PURPOSE: We studied the relation between quantitative interictal subdural EEG data and visually defined ictal subdural EEG findings in children with intractable neocortical epilepsy, and determined whether interictal EEG data are predictive of ictal EEG onset zones. METHODS: Thirteen children (aged 1.2-15.4 years) underwent prolonged intracranial EEG recording, using 48- to 120-channel subdural electrodes. Three distinct 10-min segments of the continuous interictal EEG recording were selected for each patient, and the spike frequency for each channel was determined by using an automatic spike-detection program. Subsequently the average spike frequency of each electrode was compared with ictal assessment (onset, spread, and no early ictal involvement). In addition, 50 distinct interictal spikes were averaged for each patient, and the amplitude and latency after the leading spike (averaged spike showing the earliest peak) were measured for each electrode and analyzed with respect to ictal EEG findings. RESULTS: Reproducibility of the spike-frequency pattern derived from three 10-min segments was high (Kendall's W, 0.85 +/- 0.08). Electrodes showing the highest spike frequency, the highest spike amplitude, and the leading spike were found to be a part of the seizure onset in 13 of 13, 12 of 13, and 10 of 13 cases, respectively. There was significant correlation between ictal assessment and spike frequency as well as spike amplitude. A receiver operating characteristics analysis showed that a cutoff threshold at 14% of the maximal spike frequency resulted in a specificity of 0.90 and a sensitivity of 0.77 for the detection of seizure-onset electrodes. CONCLUSIONS: Quantitative interictal subdural EEG may predict ictal-onset zones in children with intractable neocortical epilepsy.
PURPOSE: We studied the relation between quantitative interictal subdural EEG data and visually defined ictal subdural EEG findings in children with intractable neocortical epilepsy, and determined whether interictal EEG data are predictive of ictal EEG onset zones. METHODS: Thirteen children (aged 1.2-15.4 years) underwent prolonged intracranial EEG recording, using 48- to 120-channel subdural electrodes. Three distinct 10-min segments of the continuous interictal EEG recording were selected for each patient, and the spike frequency for each channel was determined by using an automatic spike-detection program. Subsequently the average spike frequency of each electrode was compared with ictal assessment (onset, spread, and no early ictal involvement). In addition, 50 distinct interictal spikes were averaged for each patient, and the amplitude and latency after the leading spike (averaged spike showing the earliest peak) were measured for each electrode and analyzed with respect to ictal EEG findings. RESULTS: Reproducibility of the spike-frequency pattern derived from three 10-min segments was high (Kendall's W, 0.85 +/- 0.08). Electrodes showing the highest spike frequency, the highest spike amplitude, and the leading spike were found to be a part of the seizure onset in 13 of 13, 12 of 13, and 10 of 13 cases, respectively. There was significant correlation between ictal assessment and spike frequency as well as spike amplitude. A receiver operating characteristics analysis showed that a cutoff threshold at 14% of the maximal spike frequency resulted in a specificity of 0.90 and a sensitivity of 0.77 for the detection of seizure-onset electrodes. CONCLUSIONS: Quantitative interictal subdural EEG may predict ictal-onset zones in children with intractable neocortical epilepsy.
Authors: Helen R Sabolek; Waldemar B Swiercz; Kyle P Lillis; Sydney S Cash; Gilles Huberfeld; Grace Zhao; Linda Ste Marie; Stéphane Clemenceau; Greg Barsh; Richard Miles; Kevin J Staley Journal: J Neurosci Date: 2012-02-29 Impact factor: 6.167
Authors: Yuan Lai; Xin Zhang; Wim van Drongelen; Michael Korhman; Kurt Hecox; Ying Ni; Bin He Journal: Neuroimage Date: 2010-07-17 Impact factor: 6.556
Authors: Helen C Wu; Fabien Dachet; Farhad Ghoddoussi; Shruti Bagla; Darren Fuerst; Jeffrey A Stanley; Matthew P Galloway; Jeffrey A Loeb Journal: Epilepsia Date: 2017-07-17 Impact factor: 5.864
Authors: Eric D Marsh; Bradley Peltzer; Merritt W Brown; Courtney Wusthoff; Phillip B Storm; Brian Litt; Brenda E Porter Journal: Epilepsia Date: 2009-09-22 Impact factor: 5.864