Automatic detection of rhythmic and periodic patterns in critical care EEG based on American Clinical Neurophysiology Society (ACNS) standardized terminology.

AIMS OF THE STUDY: Continuous EEG from critical care patients needs to be evaluated time efficiently to maximize the treatment effect. A computational method will be presented that detects rhythmic and periodic patterns according to the critical care EEG terminology (CCET) of the American Clinical Neurophysiology Society (ACNS). The aim is to show that these detected patterns support EEG experts in writing neurophysiological reports. MATERIALS AND METHODS: First of all, three case reports exemplify the evaluation procedure using graphically presented detections. Second, 187 hours of EEG from 10 critical care patients were used in a comparative trial study. For each patient the result of a review session using the EEG and the visualized pattern detections was compared to the original neurophysiology report. RESULTS: In three out of five patients with reported seizures, all seizures were reported correctly. In two patients, several subtle clinical seizures with unclear EEG correlation were missed. Lateralized periodic patterns (LPD) were correctly found in 2/2 patients and EEG slowing was correctly found in 7/9 patients. In 8/10 patients, additional EEG features were found including LPDs, EEG slowing, and seizures. CONCLUSION: The use of automatic pattern detection will assist in review of EEG and increase efficiency. The implementation of bedside surveillance devices using our detection algorithm appears to be feasible and remains to be confirmed in further multicenter studies.

Inter-rater agreement on identification of electrographic seizures and periodic discharges in ICU EEG recordings.

OBJECTIVE: This study investigated inter-rater agreement (IRA) among EEG experts for the identification of electrographic seizures and periodic discharges (PDs) in continuous ICU EEG recordings. METHODS: Eight board-certified EEG experts independently identified seizures and PDs in thirty 1-h EEG segments which were selected from ICU EEG recordings collected from three medical centers. IRA was compared between seizure and PD identifications, as well as among rater groups that have passed an ICU EEG Certification Test, developed by the Critical Care EEG Monitoring Research Consortium (CCEMRC). RESULTS: Both kappa and event-based IRA statistics showed higher mean values in identification of seizures compared to PDs (k=0.58 vs. 0.38; p<0.001). The group of rater pairs who had both passed the ICU EEG Certification Test had a significantly higher mean IRA in comparison to rater pairs in which neither had passed the test. CONCLUSIONS: IRA among experts is significantly higher for identification of electrographic seizures compared to PDs. Additional instruction, such as the training module and certification test developed by the CCEMRC, could enhance this IRA. SIGNIFICANCE: This study demonstrates more disagreement in the labeling of PDs in comparison to seizures. This may be improved by education about standard EEG nomenclature.

Hippocampal atrophy in temporal lobe epilepsy: the 'generator' and 'receiver'.

OBJECTIVE: Some patients with unilateral medial temporal lobe epilepsy (MTLE) display bilateral hippocampal atrophy on MRI, even though seizures originate in only one hippocampus. The correct identification of the epileptogenic hippocampus (the 'generator') vs the non-epileptogenic (the 'receiver') may lead to better surgical planning and results. MATERIALS AND METHODS: We studied 14 patients with MTLE (eight left and six right) who became seizure free after unilateral hippocampal resection, with hippocampal sclerosis confirmed by histology. Hippocampal tridimensional morphometry was performed comparing patients and healthy controls employing a voxel-wise Wilcoxon test. Results were corrected for multiple comparisons with the application of a False Discovery Rate (FDR)-corrected threshold for q < 0.05. RESULTS: Patients with MTLE showed atrophy involving the ipsilateral hippocampus and the contralateral hippocampus, more pronouncedly within the ipsilateral hippocampus in the anterior-inferior aspect of the hippocampal head (left MTLE, left hippocampus x = -28, y = -16, z = -24, Z = 3.6; right MTLE, right hippocampus x = 22, y = -11, z = -27, Z = 2.9). On the contralateral hippocampus, the atrophy was more noticeable in the posterior head and body areas. CONCLUSION: The epileptogenic hippocampal atrophy has an anatomically distinct pattern compared with the contralateral hippocampus. This information may help guide the presurgical assessment of MTLE.

SIGNAL REGULARITY-BASED AUTOMATED SEIZURE DETECTION SYSTEM FOR SCALP EEG MONITORING.

The purpose of the present study was to build a clinically useful automated seizure detection system for scalp EEG recordings. To achieve this, a computer algorithm was designed to translate complex multichannel scalp EEG signals into several dynamical descriptors, followed by the investigations of their spatiotemporal properties that relate to the ictal (seizure) EEG patterns as well as to normal physiologic and artifact signals. This paper describes in detail this novel seizure detection algorithm and reports its performance in a large clinical dataset.

