Subcortical Shape Analysis in Patients with Neurocysticercosis Presenting with Seizures
Abstract number :
2.141
Submission category :
5. Neuro Imaging / 5A. Structural Imaging
Year :
2021
Submission ID :
1825810
Source :
www.aesnet.org
Presentation date :
12/5/2021 12:00:00 PM
Published date :
Nov 22, 2021, 06:50 AM
Authors :
Corey Ratcliffe, BSc, MRes - University of Liverpool; Guleed Adan, Dr - University of Liverpool; Christophe de Bézenac, Dr - University of Liverpool; Sanjib Sinha, Dr - NIMHANS; Jitender Saini, Dr - NIMHANS; Anthony Marson, Prof - University of Liverpool; Simon Keller, Dr - University of Liverpool
Rationale: Neurocysticercosis (NCC), a parasitic CNS infection endemic to developing nations, is the leading global cause of acquired epilepsy. It is currently unknown why some patients with NCC develop recurrent seizures, although previous research has suggested that ictogenesis is a consequence of abnormal sub-cortical circuitry. There is evidence for a relationship between hippocampal sclerosis and increased seizure incidence in NCC, and other subcortical structures, the thalamus in particular, are increasingly reported as abnormal in new-onset epilepsy. A relative sparsity of biomarker literature has been identified in NCC-based epileptogenesis, and so the present study aimed to assess the putative importance of sub-cortical abnormalities in NCC to the expression of spontaneous recurrent seizures. A common approach in epilepsy research, sub-cortical surface shape analysis, quantifies surface deflation of sub-cortical structures, providing a proxy measurement for localised atrophy.
Methods: Clinical histories and 3D-T1 MRI data were acquired from 83 patients with probable NCC, 49 with recurrent seizures and 34 without. The imaging data were examined using an established surface shape segmentation tool (FIRST) included as part of the FSL-ANAT processing pipeline in the FMRIB Software Library, with sex and age included as nuisance regressors in the final model. The FSL-ANAT pipeline reorientated, cropped, bias-field corrected, spatially normalised, brain-extracted, tissue-type segmented and parcellated the subcortical structures for surface shape analysis. The sub-cortical segmentations are input into a non-parametric t-test, which uses a permutation-modelled null to calculate and output multiple-comparison corrected (at p < 0.5) clusters of regional inward surface deflation on a 3D surface mesh.
Neuro Imaging