4 resultados para Temporal Analysis
Resumo:
Objective: The epilepsy associated with the hypothalamic hamartomas constitutes a syndrome with peculiar seizures, usually refractory to medical therapy, mild cognitive delay, behavioural problems and multifocal spike activity in the scalp electroencephalogram (EEG). The cortical origin of spikes has been widely assumed but not specifically demonstrated. Methods: We present results of a source analysis of interictal spikes from 4 patients (age 2–25 years) with epilepsy and hypothalamic hamartoma, using EEG scalp recordings (32 electrodes) and realistic boundary element models constructed from volumetric magnetic resonance imaging (MRIs). Multifocal spike activity was the most common finding, distributed mainly over the frontal and temporal lobes. A spike classification based on scalp topography was done and averaging within each class performed to improve the signal to noise ratio. Single moving dipole models were used, as well as the Rap-MUSIC algorithm. Results: All spikes with good signal to noise ratio were best explained by initial deep sources in the neighbourhood of the hamartoma, with late sources located in the cortex. Not a single patient could have his spike activity explained by a combination of cortical sources. Conclusions: Overall, the results demonstrate a consistent origin of spike activity in the subcortical region in the neighbourhood of the hamartoma, with late spread to cortical areas.
Resumo:
Objective: Gelastic seizures are a frequent and well established manifestation of the epilepsy associated with hypothalamic hamartomas. The scalp EEG recordings very seldom demonstrate clear spike activity and the information about the ictal epilepsy dynamics is limited. In this work, we try to isolate epileptic rhythms in gelastic seizures and study their generators. Methods: We extracted rhythmic activity from EEG scalp recordings of gelastic seizures using decomposition in independent components (ICA) in three patients, two with hypothalamic hamartomas and one with no hypothalamic lesion. Time analysis of these rhythms and inverse source analysis was done to recover their foci of origin and temporal dynamics. Results: In the two patients with hypothalamic hamartomas consistent ictal delta (2–3 Hz) rhythms were present, with subcortical generators in both and a superficial one in a single patient. The latter pattern was observed in the patient with no hypothalamic hamartoma visible in MRI. The deep generators activated earlier than the superficial ones, suggesting a consistent sub-cortical origin of the rhythmical activity. Conclusions: Our data is compatible with early and brief epileptic generators in deep sub-cortical regions and more superficial ones activating later. Significance: Gelastic seizures express rhythms on scalp EEG compatible with epileptic activity originating in sub-cortical generators and secondarily involving cortical ones.
Resumo:
Objective: The Panayiotopoulos type of idiopathic occipital epilepsy has peculiar and easily recognizable ictal symptoms, which are associated with complex and variable spike activity over the posterior scalp areas. These characteristics of spikes have prevented localization of the particular brain regions originating clinical manifestations. We studied spike activity in this epilepsy to determine their brain generators. Methods: The EEG of 5 patients (ages 7–9) was recorded, spikes were submitted to blind decomposition in independent components (ICs) and those to source analysis (sLORETA), revealing the spike generators. Coherence analysis evaluated the dynamics of the components. Results: Several ICs were recovered for posterior spikes in contrast to central spikes which originated a single one. Coherence analysis supports a model with epileptic activity originating near lateral occipital area and spreading to cortical temporal or parietal areas. Conclusions: Posterior spikes demonstrate rapid spread of epileptic activity to nearby lobes, starting in the lateral occipital area. In contrast, central spikes remain localized in the rolandic fissure. Significance: Rapid spread of posterior epileptic activity in the Panayitopoulos type of occipital lobe epilepsy is responsible for the variable and poorly localized spike EEG. The lateral occipital cortex is the primary generator of the epileptic activity.
Resumo:
PURPOSE: To determine the correlation between ocular blood flow velocities and ocular pulse amplitude (OPA) in glaucoma patients using colour Doppler imaging (CDI) waveform analysis. METHOD: A prospective, observer-masked, case-control study was performed. OPA and blood flow variables from central retinal artery and vein (CRA, CRV), nasal and temporal short posterior ciliary arteries (NPCA, TPCA) and ophthalmic artery (OA) were obtained through dynamic contour tonometry and CDI, respectively. Univariate and multiple regression analyses were performed to explore the correlations between OPA and retrobulbar CDI waveform and systemic cardiovascular parameters (blood pressure, blood pressure amplitude, mean ocular perfusion pressure and peripheral pulse). RESULTS: One hundred and ninety-two patients were included [healthy controls: 55; primary open-angle glaucoma (POAG): 74; normal-tension glaucoma (NTG): 63]. OPA was statistically different between groups (Healthy: 3.17 ± 1.2 mmHg; NTG: 2.58 ± 1.2 mmHg; POAG: 2.60 ± 1.1 mmHg; p < 0.01), but not between the glaucoma groups (p = 0.60). Multiple regression models to explain OPA variance were made for each cohort (healthy: p < 0.001, r = 0.605; NTG: p = 0.003, r = 0.372; POAG: p < 0.001, r = 0.412). OPA was independently associated with retrobulbar CDI parameters in the healthy subjects and POAG patients (healthy CRV resistance index: β = 3.37, CI: 0.16-6.59; healthy NPCA mean systolic/diastolic velocity ratio: β = 1.34, CI: 0.52-2.15; POAG TPCA mean systolic velocity: β = 0.14, CI 0.05-0.23). OPA in the NTG group was associated with diastolic blood pressure and pulse rate (β = -0.04, CI: -0.06 to -0.01; β = -0.04, CI: -0.06 to -0.001, respectively). CONCLUSIONS: Vascular-related models provide a better explanation to OPA variance in healthy individuals than in glaucoma patients. The variables that influence OPA seem to be different in healthy, POAG and NTG patients.