Assessment of a scalp EEG-based automated seizure detection system.

OBJECTIVE: The purpose of this study was to evaluate and validate an offline, automated scalp EEG-based seizure detection system and to compare its performance to commercially available seizure detection software. METHODS: The test seizure detection system, IdentEvent™, was developed to enhance the efficiency of post-hoc long-term EEG review in epilepsy monitoring units. It translates multi-channel scalp EEG signals into multiple EEG descriptors and recognizes ictal EEG patterns. Detection criteria and thresholds were optimized in 47 long-term scalp EEG recordings selected for training (47 subjects, ∼3653h with 141 seizures). The detection performance of IdentEvent was evaluated using a separate test dataset consisting of 436 EEG segments obtained from 55 subjects (∼1200h with 146 seizures). Each of the test EEG segments was reviewed by three independent epileptologists and the presence or absence of seizures in each epoch was determined by majority rule. Seizure detection sensitivity and false detection rate were calculated for IdentEvent as well as for the comparable detection software (Persyst's Reveal®, version 2008.03.13, with three parameter settings). Bootstrap re-sampling was applied to establish the 95% confidence intervals of the estimates and for the performance comparison between two detection algorithms. RESULTS: The overall detection sensitivity of IdentEvent was 79.5% with a false detection rate (FDR) of 2 per 24h, whereas the comparison system had 80.8%, 76%, and 74% sensitivity using its three detection thresholds (perception score) with FDRs of 13, 8, and 6 per 24h, respectively. Bootstrap 95% confidence intervals of the performance difference revealed that the two detection systems had comparable detection sensitivity, but IdentEvent generated a significantly (p<0.05) smaller FDR. CONCLUSIONS: The study validates the performance of the IdentEvent™ seizure detection system. SIGNIFICANCE: With comparable detection sensitivity, an improved false detection rate makes the automated seizure detection software more useful in clinical practice.

Asymmetrical extra-hippocampal grey matter loss related to hippocampal atrophy in patients with medial temporal lobe epilepsy.

BACKGROUND: Structural neuroimaging studies have consistently shown a pattern of extra-hippocampal atrophy in patients with left and right drug-refractory medial temporal lobe epilepsy (MTLE). However, it is not yet completely understood how extra-hippocampal atrophy is related to hippocampal atrophy. Moreover, patients with left MTLE often exhibit more intense cognitive impairment, and subtle brain asymmetries have been reported in patients with left MTLE versus right MTLE but have not been explored in a controlled study. OBJECTIVES: To investigate the association between extra-hippocampal and hippocampal atrophy in patients with MTLE, and the effect of side of hippocampal atrophy on extra-hippocampal atrophy. METHODS: Voxel-based morphometry analyses of magnetic resonance images of the brain were performed to determine the correlation between regional extra-hippocampal grey matter volume and hippocampal grey matter volume. The results from 36 patients with right and left MTLE were compared, and results from the two groups were compared with those from 49 healthy controls. RESULTS: Compared with controls, patients with MTLE showed a more intense correlation between hippocampal grey matter volume and regional grey matter volume in locations such as the contralateral hippocampus, bilateral parahippocampal gyri and frontal and parietal areas. Compared with right MTLE, patients with left MTLE exhibited a wider area of atrophy related to hippocampal grey matter loss, encompassing both the contralateral and ipsilateral hemispheres, particularly affecting the contralateral hippocampus. CONCLUSIONS: Our results suggest that left hippocampal atrophy is associated with a larger degree of extra-hippocampal atrophy. This may help to explain the more intense cognitive impairment usually observed in these patients.

Neurophysiologic correlates of psychiatric disorders and potential applications in epilepsy.

There is increasing interest in psychiatric assessment using neurophysiologic tools such as electroencephalography (EEG), magnetoencephalography (MEG), and transcranial magnetic stimulation (TMS). This is because these technologies have good temporal resolution, are relatively noninvasive, and (with the exception of MEG) are economical. Many different experimental paradigms and analysis techniques for the assessment of psychiatric patients involving these technologies are reviewed including conventional quantitative electroencephalography (QEEG), EEG cordance, low-resolution electromagnetic tomography (LORETA), frontal midline theta, midlatency auditory evoked potentials (P50, N100, P300), loudness dependency of the auditory evoked potential (LDAEP), mismatch negativity (MMN), contingent negative variation (CNV), and transcranial magnetic stimulation (TMS). Many of these neurophysiologic stimulus paradigms hold the promise of improving psychiatric patient care by improving diagnostic precision, predicting treatment response, and providing new phenotypes for genetic studies. Large cooperative multisite studies need to be designed to test and validate a few of these paradigms so that they might find use in routine clinical practice.