Diagnosis Of Temporal Lobe Epilepsy Research Articles

Cognition in adult patients with newly diagnosed non-lesional temporal lobe epilepsy

ObjectiveTo evaluate whether cognitive performance is affected in newly diagnosed temporal lobe epilepsy (TLE) and to determine the most vulnerable cognitive domains. MethodsIn this baseline longitudinal study, differences in memory and non-memory cognitive functions were assessed using comprehensive neuropsychological test batteries in 21 adult patients with newly diagnosed non-lesional TLE and individually matched controls. In addition, the analyses included ratings of self-perceived emotional status. ResultsThe patients performed more poorly than the control group regarding delayed visual memory (p = 0.013) and executive function tasks related to switching (Trail Making Test and verbal fluency shifting; p = 0.025 and p = 0.03, respectively). We found no differences in verbal learning and memory, attention/working memory/processing speed, and other executive functions. SignificanceOur results show that patients with TLE often have specific cognitive deficits at time of diagnosis, even in the absence of structural brain abnormalities. This supports the hypothesis that memory dysfunction is linked to an underlying pathology rather than to the effect of recurrent seizures, long-term use of anti-seizure medication, or other epilepsy-related factors. As certain executive functions are affected at an early stage, the pathology may involve brain regions beyond the temporal lobe and may comprise larger brain networks. These results indicate the need for greater awareness of cognition at the time of diagnosis of TLE and before initiation of treatment, and integration of neuropsychological assessment into early routine clinical care.

Circulating microRNA: The Potential Novel Diagnostic Biomarkers to Predict Drug Resistance in Temporal Lobe Epilepsy, a Pilot Study.

MicroRNAs (miRNAs) are small noncoding RNAs that have emerged as new potential epigenetic biomarkers. Here, we evaluate the efficacy of six circulating miRNA previously described in the literature as biomarkers for the diagnosis of temporal lobe epilepsy (TLE) and/or as predictive biomarkers to antiepileptic drug response. We measured the differences in serum miRNA levels by quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) assays in a cohort of 27 patients (14 women and 13 men; mean ± SD age: 43.65 ± 17.07) with TLE compared to 20 healthy controls (HC) matched for sex, age and ethnicity (11 women and 9 men; mean ± SD age: 47.5 ± 9.1). Additionally, patients were classified according to whether they had drug-responsive (n = 17) or drug-resistant (n = 10) TLE. We have investigated any correlations between miRNAs and several electroclinical parameters. Three miRNAs (miR-142, miR-146a, miR-223) were significantly upregulated in patients (expressed as average expression ± SD). In detail, miR-142 expression was 0.40 ± 0.29 vs. 0.16 ± 0.10 in TLE patients compared to HC (t-test, p < 0.01), miR-146a expression was 0.15 ± 0.11 vs. 0.07 ± 0.04 (t-test, p < 0.05), and miR-223 expression was 6.21 ± 3.65 vs. 1.23 ± 0.84 (t-test, p < 0.001). Moreover, results obtained from a logistic regression model showed the good performance of miR-142 and miR-223 in distinguishing drug-sensitive vs. drug-resistant TLE. The results of this pilot study give evidence that miRNAs are suitable targets in TLE and offer the rationale for further confirmation studies in larger epilepsy cohorts.

Long-Term Surgical Outcomes and Predictors of Surgical Treatment in Temporal Lobe Epilepsy

Background: Surgical treatment of epilepsy is a favored modality in the management of refractory temporal lobe epilepsy (TLE) and known to be quite effective. The aim of this study was to evaluate the long-term outcomes in surgical treatment of TLE and to identify prognostic factors influencing postoperative seizure remission. Materials and Methods: The patients who underwent anterior temporal lobectomy (ATL) with the diagnosis of refractory TLE in our center between the years of 2006 and 2020 were included. Preoperative workup process was carried out by a multidisciplinary team and consisted of neuropsychological examination, long-term electroencephalography, brain magnetic resonance imaging (MRI), and fluorodeoxyglucose positron emission tomography (FDG-PET) for each patient. Postoperative assessment of seizure control was repeated every year following surgery and categorized according to Engel's outcome classification. The predictive value of baseline demographic, clinical, laboratory, imaging, and histopathological parameters on postoperative seizure control was also evaluated. Results: One hundred and forty-three patients who underwent ATL with the diagnosis of TLE were included. According to Engel's classification, the seizure freedom rate was found to be 83.2% at the 2nd year, 81.3% at the 4th year, and 79.2% at the 10th year after surgery. In the univariate analysis, febrile seizure (FS) history, unilateral interictal epileptiform discharges (IEDs), hippocampal sclerosis (HS) on MRI, unilateral temporal hypometabolism (HM) on FDG-PET, and HS in histopathology were predictors of seizure control at the postoperative 2nd and 10th years. FS history, unilateral localization of IEDs, and unilateral FDG-PET findings of temporal HM were found to be the independent predictors of postoperative seizure control on multivariate analysis. Conclusions: In the current study, we revealed that epilepsy surgery provides effective seizure control and represents a beneficial therapeutic option in refractory TLE. Our results also suggested that FS history, unilateral IEDs, and unilateral FDG-PET findings of temporal HM were independent predictors of seizure remission in these patients.

