Combining Tractography and Intracranial EEG To Define the Structural Epileptic Network
Poster No:
1238
Submission Type:
Abstract Submission
Authors:
Arash Sarshoghi1,2, Denahin Toffa2, Emna Guibene1,2, Arman Sarshoghi3, Maxime Descoteaux4, François Rheault4, Elie Bou Assi1, Dang Nguyen1,5, Guillaume Theaud2, Sami Obaid2,6,1
Institutions:
1Department of Neuroscience, University of Montreal, Montreal, Canada, 2Neuroscience Research Axis, University of Montreal Hospital Research Center (CRCHUM), Montreal, Canada, 3Department of Medicine, University of Montreal, Montreal, Canada, 4University of Sherbrooke, Sherbrooke, Canada, 5Department of Neurology, University of Montreal Hospital Center (CHUM), Montreal, Canada, 6Division of Neurosurgery, Department of Surgery, University of Montreal Hospital Center (CHUM), Montreal, Canada
First Author:
Arash Sarshoghi
Department of Neuroscience, University of Montreal|Neuroscience Research Axis, University of Montreal Hospital Research Center (CRCHUM)
Montreal, Canada|Montreal, Canada
Department of Neuroscience, University of Montreal|Neuroscience Research Axis, University of Montreal Hospital Research Center (CRCHUM)
Montreal, Canada|Montreal, Canada
Co-Author(s):
Denahin Toffa
Neuroscience Research Axis, University of Montreal Hospital Research Center (CRCHUM)
Montreal, Canada
Neuroscience Research Axis, University of Montreal Hospital Research Center (CRCHUM)
Montreal, Canada
Emna Guibene
Department of Neuroscience, University of Montreal|Neuroscience Research Axis, University of Montreal Hospital Research Center (CRCHUM)
Montreal, Canada|Montreal, Canada
Department of Neuroscience, University of Montreal|Neuroscience Research Axis, University of Montreal Hospital Research Center (CRCHUM)
Montreal, Canada|Montreal, Canada
Dang Nguyen
Department of Neuroscience, University of Montreal|Department of Neurology, University of Montreal Hospital Center (CHUM)
Montreal, Canada|Montreal, Canada
Department of Neuroscience, University of Montreal|Department of Neurology, University of Montreal Hospital Center (CHUM)
Montreal, Canada|Montreal, Canada
Guillaume Theaud
Neuroscience Research Axis, University of Montreal Hospital Research Center (CRCHUM)
Montreal, Canada
Neuroscience Research Axis, University of Montreal Hospital Research Center (CRCHUM)
Montreal, Canada
Sami Obaid
Neuroscience Research Axis, University of Montreal Hospital Research Center (CRCHUM)|Division of Neurosurgery, Department of Surgery, University of Montreal Hospital Center (CHUM)|Department of Neuroscience, University of Montreal
Montreal, Canada|Montreal, Canada|Montreal, Canada
Neuroscience Research Axis, University of Montreal Hospital Research Center (CRCHUM)|Division of Neurosurgery, Department of Surgery, University of Montreal Hospital Center (CHUM)|Department of Neuroscience, University of Montreal
Montreal, Canada|Montreal, Canada|Montreal, Canada
Introduction:
Epilepsy affects approximately 50 million people globally, significantly impacting quality of life and healthcare systems1. While anti-seizure medications effectively control seizures in most patients, approximately one-third develop drug-resistant epilepsy, for whom epilepsy surgery represents a potentially curative option2. However, current surgical outcomes remain suboptimal, with 25-35% of operated patients continuing to experience seizures following the intervention3. Intracranial electroencephalography (icEEG), the gold standard for localizing seizure onset, offers direct recordings of neural activity within the cortex and thereby allows characterization of the cortical nodes of the epileptic network; however, it provides no information regarding the white matter components of the circuit4. By enabling reconstruction of white matter pathways, diffusion MRI tractography could complement icEEG to describe the white matter edges involved in the epileptic network.
Methods:
MRI scans (DWI and T1) were obtained from 16 patients with icEEG studies and 49 healthy controls. Images were processed through a comprehensive tractography and structural connectivity pipeline: 1) Tractoflow generated tractograms5, 2) Freesurfer-Flow segmented brains into 246 Brainnetome atlas parcels6, 3) Surface-Enhanced Tractography processed the initial tractograms and corrected for the gyral bias7, and 4) Connectoflow generated connectivity strength (CS)-weighted matrices8. An expert epileptologist classified icEEG contacts into seizure onset zone (SOZ; initial ictal activity), seizure propagation zone (SPZ; subsequent ictal activity), irritative zone (IZ; high interictal activity), or non-involved zone (NIZ; no activity). White matter streamlines were assigned to intrazonal (SOZ↔SOZ...NIZ↔NIZ) or interzonal (SOZ↔SPZ...IZ↔NIZ) networks. CS of analogous networks in healthy controls were also extracted. Across-group, within-network comparisons used False Discovery Rate (FDR)-corrected Mann-Whitney U tests, while within-group, across-network comparisons used Kruskal-Wallis tests, followed by post-hoc FDR-corrected Mann-Whitney U tests for specific comparisons. Both parcel volume-normalized streamline count and Convex Optimization for Microstructure Informed Tractography (COMMIT) weight, a biologically representative quantitative marker of connectivity, were used as CS metrics.
