Investigating the Neural Correlates of Breathing in Sudden Unexpected Death in Epilepsy (SUDEP) Using Resting-state fMRI Connectivity
Abstract number :
2.157
Submission category :
5. Neuro Imaging / 5B. Functional Imaging
Year :
2021
Submission ID :
1826202
Source :
www.aesnet.org
Presentation date :
12/5/2021 12:00:00 PM
Published date :
Nov 22, 2021, 06:53 AM
Authors :
Michalis Kassinopoulos, PhD - University College London; Laren Alphan - Department of Clinical and Experimental Epilepsy - University College London; Ronald Harper - Brain Research Institute - University of California at Los Angeles; Maxime Guye - APHM - Hôpital Universitaire Timone; Beate Diehl - Department of Clinical and Experimental Epilepsy - University College London; Louis Lemieux - Department of Clinical and Experimental Epilepsy - University College London
Rationale: Sudden unexpected death in epilepsy (SUDEP) is an important cause of premature mortality among people with epilepsy, second only to stroke in years of potential life lost from neurological diseases. Evidence from witnessed and monitored SUDEP cases indicate respiratory failures; yet, the underlying mechanisms remain obscure. Seizure-induced apnea is known to lead to low levels of oxygen saturation, and postictal central apnea is a risk factor for SUDEP. However, although some patients succumb to SUDEP after a few seizures, others survive hundreds of similar seizures, which suggests that additional pathophysiological mechanisms may exist in SUDEP victims (Devinsky & Sisodiya, Epilepsy Curr. 2021; 20:29-31). We sought to compare fMRI patterns of brain connectivity related to regular and irregular breathing in SUDEP cases with living epilepsy patients of varying SUDEP risk, and healthy controls.
Methods: Retrospective resting-state 3T fMRI data from 47 drug-resistant epilepsy patients: 19 low-SUDEP risk (no GTCS in the year preceding the scan), 19 high-risk ( >3 GTCS in the year preceding the scan) and 9 SUDEP cases, and 25 healthy controls, were analyzed. Motion and physiological artifacts were removed using aCompCor and global signal regression. The global signal, a signal strongly driven by breathing rate changes (Kassinopoulos & Mitsis, NeuroImage 2019; 202:116150), was also used to identify periods with regular and irregular breathing. Subsequently, the differences in thalamic functional connectivity (FC) between periods with regular and irregular breathing were computed for each subject. Following principal component analysis (Leonardi et al., NeuroImage 2013; 83:937-950) the subject-specific weights of 10 components were compared between the groups using one-way ANOVA (Fig. 1).
Results: One principal component exhibited significant differences in the subject-specific weights between the 4 groups (f-statistic: 5.9, p< 0.001), with the following thalamic connectivity pattern: positive correlations: bilateral frontal gyrus, posterior cingulate cortex, precuneus, angular gyrus, inferior parietal lobe and middle temporal gyrus; negative correlations: cuneus, bilateral lingual gyrus, fusiform gyrus, inferior frontal gyrus and left insula (Fig. 2). This connectivity was reduced in low-risk compared to healthy controls; whereas, the opposite trend was observed for SUDEP. High-risk patients exhibited similar levels as controls.
Neuro Imaging