Asymmetrical extra-hippocampal grey matter loss related to hippocampal atrophy in patients with medial temporal lobe epilepsy

Causal Connectivity Network Analysis of Ictal Electrocorticogram With Temporal Lobe Epilepsy Based on Dynamic Phase Transfer Entropy

Temporallobe epilepsy (TLE) has been conceptualized as a brain network disease, which generates brain connectivity dynamics within and beyond the temporal lobe structures in seizures. The hippocampus is a representative epileptogenic focus in TLE. Understanding the causal connectivity in terms of brain network during seizures is crucial in revealing the triggering mechanism of epileptic seizures originating from the hippocampus (HPC) spread to the lateral temporal cortex (LTC) by ictal electrocorticogram (ECoG), particularly in high-frequency oscillations (HFOs) bands. In this study, we proposed the unified-epoch dynamic causality analysis method to investigate the causal influence dynamics between two brain regions (HPC and LTC) at interictal and ictal phases in the frequency range of 1-500 Hz by introducing the phase transfer entropy (PTE) out/in-ratio and sliding window. We also proposed PTE-based machine learning algorithms to identify epileptogenic zone (EZ). Nine patients with a total of 26 seizures were included in this study. We hypothesized that: 1) HPC is the focus with the stronger causal connectivity than that in LTC in the ictal state at gamma and HFOs bands. 2) Causal connectivity in the ictal phase shows significant changes compared to that in the interictal phase. 3) The PTE out/in-ratio in the HFOs band can identify the EZ with the best prediction performance.

The Thalamic and Intracortical Inhibitory Function of Somatosensory System Is Unchanged in Mesial Temporal Lobe Epilepsy With Hippocampal Sclerosis

PURPOSE

In mesial temporal lobe epilepsy with hippocampal sclerosis, there is parietal atrophy and cognitive involvement in related domains. In this context, we hypothesized that inhibitory input into somatosensory cortex and thalamus may be increased in these patients, which could improve after epilepsy surgery. Thus, we analyzed the inhibitory function of somatosensory system by studying surround inhibition (SI) and recovery function of somatosensory evoked potentials in patients with mesial temporal lobe epilepsy with hippocampal sclerosis.

METHODS

Nine patients with unoperated mesial temporal lobe epilepsy with hippocampal sclerosis, 10 patients who underwent epilepsy surgery, and 12 healthy subjects were included. For SI of somatosensory evoked potentials, we recorded somatosensory evoked potentials after stimulating median or ulnar nerve at wrist separately and after median and ulnar nerves simultaneously and calculated SI% in all participants. For recovery function of somatosensory evoked potentials, paired stimulation of median nerve at 40- and 100-millisecond intervals was performed. We compared the findings among groups. As a secondary analysis, we determined the outliers in the patient group and analyzed the relation to the clinical findings.

RESULTS

The mean SI% or recovery function was similar among three groups. However, there were five patients with SI loss on normal side in the patient group, which was related to the antiseizure drugs.

CONCLUSIONS

In contrast to our hypothesis, both intracortical (SI) and thalamic/striatal (recovery function) inhibitory modulation of the somatosensory cortex was not altered in mesial temporal lobe epilepsy with hippocampal sclerosis and did not differ in surgical and nonsurgical groups.

The role of the temporal pole in temporal lobe epilepsy: A diffusion kurtosis imaging study

