Currently, monitoring system of awareness of the depth of anesthesia has been more and more widely used in clinical practices. The intelligent evaluation algorithm is the key technology of this type of equipment. On the basis of studies about changes of electroencephalography (EEG) features during anesthesia, a discussion about how to select reasonable EEG parameters and classification algorithm to monitor the depth of anesthesia has taken place. A scheme which combines time domain analysis, frequency domain analysis and the variability of EEG and decision tree as classifier and least squares to compute Depth of anesthesia Index (DOAI) is proposed in this paper. Using the EEG of 40 patients who underwent general anesthesia with propofol, and the classification and the score of the EEG annotated by anesthesiologist, we verified this scheme with experiments. Classification and scoring was based on a combination of modified observer assessment of alertness/sedation (MOAA/S), and the changes of EEG parameters of patients during anesthesia. Then we used the BIS index to testify the validation of the DOAI. Results showed that Pearson's correlation coefficient between the DOAI and the BIS over the test set was 0.89. It is demonstrated that the method is feasible and has good accuracy.
Uncovering the alterations of neural interactions within the brain during epilepsy is important for the clinical diagnosis and treatment. Previous studies have shown that the phase-amplitude coupling (PAC) can be used as a potential biomarker for locating epileptic zones and characterizing the transition of epileptic phases. However, in contrast to the θ-γ coupling widely investigated in epilepsy, few studies have paid attention to the β-γ coupling, as well as its potential applications. In the current study, we use the modulation index (MI) to calculate the scalp electroencephalography (EEG)-based β-γ coupling and investigate the corresponding changes during different epileptic phases. The results show that the β-γ coupling of each brain region changes with the evolution of epilepsy, and in several brain regions, the β-γ coupling decreases during the ictal period but increases in the post-ictal period, where the differences are statistically significant. Moreover, the alterations of β-γ coupling between different brain regions can also be observed, and the strength of β-γ coupling increases in the post-ictal period, where the differences are also significant. Taken together, these findings not only contribute to understanding neural interactions within the brain during the evolution of epilepsy, but also provide a new insight into the clinical treatment.
ObjectiveThe aim was to summarize the seizure and video electroencephalogram (VEEG) characteristics of Dyke-Davidoff-Masson syndrome (DDMS). Methods The case data of four patients with Dyke-Davidoff-Masson syndrome (DDMS) who attended the Epilepsy Center of Hunan Provincial Brain Hospital from March 2022 to March 2023 were retrospectively analyzed to summarize the clinical manifestations of their seizures and the characteristics of their video electroencephalogram (VEEG). Results One case of symptomatic epilepsy with focal seizures; VEEG showed poor background activity alpha rhythmic modulation, amplitude modulation, and increased distribution of slow wave activity in the left frontal and temporal regions; bilateral frontal-central and anterior-temporal regions (more so on the left side), with sharp and slow composite wave issuance.Two cases of symptomatic epilepsy with focal seizures progressing to generalized seizures; in one case, the VEEG showed: background activity α-rhythmic modulation, amplitude modulation is possible, the left frontal, central, anterior temporal region slow wave increase; the left frontal central, parietal anterior temporal region spike-like slow wave activity mixed with spike wave, spike-slow complex wave short-medium-range issuance; the other VEEG showed: background activity α-rhythmic modulation, amplitude modulation is possible, the right frontal central, anterior temporal region slow wave increase; right frontal, central, and anterior temporal region for the famous medium-extremely high-high-amplitude slow wave activity mixed with spike wave, spike-slow complex wave short-medium-range issuance. One case of symptomatic epilepsy with generalized seizures; VEEG showed bilateral occipital alpha rhythm asymmetry, right occipital region <50% of the left side, poor regulation and amplitude modulation; bilateral frontal pole, frontal region, anterior temporal region spike and spiking slow complex wave discharges (right side was prominent), and right pterionic electrodes, anterior temporal and mesial temporal spike and spiking slow wave discharges. Conclusions Epileptic seizures are one of the main clinical manifestations of DDMS and most of them are consulted after a seizure, and their seizure types tend to be focal seizures or progress to generalized seizures, and most of them are drug-refractory epilepsies. The results of VEEG monitoring tend to be characterized by abnormal background activity, increased slow-wave activity, and the site of epileptogenic wave-like discharges tends to be in line with the site of cerebral softening foci or the site of the atrophic side of the brain as shown by cranial MRI.
Epileptic seizures and the interictal epileptiform discharges both have similar waveforms. And a method to effectively extract features that can be used to distinguish seizures is of crucial importance both in theory and clinical practice. We constructed state transfer networks by using visibility graphlet at multiple sampling intervals and analyzed network features. We found that the characteristics waveforms in ictal periods were more robust with various sampling intervals, and those feature network structures did not change easily in the range of the smaller sampling intervals. Inversely, the feature network structures of interictal epileptiform discharges were stable in range of relatively larger sampling intervals. Furthermore, the feature nodes in networks during ictal periods showed long-term correlation along the process, and played an important role in regulating system behavior. For stereo-electroencephalography at around 500 Hz, the greatest difference between ictal and the interictal epileptiform occurred at the sampling interval around 0.032 s. In conclusion, this study effectively reveals the correlation between the features of pathological changes in brain system and the multiple sampling intervals, which holds potential application value in clinical diagnosis for identifying, classifying, and predicting epilepsy.