Multi-Head Self-Attention Model for Classification of Temporal Lobe Epilepsy Subtypes.

As a long-standing chronic disease, Temporal Lobe Epilepsy (TLE), resulting from abnormal discharges of neurons and characterized by recurrent episodic central nervous system dysfunctions, has affected more than 70% of drug-resistant epilepsy patients across the world. As the etiology and clinical symptoms are complicated, differential diagnosis of TLE mainly relies on experienced clinicians, and specific diagnostic biomarkers remain unclear. Though great effort has been made regarding the genetics, pathology, and neuroimaging of TLE, an accurate and effective diagnosis of TLE, especially the TLE subtypes, remains an open problem. It is of a great importance to explore the brain network of TLE, since it can provide the basis for diagnoses and treatments of TLE. To this end, in this paper, we proposed a multi-head self-attention model (MSAM). By integrating the self-attention mechanism and multilayer perceptron method, the MSAM offers a promising tool to enhance the classification of TLE subtypes. In comparison with other approaches, including convolutional neural network (CNN), support vector machine (SVM), and random forest (RF), experimental results on our collected MEG dataset show that the MSAM achieves a supreme performance of 83.6% on accuracy, 90.9% on recall, 90.7% on precision, and 83.4% on F1-score, which outperforms its counterparts. Furthermore, effectiveness of varying head numbers of multi-head self-attention is assessed, which helps select the optimal number of multi-head. The self-attention aspect learns the weights of different signal locations which can effectively improve classification accuracy. In addition, the robustness of MSAM is extensively assessed with various ablation tests, which demonstrates the effectiveness and generalizability of the proposed approach.

Interictal Heart Rate Variability Analysis Reveals Lateralization of Cardiac Autonomic Control in Temporal Lobe Epilepsy

Purpose: The temporal lobe, a critical hub for cognition, also plays a central role in the regulation of autonomic cardiovascular functions. Lesions in this area are usually associated with abnormalities in the regulation of heart rate (HR) and blood pressure (BP). The analysis of the heart rate variability (HRV) is useful to evaluate the cardiac parasympathetic nervous system activity. This study aims at comparing HRV changes occurring in two groups of patients suffering from Temporal Lobe Epilepsy (TLE). To that aim, we evaluated patients differentiated by the right or left location of the epileptic foci.Materials and Methods: Fifty-two adult patients with a diagnosis of TLE were enrolled. Each patient underwent a 20-min EEG + EKG recording in resting state. According to the localization of epileptic focus, patients were divided into two subgroups: right TLE (R-TLE) and left TLE (L-TLE). HRV parameters were calculated with a short-lasting analysis of EKG recordings. Time-domain and frequency domain-related, as well as non-linear analysis, parameters, were compared between the two groups.Results: Compared to the R-TLE group, L-TLE subjects showed a significant decrease in low frequency (LF) (p < 0.01) and low frequency/high-frequency ratio (LF/HF) (p < 0.001) as well as increased HF values (p < 0.01), a parameter indicative of the presence of an increased cardiac vagal tone. These results were also confirmed in the subgroup analysis that took into account the seizure types, responses to antiepileptic drugs, seizure frequencies, and etiology.Conclusions: The main finding of the study is that, compared to R-TLE, L-TLE is associated with increased cardiac vagal tone. These results indicate that patients with TLE exhibit a lateralized cardiac autonomic control. L-TLE patients may have a lower risk of developing cardiac dysfunctions and less susceptible to develop Sudden Death for Epilepsy (SUDEP).

