Abstracts

Peri-ictal white matter changes using DTI- a prospective study

Abstract number : 1.230
Submission category : 5. Neuro Imaging / 5A. Structural Imaging
Year : 2017
Submission ID : 342611
Source : www.aesnet.org
Presentation date : 12/2/2017 5:02:24 PM
Published date : Nov 20, 2017, 11:02 AM

Authors :
Jennifer Williams, TBSI, Trinity College Dublin and Dept of Neurology, St. James's , Dublin.; Peter Bede, St James's Hospital and Trinity College Dublin; Una Kennedy, St James's Hospital, Dublin; James Meaney, St.James's Hospital, Dublin 8.; and Colin Doh

Rationale: Studies utilizing MRI and DTI (Diffusion Tensor Imaging) have shown that in chronic epilepsy cohorts microstructural changes both within the hippocampus and subcortical brain structures can be identified. The aim of this study was to characterize peri-ictal white matter alterations and to assess reversibility in the acute peri-ictal period. Multiple white matter indices were evaluated to explore if the pathological substrate of these changes is primarily inflammation, axonal and myelination related change. Methods: Patients were prospectively recruited from the emergency department of a tertiary referral hospital. Patients were scanned within 72hrs of a convulsion, clinical and laboratory data were recorded. The patients were followed up at a 6 week interval, re-scanned and clinically assessed. MR data were acquired on a 3T Philips Achieva system with a gradient strength of 80 mT/m and slew rate of 100 T/m/s using an 8-channel receive-only head coil. DTI were acquired using a spin-echo planar imaging (SE-EPI) sequence with a 32-direction Stejskal-Tanner diffusion encoding scheme. Pre-processing included eddy current and motion corrections and brain-tissue extraction. A DTI model was fitted at each voxel, generating maps of fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD). Each subject's FA data was projected onto a mean FA skeleton representing the common white matter tracts and the resulting data were subsequently fed into voxel-wise cross-subject statistics. Peri-ictal and follow-up scans were compared with healthy controls using a voxel-based generalised linear model and permutation-based non-parametric testing. Results: 20 patients and 20 controls were recruited into the study at T1 and 16 patients had follow up at T2.FA analyses did not reveal significant peri-ictal white matter alterations. MD, AD and RD analyses revealed significant peri-ictal white matter alterations in comparison to controls which subsided at follow-up. AD analyses captured peri-ictal right temporal and para-hippocampal white matter alterations which reversed on follow-up. (Figure 1.) MD analyses reveal additional peri-ictal corpus callosum, thalamic, occipital and parietal diffusivity changes which partially resolved on follow-up imaging. RD analyses mirrored the findings of AD statistical maps confirming a similar reduction of white matter change on follow-up imaging. (Figure 2.) Conclusions: The study confirms considerable dynamic post ictal-white matter changes which show partial resolution over time. Despite ample reports of qualitative peri-ictal changes there is a paucity of prospective quantitative neuroimaging studies to specifically evaluate the location, chronology and nature of these alterations. Using multiple diffusivity metrics allows a more detailed characterisation of transient white matter pathology and contributes to our understanding of focal molecular processes and deciphering anatomical vulnerability patterns in epileptogenesis. Funding: This work was supported via the St. James's Hospital Foundation and the Academic Unit of Neurology in Trinity College Dublin.
Neuroimaging