Neocortical thinning in "benign" mesial temporal lobe epilepsy

May anti-seizure medications alter brain structure in temporal lobe epilepsy? A prospective study

Mild mesial temporal lobe epilepsy (MTLE) patients may remain untreated for a considerable time after disease onset or achieve seizure control with a single anti-seizures medication (ASM). Thus, they represent an optimal population to investigate whether ASMs might have influence on brain structure. We consecutively enrolled 56 mild MTLE patients (22/56 untreated, 34/56 on-monotherapy) and 58 healthy controls, matched for age and gender. All subjects underwent 3T-brain MRI, using FreeSurfer for automated morphometry. Differences in gray matter were assessed using one-way Analysis of Covariance (ANCOVA), adjusting for age, disease duration and intracranial volume. No significant change was observed between treated and untreated patients. We observed a significant reduction in cortical thickness of left inferior parietal, inferior temporal, middle temporal gyri, and right inferior parietal gyrus, temporal pole in monotherapy patients compared to healthy controls, as well as an increase in left isthmus of cingulate gyrus in untreated MTLE subjects compared to controls. Surface and subcortical volumes analysis revealed no differences among groups. Our study demonstrated no substantial morphological abnormalities between untreated mild MTLE patients and those undergoing monotherapy. Although exploratory, these results may reassure about safety of commonly used drugs and their marginal role in influencing neuroimaging results. PLAIN LANGUAGE SUMMARY: This study investigated the following question: can medications against epileptic seizures have an effect on brain structure in mild mesial temporal lobe? Preliminary results from our analyses suggest not, as we did not find any difference in brain gray matter between untreated patients and those treated with a single anti-seizures medication. On the other hand, epilepsy patients presented cortical thinning compared to healthy controls in several regions of the temporal and parietal lobes, in line with previous studies investigating the disease.

Altered spread of waves of activities at large scale is influenced by cortical thickness organization in temporal lobe epilepsy: a magnetic resonance imaging-high-density electroencephalography study

Temporal lobe epilepsy is a brain network disorder characterized by alterations at both the structural and the functional levels. It remains unclear how structure and function are related and whether this has any clinical relevance. In the present work, we adopted a novel methodological approach investigating how network structural features influence the large-scale dynamics. The functional network was defined by the spatio-temporal spreading of aperiodic bursts of activations (neuronal avalanches), as observed utilizing high-density electroencephalography in patients with temporal lobe epilepsy. The structural network was modelled as the region-based thickness covariance. Loosely speaking, we quantified the similarity of the cortical thickness of any two brain regions, both across groups and at the individual level, the latter utilizing a novel approach to define the subject-wise structural covariance network. In order to compare the structural and functional networks (at the nodal level), we studied the correlation between the probability that a wave of activity would propagate from a source to a target region and the similarity of the source region thickness as compared with other target brain regions. Building on the recent evidence that large-waves of activities pathologically spread through the epileptogenic network in temporal lobe epilepsy, also during resting state, we hypothesize that the structural cortical organization might influence such altered spatio-temporal dynamics. We observed a stable cluster of structure-function correlation in the bilateral limbic areas across subjects, highlighting group-specific features for left, right and bilateral temporal epilepsy. The involvement of contralateral areas was observed in unilateral temporal lobe epilepsy. We showed that in temporal lobe epilepsy, alterations of structural and functional networks pair in the regions where seizures propagate and are linked to disease severity. In this study, we leveraged on a well-defined model of neurological disease and pushed forward personalization approaches potentially useful in clinical practice. Finally, the methods developed here could be exploited to investigate the relationship between structure-function networks at subject level in other neurological conditions.

Interpretable deep learning-based hippocampal sclerosis classification

OBJECTIVE

To evaluate the performance of a deep learning model for hippocampal sclerosis classification on the clinical dataset and suggest plausible visual interpretation for the model prediction.

METHODS

T2-weighted oblique coronal images of the brain MRI epilepsy protocol performed on patients were used. The training set included 320 participants with 160 no, 100 left and 60 right hippocampal sclerosis, and cross-validation was implemented. The test set consisted of 302 participants with 252 no, 25 left and 25 right hippocampal sclerosis. As the test set was imbalanced, we took an average of the accuracy achieved within each group to measure a balanced accuracy for multiclass and binary classifications. The dataset was composed to include not only healthy participants but also participants with abnormalities besides hippocampal sclerosis in the control group. We visualized the reasons for the model prediction using the layer-wise relevance propagation method.

RESULTS

When evaluated on the validation of the training set, we achieved multiclass and binary classification accuracy of 87.5% and 88.8% from the voting ensemble of six models. Evaluated on the test sets, we achieved multiclass and binary classification accuracy of 91.5% and 89.76%. The distinctly sparse visual interpretations were provided for each individual participant and group to suggest the contribution of each input voxel to the prediction on the MRI.

SIGNIFICANCE

The current interpretable deep learning-based model is promising for adapting effectively to clinical settings by utilizing commonly used data, such as MRI, with realistic abnormalities faced by neurologists to support the diagnosis of hippocampal sclerosis with plausible visual interpretation.

Resting-State MEG Source Space Network Metrics Associated with the Duration of Temporal Lobe Epilepsy

To evaluate the relationship between the network metrics of 68 brain regions and duration of temporal lobe epilepsy (TLE). Magnetoencephalography (MEG) data from 53 patients with TLE (28 left TLE, 25 right TLE) were recorded between seizures at resting state and analyzed in six frequency bands: delta (0.1-4 Hz), theta (4-8 Hz), lower alpha (8-10 Hz), upper alpha (10-13 Hz), beta (13-30 Hz), and lower gamma (30-48 Hz). Three local network metrics, betweenness centrality, nodal degree, and nodal efficiency, were chosen to analyze the functional brain network. In Left, Right, and All (Left + Right) TLE groups, different metrics provide significant positive or negative correlations with the duration of TLE, in different frequency bands, and in different brain regions. In the Left TLE group, significant correlation between TLE duration and metric exists in the delta, beta, or lower gamma band, with network betweenness centrality, nodal degree, or nodal efficiency, in left caudal middle frontal, left middle temporal, or left supramarginal. In the Right TLE group, significant correlation exists in lower gamma or delta band, with nodal degree, or nodal efficiency, in left precuneus or right temporal pole. In the All TLE group, the significant correlation exists in delta, theta, beta, or lower gamma band, with nodal degree, or betweenness centrality, in either left or right hemisphere. Network metrics for some specific brain regions changed in patients with TLE as the duration of their TLE increased. Further researching these changes may be important for studying the pathogenesis, presurgical evaluation, and clinical treatment of long-term TLE.

