MRI-negative Temporal Lobe Epilepsy Research Articles

Automated detection of MRI-negative temporal lobe epilepsy with ROI-based morphometric features and machine learning.

Temporal lobe epilepsy (TLE) predominantly originates from the anteromedial basal region of the temporal lobe, and its prognosis is generally favorable following surgical intervention. However, TLE often appears negative in magnetic resonance imaging (MRI), making it difficult to quantitatively diagnose the condition solely based on clinical symptoms. There is a pressing need for a quantitative, automated method for detecting TLE. This study employed MRI scans and clinical data from 51 retrospective epilepsy cases, dividing them into two groups: 34 patients in TLE group and 17 patients in non-TLE group. The criteria for defining the TLE group were successful surgical removal of the epileptogenic zone in the temporal lobe and a favorable postoperative prognosis. A standard procedure was used for normalization, brain extraction, tissue segmentation, regional brain partitioning, and cortical reconstruction of T1 structural MRI images. Morphometric features such as gray matter volume, cortical thickness, and surface area were extracted from a total of 20 temporal lobe regions in both hemispheres. Support vector machine (SVM), extreme learning machine (ELM), and cmcRVFL+ classifiers were employed for model training and validated using 10-fold cross-validation. The results demonstrated that employing ELM classifiers in conjunction with specific temporal lobe gray matter volume features led to a better identification of TLE. The classification accuracy was 92.79%, with an area under the curve (AUC) value of 0.8019. The method proposed in this study can significantly assist in the preoperative identification of TLE patients. By employing this method, TLE can be included in surgical criteria, which could alleviate patient symptoms and improve prognosis, thereby bearing substantial clinical significance.

In vivo γ-aminobutyric acid alterations as a biomarker of the therapeutic effect of MRI-negative temporal lobe epilepsy

In vivo γ-aminobutyric acid alterations as a biomarker of the therapeutic effect of MRI-negative temporal lobe epilepsy

Skull-base temporal encephalocele: Hidden cause of temporal lobe epilepsy.

In the present study patients with previously diagnosed MRI-negative temporal lobe epilepsy (TLE) on long-term video electroencephalography (VEEG) monitoring were re-evaluated with high resolution 3T MRI brain to look out for a skull base temporal lobe encephalocoele (TE). A total of 234 VEEGs were analyzed. TLE had been diagnosed in 104 patients based on semiology, ictal, interictal EEG data, and brain positron emission tomography (PET) studies. Of these, 99 patients had temporal lobe abnormality (78 had mesial temporal sclerosis, 8 had tumor, 3 had focal cortical dysplasia, and 10 had mixed pathology). Out of the five 1.5T MRI-negative TLE patients, two patients were diagnosed with TE on subsequent 3T MRI brain scans and one patient underwent electrocorticography-guided tailored resection for complete removal of epileptogenic tissue; with Engels class I seizure freedom at one year follow-up. We propose that TE should be carefully searched for, as a cause of refractory TLE, using high-resolution MRI sequences.

Distinguishing Patients with MRI-Negative Temporal Lobe Epilepsy from Normal Controls Based on Individual Morphological Brain Network.

Temporal Lobe Epilepsy (TLE) is the most common subtype of focal epilepsy and the most refractory to drug treatment. Roughly 30% of patients do not have easily identifiable structural abnormalities. In other words, MRI-negative TLE has normal MRI scans on visual inspection. Thus, MRI-negative TLE is a diagnostic and therapeutic challenge. In this study, we investigate the cortical morphological brain network to identify MRI-negative TLE. The 210 cortical ROIs based on the Brainnetome atlas were used to define the network nodes. The least absolute shrinkage and selection operator (LASSO) algorithm and Pearson correlation methods were used to calculate the inter-regional morphometric features vector correlation respectively. As a result, two types of networks were constructed. The topological characteristics of networks were calculated by graph theory. Then after, a two-stage feature selection strategy, including a two-sample t-test and support vector machine-based recursive feature elimination (SVM-RFE), was performed in feature selection. Finally, classification with support vector machine (SVM) and leave-one-out cross-validation (LOOCV) was employed for the training and evaluation of the classifiers. The performance of two constructed brain networks was compared in MRI-negative TLE classification. The results indicated that the LASSO algorithm achieved better performance than the Pearson pairwise correlation method. The LASSO algorithm provides a robust method of individual morphological network construction for distinguishing patients with MRI-negative TLE from normal controls.

