Dataset Information

Automated diagnosis of temporal lobe epilepsy in the absence of interictal spikes.

ABSTRACT:

Objective

To diagnose and lateralise temporal lobe epilepsy (TLE) by building a classification system that uses directed functional connectivity patterns estimated during EEG periods without visible pathological activity.

Methods

Resting-state high-density EEG recording data from 20 left TLE patients, 20 right TLE patients and 35 healthy controls was used. Epochs without interictal spikes were selected. The cortical source activity was obtained for 82 regions of interest and whole-brain directed functional connectivity was estimated in the theta, alpha and beta frequency bands. These connectivity values were then used to build a classification system based on two two-class Random Forests classifiers: TLE vs healthy controls and left vs right TLE. Feature selection and classifier training were done in a leave-one-out procedure to compute the mean classification accuracy.

Results

The diagnosis and lateralization classifiers achieved a high accuracy (90.7% and 90.0% respectively), sensitivity (95.0% and 90.0% respectively) and specificity (85.7% and 90.0% respectively). The most important features for diagnosis were the outflows from left and right medial temporal lobe, and for lateralization the right anterior cingulate cortex. The interaction between features was important to achieve correct classification.

Significance

This is the first study to automatically diagnose and lateralise TLE based on EEG. The high accuracy achieved demonstrates the potential of directed functional connectivity estimated from EEG periods without visible pathological activity for helping in the diagnosis and lateralization of TLE.

SUBMITTER: Verhoeven T

PROVIDER: S-EPMC5842753 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Publications

Automated diagnosis of temporal lobe epilepsy in the absence of interictal spikes.

Verhoeven Thibault T Coito Ana A Plomp Gijs G Thomschewski Aljoscha A Pittau Francesca F Trinka Eugen E Wiest Roland R Schaller Karl K Michel Christoph C Seeck Margitta M Dambre Joni J Vulliemoz Serge S van Mierlo Pieter P

NeuroImage. Clinical 20170928

<h4>Objective</h4>To diagnose and lateralise temporal lobe epilepsy (TLE) by building a classification system that uses directed functional connectivity patterns estimated during EEG periods without visible pathological activity.<h4>Methods</h4>Resting-state high-density EEG recording data from 20 left TLE patients, 20 right TLE patients and 35 healthy controls was used. Epochs without interictal spikes were selected. The cortical source activity was obtained for 82 regions of interest and whole ...[more]

PMID: 29527470

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Project description:In temporal lobe epilepsy (TLE), the epileptogenic focus is focal and unilateral in the majority of patients. A key characteristic of focal TLE is the presence of subclinical epileptiform activity in both the ictal and contralateral "healthy" hemisphere. Such interictal activity is clinically important, as it may reflect the spread of pathology, potentially leading to secondary epileptogenesis. The role played by white matter pathways in this process is unknown.We compared three interhemispheric white matter tracts (anterior commissure, fornix, and tapetum) to determine the pathway most associated with the presence of contralateral interictal spikes. Forty patients with unilateral left or right TLE were categorized based on the presence or absence of contralateral interictal spikes. Analyses of variance (ANOVAs) were run on diffusion properties from each tract.The analyses revealed that patients with left TLE and with bilateral interictal spikes had lower fractional anisotropy (FA) and higher mean diffusivity (MD) in the tapetum. Patients with right TLE did not show this effect. No significant associations with bilateral activity were observed for the other tracts. Blood oxygen level-dependent (BOLD) functional connectivity data revealed that homotopic lateral, not mesial, temporal areas were reliably correlated in bilateral patients, independent of ictal side.Our results indicate that, among the tracts investigated, only the tapetum was associated with contralateral epileptiform activity, implicating this structure in seizures and possible secondary epileptogenesis. We describe two mechanisms that might explain this association (the interruption of inhibitory signals or the toxic effect of carrying epileptiform signals toward the healthy hemisphere), but also acknowledge other rival factors that may be at work. We also report that patients with TLE with bilateral spikes had increased lateral bitemporal lobe connectivity. Our current results can be seen as bringing together important functional and structural data to elucidate the basis of contralateral interictal activity in focal, unilateral epilepsy. A PowerPoint slide summarizing this article is available for download in the Supporting Information section here.

Project description:Patients with drug-resistant temporal lobe epilepsy often undergo intracranial EEG recording to capture multiple seizures in order to lateralize the seizure onset zone. This process is associated with morbidity and often ends in postoperative seizure recurrence. Abundant interictal (between-seizure) data are captured during this process, but these data currently play a small role in surgical planning. Our objective was to predict the laterality of the seizure onset zone using interictal intracranial EEG data in patients with temporal lobe epilepsy. We performed a retrospective cohort study (single-centre study for model development; two-centre study for model validation). We studied patients with temporal lobe epilepsy undergoing intracranial EEG at the University of Pennsylvania (internal cohort) and the Medical University of South Carolina (external cohort) between 2015 and 2022. We developed a logistic regression model to predict seizure onset zone laterality using several interictal EEG features derived from recent publications. We compared the concordance between the model-predicted seizure onset zone laterality and the side of surgery between patients with good and poor surgical outcomes. Forty-seven patients (30 female; ages 20-69; 20 left-sided, 10 right-sided and 17 bilateral seizure onsets) were analysed for model development and internal validation. Nineteen patients (10 female; ages 23-73; 5 left-sided, 10 right-sided, 4 bilateral) were analysed for external validation. The internal cohort cross-validated area under the curve for a model trained using spike rates was 0.83 for a model predicting left-sided seizure onset and 0.68 for a model predicting right-sided seizure onset. Balanced accuracies in the external cohort were 79.3% and 78.9% for the left- and right-sided predictions, respectively. The predicted concordance between the laterality of the seizure onset zone and the side of surgery was higher in patients with good surgical outcome. We replicated the finding that right temporal lobe epilepsy was harder to distinguish in a separate modality of resting-state functional MRI. In conclusion, interictal EEG signatures are distinct across seizure onset zone lateralities. Left-sided seizure onsets are easier to distinguish than right-sided onsets. A model trained on spike rates accurately identifies patients with left-sided seizure onset zones and predicts surgical outcome. A potential clinical application of these findings could be to either support or oppose a hypothesis of unilateral temporal lobe epilepsy when deciding to pursue surgical resection or ablation as opposed to device implantation.

