Improvement in Detectability of fMRI Responses Related to IEDs with Multi-Echo Scanning
Poster No:
215
Submission Type:
Abstract Submission
Authors:
Zhengchen Cai1, Thaera Arafat1, Nicolás von Ellenrieder1, Boris Bernhardt1, Jean Gotman1
Institutions:
1The Neuro (Montreal Neurological Institute-Hospital), Montreal, Quebec
First Author:
Co-Author(s):
Introduction:
Simultaneous electroencephalography–functional magnetic resonance imaging (EEG-fMRI) provides whole-brain coverage with high spatial resolution from fMRI and specificity to EEG-derived epileptic activity, making it a unique and noninvasive tool for epilepsy presurgical evaluation (Khoo et al., 2018). Its sensitivity in detecting the epileptogenic zone is approximately 0.6 (Koupparis et al., 2021) since the key challenge is the relatively low contrast-to-noise ratio of the fMRI response, especially when only a few epileptic discharges are detected during the EEG-fMRI scan. Multi-echo fMRI collects functional images across different echo times, and combining these images removes motion- and physiological noise effects, ultimately boosting sensitivity (Kundu et al., 2012). In this study, we investigated the detectability of fMRI responses related to interictal epileptic discharges (IEDs) using EEG-fMRI scans using multi-echo fMRI.
Methods:
We scanned 14 patients with EEG-fMRI using a multi-echo fMRI sequence on a Siemens 3T scanner (3.7 mm isotropic voxel, TE = 11.4, 24.7, and 38.0ms; TR = 1.90s for 3 patients and 1.05s for 11 patients). MR gradient artifact in EEG was removed using an average template subtraction approach. Ballistocardiogram artifact in EEG was removed using concurrent carbon wire loop recordings (van der Meer et al., 2016). IEDs were annotated by an experienced neurophysiologist (T.A.) on processed EEGs. Functional images were processed using AFNI software (Cox, 1996), resulting in three IED response maps for each type of IED of each patient using: 1) the single echo (SE) – 2nd echo of the multi-echo scan; 2) the optimally combined multi-echo (OC) algorithm; and 3) the multi-echo independent component analysis (ICA) algorithm. To assess the improvement in fMRI temporal signal-to-noise ratio (tSNR), the ratio of tSNR for each multi-echo method to the single echo was calculated. The tSNR was defined as the mean signal divided by its standard deviation after drift removal and motion correction. Voxel-wise t-value ratios within the common statistically significant IED response voxels across the three methods were computed to evaluate improvements in the standardized response effect. Similarly, improvements in IED-related fMRI signal changes were assessed using percentage change ratios.
Results:
Fig. 1 shows that the OC and ICA multi-echo methods improved the fMRI tSNR by a median of 29% (95% CI [0, 55]) and 48% (95% CI [0, 71]), respectively, across all brain voxels, compared to the SE. Improvement in tSNR was observed over the whole brain, with prominent effects in the inferior temporal and frontal lobes. Multi-echo methods provided a greater number of statistically significant voxels associated with IED responses (median ± mean absolute deviation: 18 ± 27 for SE, 31 ± 46 for OC, and 33 ± 49 for ICA).
In Fig. 2, the t-values of all significant voxels from the multi-echo methods were slightly higher than those from SE (with median ratio values larger than 1), while the multi-echo methods reduced the overestimation of fMRI percentage changes, as indicated by the ratios of IED-related fMRI percentage changes (compared to SE) being smaller than 1 (Cai et al., 2023).
In Fig. 2, the t-values of all significant voxels from the multi-echo methods were slightly higher than those from SE (with median ratio values larger than 1), while the multi-echo methods reduced the overestimation of fMRI percentage changes, as indicated by the ratios of IED-related fMRI percentage changes (compared to SE) being smaller than 1 (Cai et al., 2023).
Conclusions:
Overall, acquiring multi-echo fMRI data appears to have no significant drawbacks and offers moderate improvement in the detectability of fMRI responses related to IEDs compared to contentional SE acquisitions. Multi-echo primarily aids in reducing noise, resulting in less overestimation of the fMRI response amplitude while maintaining statistical power. Greater improvement may be anticipated when the epileptic focus is on the inferior temporal and frontal lobes. Further assessment is needed to evaluate the improvement in clinical utility by comparing it to the epileptic focus.
Disorders of the Nervous System:
Neurodegenerative/ Late Life (eg. Parkinson’s, Alzheimer’s) 1
Modeling and Analysis Methods:
Activation (eg. BOLD task-fMRI)
EEG/MEG Modeling and Analysis
Novel Imaging Acquisition Methods:
BOLD fMRI 2
EEG
Keywords:
Electroencephaolography (EEG)
Epilepsy
FUNCTIONAL MRI
1|2Indicates the priority used for review
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Provide references using APA citation style.
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