γ-Aminobutyric acid as a biomarker of the lateralizing and monitoring drug effect in patients with magnetic resonance imaging-negative temporal lobe epilepsy.

Despite verifying proton magnetic resonance spectroscopy (1H-MRS) for focal localization in magnetic resonance imaging (MRI)-negative temporal lobe epilepsy (TLE), it is necessary to illustrate metabolic changes and screen for effective biomarkers for monitoring therapeutic effect. We used 1H-MRS to investigate the role of metabolic levels in MRI-negative TLE. Thirty-seven patients (n = 37, 14 women) and 20 healthy controls (n = 20, 11 women) were investigated by 1H-MRS. We compared the metabolite level changes in the epileptic and contralateral sides on the mesial temporal and dorsolateral prefrontal cortices and analyzed their association with clinical symptoms. γ-Aminobutyric acid (GABA) levels were significantly lower on the epileptic side (2.292 ± 0.890) than in the contralateral side (2.662 ± 0.742, p = 0.029*) in patients on the mesial temporal lobe. N-acetylaspartate (NAA) levels were significantly lower on the epileptic side (7.284 ± 1.314) than on the contralateral side (7.655 ± 1.549, p = 0.034*). NAA + N-acetylaspartylglutamate levels were significantly lower on the epileptic side (7.668 ± 1.406) than on the contralateral side (8.086 ± 1.675, p = 0.032*). Glutamate levels were significantly lower on the epileptic side (7.773 ± 1.428) than on the contralateral side (8.245 ± 1.616, p = 0.040*). Moreover, a significant negative correlation was found between GABA levels in the epileptic mesial temporal lobe and tonic-clonic seizure frequency (r = -0.338, p = 0.046*). γ-Aminobutyric acid (GABA) is a potential biomarker for lateralization and monitoring seizure frequency in MRI-negative TLE.

Static and temporal dynamic alteration of intrinsic brain activity in MRI-negative temporal lobe epilepsy

PurposeTo comprehensively explore the potential brain activity abnormalities affected by MRI-negative temporal lobe epilepsy (TLE) and to detect whether the changes were associated with cognition and help in the diagnosis or lateralization. MethodSix static intrinsic brain activity (IBA) indicators (ALFF, fALFF, ReHo, DC, GSCorr, VMHC) and their corresponding six temporal dynamic indicators in 39 unilateral MRI-negative TLE patients and 42 healthy volunteers were compared. Correlation analyses were performed between these indicators in areas displaying group differences, cognitive function, and epilepsy duration. ROC analyses were performed to test the diagnostic and lateralization ability of the IBA parameters. ResultsConsiderable overlap was present among the abnormal brain regions detected by different static and dynamic indicators, including (1) alteration of fALFF, Reho, DC, VMHC, dfALFF, dReHo, and dDC in the temporal neocortex (predominately ipsilateral to the epileptogenic foci); (2) decreased dGSCorr and dVMHC in the occipital lobe. Meanwhile, the ReHo and VMHC values in the temporal neocortex correlated with the cognition scores or epilepsy duration (P < 0.01). The ROC analysis results revealed moderate diagnosis or lateralization efficiency of several IBA indicators (fALFF, dfALFF, ReHo, DC, dDC, and VMHC). ConclusionThe abnormal condition of neuronal activity in the temporal neocortex, predominately lateralized to the epileptic side, was a crucial feature in patients with MRI-negative TLE and might offer diagnosis or lateralization information. The application of dynamic intrinsic brain activity indicators played a complementary role, further revealing the temporal variability decline of the occipital lobe in MRI-negative TLE patients.

Temporal encephaloceles and coexisting epileptogenic lesions.

