Predicting the Epileptic Seizure Onset Zone with Brain-Wide Alterations of Temporal Dynamics in fMRI
Abstract number :
1.259
Submission category :
5. Neuro Imaging / 5B. Functional Imaging
Year :
2023
Submission ID :
336
Source :
www.aesnet.org
Presentation date :
12/2/2023 12:00:00 AM
Published date :
Authors :
First Author: Karl-Heinz Nenning, PhD – Nathan S. Kline Institute for Psychiatric Research
Presenting Author: Erkam Zengin, MD – Zucker School of Medicine at Hofstra/Northwell
Ting Xu, PhD – Child Mind Institute; Erkam Zengin, MD – Northwell Health; Gelana Tostaeva, BS – Northwell Health; Elisabeth Freund, MS – Northwell Health; Stanley Colcombe, PhD – Nathan S. Kline Institute for Psychiatric Research; Ashesh Mehta, MD, PhD – Northwell Health; Michael Milham, MD, PhD – Child Mind Institute; Stephan Bickel, MD, PhD – Northwell Health
Rationale: Epilepsy has been recognized as a network disease that can disturb brain regions beyond a focal seizure onset. Previous studies linked an altered autocorrelation function (ACF) of brain activation to disturbed brain dynamics in the seizure onset region and beyond. Here, we used resting-state functional magnetic resonance imaging (rs-fMRI) to quantify brain-wide ACF decay rates in medically refractory epilepsy patients with medial temporal lobe seizure onset verified by intracranial EEG recordings, and how they may be disrupted due to the underlying disease. The ultimate goal is to determine the potential use of ACF decay rates to identify seizure onset zones (SOZ).
Methods: We studied rs-fMRI data (2mm isotropic voxels) from 17 patients with stereo EEG confirmed unilateral mesial temporal lobe epilepsy (TLE; 11 left). For each voxel, we established a feature vector characterizing the temporal dynamics based on different ACF decay rate measures (at half, at zero, and exponential). As a normative baseline, we utilized data from a group of 652 healthy controls (Cam-CAN). For each patient and voxel we quantified the deviation of the ACF decay rates from the healthy control population as an ACF anomaly score (z-score). We evaluated how these ACF anomalies differ between hemispheres ipsi- and contralateral to the seizure onset, and examined systematic deviations from the healthy baseline. Moreover, for each intracranial EEG electrode, we calculated the corresponding fMRI ACF anomalies and evaluated their predictive performance to classify electrodes that map the potential SOZ.
Results: Consistent deviations from healthy controls were observed ipsilateral but also contralateral to the seizure focus. Overall, we observed a trend towards slower ACF decay rates (a more constrained temporal dynamic) in temporal regions ipsilateral to the seizure onset. But slower ACF decay rates ipsilateral were also observed in precentral regions such as the inferior precentral sulcus and the precentral gyrus head/face area. Preliminary analysis of the lateralization of the ACF decay rates indicated that both the hippocampus and the insula, but also other subcortical structures as well as the cerebellum, exhibit altered temporal dynamics that can be associated with the side of seizure onset. Importantly, patient-specific classification of SOZ related electrodes demonstrated that fMRI ACF anomalies are sensitive to focal alterations and applicable in a predictive framework.
Conclusions: Our findings revealed widespread alterations of neural temporal dynamics in patients with temporal lobe epilepsy. The overall trend to a slower ACF decay suggests that spontaneous neural activity is less dynamic and more slowly changing in epilepsy. Also, the observed alterations on the contralateral hemisphere emphasize the notion of epilepsy as a network disease, affecting brain regions beyond a focal seizure onset. These preliminary results indicate that ACF anomalies show promise for non-invasively delineating seizure onset zones from rs-fMRI.
Funding: None
Neuro Imaging