diagnosed with FS and 118 matched healthy controls at a tertiary epilepsy referral centre. We used the Computational Anatomy Toolbox (CAT12) in SPM12 to estimate cortical thickness and brain volumes. Volumes of the hippocampus and other subcortical structures, including the thalamus, amygdala, caudate, putamen, and globus pallidus, as well as the total intracranial volume (TIV), were extracted using Hipposeg and Geodesic Information Flows (GIF), two deep learning segmentation, two deep learning segmentation tools freely available through NiftyWeb (http://cmictig.cs.ucl.ac.uk/niftyweb, UCL Centre for Medical Image Computing, UK). Thalamic segmentations were processed via THOMAS on Freesurfer. Vertex-wise surface-based cortical thickness and volume-based analyses were performed with CAT12 using a full-factorial analysis. Multiple variate general linear models were fitted in SPSS for hippocampal, subcortical, brainstem, cerebellar and thalamic subnuclei volumes. All models were corrected for age at scan, sex, and TIV with family-wise error (FWE) correction in SPM and Bonferroni correction in SPSS.
Results: People with FS demonstrated significantly reduced cortical thickness in the insula bilaterally (right: 1083 vertices, p< 0.001, FWE-corrected; left: 515 vertices, p=0.005, FWE-corrected), left Rolandic operculum (4721 vertices, p< 0.001, FWE-corrected), right superior frontal gyrus (1808 vertices, p< 0.001, FWE-corrected), and right anterior cingulate cortex (1389 vertices, p< 0.001, FWE-corrected). In the volume-based analysis, people with FS showed decreased volumes bilaterally in the hippocampus and thalamus, midbrain and cerebellum (p< 0.001, FWE-corrected). Analysis of thalamus subnuclei revealed atrophies in nuclei related to visual and somatosensory functions (p< 0.001, Bonferroni-corrected).
Neuro Imaging