How cerebral cortex protects itself from interictal spikes: The alpha/beta inhibition mechanism

Interactions between interictal epileptiform discharges (IEDs) and distant cortical regions subserve potential effects on cognition of patients with focal epilepsy. We hypothesize that "healthy" brain areas at a distance from the epileptic focus may respond to the interference of IEDs by generating inhibitory alpha and beta oscillations. We predict that more prominent alpha-beta oscillations can be found in patients with less impaired neurocognitive profile. We performed a source imaging magnetoencephalography study, including 41 focal epilepsy patients: 21 with frontal lobe epilepsy (FLE) and 20 with mesial temporal lobe epilepsy. We investigated the effect of anterior (i.e., frontal and temporal) IEDs on the oscillatory pattern over posterior head regions. We compared cortical oscillations (5-80 Hz) temporally linked to 3,749 IEDs (1,945 frontal and 1,803 temporal) versus an equal number of IED-free segments. We correlated results from IED triggered oscillations to global neurocognitive performance. Only frontal IEDs triggered alpha-beta oscillations over posterior head regions. IEDs with higher amplitude triggered alpha-beta oscillations of higher magnitude. The intensity of posterior head region alpha-beta oscillations significantly correlated with a better neuropsychological profile. Our study demonstrated that cerebral cortex protects itself from IEDs with generation of inhibitory alpha-beta oscillations at distant cortical regions. The association of more prominent oscillations with a better cognitive status suggests that this mechanism might play a role in determining the cognitive resilience in patients with FLE.

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.

Temporal and extratemporal atrophic manifestation of temporal lobe epilepsy using voxel-based morphometry and corticometry: clinical application in lateralization of epileptogenic zone

BACKGROUND

Advances in MRI acquisition and data processing have become important for revealing brain structural changes. Previous studies have reported widespread structural brain abnormalities and cortical thinning in patients with temporal lobe epilepsy (TLE), as the most common form of focal epilepsy.

METHODS

In this research, healthy control cases (n = 20) and patients with left TLE (n = 19) and right TLE (n = 14) were recruited, all underwent 3.0 T MRI with magnetization-prepared rapid gradient echo sequence to acquire T1-weighted images. Morphometric alterations in gray matter were identified using voxel-based morphometry (VBM). Volumetric alterations in subcortical structures and cortical thinning were also determined.

RESULTS

Patients with left TLE demonstrated more prevailing and widespread changes in subcortical volumes and cortical thickness than right TLE, mainly in the left hemisphere, compared to the healthy group. Both VBM analysis and subcortical volumetry detected significant hippocampal atrophy in ipsilateral compared to contralateral side in TLE group. In addition to hippocampus, subcortical volumetry found the thalamus and pallidum bilaterally vulnerable to the TLE. Furthermore, the TLE patients underwent cortical thinning beyond the temporal lobe, affecting gray matter cortices in frontal, parietal, and occipital lobes in the majority of patients, more prevalently for left TLE cases. Exploiting volume changes in individual patients in the hippocampus alone led to 63.6% sensitivity and 100% specificity for lateralization of TLE.

CONCLUSION

Alteration of gray matter volumes in subcortical regions and neocortical temporal structures and also cortical gray matter thickness were evidenced as common effects of epileptogenicity, as manifested by the majority of cases in this study.

The ENIGMA-Epilepsy working group: Mapping disease from large data sets

Epilepsy is a common and serious neurological disorder, with many different constituent conditions characterized by their electro clinical, imaging, and genetic features. MRI has been fundamental in advancing our understanding of brain processes in the epilepsies. Smaller-scale studies have identified many interesting imaging phenomena, with implications both for understanding pathophysiology and improving clinical care. Through the infrastructure and concepts now well-established by the ENIGMA Consortium, ENIGMA-Epilepsy was established to strengthen epilepsy neuroscience by greatly increasing sample sizes, leveraging ideas and methods established in other ENIGMA projects, and generating a body of collaborating scientists and clinicians to drive forward robust research. Here we review published, current, and future projects, that include structural MRI, diffusion tensor imaging (DTI), and resting state functional MRI (rsfMRI), and that employ advanced methods including structural covariance, and event-based modeling analysis. We explore age of onset- and duration-related features, as well as phenomena-specific work focusing on particular epilepsy syndromes or phenotypes, multimodal analyses focused on understanding the biology of disease progression, and deep learning approaches. We encourage groups who may be interested in participating to make contact to further grow and develop ENIGMA-Epilepsy.

Microstructural imaging in temporal lobe epilepsy: Diffusion imaging changes relate to reduced neurite density

PURPOSE

Previous imaging studies in patients with refractory temporal lobe epilepsy (TLE) have examined the spatial distribution of changes in imaging parameters such as diffusion tensor imaging (DTI) metrics and cortical thickness. Multi-compartment models offer greater specificity with parameters more directly related to known changes in TLE such as altered neuronal density and myelination. We studied the spatial distribution of conventional and novel metrics including neurite density derived from NODDI (Neurite Orientation Dispersion and Density Imaging) and myelin water fraction (MWF) derived from mcDESPOT (Multi-Compartment Driven Equilibrium Single Pulse Observation of T1/T2)] to infer the underlying neurobiology of changes in conventional metrics.

METHODS

20 patients with TLE and 20 matched controls underwent magnetic resonance imaging including a volumetric T1-weighted sequence, multi-shell diffusion from which DTI and NODDI metrics were derived and a protocol suitable for mcDESPOT fitting. Models of the grey matter-white matter and grey matter-CSF surfaces were automatically generated from the T1-weighted MRI. Conventional diffusion and novel metrics of neurite density and MWF were sampled from intracortical grey matter and subcortical white matter surfaces and cortical thickness was measured.

RESULTS

In intracortical grey matter, diffusivity was increased in the ipsilateral temporal and frontopolar cortices with more restricted areas of reduced neurite density. Diffusivity increases were largely related to reductions in neurite density, and to a lesser extent CSF partial volume effects, but not MWF. In subcortical white matter, widespread bilateral reductions in fractional anisotropy and increases in radial diffusivity were seen. These were primarily related to reduced neurite density, with an additional relationship to reduced MWF in the temporal pole and anterolateral temporal neocortex. Changes were greater with increasing epilepsy duration. Bilaterally reduced cortical thickness in the mesial temporal lobe and centroparietal cortices was unrelated to neurite density and MWF.

CONCLUSIONS

Diffusivity changes in grey and white matter are primarily related to reduced neurite density with an additional relationship to reduced MWF in the temporal pole. Neurite density may represent a more sensitive and specific biomarker of progressive neuronal damage in refractory TLE that deserves further study.