This study was performed to identify coexisting structural lesions in patients with epilepsy and known temporal encephaloceles (TEs). Forty-seven structural magnetic resonance imaging (MRI) scans of patients with epilepsy and radiologically diagnosed TEs were retrospectively reviewed visually and using an automated postprocessing software, the Morphometric Analysis Program v2018 (MAP18), to depict additional subtle, potentially epileptogenic lesions in the 3D T1-weighted MRI data. All imaging findings were evaluated in the context of clinical and electroencephalographical findings. The study population consisted of 47 epilepsy patients (38.3% female, n=18). The median age at the time of the scan was 40 years (range 12-81 years). Twenty-one out of 47 MRI scans (44.7%) showed coexisting lesions in the initial MRI evaluation; in 38.3% (n=18) of patients, those lesions were considered probably epileptogenic. After postprocessing, probable epileptogenic lesions were identified in 53.2% (n=25) of patients. Malformations of cortical development had initially been reported in 17.0% (n=8) of patients with TEs, which increased to 38.3% (n=18) after postprocessing. TEs and other epileptogenic lesions were considered equally epileptogenic in 21.3% (n=10) of the cases in the initial MR reports and 25.5% (n=12) of the cases after postprocessing. Temporal encephaloceles are a potential cause of MRI-negative temporal lobe epilepsy. According to our data, TEs can occur with other lesions, suggesting that increased awareness is also required in patients with lesional epilepsy. TEs may not always be epileptogenic; hence, their occurrence with other structural pathologies may influence the presurgical evaluation and surgical approach. Finally, TEs can be associated with malformations of cortical development, which may indicate a common developmental etiology of those lesions.

Clinical characteristics of MRI-negative temporal lobe epilepsy.

To investigate the characteristics of patients with MRI-negative temporal lobe epilepsy (TLE) (1.5T brain MRI) in comparison with: (i) patients with hippocampal sclerosis (HS)-TLE; (ii) persons with non-HS structural TLE; and (iii) patients with dual pathology. This was a retrospective study. All patients with an electro-clinical diagnosis of TLE were studied at the outpatient epilepsy clinic at Shiraz University of Medical Sciences, Shiraz, Iran, from 2008 until 2020. Six hundred and forty-one patients were studied [273 (42.6%) HS, 154 (24.0%) non-HS structural TLE, 174 (27.1%) MRI-negative TLE, and 40 (6.2%) dual pathology]. The groups differed significantly. Important dissimilarities included: (i) compared with HS-TLE group, patients with MRI-negative TLE more often had a family history of epilepsy and less often had a history of febrile convulsion; (ii) compared with non-HS structural TLE group, patients with MRI-negative TLE more often had focal to bilateral tonic-clonic seizures, less often had focal seizures with impaired awareness, and more often had a family history of epilepsy; (iii) compared with the dual pathology group, patients with MRI-negative TLE less often were male and less often had a history of febrile convulsion. Patients with MRI-negative TLE are not a homogenous group of people and it is not necessarily a distinct entity from other forms of TLE either. With the emergence of advanced imaging technologies, the underlying pathologies of MRI-negative TLE may be revealed.

A Study of Spontaneous Brain Activity on Resting-State Functional Magnetic Resonance Imaging in Adults with MRI-Negative Temporal Lobe Epilepsy.

PurposePatients with magnetic resonance imaging (MRI)-negative temporal lobe epilepsy (TLE-N) represent an important subgroup of temporal lobe epilepsy (TLE). Here, we aimed to combine three voxel-based local brain area analysis methods of resting-state functional MRI (rs-fMRI), to examine the TLE-N patients’ resting brain function based on neural synchronization and intensity of local brain areas.MethodsThe study included 47 patients with TLE, including 28 cases of drug-controlled TLE (cTLE-N) and 19 cases of drug-resistant TLE-N (rTLE-N), as well as 30 participants in the healthy control (HC) group. To comprehensively assess the altered brain function associated with TLE-N patients, we analyzed three data-driven rs-fMRI algorithms for amplitude of low-frequency fluctuations (ALFF), fractional ALFF (fALFF) and regional homogeneity (ReHo).ResultsCompared to the HC group, the distribution of abnormal functional brain areas in cTLE-N patients was dominated by occipital lobe activation, as measured by increased fALFF values in the superior occipital gyrus (SOG) and increased ReHo values in the lingual gyrus (Lin), fusiform gyrus, and middle occipital gyrus. Patients with rTLE-N exhibited a diffuse distribution of abnormal functional brain areas, showing increased fALFF values in the SOG, Lin, superior temporal gyrus, and postcentral gyrus, and decreased fALFF values in the inferior frontal gyrus orbital, parahippocampal gyrus, and superior frontal gyrus orbital. The ReHo values were reduced in the orbital region of the middle frontal gyrus, the precuneus, and the parietal inferior angular gyrus; while ReHo values were elevated values in several frontal, temporal, occipital, and subcortical brain areas.ConclusionPatients with rTLE-N have local brain activity changes in the prefrontal limbic system and default model network dysfunction, while cTLE-N patients have local brain activity changes in the visual functional areas. Different epilepsy networks exist between cTLE-N and rTLE-N.