Genome-wide microRNA profiling of plasma from three different animal models identifies biomarkers of temporal lobe epilepsy

Epilepsy diagnosis is complex, requires a team of specialists and relies on in-depth patient and family history, MRI-imaging and EEG monitoring. There is therefore an unmet clinical need for a non-invasive, molecular-based, biomarker to either predict the development of epilepsy or diagnose a patient with epilepsy who may not have had a witnessed seizure. Recent studies have demonstrated a role for microRNAs in the pathogenesis of epilepsy. MicroRNAs are short non-coding RNA molecules which negatively regulate gene expression, exerting profound influence on target pathways and cellular processes. The presence of microRNAs in biofluids, ease of detection, resistance to degradation and functional role in epilepsy render them excellent candidate biomarkers.Here we performed the first multi-model, genome-wide profiling of plasma microRNAs during epileptogenesis and in chronic temporal lobe epilepsy animals. From video-EEG monitored rats and mice we serially sampled blood samples and identified a set of dysregulated microRNAs comprising increased miR-93-5p, miR-142-5p, miR-182-5p, miR-199a-3p and decreased miR-574-3p during one or both phases. Validation studies found miR-93-5p, miR-199a-3p and miR-574-3p were also dysregulated in plasma from patients with intractable temporal lobe epilepsy. Treatment of mice with common anti-epileptic drugs did not alter the expression levels of any of the five miRNAs identified, however administration of an anti-epileptogenic microRNA treatment prevented dysregulation of several of these miRNAs. The miRNAs were detected within the Argonuate2-RISC complex from both neurons and microglia indicating these miRNA biomarker candidates can likely be traced back to specific brain cell types.The current studies identify additional circulating microRNA biomarkers of experimental and human epilepsy which may support diagnosis of temporal lobe epilepsy via a quick, cost-effective rapid molecular-based test.

CpG methylation signature defines human temporal lobe epilepsy and predicts drug-resistant.

AimsTemporal lobe epilepsy (TLE) is the most common focal epilepsy syndrome in adults and frequently develops drug resistance. Studies have investigated the value of peripheral DNA methylation signature as molecular biomarker for diagnosis or prognosis. We aimed to explore methylation biomarkers for TLE diagnosis and pharmacoresistance prediction.MethodsWe initially conducted genome‐wide DNA methylation profiling in TLE patients, and then selected candidate CpGs in training cohort and validated in another independent cohort by employing machine learning algorithms. Furthermore, nomogram comprising DNA methylation and clinicopathological data was generated to predict the drug response in the entire patient cohort. Lastly, bioinformatics analysis for CpG‐associated genes was performed using Ingenuity Pathway Analysis.ResultsAfter screening and validation, eight CpGs were identified for diagnostic biomarker with an area under the curve (AUC) of 0.81 and six CpGs for drug‐resistant prediction biomarker with an AUC of 0.79. The nomogram for drug‐resistant prediction comprised methylation risk score, disease course, seizure frequency, and hippocampal sclerosis, with AUC as high as 0.96. Bioinformatics analysis indicated drug response–related CpGs corresponding genes closely related to DNA methylation.ConclusionsThis study demonstrates the ability to use peripheral DNA methylation signature as molecular biomarker for epilepsy diagnosis and drug‐resistant prediction.

Early Detection of Temporal Lobe Epilepsy: Identification of Novel Candidate Genes and Potential Biomarkers Using Integrative Genomics Analysis

Currently afflicting more than 50 million people worldwide, epilepsy is the spectrum disorder characterizing seizures that occur without other plausible medical explanations. Temporal lobe epilepsy (TLE) is one of the most common forms of epilepsy. Current clinical methods; including MRI scans, EEG tests, and doctor visits; can take upwards of several months to confirm a TLE diagnosis; during this time, patients may experience additional seizures and are at an increased risk for other psychiatric disorders. The purpose of this study is to identify candidate genetic biomarkers to facilitate the earlier detection and diagnosis of TLE through gene-based testing (e.g., genomic heatmap analysis or genetic and/or microarray testing). It was hypothesized that potential biomarkers could be identified by analyzing genes that are normally significantly overexpressed in the temporal lobe relative to the gray matter. Statistical and functional analysis was performed on significantly overexpressed genes (≥3.000 fold change) in the gene expression profiles of four donors without epilepsy. The experimental-evidence-based STRING protein interactions analysis showed associations between genes found in DAVID keyword search and other genes facilitating network interconnectivity. After evaluation of the genes’ STRING enriched functions, changes in the expression of the genes CAMK2A, NPY, DLG4, MEF2C, and MAPK7 were concluded to be potential biomarkers for TLE, confirming the original hypothesis. Specifically, the identification of MEF2C and MAPK7 for this purpose is relatively novel in the fields of bioinformatics and neurogenetics. Future work includes investigating the utility of the candidate genes in real-world gene-based diagnostic methods.