Aberrant functional connectivity of the cingulate subregions in right-sided temporal lobe epilepsy

Patients with temporal lobe epilepsy (TLE) have been indicated to exhibit abnormal resting-state functional connectivity (rsFC) of the cingulate cortex. However, it has remained elusive whether cingulate subregions show different connectivity patterns in TLE. The present study aimed to investigate the differences in rsFC of each cingulate subregion between patients with right-sided TLE (rTLE) and healthy controls (HCs), as well as their association with executive control performance in rTLE. A total of 27 patients with rTLE and 20 age-, sex- and education-matched healthy controls were recruited and all participants underwent resting-state functional MRI and an attention network test for the assessment executive control function. In each hemisphere, the cingulate gyrus (CG) was divided into CG-1 (dorsal area 23; A23d), CG-2 (rostroventral area 24; A24rv), CG-3 (pregenual area 32; A32p), CG-4 (ventral area 23; A23v), CG-5 (caudodorsal area 24; A24cd), CG-6 (caudal area 24; A23c) and CG-7 (subgenual area 32; A32sg). Pearson's correlation analysis was performed to assess the correlation between the altered FCs of the cingulate subregions and clinical variables. In patients with rTLE, the majority of the cingulate subregions exhibited decreased rsFC; this was primarily restricted to the right CG-2, the bilateral CG-6 and the bilateral CG-7. Increased rsFC was only detected in rTLE restricted to the left CG-1. Impairments in executive control efficiency were identified in patients with rTLE in comparison with the HCs. Significant alterations in rsFC between the cingulate subregion and the brain regions were mostly decreased (and some slightly increased), suggesting that FC may potentially have a left-side advantage in patients with rTLE. FC variations of the cingulate subregions were indicated to be specific to rTLE. In addition, increased connectivity in the left CG-1 and left superior frontal gyrus were negatively correlated with executive control performance, suggesting a compensatory mechanism on executive control deficits in pathological conditions. This information on differentially altered FC patterns of the cingulate subregions may provide a deeper understanding of the complex neurological mechanisms and executive control dysfunctions underlying rTLE.

Machine learning for detecting mesial temporal lobe epilepsy by structural and functional neuroimaging

Mesial temporal lobe epilepsy (mTLE), the most common type of focal epilepsy, is associated with functional and structural brain alterations. Machine learning (ML) techniques have been successfully used in discriminating mTLE from healthy controls. However, either functional or structural neuroimaging data are mostly used separately as input, and the opportunity to combine both has not been exploited yet. We conducted a multimodal ML study based on functional and structural neuroimaging measures. We enrolled 37 patients with left mTLE, 37 patients with right mTLE, and 74 healthy controls and trained a support vector ML model to distinguish them by using each measure and the combinations of the measures. For each single measure, we obtained a mean accuracy of 74% and 69% for discriminating left mTLE and right mTLE from controls, respectively, and 64% when all patients were combined. We achieved an accuracy of 78% by integrating functional data and 79% by integrating structural data for left mTLE, and the highest accuracy of 84% was obtained when all functional and structural measures were combined. These findings suggest that combining multimodal measures within a single model is a promising direction for improving the classification of individual patients with mTLE.

Disruption and lateralization of cerebellar-cerebral functional networks in right temporal lobe epilepsy: A resting-state fMRI study

Numerous studies have highlighted important roles for the cerebellum in cognition and movement, based on numerous fiber connections between the cerebrum and cerebellum. Abnormal cerebellar activity caused by epileptic discharges has been reported in previous studies, but researchers have not clearly determined whether aberrant cerebellar activity contributes to the disruption of the cerebellar-cerebral networks in right temporal lobe epilepsy (rTLE). Here, thirty patients with rTLE and 30 age- and sex-matched healthy controls (HCs) were recruited. All participants underwent the Attention Network Test (ANT) and resting-state functional magnetic resonance imaging (rs-fMRI) scanning. Cerebellar functional networks were extracted and analyzed by defining seeds in the cerebellum. A correlation analysis was performed between attentional performance and voxels that showed differences in functional connectivity (FC) in patients compared with HCs. Relative to HCs, patients exhibited significantly decreased FC in the dentate nucleus (DN) network (right DN with the left postcentral gyrus, left precentral gyrus, left cuneus, and left calcarine gyrus) and motor network (right cerebellar lobule V with the right putamen) and increased FC in the executive control network (right cerebellar crus I with the right inferior parietal lobule). Alerting, orienting, and executive control performances were impaired in patients with rTLE. Furthermore, the executive control effect was significantly correlated with aberrant FC strength between the right DN and the left precentral/postcentral gyrus. Our findings highlight that the disrupted cerebellar-cerebral functional network ipsilateral to the epileptogenic focus causes both impairments in and compensatory effects on attentional deficits in patients with rTLE. These findings contribute to our understanding of the cerebellar damage caused by epileptic discharges and the corresponding effect on attentional performance.

Structural brain abnormalities in the common epilepsies assessed in a worldwide ENIGMA study

Progressive functional decline in the epilepsies is largely unexplained. We formed the ENIGMA-Epilepsy consortium to understand factors that influence brain measures in epilepsy, pooling data from 24 research centres in 14 countries across Europe, North and South America, Asia, and Australia. Structural brain measures were extracted from MRI brain scans across 2149 individuals with epilepsy, divided into four epilepsy subgroups including idiopathic generalized epilepsies (n =367), mesial temporal lobe epilepsies with hippocampal sclerosis (MTLE; left, n = 415; right, n = 339), and all other epilepsies in aggregate (n = 1026), and compared to 1727 matched healthy controls. We ranked brain structures in order of greatest differences between patients and controls, by meta-analysing effect sizes across 16 subcortical and 68 cortical brain regions. We also tested effects of duration of disease, age at onset, and age-by-diagnosis interactions on structural measures. We observed widespread patterns of altered subcortical volume and reduced cortical grey matter thickness. Compared to controls, all epilepsy groups showed lower volume in the right thalamus (Cohen’s d = −0.24 to −0.73; P < 1.49 × 10⁻⁴), and lower thickness in the precentral gyri bilaterally (d = −0.34 to −0.52; P < 4.31 × 10⁻⁶). Both MTLE subgroups showed profound volume reduction in the ipsilateral hippocampus (d = −1.73 to −1.91, P < 1.4 × 10⁻¹⁹), and lower thickness in extrahippocampal cortical regions, including the precentral and paracentral gyri, compared to controls (d = −0.36 to −0.52; P < 1.49 × 10⁻⁴). Thickness differences of the ipsilateral temporopolar, parahippocampal, entorhinal, and fusiform gyri, contralateral pars triangularis, and bilateral precuneus, superior frontal and caudal middle frontal gyri were observed in left, but not right, MTLE (d = −0.29 to −0.54; P < 1.49 × 10⁻⁴). Contrastingly, thickness differences of the ipsilateral pars opercularis, and contralateral transverse temporal gyrus, were observed in right, but not left, MTLE (d = −0.27 to −0.51; P < 1.49 × 10⁻⁴). Lower subcortical volume and cortical thickness associated with a longer duration of epilepsy in the all-epilepsies, all-other-epilepsies, and right MTLE groups (beta, b < −0.0018; P < 1.49 × 10⁻⁴). In the largest neuroimaging study of epilepsy to date, we provide information on the common epilepsies that could not be realistically acquired in any other way. Our study provides a robust ranking of brain measures that can be further targeted for study in genetic and neuropathological studies. This worldwide initiative identifies patterns of shared grey matter reduction across epilepsy syndromes, and distinctive abnormalities between epilepsy syndromes, which inform our understanding of epilepsy as a network disorder, and indicate that certain epilepsy syndromes involve more widespread structural compromise than previously assumed.

