Treatment of intractable focal epilepsy by resection of the seizure onset zone (SOZ) is often effective provided the SOZ can be reliably identified. Focal epilepsy, however, is fundamentally a network-based disease. The seizure onset zone is connected to a network whose other nodes may also exhibit abnormal neural activity either concurrently or subsequently. In patients without MRI detectable lesions, differentiation of the onset zone from these other nodes in the network can be difficult, even with the use of invasive recordings. The goal of this project is to improve SOZ identification, ultimately reducing the need for presurgical invasive recordings where possible, and guiding placement of electrodes in those patients who do need invasive monitoring. To achieve this goal, in Aim 1 we will build a functional connectivity atlas from a database of invasive Cortico-Cortical Evoked Potential (CCEP) recordings to identify common interaction networks in patients with partial epilepsy and to investigate the degree to which these are dependent on the location of the SOZ. To construct the atlas, patient data will be coregistered to a labelled anatomical atlas using a cortically constrained warping of each subject's structural MRI.
In Aim 2, CCEPs data will be supplemented in the atlas with other data that provide additional insight into the brain regions involved in the seizure: regions of hypometabolism in interictal FDG PET, hypermetabolism in ictal SPECT, interictal spike localization from EEG and MEG and invasive recordings, functional areas associated with seizure semiology, MR-identified lesions, area of resection, post-surgical Engel classification. Using machine-learning methods, we will perform a sequence of tests to examine the degree to which the atlas can be used to identify the SOZ in individual subjects. Finally, in Aim 3, we will investigate the potential for using regional connectivity established frm noninvasive MEG data and resting state MRI in combination with the CCEPs atlas to identify these networks, with the ultimate goal of reducing the need for invasive monitoring. Retrospective analysis using a leave-one- out approach and comparison with outcomes will be used to quantify improvement in identification of the onset zone from both invasive and noninvasive recordings.

Public Health Relevance

Epilepsy affects millions of Americans, and for many, surgery is the best option to control their seizures. Improved surgical outcomes, however, requires a better understanding of the brain networks involved in seizure propagation. A brain atlas using data recorded from electrodes implanted in patients will yield new insights into pathways of the brain and will ultimately assist neurologists and neurosurgeons in better localizing and resecting the area of the brain that is causing seizures.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Research Project (R01)
Project #
5R01NS089212-04
Application #
9442865
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Whittemore, Vicky R
Project Start
2015-03-01
Project End
2020-02-29
Budget Start
2018-03-01
Budget End
2019-02-28
Support Year
4
Fiscal Year
2018
Total Cost
Indirect Cost
Name
Cleveland Clinic Lerner
Department
Other Basic Sciences
Type
Schools of Medicine
DUNS #
135781701
City
Cleveland
State
OH
Country
United States
Zip Code
44195
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