The Utility of the Repeatable Battery of Neuropsychological Status in Patients with Temporal and Non-temporal Lobe Epilepsy.

The Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) is a brief neuropsychological battery that has been validated in the assessment of dementia and other clinical populations. The current study examines the utility of the RBANS in patients with epilepsy. Ninety-eight patients with epilepsy completed the RBANS as part of a more comprehensive neuropsychological evaluation. Performance on the RBANS was evaluated for patients with a diagnosis of temporal lobe epilepsy (TLE; n=51) and other epilepsy patients (non-TLE, n=47) in comparison to published norms. Multivariate analysis of variance compared group performances on RBANS indices. Rates of impairment were also compared across groups using cutoff scores of ≤1.0 and ≤1.5 standard deviations below the normative mean. Exploratory hierarchical regressions were used to examine the relations between epilepsy severity factors (i.e., age of onset, disease duration, and number of antiepileptic drugs [AEDs]) and RBANS performance. TLE and non-TLE patients performed below the normative sample across all RBANS indices. Those with TLE performed worse than non-TLE patients on the Immediate and Delayed Memory indices and exhibited higher rates of general cognitive impairment. Number of AEDs was the only epilepsy severity factor that significantly predicted RBANS total performance, accounting for 14% of the variance. These findings suggest that the RBANS has utility in evaluating cognition in patients with epilepsy and can differentiate TLE and non-TLE patients. Additionally, number of AEDs appears to be associated with global cognitive performance in adults with epilepsy.

Racial differences in adult-onset MRI-negative temporal lobe epilepsy

ObjectiveWe recently detected a significant racial difference in our population with temporal lobe epilepsy (TLE) at the University of Alabama at Birmingham (UAB) seizure monitoring unit. We found that Black patients were more likely than their White counterparts to carry a TLE diagnosis. Using this same patient population, we focus on the patients with TLE to better describe the relationship between race and epidemiology in this population. MethodsWe analyzed the data from patients diagnosed with TLE admitted to the UAB seizure monitoring unit between January 2000 and December 2011. For patients with a video electroencephalography (EEG) confirmed diagnosis of TLE (n = 385), basic demographic information including race and magnetic resonance imaging (MRI) findings were collected. Descriptive statistics and multivariate logistic regression were used to explore the relationship between MRI findings, demographic data, and race. ResultsFor Black patients with TLE, we found that they were more likely to be female (odds ratio [OR] = 1.91, 95% confidence interval [CI]: 1.14–3.19), have seizure onset in adulthood (OR = 2.39, 95% CI: 1.43–3.19), and have normal MRIs (OR = 1.69, 95% CI: 1.04–2.77) compared to White counterparts with TLE after adjusting for covariates. ConclusionsThese data suggest that Black race (compared to White) is associated with higher expression of adult-onset MRI-negative TLE, an important subtype of epilepsy with unique implications for evaluation, treatment, and prognosis. If validated in other cohorts, the findings may explain the lower reported rates of epilepsy surgery utilization among Blacks. The racial differences in surgical utilization could be due to a greater prevalence of an epilepsy that is less amenable to surgical resection rather than to cultural differences or access to care.

CpG Methylation Signature Define Human Temporal Lobe Epilepsy and Predict Drug-Resistant

