Search

Objective: Evidence suggests that the most promising results in interictal localization of the epileptogenic zone (EZ) are achieved by a combination of multiple stereo‐electroencephalography (SEEG) biomarkers in machine learning models. These biomarkers usually include SEEG features calculated in standard frequency bands, but also high‐frequency (HF) bands. Unfortunately, HF features require extra effort to record, store, and process. Here we investigate the added value of these HF features for EZ localization and postsurgical outcome prediction. Methods: In 50 patients we analyzed 30 min of SEEG recorded during non–rapid eye movement sleep and tested a logistic regression model with three different sets of features. The first model used broadband features (1–500 Hz); the second model used low‐frequency features up to 45 Hz; and the third model used HF features above 65 Hz. The EZ localization by each model was evaluated by various metrics including the area under the precision‐recall curve (AUPRC) and the positive predictive value (PPV). The differences between the models were tested by the Wilcoxon signed‐rank tests and Cliff's Delta effect size. The differences in outcome predictions based on PPV values were further tested by the McNemar test. Results: The AUPRC score of the random chance classifier was.098. The models (broad‐band, low‐frequency, high‐frequency) achieved median AUPRCs of.608,.582, and.522, respectively, and correctly predicted outcomes in 38, 38, and 33 patients. There were no statistically significant differences in AUPRC or any other metric between the three models. Adding HF features to the model did not have any additional contribution. Significance: Low‐frequency features are sufficient for correct localization of the EZ and outcome prediction with no additional value when considering HF features. This finding allows significant simplification of the feature calculation process and opens the possibility of using these models in SEEG recordings with lower sampling rates, as commonly performed in clinical routines. [ABSTRACT FROM AUTHOR]

Objective: Focal cortical dysplasia (FCD), hippocampal sclerosis (HS), nonspecific gliosis (NG), and normal tissue (NT) comprise the majority of histopathological results of surgically treated drug‐resistant epilepsy patients. Epileptic spikes, high‐frequency oscillations (HFOs), and connectivity measures are valuable biomarkers of epileptogenicity. The question remains whether they could also be utilized for preresective differentiation of the underlying brain pathology. This study explored spikes and HFOs together with functional connectivity in various epileptogenic pathologies. Methods: Interictal awake stereoelectroencephalographic recordings of 33 patients with focal drug‐resistant epilepsy with seizure‐free postoperative outcomes were analyzed (15 FCD, 8 HS, 6 NT, and 4 NG). Interictal spikes and HFOs were automatically identified in the channels contained in the overlap of seizure onset zone and resected tissue. Functional connectivity measures (relative entropy, linear correlation, cross‐correlation, and phase consistency) were computed for neighboring electrode pairs. Results: Statistically significant differences were found between the individual pathologies in HFO rates, spikes, and their characteristics, together with functional connectivity measures, with the highest values in the case of HS and NG/NT. A model to predict brain pathology based on all interictal measures achieved up to 84.0% prediction accuracy. Significance: The electrophysiological profile of the various epileptogenic lesions in epilepsy surgery patients was analyzed. Based on this profile, a predictive model was developed. This model offers excellent potential to identify the nature of the underlying lesion prior to resection. If validated, this model may be particularly valuable for counseling patients, as depending on the lesion type, different outcomes are achieved after epilepsy surgery. [ABSTRACT FROM AUTHOR]

Objective Mesial temporal lobe epilepsy ( mTLE) is a severe neurological disorder characterized by recurrent seizures. mTLE is frequently accompanied by neurodegeneration in the hippocampus resulting in hippocampal sclerosis ( HS), the most common morphological correlate of drug resistance in mTLE patients. Incomplete knowledge of pathological changes in mTLE+ HS complicates its therapy. The pathological mechanism underlying mTLE+ HS may involve abnormal gene expression regulation, including posttranscriptional networks involving micro RNAs (mi RNAs). mi RNA expression deregulation has been reported in various disorders, including epilepsy. However, the mi RNA profile of mTLE+ HS is not completely known and needs to be addressed. Methods Here, we have focused on hippocampal mi RNA profiling in 33 mTLE+ HS patients and nine postmortem controls to reveal abnormally expressed mi RNAs. In this study, we significantly reduced technology-related bias (the most common source of false positivity in mi RNA profiling data) by combining two different mi RNA profiling methods, namely next generation sequencing and mi RNA-specific quantitative real-time polymerase chain reaction. Results These methods combined have identified and validated 20 mi RNAs with altered expression in the human epileptic hippocampus; 19 mi RNAs were up-regulated and one down-regulated in mTLE+ HS patients. Nine of these mi RNAs have not been previously associated with epilepsy, and 19 aberrantly expressed mi RNAs potentially regulate the targets and pathways linked with epilepsy (such as potassium channels, γ-aminobutyric acid, neurotrophin signaling, and axon guidance). Significance This study extends current knowledge of mi RNA-mediated gene expression regulation in mTLE+ HS by identifying mi RNAs with altered expression in mTLE+ HS, including nine novel abnormally expressed mi RNAs and their putative targets. These observations further encourage the potential of micro RNA-based biomarkers or therapies. [ABSTRACT FROM AUTHOR]