For refractory epilepsy requiring surgical treatment in clinic, precise preoperative positioning of the epileptogenic zone is the key to improving the success rate of clinical surgical treatment. Although the use of electrical stimulation to locate epileptogenic zone has been widely carried out in many medical centers, the preoperative implantation evaluation of stereoelectroencephalography (SEEG) and the interpretation of electrical stimulation induced EEG activity are still not perfect and rigorous. Especially, there are still technological limitations and unknown areas regarding electrode implantation mode, stimulation parameters design, and surgical prognosis correlation. In this paper, the clinical background, application status, technical progress and development trend of SEEG-based stereo-electric stimulation-induced cerebral electrical activity in the evaluation of refractory epilepsy are reviewed, and applications of this technology in clinical epileptogenic zone localization and cerebral cortical function evaluation are emphatically discussed. Additionally, the safety during both of high-frequency and low-frequency electrical stimulations which are commonly used in clinical evaluation of refractory epilepsy are also discussed.
PurposeTo analyze the effect of medication withdraw (MW) on long-term electroencephalogram (EEG) monitoring in children who need preoperative assessment for refractory epilepsy.MethodsRetrospective analysis was performed on the data of preoperative long-term EEG monitoring of children with refractory epilepsy who needed preoperative evaluation in the Pediatric Epilepsy Center of Peking University First Hospital from August 2018 to December 2019. Monitoring duration: at least three habitual seizures were detected, or the monitoring duration were as long as 10 days. MW protocol was according to the established plan.ResultsA total of 576 children (median age 4.4 years) required presurgical ictal EEGs, and 75 (75/576, 13.0%) needed MW for ictal EEGs. Among the 75 cases, 38 were male and 37 were female. The age range was from 15 months to 17 years (median age: 7.0 years). EEG and clinical data of with 65 children who strictly obey the MW protocol were analyzed. The total monitoring duration range was from 44.1 h (about 2 days) to 241.8 h (about 10 days)(median: 118.9 h (about 5 days)). Interictal EEG features before MW were including focal interictal epileptiform discharge (IED) in 39 cases (39/65, 60%), focal and generalized IED in 2 cases (2/65, 3.1%), multifocal IED in 20 cases (20/65, 30.7%), multifocal and generalized IED in 2 cases (2/65, 3.1%), and no IED in 2 cases (2/65, 3.1%). After MW, 18 cases (18/65, 27.7%) had no change in IED and the other 47 cases had changes of IED after MW. And IEDs in 46 cases (46/65, 70.8%) were aggravated, and IED was decreased in 1 case. The pattern of aggravated IED was original IED increasement, in 41 cases (41/46, 89.1%), and 5 cases (5 /46, 10.9%) had generalized IED which was not detected before MW. Of the 46 patients with IED exacerbations, 87.3% appeared within 3 days after MW. Habitual seizures were detected in 56 cases (86.2%, 56/65) after MW, and within 3 days of MW in 80.4% cases. Eight patients (14.3%) had secondary bilateral-tonic seizure (BTCS), of which only 1 patient had no BTCS in his habitual seizures. In 56 cases, 94.6% (53/56) had seizures after MW of two kinds of AEDs.Conclusions① In this group, thirteen percent children with intractable epilepsy needed MW to obtain ictal EEG; ② Most of them (86.2%) could obtain ictal EEG by MW. The IED and ictal EEG after MW were still helpful for localization of epileptogenic zone; ③ Most of the patients can obtain ictal EEG within 3 days after MW or after MW of two kinds of AEDs;4. The new secondary generalization was extremely rare.
The purpose of using brain-computer interface (BCI) is to build a bridge between brain and computer for the disable persons, in order to help them to communicate with the outside world. Electroencephalography (EEG) has low signal to noise ratio (SNR), and there exist some problems in the traditional methods for the feature extraction of EEG, such as low classification accuracy, lack of spatial information and huge amounts of features. To solve these problems, we proposed a new method based on time domain, frequency domain and space domain. In this study, independent component analysis (ICA) and wavelet transform were used to extract the temporal, spectral and spatial features from the original EEG signals, and then the extracted features were classified with the method combined support vector machine (SVM) with genetic algorithm (GA). The proposed method displayed a better classification performance, and made the mean accuracy of the Graz datasets in the BCI Competitions of 2003 reach 96%. The classification results showed that the proposed method with the three domains could effectively overcome the drawbacks of the traditional methods based solely on time-frequency domain when the EEG signals were used to describe the characteristics of the brain electrical signals.
