title: Statistical modeling of ICEEG features that determine resection planning.
abstract: OBJECTIVE
  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.
  
  
  METHODS
  Patients with ICEEG electrodes and subsequent surgical resection were retrospectively identified. Only the first 15s of ictal activity, which was divided into five 3-s 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.
authors.affiliation: Department of Neurosurgery, University of Alabama at Birmingham, Birmingham, AL, United States.
authors.forename: Matthew C
authors.initials: MC
authors.lastname: Davis
authors.affiliation: University of Alabama at Birmingham School of Medical, Birmingham, AL, United States. Electronic address: devinb@uab.edu.
authors.forename: Devin R
authors.initials: DR
authors.lastname: Broadwater
authors.affiliation: School of Medicine, University of South Alabama, Mobile, AL, United States.
authors.forename: Winn H
authors.initials: WH
authors.lastname: Mathews
authors.affiliation: UAB Epilepsy Center, University of Alabama at Birmingham, Birmingham, AL, United States.
authors.forename: A Lebron
authors.initials: AL
authors.lastname: Paige
authors.affiliation: UAB Epilepsy Center, University of Alabama at Birmingham, Birmingham, AL, United States.
authors.forename: Jennifer L
authors.initials: JL
authors.lastname: DeWolfe
authors.affiliation: UAB Epilepsy Center, University of Alabama at Birmingham, Birmingham, AL, United States.
authors.forename: Ro A
authors.initials: RA
authors.lastname: Elgavish
authors.affiliation: Department of Neurosurgery, University of Alabama at Birmingham, Birmingham, AL, United States.
authors.forename: Kristen O
authors.initials: KO
authors.lastname: Riley
authors.affiliation: UAB Epilepsy Center, University of Alabama at Birmingham, Birmingham, AL, United States.
authors.forename: Lawrence W
authors.initials: LW
authors.lastname: Ver Hoef
mesh_terms: D000328:Adult; D002540:Cerebral Cortex / Q000503:physiopathology*; D000069280:Electrocorticography / Q000379:methods*; D006801:Humans; D015233:Models, Statistical; D012189:Retrospective Studies; D012640:Seizures / Q000503:physiopathology* / Q000601:surgery*
keywords: Electroencephalography; Epilepsy; Neurology; Neurosurgery; Outcome assessment