Normal cerebral cortical thickness in first-degree relatives of temporal lobe epilepsy patients

Objective

To examine cerebral cortex thickness in asymptomatic first-degree relatives of patients with mesial temporal lobe epilepsy (MTLE).

Methods

We investigated 127 asymptomatic first-degree relatives of patients with MTLE due to hippocampal sclerosis (HS) (mean age ± SD = 39.4 ± 13 years) and 203 healthy control individuals (mean age ± SD = 36.0 ± 11 years). Participants underwent a comprehensive clinical evaluation and structural brain MRI at 3 study sites. Images were processed simultaneously at each site using a surface-based morphometry method to quantify global brain measures, hippocampal volumes, and cerebral cortical thickness. Differences in brain measures between relatives of patients and controls were examined using generalized models, while controlling for relevant covariates, including age and sex.

Results

None of the asymptomatic first-degree relatives of MTLE + HS patients showed evidence of HS on qualitative image assessments. Compared to the healthy controls, the asymptomatic relatives of patients displayed no significant differences in intracranial volume, average hemispheric surface area, or hippocampal volume. Similarly, no significant cerebral cortical thinning was identified in the relatives of patients. This was consistent across the 3 cohorts.

Conclusion

Lack of cortical thickness changes in the asymptomatic relatives of patients indicates that the previously characterized MTLE + HS-related cortical thinning is not heritable, and is likely driven by disease-related factors. This finding therefore argues for early and aggressive intervention in patients with medically intractable epilepsy.

Automated detection of focal cortical dysplasia type II with surface-based magnetic resonance imaging postprocessing and machine learning

OBJECTIVE

Focal cortical dysplasia (FCD) is a major pathology in patients undergoing surgical resection to treat pharmacoresistant epilepsy. Magnetic resonance imaging (MRI) postprocessing methods may provide essential help for detection of FCD. In this study, we utilized surface-based MRI morphometry and machine learning for automated lesion detection in a mixed cohort of patients with FCD type II from 3 different epilepsy centers.

METHODS

Sixty-one patients with pharmacoresistant epilepsy and histologically proven FCD type II were included in the study. The patients had been evaluated at 3 different epilepsy centers using 3 different MRI scanners. T1-volumetric sequence was used for postprocessing. A normal database was constructed with 120 healthy controls. We also included 35 healthy test controls and 15 disease test controls with histologically confirmed hippocampal sclerosis to assess specificity. Features were calculated and incorporated into a nonlinear neural network classifier, which was trained to identify lesional cluster. We optimized the threshold of the output probability map from the classifier by performing receiver operating characteristic (ROC) analyses. Success of detection was defined by overlap between the final cluster and the manual labeling. Performance was evaluated using k-fold cross-validation.

RESULTS

The threshold of 0.9 showed optimal sensitivity of 73.7% and specificity of 90.0%. The area under the curve for the ROC analysis was 0.75, which suggests a discriminative classifier. Sensitivity and specificity were not significantly different for patients from different centers, suggesting robustness of performance. Correct detection rate was significantly lower in patients with initially normal MRI than patients with unequivocally positive MRI. Subgroup analysis showed the size of the training group and normal control database impacted classifier performance.

SIGNIFICANCE

Automated surface-based MRI morphometry equipped with machine learning showed robust performance across cohorts from different centers and scanners. The proposed method may be a valuable tool to improve FCD detection in presurgical evaluation for patients with pharmacoresistant epilepsy.

Cortical morphology in patients with transient global amnesia

OBJECTIVE

This study evaluated alterations in cortical morphology in patients with transient global amnesia (TGA).

MATERIALS AND METHODS

Diagnoses of TGA occurred at our hospital. Evaluation involved a structured interview to obtain clinical information and a brain magnetic resonance imaging scan. We analyzed whole-brain T1-weighted MRI data using FreeSurfer 5.1. Measures of cortical morphology, such as thickness, surface area, volume, and curvature were compared between patients with TGA and healthy controls. We also quantified the correlations between clinical variables and each measure of abnormal cortical morphology.

RESULTS

Seventy patients met the inclusion criteria. Compared to healthy controls, patients with TGA had significant alterations in cortical thickness in several regions of bilateral hemisphere. Moreover, several regions of cortical volumes in left hemisphere were significantly different between patients with TGA and healthy controls. In addition, there were significant correlations between the durations of episodes and cortical thickness, especially in the parietal cortex. However, there were no differences between groups in other measures of cortical morphology, including surface area and curvatures.

CONCLUSIONS

We observed significant alterations in cortical morphology in patients with TGA; these alterations are implicated in the pathogenesis of TGA.

Progression of gray matter atrophy in seizure-free patients with temporal lobe epilepsy

OBJECTIVES

To investigate the presence and progression of gray matter (GM) reduction in seizure-free patients with temporal lobe epilepsy (TLE).

METHODS

We enrolled 39 consecutive TLE patients, seizure-free for at least 2 years--20 with magnetic resonance imaging (MRI) signs of hippocampal sclerosis (TLE-HS), 19 with normal MRI (TLE-NL), and 74 healthy controls. For longitudinal analysis, we included individuals who had a second MRI with minimum interval of 18 months: 21 patients (10 TLE-HS, 11 TLE-NL) and 11 controls. Three-dimensional (3D) T1 -weighted images acquired in 3 Tesla MRI were analyzed with voxel-based morphometry (VBM). The images of patients with right-sided interictal epileptogenic zone (EZ) were right-left flipped, as well as a comparable proportion of controls. Cross-sectional analysis: The patients' images from each group were compared to controls to investigate differences in GM volumes. Longitudinal analysis: The first and second images were compared in each group to look for decreased GM volume.

RESULTS

Cross-sectional analysis: Patients with TLE-HS had diffuse GM atrophy, including hippocampus and parahippocampal gyrus, insula, frontal, and occipital lobes ipsilateral to EZ, bilateral thalamus and contralateral orbitofrontal gyrus, and caudate. In contrast, TLE-NL group did not present significant differences compared to controls. Longitudinal analysis: TLE-HS presented progressive GM reduction in ipsilateral insula and occipital lobe, contralateral motor area, and bilateral temporal and frontal lobes. TLE-NL had GM progression in ipsilateral hypothalamus and parietal lobe, contralateral cerebellum, and bilateral temporal lobe. Controls did not show changes in GM volume between MRIs.

