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Neuroimaging the epileptogenic process.

ABSTRACT: Epilepsy is one of the most common chronic neurological conditions worldwide. Anti-epileptic drugs (AEDs) can suppress seizures, but do not affect the underlying epileptic state, and many epilepsy patients are unable to attain seizure control with AEDs. To cure or prevent epilepsy, disease-modifying interventions that inhibit or reverse the disease process of epileptogenesis must be developed. A major limitation in the development and implementation of such an intervention is the current poor understanding, and the lack of reliable biomarkers, of the epileptogenic process. Neuroimaging represents a non-invasive medical and research tool with the ability to identify early pathophysiological changes involved in epileptogenesis, monitor disease progression, and assess the effectiveness of possible therapies. Here we will provide an overview of studies conducted in animal models and in patients with epilepsy that have utilized various neuroimaging modalities to investigate epileptogenesis.

SUBMITTER: Shultz SR

PROVIDER: S-EPMC3996128 | biostudies-literature | 2014 Apr

REPOSITORIES: biostudies-literature

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Neuroimaging the epileptogenic process.

Shultz Sandy R SR O'Brien Terence J TJ Stefanidou Maria M Kuzniecky Ruben I RI

Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics 20140401 2

Epilepsy is one of the most common chronic neurological conditions worldwide. Anti-epileptic drugs (AEDs) can suppress seizures, but do not affect the underlying epileptic state, and many epilepsy patients are unable to attain seizure control with AEDs. To cure or prevent epilepsy, disease-modifying interventions that inhibit or reverse the disease process of epileptogenesis must be developed. A major limitation in the development and implementation of such an intervention is the current poor un ...[more]

PMID: 24488707

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Project description:Accurate localization of the epileptogenic zone (EZ) is a key factor to obtain good surgical outcome for refractory epilepsy patients. However, no technique, so far, can precisely locate the EZ, and there are barely any reports on the combined application of multiple technologies to improve the localization accuracy of the EZ. In this study, we aimed to explore the use of a multimodal method combining PET-MRI, fluid and white matter suppression (FLAWS)-a novel MRI sequence, and high-frequency oscillation (HFO) automated analysis to delineate EZ. We retrospectively collected 15 patients with refractory epilepsy who underwent surgery and used the above three methods to detect abnormal brain areas of all patients. We compared the PET-MRI, FLAWS, and HFO results with traditional methods to evaluate their diagnostic value. The sensitivities, specificities of locating the EZ, and marking extent removed versus not removed [RatioChann(ev)] of each method were compared with surgical outcome. We also tested the possibility of using different combinations to locate the EZ. The marked areas in every patient established using each method were also compared to determine the correlations among the three methods. The results showed that PET-MRI, FLAWS, and HFOs can provide more information about potential epileptic areas than traditional methods. When detecting the EZs, the sensitivities of PET-MRI, FLAWS, and HFOs were 68.75, 53.85, and 87.50%, and the specificities were 80.00, 33.33, and 100.00%. The RatioChann(ev) of HFO-marked contacts was significantly higher in patients with good outcome than those with poor outcome (p< 0.05). When intracranial electrodes covered all the abnormal areas indicated by neuroimaging with the overlapping EZs being completely removed referred to HFO analysis, patients could reach seizure-free (p < 0.01). The periphery of the lesion marked by neuroimaging may be epileptic, but not every lesion contributes to seizures. Therefore, approaches in multimodality can detect EZ more accurately, and HFO analysis may help in defining real epileptic areas that may be missed in the neuroimaging results. The implantation of intracranial electrodes guided by non-invasive PET-MRI and FLAWS findings as well as HFO analysis would be an optimized multimodal approach for locating EZ.

Project description:Defining a bio-electrical marker for the brain area responsible for initiating a seizure remains an unsolved problem. Fast gamma activity has been identified as the most specific marker for seizure onset, but conflicting results have been reported. In this study, we describe an alternative marker, based on an objective description of interictal to ictal transition, with the aim of identifying a time-frequency pattern or 'fingerprint' that can differentiate the epileptogenic zone from areas of propagation. Seventeen patients who underwent stereoelectroencephalography were included in the study. Each had seizure onset characterized by sustained gamma activity and were seizure-free after tailored resection or laser ablation. We postulated that the epileptogenic zone was always located inside the resection region based on seizure freedom following surgery. To characterize the ictal frequency pattern, we applied the Morlet wavelet transform to data from each pair of adjacent intracerebral electrode contacts. Based on a visual assessment of the time-frequency plots, we hypothesized that a specific time-frequency pattern in the epileptogenic zone should include a combination of (i) sharp transients or spikes; preceding (ii) multiband fast activity concurrent; with (iii) suppression of lower frequencies. To test this hypothesis, we developed software that automatically extracted each of these features from the time-frequency data. We then used a support vector machine to classify each contact-pair as being within epileptogenic zone or not, based on these features. Our machine learning system identified this pattern in 15 of 17 patients. The total number of identified contacts across all patients was 64, with 58 localized inside the resected area. Subsequent quantitative analysis showed strong correlation between maximum frequency of fast activity and suppression inside the resection but not outside. We did not observe significant discrimination power using only the maximum frequency or the timing of fast activity to differentiate contacts either between resected and non-resected regions or between contacts identified as epileptogenic versus non-epileptogenic. Instead of identifying a single frequency or a single timing trait, we observed the more complex pattern described above that distinguishes the epileptogenic zone. This pattern encompasses interictal to ictal transition and may extend until seizure end. Its time-frequency characteristics can be explained in light of recent models emphasizing the role of fast inhibitory interneurons acting on pyramidal cells as a prominent mechanism in seizure triggering. The pattern clearly differentiates the epileptogenic zone from areas of propagation and, as such, represents an epileptogenic zone 'fingerprint'.awx306media15687076823001.

Dataset Information

Neuroimaging the epileptogenic process.

Publications

Neuroimaging the epileptogenic process.

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