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Project description:ObjectiveTo provide a multi-atlas framework for automated hippocampus segmentation in temporal lobe epilepsy (TLE) and clinically validate the results with respect to surgical lateralization and post-surgical outcome.MethodsWe retrospectively identified 47 TLE patients who underwent surgical resection and 12 healthy controls. T1-weighted 3 T MRI scans were acquired for all subjects, and patients were identified by a neuroradiologist with regards to lateralization and degree of hippocampal sclerosis (HS). Automated segmentation was implemented through the Joint Label Fusion/Corrective Learning (JLF/CL) method. Gold standard lateralization was determined from the surgically resected side in Engel I (seizure-free) patients at the two-year timepoint. ROC curves were used to identify appropriate thresholds for hippocampal asymmetry ratios, which were then used to analyze JLF/CL lateralization.ResultsThe optimal template atlas based on subject images with varying appearances, from normal-appearing to severe HS, was demonstrated to be composed entirely of normal-appearing subjects, with good agreement between automated and manual segmentations. In applying this atlas to 26 surgically resected seizure-free patients at a two-year timepoint, JLF/CL lateralized seizure onset 92% of the time. In comparison, neuroradiology reads lateralized 65% of patients, but correctly lateralized seizure onset in these patients 100% of the time. When compared to lateralized neuroradiology reads, JLF/CL was in agreement and correctly lateralized all 17 patients. When compared to nonlateralized radiology reads, JLF/CL correctly lateralized 78% of the nine patients.SignificanceWhile a neuroradiologist's interpretation of MR imaging is a key, albeit imperfect, diagnostic tool for seizure localization in medically-refractory TLE patients, automated hippocampal segmentation may provide more efficient and accurate epileptic foci localization. These promising findings demonstrate the clinical utility of automated segmentation in the TLE MR imaging pipeline prior to surgical resection, and suggest that further investigation into JLF/CL-assisted MRI reading could improve clinical outcomes. Our JLF/CL software is publicly available at https://www.nitrc.org/projects/ashs/.

Project description:Scalp electroencephalography (EEG) and intraoperative electrocorticography (ECoG) are routinely used in the evaluation of magnetic resonance imaging-negative temporal lobe epilepsy (TLE) undergoing standard anterior temporal lobectomy with amygdalohippocampectomy (ATL), but the utility of interictal epileptiform discharge (IED) identification and its role in outcome are poorly defined.To determine whether the following are associated with surgical outcomes in patients with magnetic resonance imaging-negative TLE who underwent standard ATL: (1) unilateral-only IEDs on preoperative scalp EEG; (2) complete resection of tissue generating IEDs on ECoG; (3) complete resection of opioid-induced IEDs recorded on ECoG; and (4) location of IEDs recorded on ECoG.Data were gathered through retrospective medical record review at a tertiary referral center. Adult and pediatric patients with TLE who underwent standard ATL between January 1, 1990, and October 15, 2010, were considered for inclusion. Inclusion criteria were magnetic resonance imaging-negative TLE, standard ECoG performed at the time of surgery, and a minimum follow-up of 12 months. Univariate analysis was performed using log-rank time-to-event analysis. Variables reaching significance with log-rank testing were further analyzed using Cox proportional hazards.Excellent or nonexcellent outcome at time of last follow-up. An excellent outcome was defined as Engel class I and a nonexcellent outcome as Engel classes II through IV.Eighty-seven patients met inclusion criteria, with 48 (55%) achieving an excellent outcome following ATL. Unilateral IEDs on scalp EEG (P?=?.001) and complete resection of brain regions generating IEDs on baseline intraoperative ECoG (P?=?.02) were associated with excellent outcomes in univariate analysis. Both were associated with excellent outcomes when analyzed with Cox proportional hazards (unilateral-only IEDs, relative risk?=?0.31 [95% CI, 0.16-0.64]; complete resection of IEDs on baseline ECoG, relative risk?=?0.39 [95% CI, 0.20-0.76]). Overall, 25 of 35 patients (71%) with both unilateral-only IEDs and complete resection of baseline ECoG IEDs had an excellent outcome.Unilateral-only IEDs on preoperative scalp EEG and complete resection of IEDs on baseline ECoG are associated with better outcomes following standard ATL in magnetic resonance imaging-negative TLE. Prospective evaluation is needed to clarify the use of ECoG in tailoring temporal lobectomy.

Dataset Information

Automated diagnosis of temporal lobe epilepsy in the absence of interictal spikes.

Objective

Methods

Results

Significance

Publications

Automated diagnosis of temporal lobe epilepsy in the absence of interictal spikes.

Similar Datasets

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