SIGNIFICANCE

Diffuse extrahippocampal GM atrophy is present in seizure-free patients with TLE-HS. In addition, there is progressive GM atrophy in patients with and without HS. These results demonstrate that not only ongoing seizures are involved in the progression of GM atrophy. An underlying pathologic mechanism could be responsible for progressive brain volume loss in TLE patients even in seizure-free periods.

Temporal lobe volume predicts Wada memory test performance in patients with mesial temporal sclerosis

The Wada test is widely used in the presurgical evaluation of potential temporal lobectomy patients to predict postoperative memory function. Expected asymmetry (EA), defined as Wada memory lateralized to the nonsurgical hemisphere, or a higher score after injection of the surgical hemisphere would be considered favorable in terms of postoperative memory outcome. However, in some cases, nonlateralized memory (NM) results, with no appreciable asymmetry, may occur because of impaired scores after both injections, often leading to denial of surgery. The reason for such nonlateralized Wada memory in patients with intractable temporal lobe epilepsy (TLE) remains unclear. Given that quantitative morphometric magnetic resonance imaging studies in TLE patients have shown bilateral regional atrophy in temporal and extratemporal structures, we hypothesized that the volume loss in contralateral temporal structures could contribute to nonlateralized Wada memory performance. To investigate this, we examined the relationship between the volume changes of temporal structures and Wada memory scores in patients with intractable TLE with mesial temporal sclerosis (MTS) using an age- and gender-matched control group. Memory was considered nonlateralized if the absolute difference in the total correct recall scores between ipsilateral and contralateral injections was <11%. Among 21 patients, Wada memory was lateralized in 15 and nonlateralized in 6 patients, with all the nonlateralized scores being observed in left TLE. The recall scores after ipsilateral injection were significantly lower in patients with an NM profile than an EA profile (23 ± 14% vs. 59 ± 18% correct recall, p ≤ 0.001). However, the recall scores after contralateral injection were low but similar between the two groups (25 ± 17% vs. 25 ± 15% correct recall, p=0.97). Compared to controls, all the patients showed greater volume loss in the temporal regions. However, patients with a NM profile showed significantly more volume loss than those with a lateralized memory profile in both contralateral and ipsilateral temporal regions (p<0.05). Left hemispheric Wada memory performance correlated positively with the size of the left mesial and neocortical temporal structures (r=0.49-0.63, p=0.005-0.04). Our study suggests that volume loss in the nonsurgical temporal structures is associated with nonlateralized Wada memory results in patients with intractable TLE.

Using network dynamic fMRI for detection of epileptogenic foci

Background

Epilepsy is one of the most prevalent neurological disorders. It remains medically intractable for about one-third of patients with focal epilepsy, for whom precise localization of the epileptogenic zone responsible for seizure initiation may be critical for successful surgery. Existing fMRI literature points to widespread network disturbances in functional connectivity. Per previous scalp and intracranial EEG studies and consistent with excessive local synchronization during interictal discharges, we hypothesized that, relative to same regions in healthy controls, epileptogenic foci would exhibit less chaotic dynamics, identifiable via entropic analyses of resting state fMRI time series.

Methods

In order to first validate this hypothesis on a cohort of patients with known ground truth, here we test individuals with well-defined epileptogenic foci (left mesial temporal lobe epilepsy). We analyzed voxel-wise resting-state fMRI time-series using the autocorrelation function (ACF), an entropic measure of regulation and feedback, and performed follow-up seed-to-voxel functional connectivity analysis. Disruptions in connectivity of the region exhibiting abnormal dynamics were examined in relation to duration of epilepsy and patients’ cognitive performance using a delayed verbal memory recall task.

Results

ACF analysis revealed constrained (less chaotic) functional dynamics in left temporal lobe epilepsy patients, primarily localized to ipsilateral temporal pole, proximal to presumed focal points. Autocorrelation decay rates differentiated, with 100 % accuracy, between patients and healthy controls on a subject-by-subject basis within a leave-one-subject out classification framework. Regions identified via ACF analysis formed a less efficient network in patients, as compared to controls. Constrained dynamics were linked with locally increased and long-range decreased connectivity that, in turn, correlated significantly with impaired memory (local left temporal connectivity) and epilepsy duration (left temporal – posterior cingulate cortex connectivity).

Conclusions

Our current results suggest that data driven functional MRI methods that target network dynamics hold promise in providing clinically valuable tools for identification of epileptic regions.

Machine learning classification of mesial temporal sclerosis in epilepsy patients

BACKGROUND AND PURPOSE

Novel approaches applying machine-learning methods to neuroimaging data seek to develop individualized measures that will aid in the diagnosis and treatment of brain-based disorders such as temporal lobe epilepsy (TLE). Using a large cohort of epilepsy patients with and without mesial temporal sclerosis (MTS), we sought to automatically classify MTS using measures of cortical morphology, and to further relate classification probabilities to measures of disease burden.

MATERIALS AND METHODS

Our sample consisted of high-resolution T1 structural scans of 169 adults with epilepsy collected across five different 1.5T and four different 3T scanners at UCLA. We applied a multiple support vector machine recursive feature elimination algorithm to morphological measures generated from FreeSurfer's automated segmentation and parcellation in order to classify Epilepsy patients with MTS (n=85) from those without MTS (N=84).

RESULTS

In addition to hippocampal volume, we found that alterations in cortical thickness, surface area, volume and curvature in inferior frontal and anterior and inferior temporal regions contributed to a classification accuracy of up to 81% (p=1.3×10(-17)) in identifying MTS. We also found that MTS classification probabilities were associated with a longer duration of disease for epilepsy patients both with and without MTS.

CONCLUSIONS

In addition to implicating extra-hippocampal involvement of MTS, these findings shed further light on the pathogenesis of TLE and may ultimately assist in the development of automated tools that incorporate multiple neuroimaging measures to assist clinicians in detecting more subtle cases of TLE and MTS.

Cortical feature analysis and machine learning improves detection of "MRI-negative" focal cortical dysplasia

Focal cortical dysplasia (FCD) is the most common cause of pediatric epilepsy and the third most common lesion in adults with treatment-resistant epilepsy. Advances in MRI have revolutionized the diagnosis of FCD, resulting in higher success rates for resective epilepsy surgery. However, many patients with histologically confirmed FCD have normal presurgical MRI studies ('MRI-negative'), making presurgical diagnosis difficult. The purpose of this study was to test whether a novel MRI postprocessing method successfully detects histopathologically verified FCD in a sample of patients without visually appreciable lesions. We applied an automated quantitative morphometry approach which computed five surface-based MRI features and combined them in a machine learning model to classify lesional and nonlesional vertices. Accuracy was defined by classifying contiguous vertices as "lesional" when they fell within the surgical resection region. Our multivariate method correctly detected the lesion in 6 of 7 MRI-positive patients, which is comparable with the detection rates that have been reported in univariate vertex-based morphometry studies. More significantly, in patients that were MRI-negative, machine learning correctly identified 14 out of 24 FCD lesions (58%). This was achieved after separating abnormal thickness and thinness into distinct classifiers, as well as separating sulcal and gyral regions. Results demonstrate that MRI-negative images contain sufficient information to aid in the in vivo detection of visually elusive FCD lesions.