Seizure Duration and Spread Dynamics in MRI-Defined Subtypes of Temporal Lobe Epilepsy.

MRI and PET imaging enables subgroups of temporal lobe epilepsy (TLE) to be defined on the basis of structural pathology. Few studies have examined the variation in electroclinical seizure spread patterns based on imaging findings. We performed a retrospective cohort study to investigate the electroclinical differences among 3 specific groups of TLE: MRI-negative PET-positive TLE (MRI-negative TLE), temporal lobe lesion TLE (lesional TLE), and unilateral hippocampal sclerosis TLE (HS-TLE). Patients with an electroclinical diagnosis of TLE who had video-scalp EEG recordings of seizures were identified from the retrospective database of the Austin Comprehensive Epilepsy Program between 2005 and 2019. The cohort was further selected into the 3 defined groups based on imaging findings, using MRI and FDG-PET. Timings of clinical and electrographic seizure progression were measured, considering the onset, ipsilateral lobar spread, contralateral spread, and termination. Durations were compared between groups using linear mixed models with inclusion of demographic and clinical covariates. A total of 105 patients (137 seizures) were included, comprising 36 with MRI-negative TLE (54 seizures), 36 with lesional TLE (18 lateral vs 16 mesial lesions; 44 seizures), and 33 with HS-TLE (39 seizures). Seizure duration was similar between MRI-negative TLE and lesional TLE (mean 75.9 vs 71.7 seconds; p = 0.91). Further dividing lesional TLE into medial vs lateral temporal revealed no timing difference. However, the HS-TLE group had longer total seizure duration (114 seconds) compared with both MRI-negative TLE (p < 0.001) and lesional TLE (p < 0.001). Progression of electrographic spread also reflected this pattern, with involvement of extratemporal regions and then the contralateral hemisphere each taking significantly longer in HS-TLE. MRI-negative TLE appears electrographically similar to lesional TLE, whether mesial or lateral, in the duration of seizures and the timing of electrographic spread. Both appear electrographically different from HS-TLE, where propagation is slower, suggesting engagement of different epileptogenic networks or seizure suppression mechanisms. This study provides Class II evidence that the electroclinical features of seizures in HS-TLE are different than MRI-negative TLE and lesional TLE.

MRI-Based Machine Learning Prediction Framework to Lateralize Hippocampal Sclerosis in Patients With Temporal Lobe Epilepsy.

MRI fails to reveal hippocampal pathology in 30% to 50% of temporal lobe epilepsy (TLE) surgical candidates. To address this clinical challenge, we developed an automated MRI-based classifier that lateralizes the side of covert hippocampal pathology in TLE. We trained a surface-based linear discriminant classifier that uses T1-weighted (morphology) and T2-weighted and fluid-attenuated inversion recovery (FLAIR)/T1 (intensity) features. The classifier was trained on 60 patients with TLE (mean age 35.6 years, 58% female) with histologically verified hippocampal sclerosis (HS). Images were deemed to be MRI negative in 42% of cases on the basis of neuroradiologic reading (40% based on hippocampal volumetry). The predictive model automatically labeled patients as having left or right TLE. Lateralization accuracy was compared to electroclinical data, including side of surgery. Accuracy of the classifier was further assessed in 2 independent TLE cohorts with similar demographics and electroclinical characteristics (n = 57, 58% MRI negative). The overall lateralization accuracy was 93% (95% confidence interval 92%-94%), regardless of HS visibility. In MRI-negative TLE, the combination of T2 and FLAIR/T1 intensities provided the highest accuracy in both the training (84%, area under the curve [AUC] 0.95 ± 0.02) and validation (cohort 1 90%, AUC 0.99; cohort 2 76%, AUC 0.94) cohorts. This prediction model for TLE lateralization operates on readily available conventional MRI contrasts and offers gain in accuracy over visual radiologic assessment. The combined contribution of decreased T1- and increased T2-weighted intensities makes the synthetic FLAIR/T1 contrast particularly effective in MRI-negative HS, setting the basis for broad clinical translation. This study provides Class II evidence that in people with TLE and MRI-negative HS, an automated MRI-based classifier accurately determines the side of pathology.