Results:
Results revealed distinct patterns in structural connectivity across the different networks. Across-group comparisons demonstrated, in epileptic patients, increased streamline counts in the IZ↔NIZ networks (p=0.0035, FDR-corrected) and reduced COMMIT weights in the NIZ↔NIZ networks (p<0.001, FDR-corrected). Across-network comparisons of streamline counts yielded overall network variations (Kruskal-Wallis H=29.72, p<0.001), with post-hoc analysis revealing six significant differences. SOZ↔SOZ connections demonstrated notably higher streamline counts compared to SOZ↔SPZ, SOZ↔NIZ, SPZ↔IZ, SPZ↔NIZ, and IZ↔NIZ connections, while NIZ↔NIZ connections also showed higher streamline counts than IZ↔NIZ connections (all p<0.05, FDR-corrected). While the across-network COMMIT weight analyses revealed overall network differences (Kruskal-Wallis H=19.71, p=0.0198), no individual zonal comparisons reached statistical significance after FDR correction.
Conclusions:
The observed zone-specific alterations in structural connectivity patterns demonstrate the potential of diffusion MRI tractography to complement icEEG by providing three-dimensional characterization of white matter networks for better surgical targeting. Additionally, these quantitative characterizations derived from icEEG - the most reliable test to identify the different zones of the epileptic network - could provide a valuable foundation for understanding the changes seen in diffusion MRI-based structural connectivity analyses.
Disorders of the Nervous System:
Neurodevelopmental/ Early Life (eg. ADHD, autism) 2
Modeling and Analysis Methods:
Classification and Predictive Modeling
Connectivity (eg. functional, effective, structural) 1
Diffusion MRI Modeling and Analysis
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
White Matter Anatomy, Fiber Pathways and Connectivity
Keywords:
Data analysis
ELECTROCORTICOGRAPHY
Epilepsy
Segmentation
Source Localization
STRUCTURAL MRI
Tractography
White Matter
WHITE MATTER IMAGING - DTI, HARDI, DSI, ETC
Other - Structural Connectivity
1|2Indicates the priority used for review
Abstract Information
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2.Mesraoua, B., Brigo, F., Lattanzi, S., Abou-Khalil, B., Hail, H. A., & Asadi-Pooya, A. A. (2023). Drug-resistant epilepsy: Definition, pathophysiology, and management. Journal of the Neurological Sciences, 452. https://doi.org/10.1016/j.jns.2023.120766
3.Téllez-Zenteno, J. F., Dhar, R., & Wiebe, S. (2005). Long-term seizure outcomes following epilepsy surgery: A systematic review and meta-analysis. Brain, 128(5), 1188–1198. https://doi.org/10.1093/brain/awh449
4.Chaudhary, U. J., Centeno, M., Carmichael, D. W., Diehl, B., Walker, M. C., Duncan, J. S., & Lemieux, L. (2021). Mapping Epileptic Networks Using Simultaneous Intracranial EEG-fMRI. Frontiers in Neurology, 12. https://doi.org/10.3389/fneur.2021.693504
5.Theaud, G., Houde, J.-C., Boré, A., Rheault, F., Morency, F., & Descoteaux, M. (2020). TractoFlow: A robust, efficient and reproducible diffusion MRI pipeline leveraging Nextflow & Singularity. NeuroImage, 218, 116889. https://doi.org/10.1016/j.neuroimage.2020.116889
6.Fan, L., Li, H., Zhuo, J., Zhang, Y., Wang, J., Chen, L., Yang, Z., Chu, C., Xie, S., Laird, A. R., Fox, P. T., Eickhoff, S. B., Yu, C., & Jiang, T. (2016). The Human Brainnetome Atlas: A New Brain Atlas Based on Connectional Architecture. Cerebral Cortex (New York, N.Y.: 1991), 26(8), 3508–3526. https://doi.org/10.1093/cercor/bhw157
7.St-Onge, E., Daducci, A., Girard, G., & Descoteaux, M. (2018). Surface-enhanced tractography (SET). NeuroImage, 169, 524–539. https://doi.org/10.1016/j.neuroimage.2017.12.036
8.Rheault, François & Houde, Jean-Christophe & Sidhu, Jasmeen & Obaid, Sami & Guberman, Guido & Daducci, Alessandro & Descoteaux, Maxime. (2021). Connectoflow: A cutting-edge Nextflow pipeline for structural connectomics.