White matter abnormalities differentiate severe from benign temporal lobe epilepsy

OBJECTIVE

Temporal and extratemporal white matter abnormalities have been identified frequently in patients with refractory mesial temporal lobe epilepsy (rMTLE). However, the identification of potential water diffusion abnormalities in patients with drug-responsive, benign MTLE (bMTLE) is still missing. The aim of this study was to identify markers of refractoriness in MTLE.

METHODS

The study group included 48 patients with bMTLE (mean age 42.8 + 13.5 years), 38 with rMTLE (mean age 41.7 + 14.1 years) and 54 healthy volunteers. Diffusion tensor imaging (DTI) was performed to measure mean diffusivity (MD) and fractional anisotropy (FA) in a regions-of-interest analysis comprising hippocampi and temporal lobe gray and white matter regions. The presence of hippocampal sclerosis (Hs) was assessed using automated magnetic resonance imaging (MRI) evaluation. For statistics we used chi-square test; two-tailed, two-sample t-test; and stratified linear regression.

RESULTS

The significant demographic differences between the two patient groups were sex (p = 0.003), duration of epilepsy (p = 0.003) and complex febrile convulsions (p = 0.0001). In rMTLE, temporal white matter MD was higher and FA lower, as compared to bMTLE. The analysis of diagnostic accuracy (area under the receiver operator characteristic [ROC] curve [AUC]) showed that FA had an AUC for discriminating patients affected from those unaffected by refractory MTLE of 74.0% (p < 0.001), a value that was higher than that of temporal MD (64.0%), hippocampus volume (65.0%), and Hs (66.0%).

SIGNIFICANCE

We performed DTI measurements in MTLE and found a significant reduction of FA along the white matter of the temporal lobes in rMTLE, suggesting it as a valuable measure of refractoriness in MTLE.

Temporal Cortex Morphology in Mesial Temporal Lobe Epilepsy Patients and Their Asymptomatic Siblings

Temporal cortex abnormalities are common in patients with mesial temporal lobe epilepsy due to hippocampal sclerosis (MTLE+HS) and believed to be relevant to the underlying mechanisms. In the present study, we set out to determine the familiarity of temporal cortex morphologic alterations in a cohort of MTLE+HS patients and their asymptomatic siblings. A surface-based morphometry (SBM) method was applied to process MRI data acquired from 140 individuals (50 patients with unilateral MTLE+HS, 50 asymptomatic siblings of patients, and 40 healthy controls). Using a region-of-interest approach, alterations in temporal cortex morphology were determined in patients and their asymptomatic siblings by comparing with the controls. Alterations in temporal cortex morphology were identified in MTLE+HS patients ipsilaterally within the anterio-medial regions, including the entorhinal cortex, parahippocampal gyrus, and temporal pole. Subtle but similar pattern of morphology changes with a medium effect size were also noted in the asymptomatic siblings. These localized alterations were related to volume loss that appeared driven by shared contractions in cerebral cortex surface area. These findings indicate that temporal cortex morphologic alterations are common to patients and their asymptomatic siblings and suggest that such localized traits are possibly heritable.

The consequences of refractory epilepsy and its treatment

Seizures in some 30% to 40% of patients with epilepsy fail to respond to antiepileptic drugs or other treatments. While much has been made of the risks of new drug therapies, not enough attention has been given to the risks of uncontrolled and progressive epilepsy. This critical review summarizes known risks associated with refractory epilepsy, provides practical clinical recommendations, and indicates areas for future research. Eight international epilepsy experts from Europe, the United States, and South America met on May 4, 2013, to present, review, and discuss relevant concepts, data, and literature on the consequences of refractory epilepsy. While patients with refractory epilepsy represent the minority of the population with epilepsy, they require the overwhelming majority of time, effort, and focus from treating physicians. They also represent the greatest economic and psychosocial burdens. Diagnostic procedures and medical/surgical treatments are not without risks. Overlooked, however, is that these risks are usually smaller than the risks of long-term, uncontrolled seizures. Refractory epilepsy may be progressive, carrying risks of structural damage to the brain and nervous system, comorbidities (osteoporosis, fractures), and increased mortality (from suicide, accidents, sudden unexpected death in epilepsy, pneumonia, vascular disease), as well as psychological (depression, anxiety), educational, social (stigma, driving), and vocational consequences. Adding to this burden is neuropsychiatric impairment caused by underlying epileptogenic processes ("essential comorbidities"), which appears to be independent of the effects of ongoing seizures themselves. Tolerating persistent seizures or chronic medicinal adverse effects has risks and consequences that often outweigh risks of seemingly "more aggressive" treatments. Future research should focus not only on controlling seizures but also on preventing these consequences.

Specific resting-state brain networks in mesial temporal lobe epilepsy

We studied with functional magnetic resonance imaging (fMRI) differences in resting-state networks between patients with mesial temporal lobe epilepsy (MTLE) and healthy subjects. To avoid any a priori hypothesis, we use a data-driven analysis assessing differences between groups independently of structures involved. Shared and specific independent component analysis (SSICA) is an exploratory method based on independent component analysis, which performs between-group network comparison. It extracts and classifies components (networks) in those common between groups and those specific to one group. Resting fMRI data were collected from 10 healthy subjects and 10 MTLE patients. SSICA was applied multiple times with altered initializations and different numbers of specific components. This resulted in many components specific to patients and to controls. Spatial clustering identified the reliable resting-state networks among all specific components in each group. For each reliable specific network, power spectrum analysis was performed on reconstructed time-series to estimate connectivity in each group and differences between groups. Two reliable networks, corresponding to statistically significant clusters robustly detected with clustering were labeled as specific to MTLE and one as specific to the control group. The most reliable MTLE network included hippocampus and amygdala bilaterally. The other MTLE network included the postcentral gyri and temporal poles. The control-specific network included bilateral precuneus, anterior cingulate, thalamus, and parahippocampal gyrus. Results indicated that the two MTLE networks show increased connectivity in patients, whereas the control-specific network shows decreased connectivity in patients. Our findings complement results from seed-based connectivity analysis (1). The pattern of changes in connectivity between mesial temporal lobe structures and other areas may help us understand the cognitive impairments often reported in patients with MTLE.

Frequent seizures are associated with a network of gray matter atrophy in temporal lobe epilepsy with or without hippocampal sclerosis

Objective

Patients with temporal lobe epilepsy (TLE) with hippocampal sclerosis (HS) have diffuse subtle gray matter (GM) atrophy detectable by MRI quantification analyses. However, it is not clear whether the etiology and seizure frequency are associated with this atrophy. We aimed to evaluate the occurrence of GM atrophy and the influence of seizure frequency in patients with TLE and either normal MRI (TLE-NL) or MRI signs of HS (TLE-HS).

