Abstracts

Resting-State Functional Magnetic Resonance Imaging in Functional Seizures: A Systematic Review and Meta-analysis

Abstract number : 3.24
Submission category : 5. Neuro Imaging / 5B. Functional Imaging
Year : 2023
Submission ID : 999
Source : www.aesnet.org
Presentation date : 12/4/2023 12:00:00 AM
Published date :

Authors :
Presenting Author: Maryam Homayoun, MD – Monash University

Alfred Lo, MPhil – University of Melbourne; Patrick Kwan, MB, BChir, PhD, FRCP, FRACP, FAHMS – Monash University and University of Melbourne; Tobias Winton-Brwon, BA, BSc, MBBS (hons), MRCPsych, FRANZCP, AFRACMA, PhD – Monash University; Andrew Neal, MBBS, BMedSci, FRACP, PhD – Monash University and University of Melbourne; Richard Kanaan, BA, MA, MBBS, MRCPsych, PhD, FRANZCP – University of Melbourne

Rationale:

Functional seizures (FS) are abrupt changes in consciousness and behaviours related to psychological causes that resemble epileptic seizures but are not associated with epileptiform discharges in the brain. Current FS diagnosis relies on patients’ clinical profiles and negative ictal recordings obtained during video electroencephalogram monitoring. However, recent models propose that FS symptoms are associated with structural and functional brain abnormalities, which may be used as biomarkers to support the diagnosis and prognosis, and to guide treatment. This systematic review aimed to review studies using quantitative brain imaging analysis in patients with FS compared with healthy controls (HC).



Methods:

From an initial pool of 1793 potential studies, 21 studies were included in this systematic review after the screening of titles, abstracts, and full-text articles, and exclusion of duplicates and other non-suitable studies. There was a range of neuroimaging methods and analyses used in the 21 included studies. Due to difficulty integrating the result of different modalities and methods, the result of five seed-based/region of interest (ROI)-to-whole brain functional connectivity analysis is being presented here which is the most used method in the included studies.

We retrieved all coordinates of abnormal functional connectivity associated with FS compared to HC. Then each seed was categorized into a network by its location within a priori 7-network parcellation (Thomas Yeo et al., 2011). Activation likelihood estimation (ALE) meta-analysis (1,000 permutations, cluster-level family-wise error-corrected P < 0.05) was then performed for just the somatomotor network (SMN), but not for the frontoparietal, visual, default mode, ventral attention (VAN), dorsal attention (DAN) and limbic/sub-cortical network (due to a lack of primary studies) to identify area(s) of significant convergence among the coordinates.

Neuro Imaging