The early diagnosis of children with autism spectrum disorders (ASD) is essential. Electroencephalography (EEG) is one of most commonly used neuroimaging techniques as the most accessible and informative method. In this study, approximate entropy (ApEn), sample entropy (SaEn), permutation entropy (PeEn) and wavelet entropy (WaEn) were extracted from EEGs of ASD child and a control group, and Student's t-test was used to analyze between-group differences. Support vector machine (SVM) algorithm was utilized to build classification models for each entropy measure derived from different regions. Permutation test was applied in search for optimize subset of features, with which the SVM model achieved best performance. The results showed that the complexity of EEGs in children with autism was lower than that of the normal control group. Among all four entropies, WaEn got a better classification performance than others. Classification results vary in different regions, and the frontal lobe showed the best performance. After feature selection, six features were filtered out and the accuracy rate was increased to 84.55%, which can be convincing for assisting early diagnosis of autism.
ObjectiveTo study the therapeutic efficacy of stereoelectroencephalography (SEEG)-guided radiofrequency thermo-coagulation ablation (RF-TC) in the treatment of tuberous sclerosis (TSC) related epilepsy and to investigate the prediction of the therapeutic response to SEEG-guided RF-TC for the efficacy of the subsequent surgical treatment. MethodsWe retrospectively analyze TSC patients who underwent SEEG phase II evaluation from January 2014 to January 2023, and to select patients who underwent RF-TC after completion of SEEG monitoring, study the seizure control of patients after RF-TC, and classify patients into effective and ineffective groups for RF-TC treatment according to the results of RF-TC treatment, compare the surgical outcomes of patients in the two groups after SEEG, to explore the prediction of surgical outcome by RF-TC treatment. Results59 patients with TSC were enrolled, 53 patients (89.83%) were genetic detection, of which 28 (52.83%) were TSC1-positive, 21 (39.62%) were TSC2-positive, and 4 (7.54%) were negative, with 33 (67.34%) de novo mutations. The side of the SEEG electrode placement: left hemisphere in 9 cases, right hemisphere in 13 cases, and bilateral hemisphere in 37 cases. 37 patients (62.71%) were seizure-free at 3 months, 31 patients (52.54%) were seizure-free at 6 months, 29 patients (49.15%) were seizure-free at 12 months, and 20 patients (39.21%) were seizure-free at 24 months or more. 11 patients had a seizure reduction of more than 75% after RF-TC, and the remaining 11 patients showed no significant change after RF-TC. There were 48 patients (81.35%) in the effective group and 11 patients (18.65%) in the ineffective group. In the effective group, 22 patients were performed focal tuber resection laser ablation, 19 cases were seizure-free (86.36%). In the ineffective group, 10 patients were performed focal tuber resection laser ablation, only 5 cases were seizure-free (50%), which was a significant difference between the two groups (P<0.05). ConclusionsOur data suggest that SEEG guided RF-TC is a safe and effective both diagnostic and therapeutic treatment for TSC-related epilepsy, and can assist in guiding the development of future resective surgical strategies and determining prognosis.
ObjectiveTo investigate the application of stereoelectroencephalography (SEEG) in the refractory epilepsy related to periventricular nodular heterotopia (PNH). MethodsTen patients with drug-resistant epilepsy related to PNHs from Guangdong Sanjiu Brain Hospital and the First Affiliated Hospital of Jinan University from April 2017 to February 2021 were studied. Electrodes were implanted based on non-invasive preoperative evaluation. Then long-term monitoring of SEEG was carried out. The patterns of epileptogenic zone (EZ) were divided into four categories based on the ictal SEEG: A. only the nodules started; B. nodules and cortex synchronous initiation; C. the cortex initiation with early spreading to nodules; D. only cortex initiation. All patients underwent SEEG-guided radiofrequency thermocoagulation (RFTC), with a follow-up of at least 12 months. ResultsAll cases were multiple nodules. Four cases were unilateral and six bilateral. Eight cases were distributed in posterior pattern, and one in anterior pattern and one in diffused pattern, respectively. Seven patients had only PNH (pure PNH) and three patients were associated with other overlying cortex malformations (PNH plus). The EZ patterns of all cases were confirmed by the ictal SEEG: six patients were in pure type A, two patients were in pure type B, one patient in type A+B and one in type A+B+C, respectively. In eight patients SEEG-guided RF-TC was targeted only to PNHs; and in two patients RFTC was directed to both heterotopias and related cortical regions. The mean follow up was (33.4±14.0) months (12 ~ 58 months). Eight patients (in pure type A or type A included) were seizure free. Two patients were effective. None of the patients had significant postoperative complications or sequelae. ConclusionThe epileptic network of Epilepsy associated with nodular heterotopia may be individualized. Not all nodules are always epileptogenic, the role of each nodule in the epileptic network may be different. And multiple epileptic patterns may occur simultaneously in the same patient. SEEG can provide individualized diagnosis and treatment, be helpful to prognosis.