Methods

We evaluated a group of 172 consecutive patients with unilateral TLE-HS or TLE-NL as defined by hippocampal volumetry and signal quantification (122 TLE-HS and 50 TLE-NL) plus a group of 82 healthy individuals. Voxel-based morphometry was performed with VBM8/SPM8 in 3T MRIs. Patients with up to three complex partial seizures and no generalized tonic-clonic seizures in the previous year were considered to have infrequent seizures. Those who did not fulfill these criteria were considered to have frequent seizures.

Results

Patients with TLE-HS had more pronounced GM atrophy, including the ipsilateral mesial temporal structures, temporal lobe, bilateral thalami and pre/post-central gyri. Patients with TLE-NL had more subtle GM atrophy, including the ipsilateral orbitofrontal cortex, bilateral thalami and pre/post-central gyri. Both TLE-HS and TLE-NL showed increased GM volume in the contralateral pons. TLE-HS patients with frequent seizures had more pronounced GM atrophy in extra-temporal regions than TLE-HS with infrequent seizures. Patients with TLE-NL and infrequent seizures had no detectable GM atrophy. In both TLE-HS and TLE-NL, the duration of epilepsy correlated with GM atrophy in extra-hippocampal regions.

Conclusion

Although a diffuse network GM atrophy occurs in both TLE-HS and TLE-NL, this is strikingly more evident in TLE-HS and in patients with frequent seizures. These findings suggest that neocortical atrophy in TLE is related to the ongoing seizures and epilepsy duration, while thalamic atrophy is more probably related to the original epileptogenic process.

Quantitative analysis of structural neuroimaging of mesial temporal lobe epilepsy

Mesial temporal lobe epilepsy (MTLE) is the most common of the surgically remediable drug-resistant epilepsies. MRI is the primary diagnostic tool to detect anatomical abnormalities and, when combined with EEG, can more accurately identify an epileptogenic lesion, which is often hippocampal sclerosis in cases of MTLE. As structural imaging technology has advanced the surgical treatment of MTLE and other lesional epilepsies, so too have the analysis techniques that are used to measure different structural attributes of the brain. These techniques, which are reviewed here and have been used chiefly in basic research of epilepsy and in studies of MTLE, have identified different types and the extent of anatomical abnormalities that can extend beyond the affected hippocampus. These results suggest that structural imaging and sophisticated imaging analysis could provide important information to identify networks capable of generating spontaneous seizures and ultimately help guide surgical therapy that improves postsurgical seizure-freedom outcomes.

Structural correlates of impaired working memory in hippocampal sclerosis

Purpose:

Temporal lobe epilepsy (TLE) has been considered to impair long-term memory, whilst not affecting working memory, but recent evidence suggests that working memory is compromised. Functional MRI (fMRI) studies demonstrate that working memory involves a bilateral frontoparietal network the activation of which is disrupted in hippocampal sclerosis (HS). A specific role of the hippocampus to deactivate during working memory has been proposed with this mechanism faulty in patients with HS. Structural correlates of disrupted working memory in HS have not been explored.

Methods:

We studied 54 individuals with medically refractory TLE and unilateral HS (29 left) and 28 healthy controls. Subjects underwent 3T structural MRI, a visuospatial n-back fMRI paradigm and diffusion tensor imaging (DTI). Working memory capacity assessed by three span tasks (digit span backwards, gesture span, motor sequences) was combined with performance in the visuospatial paradigm to give a global working memory measure. Gray and white matter changes were investigated using voxel-based morphometry and voxel-based analysis of DTI, respectively.

Key Findings:

Individuals with left or right HS performed less well than healthy controls on all measures of working memory. fMRI demonstrated a bilateral frontoparietal network during the working memory task with reduced activation of the right parietal lobe in both patient groups. In left HS, gray matter loss was seen in the ipsilateral hippocampus and parietal lobe, with maintenance of the gray matter volume of the contralateral parietal lobe associated with better performance. White matter integrity within the frontoparietal network, in particular the superior longitudinal fasciculus and cingulum, and the contralateral temporal lobe, was associated with working memory performance. In right HS, gray matter loss was also seen in the ipsilateral hippocampus and parietal lobe. Working memory performance correlated with the gray matter volume of both frontal lobes and white matter integrity within the frontoparietal network and contralateral temporal lobe.

Significance:

Our data provide further evidence that working memory is disrupted in HS and impaired integrity of both gray and white matter is seen in functionally relevant areas. We suggest this forms the structural basis of the impairment of working memory, indicating widespread and functionally significant structural changes in patients with apparently isolated HS.

Heritability of subcortical volumetric traits in mesial temporal lobe epilepsy

Objectives

We aimed to 1) determine if subcortical volume deficits are common to mesial temporal lobe epilepsy (MTLE) patients and their unaffected siblings 2) assess the suitability of subcortical volumetric traits as endophenotypes for MTLE.

Methods

MRI-based volume measurements of the hippocampus, amygdala, thalamus, caudate, putamen and pallidium were generated using an automated brain reconstruction method (FreeSurfer) for 101 unrelated ‘sporadic’ MTLE patients [70 with hippocampal sclerosis (MTLE+HS), 31 with MRI-negative TLE], 83 unaffected full siblings of patients and 86 healthy control subjects. Changes in the volume of subcortical structures in patients and their unaffected siblings were determined by comparison with healthy controls. Narrow sense heritability was estimated ipsilateral and contralateral to the side of seizure activity.

Results

MTLE+HS patients displayed significant volume deficits across the hippocampus, amygdala and thalamus ipsilaterally. In addition, volume loss was detected in the putamen bilaterally. These volume deficits were not present in the unaffected siblings of MTLE+HS patients. Ipsilaterally, the heritability estimates were dramatically reduced for the volume of the hippocampus, thalamus and putamen but remained in the expected range for the amygdala. MRI-negative TLE patients and their unaffected siblings showed no significant volume changes across the same structures and heritability estimates were comparable with calculations from a healthy population.

Conclusions

The findings indicate that volume deficits for many subcortical structures in ‘sporadic’ MTLE+HS are not heritable and likely related to acquired factors. Therefore, they do not represent suitable endophenotypes for MTLE+HS. The findings also support the view that, at a neuroanatomical level, MTLE+HS and MRI-negative TLE represent two distinct forms of MTLE.

Antidepressant therapy in epilepsy: can treating the comorbidities affect the underlying disorder?