Background: Temporal lobe epilepsy (TLE) is the most common focal epilepsy syndrome in adults and frequently develops drug resistance. Aberrant DNA methylation implicated in underlying epileptogenesis and progression mechanisms of epilepsy has gained considerable attention. A substantial number of studies have investigated the value of peripheral DNA methylation signature as molecular biomarker for diagnosis or prognosis. However, to date, methylation biomarkers for TLE diagnosis and pharmacoresistance prediction have not been explored. Methods: We initially conducted genome-wide DNA methylation profiling in TLE patients; then selected candidate CpGs in training cohort and validated those CpGs in another independent cohort by employing machine learning algorithms. Furthermore, a nomogram comprising DNA methylation and clinicopathological data was generated to predict the drug-response in the entire patient cohort. Lastly, bioinformatics analysis for CpGassociated genes was performed using Ingenuity Pathway Analysis. Findings: After screening and validation, eight CpGs were identified for diagnostic biomarker with an area under the curve (AUC) of 0.81, six CpGs for drug-resistant prediction biomarker with an AUC of 0.79. The nomogram for drug-resistant prediction comprised methylation risk score, disease course, seizure frequency, and hippocampal sclerosis,with AUC as high as 0.96. Bioinformatics analysis indicated drug-response related CpGs corresponding genes closely related to DNA methylation. Interpretation: This study introduced a methodological framework to screen and validate CpG methylation biomarker, and demonstrates the ability to use machine learning as a potential clinical tool for epilepsy diagnosis and drug-resistant prediction after more comprehensive validation. Funding Statement: This study was supported financially by Omics-based precision medicine of epilepsy being entrusted by Key Research Project of the Ministry of Science and Technology of China(No. 2016YFC0904400), and the National Natural Science Foundation of China (No.81671299 to BX, No.81671300 to LLL and No.81701182 to YJF), and the Science and Technology Department Funds of Hunan Province Key Project(No.2016JC2057 to BX and No.2018JJ3822 to HYL)and Independent Exploration and Innovation project for postgraduate of Central South University(No. 2018zzts248 to WBX). Declaration of Interests: The authors stated: None declared. Ethics Approval Statement: Written informed consent was obtained from all enrolled participants. Study was conducted in accordance with the guideline for the research involving human, and approved by the Ethics Committee of Central South University, Xiangya School of Medicine and the affiliated Xiangya Hospital.

A protocol for a randomised controlled, double-blind feasibility trial investigating fluoxetine treatment in improving memory and learning impairments in patients with mesial temporal lobe epilepsy: Fluoxetine, Learning and Memory in Epilepsy (FLAME trial)

BackgroundPeople with temporal lobe epilepsy (TLE) report significant problems with learning and memory. There are no effective therapies for combatting these problems in people with TLE, resulting in an unmet therapeutic need. The lack of treatment is, in part, due to a poor understanding of the neurobiology underlying these memory deficits. We know that hippocampal neurogenesis, a process believed to be important in learning and memory formation, is permanently reduced in chronic TLE, and this may go some way to explain the learning and memory impairments seen in people with TLE.The common anti-depressant drug fluoxetine has been shown to stimulate neurogenesis both in the healthy brain and in neurological diseases where neurogenesis is impaired. In an animal model of TLE, administration of fluoxetine was found to restore neurogenesis and improve learning on a complex spatial navigational task. We now want to test this effect in humans by investigating whether administration of fluoxetine to people with TLE can improve learning and memory.MethodsThis is a single-centre randomised controlled, double-blind feasibility trial. We plan to recruit 20 participants with a diagnosis of TLE and uni-lateral hippocampal sclerosis, confirmed by 3T MRI. Eligible participants will undergo baseline assessments of learning and memory prior to being randomised to either 20 mg/day fluoxetine or matching placebo for 60 days. Follow-up assessments will be conducted after 60 days of trial medication and then again at 60 days after cessation of trial medication. Feasibility will be assessed on measures of recruitment, retention and adherence against pre-determined criteria.DiscussionThis trial is designed to determine the feasibility of conducting a double-blind randomised controlled trial of fluoxetine for the treatment of learning and memory impairments in people with TLE. Data collected in this trial will inform the design and utility of any future efficacy trial involving fluoxetine for the treatment of learning and memory in people with TLE.Trial registrationEudraCT 2014-005088-34, registered on May 18, 2015

Brain microstructural abnormalities correlate with KCC2 downregulation in refractory epilepsy.

Dysregulations in the expression level of Na-K-Cl cotransporter (NKCC1) and K-Cl cotransporter (KCC2) genes have been detected in the brain tissues of patients with refractory epilepsy. Given the importance of these proteins in the determination of Cl equilibrium potential (ECl), evaluation of the expression changes of these transporters might assist in optimizing the diagnostic approaches and therapeutic strategies. The present investigation evaluates the expression level chloride transporters in polymorphonuclear cells and their correlation with microstructural abnormalities. Thirty cases of drug-resistant epilepsy (confirmed with temporal lobe epilepsy diagnosis) fulfilled the considered inclusion criteria. Cases were divided into two groups, one with a detectable MRI lesion (19 participants; right side) and another with no MRI findings (11 participants). Whole-brain voxel-based analysis was performed on diffusion tensor imaging to measure fractional anisotropy and mean diffusivity; neurite orientation dispersion and density imaging was performed to map neurite density index and orientation dispersion index. Our results indicated that fractional anisotropy and mean diffusivity changed in temporal and extratemporal parts of the brain, whereas the changes in neurite density index and orientation dispersion index were exclusively obvious in the temporal lobe. Molecular studies revealed significantly lower levels of KCC2 expression in patients with epilepsy, a finding that remarkably correlated with microstructural changes as well. Our research showed that downregulation of KCC2 and microstructural abnormalities might contribute to the observed refractoriness in temporal lobe epilepsy.

