Statistical Modeling of ICEEG Features that Determine Resection Planning

Statistical Modeling of ICEEG Features that Determine Resection Planning

Abstract Object The interpretation of intracranial EEG (ICEEG) recordings is a complex balance of the significance of specific rhythms and their relative timing to seizure onset. Ictal and interictal findings are evaluated in light of findings from cortical stimulation of eloquent cortex to determin...

Full description

Saved in:
Bibliographic Details
Published in:Clinical neurology and neurosurgery Vol. 147; pp. 18 - 23
Main Authors: Davis, Matthew C, Broadwater, Devin R, Mathews, Winn H, Paige, A. Lebron, DeWolfe, Jennifer L, Elgavish, Ro A, Riley, Kristen O, Ver Hoef, Lawrence W
Format: Journal Article
Language:English
Published: Netherlands Elsevier B.V 01-08-2016
Elsevier Limited
Subjects:
Adult
Age
Cerebral Cortex - physiopathology
Classification
Convulsions & seizures
Decision making
Electrocorticography - methods
Electrodes
Electroencephalography
Epilepsy
Humans
Models, Statistical
Morphology
Neurology
Neurosurgery
Outcome assessment
Planning
Retrospective Studies
Seizures - physiopathology
Seizures - surgery
Surgery
Tomography
epilepsy
electroencephalography
outcome assessment
neurosurgery
neurology
Neurology
Electroencephalography
Neurosurgery
Outcome assessment
Epilepsy
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Abstract Object The interpretation of intracranial EEG (ICEEG) recordings is a complex balance of the significance of specific rhythms and their relative timing to seizure onset. Ictal and interictal findings are evaluated in light of findings from cortical stimulation of eloquent cortex to determine the area of resection. Patients and Methods Patients with ICEEG electrodes and subsequent surgical resection were retrospectively identified. Only the first 15 seconds of ictal activity, which was divided into five 3-second epochs, was considered. Every electrode in each patient was considered a separate observation in a logistic regression model to predict whether the cortex under a given electrode was included in the planned resection. Results 19 included patients had a total of 37 unique seizures. Recordings from a total of 1306 electrodes were analyzed. The strongest predictors of resection of cortex underlying a given electrode was the presence of low-voltage fast activity in Epoch 1, rhythmic spikes in Epoch 1, interictal paroxysmal fast activity, and low-voltage fast activity in Epoch 2. High-amplitude beta spikes and rhythmic slow waves were also significant predictors in Epoch 1. Interictal spikes had a higher odds ratio of affecting the planned resection if described as “continuous” or “very frequent”. The presence of motor or language cortex were the strongest negative predictors of resecting underlying cortex. Conclusions Here we describe a novel model of ictal and interictal patterns significantly associated with the inclusion of cortex underlying a given ICEEG electrode in the surgical resection plan.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:0303-8467
1872-6968
DOI:10.1016/j.clineuro.2016.05.017