ObjectiveTo explore the clinical electrophysiology, seizure symptomatology, multimodal imaging characteristics and epileptogenic zone location of the temporal -parietal -occipital junction (TPOJ) epilepsy.MethodsThe seizure symptomatology, head MRI, PET-CT and their fusion manifestations, long-range scalp video EEG monitoring results of 6 cases of TPOJ epilepsy patients from March 2015 to August 2018 were analyzed retrospectively in the Second Hospital of Lanzhou University, and the value of localization of epileptogenic zone was analyzed, and the role of multi-modal evaluation based on SEEG in localization of epileptogenic zone was discussed.ResultsThe first symptoms: 2 of 6 patients were complicated visual hallucination; 3 were head eye deflection (2 were opposite to epileptogenic focus, 1 was ipsilateral); 1 was excessive movement. EEG of scalp: the epileptogenic potentials in intermittent period were all multi -brain regions, but could be lateralized; in seizure period, the electroencephalogram was diffuse in 4 cases, without lateralization, and could be lateralized in 2 cases (1 case was the beginning of one hemisphere, 1 case was the beginning of one posterior head). Imaging findings: MRI was negative in 2 cases, post-traumatic soft focus in 2 cases, and FCD in 2 cases; after fusion of MRI and PET-CT, low metabolic areas in a large area including TPOJ could be found. Six patients were implanted with stereotactic electrodes, and the epileptogenic focus could be identified by EEG monitoring after implantation.ConclusionFor TPOJ epilepsy, the manifestations of premonitory and multimodal images at the onset of seizure can provide important clues for the lateralition of epileptogenic zone; scalp EEG and the first symptoms except premonitory can only provide reference clues; multimodal evaluation based on stereoelectroencephalogram can accurately locate the onset of seizure.
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.
Stereo-electroencephalography (SEEG) is widely used to record the electrical activity of patients' brain in clinical. The SEEG-based epileptogenic network can better describe the origin and the spreading of seizures, which makes it an important measure to localize epileptogenic zone (EZ). SEEG data from six patients with refractory epilepsy are used in this study. Five of them are with temporal lobe epilepsy, and the other is with extratemporal lobe epilepsy. The node outflow (out-degree) and inflow (in-degree) of information are calculated in each node of epileptic network, and the overlay between selected nodes and resected nodes is analyzed. In this study, SEEG data is transformed to bipolar montage, and then the epileptic network is established by using independent effective coherence (iCoh) method. The SEEG segments at onset, middle and termination of seizures in Delta, Theta, Alpha, Beta, and Gamma rhythms are used respectively. Finally, the K-means clustering algorithm is applied on the node values of out-degree and in-degree respectively. The nodes in the cluster with high value are compared with the resected regions. The final results show that the accuracy of selected nodes in resected region in the Delta, Alpha and Beta rhythm are 0.90, 0.88 and 0.89 based on out-degree values in temporal lobe epilepsy patients respectively, while the in-degree values cannot differentiate them. In contrast, the out-degree values are higher outside the temporal lobe in the patient with extratemporal lobe epilepsy. Based on the out-degree feature in low-frequency epileptic network, this study provides a potential quantitative measure for identifying patients with temporal lobe epilepsy in clinical.
Objective To research clinical manifestations, electrophysiological characteristics of epileptic seizures arising from diagonal sulci (DS), to improve the level of the diagnosis and treatment of frontal epilepsy. MethodsWe reviewed all the patients underwent a detailed presurgical evaluation, including 5 patients with seizures to be proved originating from diagonal sulci by Stereo-electroencephalography (SEEG). All the 5 patients with detailed medical history, head Magnetic resonance (MRI), the Positron emission computered tomography (PET-CT) and psychological evaluation, habitual seizures were recorded by Video-electroencephalography (VEEG) and SEEG, we review the intermittent VEEG and ictal VEEG, analyzing the symptoms of seizures. Results 5 patients were divided into 2 groups by SEEG, group 1 including 3 patients with seizures arising from the bottom of DS, group 2 including 2 patients with seizures arising from the surface of DS, all the tow groups with seizures characterized by both having tonic and complex motors, tonic seizures were prominent in seizures from left DS, and tonic seizures may absent in seizures from right DS. Intermittent discharges with group1 were diffused, and intermittent discharges with group 2 were focal, but both brain areas of frontal and temporal were infected. Ictal EEG findings were consistent with the characteristics of neocortical seizures, the onset EEG shows voltage attenuation, seizures from bottom of DS with diffused EEG onset, and seizures from surface of DS with more focal EEG onset, but both frontal and anterior temporal regions were involved. Conclusionthe symptom of seizures arising from DS characterized by tonic and complex motor, can be divided into seizures arising from the bottom of DS and seizures from the surface of DS, with different electrophysiological characters.
ObjectiveTo explore the clinical features and EEG features of gelastic seizures, and analyze its value of lateral localization of epileptogenic area. MethodsAll patients with gelastic seizures admitted to the Sanbo Brain Hospital of Capital Medical University between January 2014 and December 2023 were reviewed and analyzed for history, symptomatology, imaging, electroencephalographic features and surgical protocols in patients who met the inclusion criteria and were followed up for at least 1 year, and surgical efficacy was assessed by using the Engel grading. ResultsA total of 51 patients with gelastic seizures were included, there were 32 (62.75%) males and 19 (37.25%) females, 21 (41.18%) with hypothalamic hamartomas (HH) and 30 (58.82%) with non-hypothalamic hamartomas. The age of onset was earlier in the HH group than in the non-HH group, with a median age of onset of 24.00 (0.00 ~ 96.00) and 78.00 (1.00 ~ 396.00) months (P<0.001). There are three types of laughter according to their characteristics: smiling or pleasant expressions, laughing out loud, crying or bitter laughter, with smiling or pleasant expressions being the most common (49.02%). Simple laughter is rare in all patients and is often accompanied by other manifestations such as autonomic symptoms, automatic movements, complex movements, and tonic seizures. Most of the HH group started with laughter whereas in the non-HH group laughter appeared mostly in the mid to late stages (P=0.007). Most of the HH group (57.14%) had preserved consciousness whereas most of the non-HH group (83.33%) had loss of consciousness (P=0.003). The interictal discharges in the HH group were mostly diffuse or multiregional, whereas those in the non-HH group were mostly regional (P=0.035). The onset of EEG during the seizure period in the HH group was mostly diffuse, whereas those in the non-HH group were mostly regional, mainly in the frontal and temporal regions, but there was no significant difference between the two groups (P=0.148). The non-HH group was mostly seen in those with definite lesions, and the most common type of lesion was FCD (focal cortical dysplasia, FCD). All patients enrolled in the group underwent surgical treatment, and stereoelectroencephalogram (SEEG) electrode implantation was performed in 13 cases in the HH group and in 17 cases in the non-HH group. 61.90% of the patients in the HH group had an Engel grade I, and 73.33% of the patients in the non-HH group had an Engel grade I. ConclusionsGelastic seizures has a complex neural network, with common causes other than hypothalamic hamartomas, and is most commonly seen in frontal or temporal lobe epilepsy, as well as in the insula or parietal lobe, with the most common type of lesion being FCD. The symptomatology, stage of onset, and electroencephalographic features of gelastic seizures can help in the differential diagnosis, and SEEG can help define the origin of the seizure and its diffusion pathway. The overall prognosis of surgical treatment was better in both the hypothalamic hamartomas and non-hypothalamic hamartomas groups.