Functional MRI in epilepsy - Comparison of Lateralization index and language scoring.

Aims:To evaluate the role of functional magnetic resonance imaging (fMRI) in epilepsy management and to ascertain whether laterality index (LI) derived from fMRI data, using routinely utilized paradigms, can serve as an adjunct to/or replace preoperative neuropsychological testing for evaluation of language lateralization and impairment.Materials and Methods:This was a prospective study which included 20 consecutive patients with a clinical diagnosis of temporal lobe epilepsy over a period of 1 year. Neuropsychological assessment included oral word association test and animal names test. The scores of both tests were compared with normographic data provided in the NIMHANS neuropsychology battery. Three fMRI paradigms were used, namely, picture naming, word generation, and sentence completion. Processing and statistical analysis were performed subsequently.Results and Conclusion:Right temporal lobe epilepsy (RTLE) was seen in 12 patients and left temporal lobe epilepsy (LTLE) in 8 patients. All patients were right handed. The activation pattern was predominantly left lateralized. Language lateralization varied with the type of paradigm. The overall percentage of patients showing left lateralization ranged from 44.00% for the picture naming task to 75% for the sentence completion. Reduced left lateralization was noted in both LTLE and RTLE patients. A negative correlation was observed in LTLE patients between performance in the verbal fluency and the lateralization index in the temporal and parietal regions of interest (ROI) in the word generation paradigm, suggesting that increased left lateralization was associated with a poorer score on neuropsychological tests. In RTLE patients, however, there was no significant correlation between performance in neuropsychological tests and LI. In conclusion, language lateralization using LI can serve as an adjunct during preoperative evaluation. However, it cannot replace neuropsychological testing.

Using Low-Frequency Oscillations to Detect Temporal Lobe Epilepsy with Machine Learning.

The National Institutes of Health-sponsored Epilepsy Connectome Project aims to characterize connectivity changes in temporal lobe epilepsy (TLE) patients. The magnetic resonance imaging protocol follows that used in the Human Connectome Project, and includes 20 min of resting-state functional magnetic resonance imaging acquired at 3T using 8-band multiband imaging. Glasser parcellation atlas was combined with the FreeSurfer subcortical regions to generate resting-state functional connectivity (RSFC), amplitude of low-frequency fluctuations (ALFFs), and fractional ALFF measures. Seven different frequency ranges such as Slow-5 (0.01-0.027 Hz) and Slow-4 (0.027-0.073 Hz) were selected to compute these measures. The goal was to train machine learning classification models to discriminate TLE patients from healthy controls, and to determine which combination of the resting state measure and frequency range produced the best classification model. The samples included age- and gender-matched groups of 60 TLE patients and 59 healthy controls. Three traditional machine learning models were trained: support vector machine, linear discriminant analysis, and naive Bayes classifier. The highest classification accuracy was obtained using RSFC measures in the Slow-4 + 5 band (0.01-0.073 Hz) as features. Leave-one-out cross-validation accuracies were ∼83%, with receiver operating characteristic area-under-the-curve reaching close to 90%. Increased connectivity from right area posterior 9-46v in TLE patients contributed to the high accuracies. With increased sample sizes in the near future, better machine learning models will be trained not only to aid the diagnosis of TLE, but also as a tool to understand this brain disorder.