There is a high incidence of psychiatric comorbidity in people with epilepsy (PWE), particularly depression. The manifold adverse consequences of comorbid depression have been more clearly mapped in recent years. Accordingly, considerable efforts have been made to improve detection and diagnosis, with the result that many PWE are treated with antidepressant drugs, medications with the potential to influence both epilepsy and depression. Exposure to older generations of antidepressants (notably tricyclic antidepressants and bupropion) can increase seizure frequency. However, a growing body of evidence suggests that newer ('second generation') antidepressants, such as selective serotonin reuptake inhibitors or serotonin-noradrenaline reuptake inhibitors, have markedly less effect on excitability and may lead to improvements in epilepsy severity. Although a great deal is known about how antidepressants affect excitability on short time scales in experimental models, little is known about the effects of chronic antidepressant exposure on the underlying processes subsumed under the term 'epileptogenesis': the progressive neurobiological processes by which the non-epileptic brain changes so that it generates spontaneous, recurrent seizures. This paper reviews the literature concerning the influences of antidepressants in PWE and in animal models. The second section describes neurobiological mechanisms implicated in both antidepressant actions and in epileptogenesis, highlighting potential substrates that may mediate any effects of antidepressants on the development and progression of epilepsy. Although much indirect evidence suggests the overall clinical effects of antidepressants on epilepsy itself are beneficial, there are reasons for caution and the need for further research, discussed in the concluding section.

Epilepsy as progressive disorders: what is the evidence that can guide our clinical decisions and how can neuroimaging help?

There is evidence that some types of epilepsy progress over time, and an important part of this knowledge has derived from neuroimaging studies. Different authors have demonstrated structural damage more pronounced in individuals with a longer duration of epilepsy, and others have been able to quantify this progression over time. However, others have failed to demonstrate progression possibly due to the heterogeneity of individuals evaluated. Currently, temporal lobe epilepsy associated with hippocampal sclerosis is regarded as a progressive disorder. Conversely, for other types of epilepsy, the evidence is not so clear. The causes of this damage progression are also unknown although there is consistent evidence that seizure is one of the mechanisms. The conflicting data about epilepsy progression can be a challenge for clinical decisions for an individual patient. Studies with homogenous groups and longer follow-up are necessary for appropriate conclusions about the real burden of damage progression in epilepsies, and neuroimaging will be essential in this context.

Functional networks in temporal-lobe epilepsy: a voxel-wise study of resting-state functional connectivity and gray-matter concentration

Temporal-lobe epilepsy (TLE) involves seizures that typically originate in the hippocampus. There is evidence that seizures involve anatomically and functionally connected brain networks within and beyond the temporal lobe. Many studies have explored the effect of TLE on gray matter and resting-state functional connectivity in the brain. However, the relationship between structural and functional changes has not been fully explored. The goal of this study was to investigate the relationship between gray matter concentration (GMC) and functional connectivity in TLE at the voxel level. A voxel-wise linear regression analysis was performed between GMC maps and whole-brain resting-state functional connectivity maps to both the left thalamus (Lthal) and the left hippocampus (LH) in a group of 15 patients with left TLE. Twenty regions were found that exhibited GMC decreases linearly correlated with resting-state functional connectivity to either the LH or the Lthal in the patient group only. A subset of these regions had significantly reduced GMC, and one of these regions also had reduced functional connectivity to the LH in TLE compared to the controls. These results suggest a network of impairment in left TLE where more severe reductions in GMC accompany decreases (LH, Lthal, right midcingulate gyrus, left precuneus, and left postcentral gyrus) or increases (LH to right thalamus) in resting functional connectivity. However, direct relationships between these imaging parameters and disease characteristics in these regions have yet to be established.

White Matter Atrophy in Patients with Mesial Temporal Lobe Epilepsy: Voxel-Based Morphometry Analysis of T1- and T2-Weighted MR Images

Introduction. Mesial temporal lobe epilepsy (MTLE) associated with hippocampal sclerosis is highly refractory to clinical treatment. MRI voxel-based morphometry (VBM) of T1-weighted images has revealed a widespread pattern of gray matter (GM) and white matter (WM) atrophy in MTLE. Few studies have investigated the role of T2-weighted images in revealing WM atrophy using VBM. Objectives. To compare the results of WM atrophy between T1- and T2-weighted images through VBM. Methods. We selected 28 patients with left and 27 with right MTLE and 60 normal controls. We analyzed T1- and T2- weighted images with SPM8, using VBM/DARTEL algorithm to extract maps of GM and WM. The second level of SPM was used to investigate areas of WM atrophy among groups. Results. Both acquisitions showed bilateral widespread WM atrophy. T1-weighted images showed higher sensibility to detect areas of WM atrophy in both groups of MTLE. T2-weighted images also showed areas of WM atrophy in a more restricted pattern, but still bilateral and with a large area of superposition with T1-weighted images. Conclusions. In MTLE, T1-weighted images are more sensitive to detect subtle WM abnormalities using VBM, compared to T2 images, although both present a good superposition of statistical maps.

Auras in temporal lobe epilepsy with hippocampal sclerosis: relation to seizure focus laterality and post surgical outcome

We examined the relationship between presence and frequency of different types of auras and side of lesion and post surgical outcomes in 205 patients with medically intractable mesial temporal lobe epilepsy (MTLE) with unilateral hippocampal sclerosis (HS). With respect to the number of auras, multiple auras were not associated with side of lesion (p=0.551). The side of HS was not associated with the type of auras reported. One hundred fifty-seven patients were operated. The occurrence of multiple auras was not associated with post-surgical outcome (p=0.740). The presence of extratemporal auras was significantly higher in patients with poor outcome. In conclusion, this study suggests that the presence of extratemporal auras in patients with MTLE-HS possibly reflects extratemporal epileptogenicity in these patients, who otherwise showed features suggestive of TLE. Therefore, TLE-HS patients undergoing pre-surgical evaluation and presenting clinical symptoms suggestive of extratemporal involvement should be more extensively evaluated to avoid incomplete resection of the epileptogenic zone.

Neural correlates of working memory in Temporal Lobe Epilepsy--an fMRI study

It has traditionally been held that the hippocampus is not part of the neural substrate of working memory (WM), and that WM is preserved in Temporal Lobe Epilepsy (TLE). Recent imaging and neuropsychological data suggest this view may need revision. The aim of this study was to investigate the neural correlates of WM in TLE using functional MRI (fMRI). We used a visuo-spatial 'n-back' paradigm to compare WM network activity in 38 unilateral hippocampal sclerosis (HS) patients (19 left) and 15 healthy controls. WM performance was impaired in both left and right HS groups compared to controls. The TLE groups showed reduced right superior parietal lobe activity during single- and multiple-item WM. No significant hippocampal activation was found during the active task in any group, but the hippocampi progressively deactivated as the task demand increased. This effect was bilateral for controls, whereas the TLE patients showed progressive unilateral deactivation only contralateral to the side of the hippocampal sclerosis and seizure focus. Progressive deactivation of the posterior medial temporal lobe was associated with better performance in all groups. Our results suggest that WM is impaired in unilateral HS and the underlying neural correlates of WM are disrupted. Our findings suggest that hippocampal activity is progressively suppressed as the WM load increases, with maintenance of good performance. Implications for understanding the role of the hippocampus in WM are discussed.