Purpose: To determine whether voxel-based morphometry (VBM) might contribute to the detection of cortical dysplasia within the temporal pole in patients with mesial temporal lobe epilepsy and hippocampal sclerosis (MTLE/HS). Methods: Eighteen patients with intractable MTLE/HS and 30 sex- and age-matched healthy controls were included in the study. All of the patients fulfilled the diagnostic criteria for MTLE/HS and underwent anteromedial temporal resection. VBM without a modulation step was applied to the magnetic resonance (MR) images of the brain. Statistical parametric maps were used to compare structural characteristics such as gray matter concentration (GMC) within the temporal pole among patients and controls separately. The acquired data were then statistically analyzed to determine the congruency between visually inspected MR imaging (MRI) scans and VBM results in the detection of morphologic abnormalities in the temporal pole compared to postoperative histopathologic findings of cortical dysplasia. Key Findings: Histopathologic examination revealed cortical dysplasia within the temporal pole in 11 patients. In detail, according to Palmini's classification, mild malformations of cortical development (mMCDs) were disclosed in three patients, focal cortical dysplasia (FCD) type Ia in three patients, and FCD type Ib in five patients. Some type of structural temporal pole abnormality was suggested by VBM in 14 patients and by visually inspected MRI scans in 11 patients. The results of VBM were in agreement with the presence/absence of cortical dysplasia in 13 patients (72.2%); this correspondence was significant (p = 0.047). In one case, VBM was false negative and in four cases it was false positive. There was congruence between the results of visual analysis and histologic proof in 55.6% of examined patients, which was not significant. Significance: We found that VBM made a superior contribution to the detection of temporopolar structural malformations (cortical dysplasia) compared to visual inspection. The agreement with postoperative histopathologic proof was clearly significant for VBM results and nonsignificant for visual inspection. [ABSTRACT FROM AUTHOR]

To determine whether changes in gray matter volume (GMV) differ according to the affected side in mesial temporal lobe epilepsy/hippocampal sclerosis (MTLE/HS) syndrome, and moreover to test the hypothesis of more pronounced structural changes in right-sided MTLE/HS. This hypothesis (especially that the contralateral thalamus is more affected in right-sided MTLE/HS) arose from the results of our recent study, wherein more expressed structural and functional changes were observed in a small sample of patients with right-sided MTLE/HS ( Brázdil et al., 2009 ). Twenty patients with left-sided and 20 with right-sided MTLE/HS and 40 sex- and age-matched healthy controls were included in the study. Voxel-based morphometry (VBM) with a modulation step was applied to magnetic resonance imaging (MRI) brain images. Statistical parametric maps were used to compare structural changes between patients and controls separately for the left- and right-sided MTLE/HS subgroups. We also compared the local GMV of the brain structures (insula and thalamus) between the subgroups of patients. In the subgroup with right-sided MTLE/HS, a reduction of GMV was detected in the mesiotemporal structures and the ipsilateral thalamus (as in left-sided MTLE/HS), but also notably in the ipsilateral insula and contralateral thalamus. A statistical analysis revealed a significantly more extensive reduction of GMV in the ipsilateral/contralateral insula and the contralateral thalamus in the subgroup with right-sided compared to left-sided MTLE/HS. We found asymmetrical morphologic changes in patients with left- and right-sided MTLE/HS syndrome (more pronounced in right-sided MTLE/HS). These differences could be theoretically explained by different neuronal networks and pathophysiologic changes in temporolimbic structures. [ABSTRACT FROM AUTHOR]