Seizure Onset Localization From Ictal Intracranial EEG Data Using Online Dynamic Mode Decomposition

Matthew McCumber; Kevin Tyner; Srijita Das; William C. Stacey; Garnett C. Smith; Mustaffa Alfatlawi; Stephen V. Gliske

doi:10.1109/ISBI53787.2023.10230340

Seizure Onset Localization From Ictal Intracranial EEG Data Using Online Dynamic Mode Decomposition

Matthew McCumber, Kevin Tyner, Srijita Das, William C. Stacey, Garnett C. Smith, Mustaffa Alfatlawi, Stephen V. Gliske

Neurosurgery

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Epilepsy is one of the most common neurological diseases. In cases where patients do not respond to medications, resective surgery is often the next best option to obtain seizure freedom. Intracranial EEG analysis is the current gold standard for resective surgery planning. However, clinical marking is subjective, and many seizures are complex with ambiguous onset locations. The objective, in this proof-of-concept study, was to determine whether quantification with dynamic mode decomposition (DMD) may assist in localizing seizure onset. We analyzed one seizure each from five patients with epilepsy and identified channels with maximal involvement in the leading dynamic mode. In three of the five cases, the area of activity identified by our method showed statistically significant correlation with clinically identified channels. We conclude that DMD effectively captures the seizure onsets and is ready for future study in larger cohorts.

Original language	English (US)
Title of host publication	2023 IEEE International Symposium on Biomedical Imaging, ISBI 2023
Publisher	IEEE Computer Society
ISBN (Electronic)	9781665473583
DOIs	https://doi.org/10.1109/ISBI53787.2023.10230340
State	Published - 2023
Event	20th IEEE International Symposium on Biomedical Imaging, ISBI 2023 - Cartagena, Colombia Duration: Apr 18 2023 → Apr 21 2023

Publication series

Name	Proceedings - International Symposium on Biomedical Imaging
Volume	2023-April
ISSN (Print)	1945-7928
ISSN (Electronic)	1945-8452

Conference

Conference	20th IEEE International Symposium on Biomedical Imaging, ISBI 2023
Country/Territory	Colombia
City	Cartagena
Period	4/18/23 → 4/21/23

Keywords

Dynamic Mode Decomposition
Epilepsy
Intracranial EEG
Seizure Localization

ASJC Scopus subject areas

Biomedical Engineering
Radiology Nuclear Medicine and imaging

Access to Document

10.1109/ISBI53787.2023.10230340

Cite this

McCumber, M., Tyner, K., Das, S., Stacey, W. C., Smith, G. C., Alfatlawi, M., & Gliske, S. V. (2023). Seizure Onset Localization From Ictal Intracranial EEG Data Using Online Dynamic Mode Decomposition. In 2023 IEEE International Symposium on Biomedical Imaging, ISBI 2023 (Proceedings - International Symposium on Biomedical Imaging; Vol. 2023-April). IEEE Computer Society. https://doi.org/10.1109/ISBI53787.2023.10230340

Seizure Onset Localization From Ictal Intracranial EEG Data Using Online Dynamic Mode Decomposition. / McCumber, Matthew; Tyner, Kevin; Das, Srijita et al.
2023 IEEE International Symposium on Biomedical Imaging, ISBI 2023. IEEE Computer Society, 2023. (Proceedings - International Symposium on Biomedical Imaging; Vol. 2023-April).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

McCumber, M, Tyner, K, Das, S, Stacey, WC, Smith, GC, Alfatlawi, M & Gliske, SV 2023, Seizure Onset Localization From Ictal Intracranial EEG Data Using Online Dynamic Mode Decomposition. in 2023 IEEE International Symposium on Biomedical Imaging, ISBI 2023. Proceedings - International Symposium on Biomedical Imaging, vol. 2023-April, IEEE Computer Society, 20th IEEE International Symposium on Biomedical Imaging, ISBI 2023, Cartagena, Colombia, 4/18/23. https://doi.org/10.1109/ISBI53787.2023.10230340

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title = "Seizure Onset Localization From Ictal Intracranial EEG Data Using Online Dynamic Mode Decomposition",

abstract = "Epilepsy is one of the most common neurological diseases. In cases where patients do not respond to medications, resective surgery is often the next best option to obtain seizure freedom. Intracranial EEG analysis is the current gold standard for resective surgery planning. However, clinical marking is subjective, and many seizures are complex with ambiguous onset locations. The objective, in this proof-of-concept study, was to determine whether quantification with dynamic mode decomposition (DMD) may assist in localizing seizure onset. We analyzed one seizure each from five patients with epilepsy and identified channels with maximal involvement in the leading dynamic mode. In three of the five cases, the area of activity identified by our method showed statistically significant correlation with clinically identified channels. We conclude that DMD effectively captures the seizure onsets and is ready for future study in larger cohorts.",

keywords = "Dynamic Mode Decomposition, Epilepsy, Intracranial EEG, Seizure Localization",

author = "Matthew McCumber and Kevin Tyner and Srijita Das and Stacey, {William C.} and Smith, {Garnett C.} and Mustaffa Alfatlawi and Gliske, {Stephen V.}",

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year = "2023",

doi = "10.1109/ISBI53787.2023.10230340",

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series = "Proceedings - International Symposium on Biomedical Imaging",

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AU - McCumber, Matthew

AU - Tyner, Kevin

AU - Das, Srijita

AU - Stacey, William C.

AU - Smith, Garnett C.

AU - Alfatlawi, Mustaffa

AU - Gliske, Stephen V.

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N2 - Epilepsy is one of the most common neurological diseases. In cases where patients do not respond to medications, resective surgery is often the next best option to obtain seizure freedom. Intracranial EEG analysis is the current gold standard for resective surgery planning. However, clinical marking is subjective, and many seizures are complex with ambiguous onset locations. The objective, in this proof-of-concept study, was to determine whether quantification with dynamic mode decomposition (DMD) may assist in localizing seizure onset. We analyzed one seizure each from five patients with epilepsy and identified channels with maximal involvement in the leading dynamic mode. In three of the five cases, the area of activity identified by our method showed statistically significant correlation with clinically identified channels. We conclude that DMD effectively captures the seizure onsets and is ready for future study in larger cohorts.

AB - Epilepsy is one of the most common neurological diseases. In cases where patients do not respond to medications, resective surgery is often the next best option to obtain seizure freedom. Intracranial EEG analysis is the current gold standard for resective surgery planning. However, clinical marking is subjective, and many seizures are complex with ambiguous onset locations. The objective, in this proof-of-concept study, was to determine whether quantification with dynamic mode decomposition (DMD) may assist in localizing seizure onset. We analyzed one seizure each from five patients with epilepsy and identified channels with maximal involvement in the leading dynamic mode. In three of the five cases, the area of activity identified by our method showed statistically significant correlation with clinically identified channels. We conclude that DMD effectively captures the seizure onsets and is ready for future study in larger cohorts.

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KW - Seizure Localization

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Seizure Onset Localization From Ictal Intracranial EEG Data Using Online Dynamic Mode Decomposition

Abstract

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Keywords

ASJC Scopus subject areas

Access to Document

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