Accurate lateralization and classification of MRI-negative 18F-FDG-PET-positive temporal lobe epilepsy using double inversion recovery and machine-learning

ObjectiveThe main objective of this study was to determine the ability of double inversion recovery (DIR) data coupled with machine-learning algorithms to distinguish normal individuals from epileptic subjects and to identify the laterality of the focus side in MRI-negative, PET-positive temporal lobe epilepsy (TLE) patients. Materials and methodsWe used whole-brain DIR data as the input features with which to train a linear support-vector machine model in 63 participants who underwent high-resolution structural MRI and DIR scans. The subjects included 20 left TLE patients, 19 right TLE patients, and 24 healthy controls (HCs). ResultsUsing the DIR data, we achieved a robust accuracy of 87.30% for discriminating among the left TLE, right TLE, and HC groups as well as 84.61%, 97.72%, and 93.02% prediction accuracies for distinguishing left TLE from right TLE, HC from right TLE, and HC from left TLE, respectively. InterpretationOur experimental results suggest that DIR data coupled with machine-learning algorithms provide a promising approach to identifying MRI-negative TLE patients, especially when fluorodeoxyglucose-PET is not available.

Extrahippocampal Radiomics Analysis Can Potentially Identify Laterality in Patients With MRI-Negative Temporal Lobe Epilepsy.

Objective: The objective of the study was to investigate whether radiomics features of extrahippocampal regions differ between patients with epilepsy and healthy controls, and whether any differences can identify patients with magnetic resonance imaging (MRI)-negative temporal lobe epilepsy (TLE).Methods: Data from 36 patients with hippocampal sclerosis (HS) and 50 healthy controls were used to construct a radiomics model. A total of 1,618 radiomics features from the affected hippocampal and extrahippocampal regions were compared with features from healthy controls and the unaffected side of patients. Using a stepwise selection method with a univariate t-test and elastic net penalization, significant predictors for identifying TLE were separately selected for the hippocampus (H+) and extrahippocampal region (H–). Each model was independently validated with an internal set of MRI-negative adult TLE patients (n = 22) and pediatric validation cohort with MRI-negative TLE (n = 20) from another tertiary center; diagnostic performance was calculated using area under the curve (AUC) of the receiver-operating-characteristic curve analysis.Results: Forty-eight significant H+ radiomic features and 99 significant H– radiomic features were selected from the affected side of patients and used to create a hippocampus model and an extrahippocampal model, respectively. Texture features were the most frequently selected feature. Training set showed slightly higher accuracy between hippocampal (AUC = 0.99) and extrahippocampal model (AUC = 0.97). In the internal validation and external validation sets, the extrahippocampal model (AUC = 0.80 and 0.92, respectively) showed higher diagnostic performance for identifying the affected side of patients than the hippocampus model (AUC = 0.67 and 0.69).Significance: Radiomics revealed extrahippocampal abnormality in the affected side of patients with TLE and could potentially help to identify MRI-negative TLE.Classification of Evidence: Class IV Criteria for Rating Diagnostic Accuracy Studies.

Evaluation of Brain Network Properties in Patients with MRI-Negative Temporal Lobe Epilepsy: An MEG Study.

Abnormal functional brain networks of temporal lobe epilepsy (TLE) patients with structural abnormalities may partially reflect structural lesions rather than either TLE per se or functional compensatory processes. In this study, we sought to investigate the brain-network properties of intractable TLE patients apart from the effects of structural abnormalities. The brain network properties of 20 left and 23 right MRI-negative TLE patients and 22 healthy controls were evaluated using magnetoencephalographic recordings in six main frequency bands. A slowing of oscillatory brain activity was observed for the left or right TLE group vs. healthy controls. The TLE groups presented significantly increased functional connectivity in the delta, theta, lower alpha and beta bands, and significantly greater values in the normalized clustering coefficient and path length, and significantly smaller values in the weighted small-world measure in the theta band when compared to healthy controls. Alterations in global and regional band powers can be attributed to spectral slowing in TLE patients. The brain networks of TLE patients displayed abnormally high synchronization in multi-frequency bands and shifted toward a more regular architecture with worse network efficiency in the theta band. Without the contamination of structural lesions, these significant findings can be helpful for better understanding of the pathophysiological mechanism of TLE. The theta band can be considered as a preferred frequency band for investigating the brain-network dysfunction of MRI-negative intractable TLE patients.

Αlpha 5 subunit-containing GABAA receptors in temporal lobe epilepsy with normal MRI.