Hemispheric Regional Based Analysis of Diffusion Tensor Imaging and Diffusion Tensor Tractography in Patients with Temporal Lobe Epilepsy and Correlation with Patient outcomes

Imaging in the field of epilepsy surgery remains an essential tool in terms of its ability to identify regions where the seizure focus might present as a resectable area. However, in many instances, an obvious structural abnormality is not visualized. This has created the opportunity for new approaches and imaging innovation in the field of epilepsy, such as with Diffusion Tensor Imaging (DTI) and Diffusion Tensor Tractography (DTT). In this study, we aim to evaluate the use of DTI and DTT as a predictive model in the field of epilepsy, specifically Temporal Lobe Epilepsy (TLE), and correlate their clinical significance with respect to postsurgical outcomes. A hemispheric based analysis was used to compare the tract density, as well as DTI indices of the specific regions of interest from the pathologic hemisphere to the healthy hemisphere in TLE patients. A total of 22 patients with TLE (12 males, 10 females, 22–57 age range) underwent either a craniotomy, Anterior Temporal Lobectomy (ATL), or a less invasive method of Selective Laser Amygdalohippocampectomy (SLAH) and were imaged using 3.0 T Philips Achieva MR scanner. Of the participants, 12 underwent SLAH while 10 underwent ATL. The study was approved by the institutional review board of Thomas Jefferson University Hospital. Informed consent was obtained from all patients. All patients had a diagnosis of TLE according to standard clinical criteria. DTI images were acquired axially in the same anatomical location prescribed for the T1-weighted images. The raw data set consisting of diffusion volumes were first corrected for eddy current distortions and motion artifacts. Various DTI indices such as Fractional Anisotropy (FA), Mean Diffusivity (MD), Radial Diffusivity (RD) and Axial Diffusivity (AD) were estimated and co-registered to the brain parcellation map obtained by freesurfer. 16 consolidated cortical and subcortical regions were selected as regions of interest (ROIs) by a functional neurosurgeon and DTI values for each ROI were calculated and compared with the corresponding ROI in the opposite hemisphere. Also, track density imaging (TDI) of 68 white matter parcels were generated using fiber orientation distribution (FOD) based deterministic fiber tracking and compared with contralateral side of the brain in each epileptic group: left mesial temporal sclerosis (LMTS) and right MTS (RMTS)). In patients with LMTS, MD and RD values of the left hippocampus decreased significantly using two-tailed t-test (p = 0.03 and p = 0.01 respectively) compared to the right hippocampus. Also, RD showed a marginally significant decrease in left amygdala (p = 0.05). DTT analysis in LMTS shows a marginally significant decrease in the left white matter supramarginal parcel (p = 0.05). In patients with RMTS, FA showed a significant decrease in the ipsilateral mesial temporal lobe (p = 0.02), parahippocampal area (p = 0.03) and thalamus (p = 0.006). RD showed a marginally significant increase in the ipsilateral hippocampus (p = 0.05) and a significant increase in the ipsilateral parahippocampal area (p = 0.03). Also, tract density of the ipsilateral white matter inferior parietal parcel showed a marginally significant increase compared to the contralateral side (p = 0.05). With respect to postsurgical outcomes, we found an association between residual seizures and tract density in five white matter segments including ipsilateral lingual (p = 0.04), ipsilateral temporal pole (p = 0.007), ipsilateral pars opercularis (p = 0.03), ipsilateral inferior parietal (p = 0.04) and contralateral frontal pole (p = 0.04). These results may have the potential to be developed into imaging prognostic markers of postoperative outcomes and provide new insights for why some patients with TLE continue to experience postoperative seizures if pathological/clinical correlates are further confirmed.

Circulating levels of adipokines are altered in patients with temporal lobe epilepsy

ObjectiveA persistent low-grade inflammatory state has been described in patients with temporal lobe epilepsy (TLE) in the interictal period. Adipokines are cytokines produced by the adipose tissue that can influence inflammatory response. The purpose of this study was to evaluate the plasma levels of adipokines in patients with TLE in comparison with controls. In addition, we sought to investigate whether the levels of adipokines were associated with clinical parameters in TLE. MethodsForty patients with TLE and 40 controls were enrolled in this study. All participants were subjected to clinical assessment that included the Mini International Neuropsychiatric Interview (MINI) and the Hamilton Depression Rating Scale (HAM-D). Peripheral blood was drawn, and plasma levels of adipokines (adiponectin, leptin, and resistin) were measured by enzyme-linked immunoassay (ELISA). ResultsPeople with TLE presented higher leptin and lower adiponectin and resistin levels in comparison with controls. The levels of these adipokines correlated negatively with illness length but not with other clinical parameters. In a binary logistic regression model, higher leptin and lower adiponectin levels remained as significant predictors of TLE diagnosis. ConclusionsThese results corroborate the view that TLE is a multisystemic condition associated with low-grade inflammation.

