STUDY OBJECTIVES: Recognizing epileptic seizures during video polysomnography (VPSG) can be challenging, particularly when using standard, limited EEG montages and paper speed. Few sleep laboratories have PSG equipment that allows for the recording of 18 channels of EEG without compromising the ability to detect sleep apnea, periodic limb movements, and parasomnias. We studied the ability of sleep medicine- and EEG-trained polysomnographers to correctly identify epileptic seizures during PSG using 4, 7, and 18 channels of simultaneous EEG, recording at conventional PSG and EEG paper speeds. The purpose of this study was to determine the value of limited EEG montages viewed with EEG reformatting capability in the identification of seizures during PSG. DESIGN: Blinded EEG analysis of seizures and arousals during VPSG. SETTING: Tertiary care hospital with sleep laboratory and epilepsy monitoring unit. PATIENTS: Subjects with focal (partial) epilepsy that underwent video-EEG monitoring. INTERVENTIONS: We designed two 7-channel EEG montages that might facilitate the identification of seizures arising from the frontal and temporal lobes. Sleep medicine- and EEG-trained polysomnographers were asked to review tracings containing frontal or temporal lobe epileptic seizures and arousals from sleep. Utilizing the capability of our digital recording equipment to reformat EEG channels and change paper speeds, we asked the readers to classify events recorded with 4, 7, and 18 channels of simultaneous EEG, at paper speeds of 10 and 30 mm/sec. MEASUREMENTS AND RESULTS: 6 readers viewed 32 sleep-related events (13 frontal lobe seizures, 11 temporal lobe seizures, and 8 arousals). The following factors were analyzed for their influence on accuracy of event detection: 1) the type of training of the reader (EEG vs. sleep medicine); 2) the number of EEG channels (4, 7, or 18); and 3) paper speed (10 vs. 30 mm/sec). Pair-wise comparisons and generalized estimating equations were used to identify factors leading to more accurate detection of seizures and arousals. 77% of events were correctly identified: 74% of seizures and 88% of arousals. Seizure detection was better using 7 and 18 channels (sensitivity of 82% and 86%, respectively) than 4 EEG channels (sensitivity of 67%) for temporal lobe seizures only. The number of EEG channels did not affect the accuracy of frontal lobe seizure detection. For EEG-trained readers, accuracy was greater using 30 mm/sec than 10 mm/sec paper speed (85% vs. 78% correct, respectively). CONCLUSIONS: Adding EEG channels and EEG reformatting capabilities to PSG interpretation improves the detection of some types of epileptic seizures. Accuracy of temporal lobe seizure detection using an abbreviated 7-channel montage approximates that of an 18-channel EEG recording. However, the same is not true of frontal lobe seizures in which accuracy was similar regardless of the number of EEG channel available. Further studies are needed to identify specific EEG montages that would best detect epileptiform activity during VPSG.
STUDY OBJECTIVES: Recognizing epileptic seizures during video polysomnography (VPSG) can be challenging, particularly when using standard, limited EEG montages and paper speed. Few sleep laboratories have PSG equipment that allows for the recording of 18 channels of EEG without compromising the ability to detect sleep apnea, periodic limb movements, and parasomnias. We studied the ability of sleep medicine- and EEG-trained polysomnographers to correctly identify epileptic seizures during PSG using 4, 7, and 18 channels of simultaneous EEG, recording at conventional PSG and EEG paper speeds. The purpose of this study was to determine the value of limited EEG montages viewed with EEG reformatting capability in the identification of seizures during PSG. DESIGN: Blinded EEG analysis of seizures and arousals during VPSG. SETTING: Tertiary care hospital with sleep laboratory and epilepsy monitoring unit. PATIENTS: Subjects with focal (partial) epilepsy that underwent video-EEG monitoring. INTERVENTIONS: We designed two 7-channel EEG montages that might facilitate the identification of seizures arising from the frontal and temporal lobes. Sleep medicine- and EEG-trained polysomnographers were asked to review tracings containing frontal or temporal lobe epileptic seizures and arousals from sleep. Utilizing the capability of our digital recording equipment to reformat EEG channels and change paper speeds, we asked the readers to classify events recorded with 4, 7, and 18 channels of simultaneous EEG, at paper speeds of 10 and 30 mm/sec. MEASUREMENTS AND RESULTS: 6 readers viewed 32 sleep-related events (13 frontal lobe seizures, 11 temporal lobe seizures, and 8 arousals). The following factors were analyzed for their influence on accuracy of event detection: 1) the type of training of the reader (EEG vs. sleep medicine); 2) the number of EEG channels (4, 7, or 18); and 3) paper speed (10 vs. 30 mm/sec). Pair-wise comparisons and generalized estimating equations were used to identify factors leading to more accurate detection of seizures and arousals. 77% of events were correctly identified: 74% of seizures and 88% of arousals. Seizure detection was better using 7 and 18 channels (sensitivity of 82% and 86%, respectively) than 4 EEG channels (sensitivity of 67%) for temporal lobe seizures only. The number of EEG channels did not affect the accuracy of frontal lobe seizure detection. For EEG-trained readers, accuracy was greater using 30 mm/sec than 10 mm/sec paper speed (85% vs. 78% correct, respectively). CONCLUSIONS: Adding EEG channels and EEG reformatting capabilities to PSG interpretation improves the detection of some types of epileptic seizures. Accuracy of temporal lobe seizure detection using an abbreviated 7-channel montage approximates that of an 18-channel EEG recording. However, the same is not true of frontal lobe seizures in which accuracy was similar regardless of the number of EEG channel available. Further studies are needed to identify specific EEG montages that would best detect epileptiform activity during VPSG.
Authors: G Bryan Young; Michael D Sharpe; Martin Savard; Eyad Al Thenayan; Loretta Norton; Corrine Davies-Schinkel Journal: Neurocrit Care Date: 2009-12 Impact factor: 3.210
Authors: Suresh Kotagal; Cynthia D Nichols; Madeleine M Grigg-Damberger; Carole L Marcus; Manisha B Witmans; Valerie G Kirk; Lynn A D'Andrea; Timothy F Hoban Journal: Sleep Date: 2012-11-01 Impact factor: 5.849