GABAA receptors containing the α5 subunit mediate tonic inhibition and are widely expressed in the limbic system. In animals, activation of α5-containing receptors impairs hippocampus-dependent memory. Temporal lobe epilepsy is associated with memory impairments related to neuron loss and other changes. The less selective PET ligand [11C]flumazenil has revealed reductions in GABAA receptors. The hypothesis that α5 subunit receptor alterations are present in temporal lobe epilepsy and could contribute to impaired memory is untested. We compared α5 subunit availability between individuals with temporal lobe epilepsy and normal structural MRI (‘MRI-negative’) and healthy controls, and interrogated the relationship between α5 subunit availability and episodic memory performance, in a cross-sectional study. Twenty-three healthy male controls (median ± interquartile age 49 ± 13 years) and 11 individuals with MRI-negative temporal lobe epilepsy (seven males; 40 ± 8) had a 90-min PET scan after bolus injection of [11C]Ro15-4513, with arterial blood sampling and metabolite correction. All those with epilepsy and six controls completed the Adult Memory and Information Processing Battery on the scanning day. ‘Bandpass’ exponential spectral analyses were used to calculate volumes of distribution separately for the fast component [VF; dominated by signal from α1 (α2, α3)-containing receptors] and the slow component (VS; dominated by signal from α5-containing receptors). We made voxel-by-voxel comparisons between: the epilepsy and control groups; each individual case versus the controls. We obtained parametric maps of VF and VS measures from a single bolus injection of [11C]Ro15-4513. The epilepsy group had higher VS in anterior medial and lateral aspects of the temporal lobes, the anterior cingulate gyri, the presumed area tempestas (piriform cortex) and the insulae, in addition to increases of ∼24% and ∼26% in the ipsilateral and contralateral hippocampal areas (P < 0.004). This was associated with reduced VF:VS ratios within the same areas (P < 0.009). Comparisons of VS for each individual with epilepsy versus controls did not consistently lateralize the epileptogenic lobe. Memory scores were significantly lower in the epilepsy group than in controls (mean ± standard deviation −0.4 ± 1.0 versus 0.7 ± 0.3; P = 0.02). In individuals with epilepsy, hippocampal VS did not correlate with memory performance on the Adult Memory and Information Processing Battery. They had reduced VF in the hippocampal area, which was significant ipsilaterally (P = 0.03), as expected from [11C]flumazenil studies. We found increased tonic inhibitory neurotransmission in our cohort of MRI-negative temporal lobe epilepsy who also had co-morbid memory impairments. Our findings are consistent with a subunit shift from α1/2/3 to α5 in MRI-negative temporal lobe epilepsy.

FLAIR-Wise Machine-Learning Classification and Lateralization of MRI-Negative 18F-FDG PET-Positive Temporal Lobe Epilepsy.

Objective: In this study, we investigated the ability of fluid-attenuated inversion recovery (FLAIR) data coupled with machine-leaning algorithms to differentiate normal and epileptic brains and identify the laterality of focus side in temporal lobe epilepsy (TLE) patients with visually negative MRI.Materials and Methods: The MRI data were acquired on a 3-T MR system (Philips Medical Systems). After pre-proceeding stage, the FLAIR signal intensities were extracted from specific regions of interest, such as the amygdala, cerebral white matter, inferior temporal gyrus, middle temporal gyrus, parahippocampal gyrus, superior temporal gyrus, and temporal pole, and fed into a classification framework followed by a support vector machine as classifier. The proposed lateralization framework was assessed in a group of MRI-negative unilateral TLE patients (N = 42; 23 left TLE and 19 right TLE) and 34 healthy controls (HCs) based on a leave-one-out cross-validation strategy.Results: Using the FLAIR data, we obtained a 75% accuracy for discriminating the three groups, as well as 87.71, 83.01, and 76.19% accuracies for HC/right TLE, HC/left TLE, and left TLE/right TLE tasks, respectively.Interpretation: The experimental results show that FLAIR data can potentially be considered an informative biomarker for improving the pre-surgical diagnostic confidence in patients with MRI-negative TLE.