Comparison of the effect of different electroencephalogram in the diagnosis of temporal lobe epilepsy

Objective To compare the clinical value of different electroencephalogram(EEG) in the diagnosis of temporal lobe epilepsy. Methods A total of 123 patients in Taizhou Central Hospital received routine EEG, dynamic EEG, routine sphenoidal electrode examination, and long sphenoidal electrode examination.The the detection rate of epileptic waves in EEG, awake and sleep phases of patients with temporal lobe epilepsy were compared. Results The detection rate of epileptiform wave by the routine EEG was 52.63%, which by the dynamic EEG was 61.11%, and there was no statistically significant difference(P>0.05). The detection rate of epileptiform wave by the long range sphenoidal electrode EEG was 63.64%, which was higher than that by the conventional sphenoidal electrode EEG(22.22%)(χ2=8.776, P<0.05). The detection rate of epileptiform wave in the sleep period EEG in temporal lobe epilepsy was 51.35%, which was higher than that in the awake period (29.73%), and the difference was statistically significant(χ2=5.739, P<0.05). Conclusion Different types of EEG have their respective advantages in diagnosis of temporal lobe epilepsy, sphenoidal electrodes and sleep induced temporal lobe epilepsy can significantly improve the detection rate of abnormal EEG, has important clinical value in the diagnosis of temporal lobe epilepsy. Key words: Epilepsy; Electroencephalography; Diagnosis

Cancer frequency detected by positron emission tomography-computed tomography in limbic encephalitis

ObjectiveParaneoplastic limbic encephalitis (LE) occurs frequently with considerable variability according to literature reports. We thus determined the cancer frequency in mixed LE subtypes sharing the diagnosis of temporal lobe epilepsy (TLE). MethodsAll patients underwent magnetic resonance imaging (MRI) of the brain, electroencephalography (EEG) recordings, neuropsychological testing, immunohistochemistry, and clinical examination together with whole body 2-fluor-2-desoxy-d-glucose (FDG)-positron emission tomography (PET)/computed tomography (CT) to detect cancer in this observatory study. ResultsNinety-three patients (median: 52 years) with TLE due to autoimmune LE were investigated. Cancer was detected in the FDG-PET/CTs of 3 out of 93 (3.2%) patients with LE. Cancer was diagnosed upon, 5 years earlier and 5 years after FDG-PET/CT in 7 of 93 (7.5%) of all patients with LE. The cancer frequency in those patients was significantly lower than that reported in the largest series of patients with LE associated with and without different antibodies (7.5% vs. 23.5%, Bootstrap test, p < 0.05), but was indistinguishable from the estimated age-dependent cancer frequency in the German regional North-Rhine-Westfalian population without LE in 2014 (Chi-square test: p = 0.2). ConclusionsOur findings reveal that the cancer frequency in patients with TLE with LE detected by FDG-PET/CT is low and not different from the age-dependent natural cancer occurrence in a regional population.

The prevalence of neural antibodies in temporal lobe epilepsy and the clinical characteristics of seropositive patients

PurposeEpileptic seizures are a common manifestation of autoimmune encephalitis, but the role of neural antibodies in long-term epilepsy remains unclear. The aim of this study was to assess the prevalence of neural-surface antibodies (NSAbs) and antibodies against glutamic acid decarboxylase (GAD) in patients with chronic temporal lobe epilepsy (TLE). MethodPatients with an electro-clinical diagnosis of TLE and a disease duration longer than one year were included. NSAbs (LGI1, CASPR2, AMPAR1/2, NMDAR, GABABR) and antibodies against GAD were detected. Only patients with significant antibody levels in serum, and/or positivity in CSF (according to antibody subtype), were enrolled in the seropositive group. Cohorts of seropositive and seronegative patients were compared regarding clinical and imaging data. ResultsSignificant serum levels of antibodies were detected in eight out of 163 (5%) TLE patients (CASPR2 n = 2, GAD n = 3, LGI1 n = 2, and GABABR n = 1). In four of them, antibodies were detected in the CSF as well (CASPR2 in one, GAD in three). Five seropositive patients had uni- or bilateral temporal lobe lesions on MRI and three patients were non-lesional. All seropositive patients had TLE of unknown cause. Seropositive patients had higher age at epilepsy onset and autoimmune comorbidity, but did not differ in other clinical, EEG or neuroimaging characteristics. Response to immunotherapy (seizure reduction >50%) was observed in three of the six patients treated. ConclusionsBesides older age at epilepsy onset and autoimmune comorbidity, seropositive patients cannot be distinguished from seronegative patients on the basis of clinical, EEG or neuroimaging data.