Pattern analysis of glucose metabolic brain data for lateralization of MRI-negative temporal lobe epilepsy

In this paper, we assessed the reliability of glucose metabolic brain data for identifying lateralization of magnetic resonance imaging (MRI)-negative temporal lobe epilepsy (TLE) patients. We designed and developed an efficacious and automatic metabolic-wise lateralization framework. The proposed lateralization framework comprises three main systematic levels. In the first stage of our investigation, we pre-processed interictal fluorodeoxyglucose positron emission tomography images to extract glucose metabolic brain data. In the second stage, we used a voxel selection method involving a feature-ranking strategy to select the most discriminative metabolic voxels. Finally, we used a support vector machine followed by a 10-fold cross-validation strategy to assess the proposed lateralization framework in 27 patients with right MRI-negative TLE and 29 patients with left MRI-negative TLE. The proposed lateralization framework achieved an excellent accuracy of 96.43 % concordance with experienced PET interpreter. Thus, we show that pattern analysis of glucose metabolic brain data can accurately lateralize MRI-negative TLE patients in the clinical setting.

Interactions between in vivo neuronal-glial markers, side of hippocampal sclerosis, and pharmacoresponse in temporal lobe epilepsy.

To evaluate the interactions of metabolic neuronal-glial changes with the presence and hemispheric-side of hippocampal sclerosis (HS) and its potential role in predicting pharmacoresistance in temporal lobe epilepsy (TLE). We included structural magnetic resonance imaging (MRI) and proton magnetic resonance spectroscopy (1 H-MRS) metabolic data for 91 patients with unilateral TLE and 50 healthy controls. We measured the values of total N-acetyl aspartate/total creatine (tNAA/tCr), glutamate/tCr (Glu/tCr), and myo-inositol/tCr (mIns/tCr). To assess the influence of the pharmacoresponse and hemispheric-side of HS on metabolic data, the relationship between clinical and MRI data, and the predictive value of NAA/Cr, we used analysis of variance/covariance and built a logistic regression model. We used bootstrap simulations to evaluate reproducibility. Bilateral tNAA/tCr reduction was associated with pharmacoresistance and with left HS, a decrease of Glu/tCr ipsilateral to the seizure focus was associated with pharmacoresistance, and ipsilateral mIns/tCr increase was related to pharmacoresistance and the presence of left HS. The logistic regression model containing clinical and 1 H-MRS data discriminated pharmacoresistance (area under the curve [AUC]=0.78). However, the reduction of tNAA/tCr was the main predictor, with the odds 2.48 greater for pharmacoresistance. Our study revealed a spectrum of neuronal-glial changes in TLE, which was associated with pharmacoresistance, being more severe in left-sided HS and less severe in MRI-negative TLE. These noninvasive, in vivo biomarkers provide valuable additional information about the interhemispheric differences in metabolic dysfunction, seizure burden, and HS, and may help to predict pharmacoresistance.

Reassessing the impact of intraoperative electrocorticography on postoperative outcome of patients undergoing standard temporal lobectomy for MRI-negative temporal lobe epilepsy.

Almost 30% of the patients with suspected temporal lobe epilepsy (TLE) have normal results on MRI. Success rates for resection of MRI-negative TLE are less favorable, ranging from 36% to 76%. Herein the authors describe the impact of intraoperative electrocorticography (ECoG) augmented by opioid activation and its effect on postoperative seizure outcome. Adult and pediatric patients with medically resistant MRI-negative TLE who underwent standardized ECoG at the time of their elective anterior temporal lobectomy (ATL) with amygdalohippocampectomy between 1990 and 2016 were included in this study. Seizure recurrence comprised the primary outcome of interest and was assessed using Kaplan-Meier and multivariable Cox regression analysis plots based on distribution of interictal epileptiform discharges (IEDs) recorded on scalp electroencephalography, baseline and opioid-induced IEDs on ECoG, and extent of resection. Of the 1144 ATLs performed at the authors' institution between 1990 and 2016, 127 (11.1%) patients (81 females) with MRI-negative TLE were eligible for this study. Patients with complete resection of tissue generating IED recorded on intraoperative ECoG were less likely to have seizure recurrence compared to those with incomplete resection on univariate analysis (p < 0.05). No difference was found in seizure recurrence between patients with bilateral independent IEDs and unilateral IEDs (p = 0.15), presence or absence of opioid-induced epileptiform activation (p = 0.61), or completeness of resection of tissue with opioid-induced IEDs on intraoperative ECoG (p = 0.41). The authors found that incomplete resection of IED-generating tissue on intraoperative ECoG was associated with an increased chance of seizure recurrence. However, they found that induction of epileptiform activity with intraoperative opioid activation did not provide useful intraoperative data predictive of improving operative results for temporal lobectomy in MRI-negative 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.