This study aimed to evaluate the use of diffusion kurtosis imaging (DKI) to detect microstructural abnormalities within the temporal pole (TP) and its temporopolar cortex in temporal lobe epilepsy (TLE) patients. DKI quantitative maps were obtained from fourteen lesional TLE and ten non-lesional TLE patients, along with twenty-three healthy controls. Data collected included mean (MK); radial (RK) and axial kurtosis (AK); mean diffusivity (MD) and axonal water fraction (AWF). Automated fiber quantification (AFQ) was used to quantify DKI measurements along the inferior longitudinal (ILF) and uncinate fasciculus (Unc). ILF and Unc tract profiles were compared between groups and tested for correlation with disease duration. To characterize temporopolar cortex microstructure, DKI maps were sampled at varying depths from superficial white matter (WM) towards the pial surface. Patients were separated according to the temporal lobe ipsilateral to seizure onset and their AFQ results were used as input for statistical analyses. Significant differences were observed between lesional TLE and controls, towards the most temporopolar segment of ILF and Unc proximal to the TP within the ipsilateral temporal lobe in left TLE patients for MK, RK, AWF and MD. No significant changes were observed with DKI maps in the non-lesional TLE group. DKI measurements correlated with disease duration, mostly towards the temporopolar segments of the WM bundles. Stronger differences in MK, RK and AWF within the temporopolar cortex were observed in the lesional TLE and noticeable differences (except for MD) in non-lesional TLE groups compared to controls. This study demonstrates that DKI has potential to detect subtle microstructural alterations within the temporopolar segments of the ILF and Unc and the connected temporopolar cortex in TLE patients including non-lesional TLE subjects. This could aid our understanding of the extrahippocampal areas, more specifically the temporal pole role in seizure generation in TLE and might inform surgical planning, leading to better seizure outcomes.

Phenotypic differences based on lateralization of intrahippocampal kainic acid injection in female mice

Clinical evidence indicates that patients with temporal lobe epilepsy (TLE) often show differential outcomes of comorbid conditions in relation to the lateralization of the seizure focus. A particularly strong relationship exists between the side of seizure focus and the propensity for distinct reproductive endocrine comorbidities in women with TLE. Therefore, here we evaluated whether targeting of left or right dorsal hippocampus for intrahippocampal kainic acid (IHKA) injection, a model of TLE, produces different outcomes in hippocampal granule cell dispersion, body weight gain, and multiple measures of reproductive endocrine dysfunction in female mice. One, two, and four months after IHKA or saline injection, in vivo measurements of estrous cycles and weight were followed by ex vivo examination of hippocampal dentate granule cell dispersion, circulating ovarian hormone and corticosterone levels, ovarian morphology, and pituitary gene expression. IHKA mice with right-targeted injection (IHKA-R) showed greater granule cell dispersion and pituitary Fshb expression compared to mice with left-targeted injection (IHKA-L). By contrast, pituitary expression of Lhb and Gnrhr were higher in IHKA-L mice compared to IHKA-R, but these values were not different from respective saline-injected controls. IHKA-L mice also showed an increased rate of weight gain compared to IHKA-R mice. Increases in estrous cycle length, however, were similar in both IHKA-L and IHKA-R mice. These findings indicate that although major reproductive endocrine dysfunction phenotypes present similarly after targeting left or right dorsal hippocampus for IHKA injection, distinct underlying mechanisms based on lateralization of epileptogenic insult may contribute to produce similar emergent reproductive endocrine outcomes.

Structural network alterations in focal and generalized epilepsy assessed in a worldwide ENIGMA study follow axes of epilepsy risk gene expression

Epilepsy is associated with genetic risk factors and cortico-subcortical network alterations, but associations between neurobiological mechanisms and macroscale connectomics remain unclear. This multisite ENIGMA-Epilepsy study examined whole-brain structural covariance networks in patients with epilepsy and related findings to postmortem epilepsy risk gene expression patterns. Brain network analysis included 578 adults with temporal lobe epilepsy (TLE), 288 adults with idiopathic generalized epilepsy (IGE), and 1328 healthy controls from 18 centres worldwide. Graph theoretical analysis of structural covariance networks revealed increased clustering and path length in orbitofrontal and temporal regions in TLE, suggesting a shift towards network regularization. Conversely, people with IGE showed decreased clustering and path length in fronto-temporo-parietal cortices, indicating a random network configuration. Syndrome-specific topological alterations reflected expression patterns of risk genes for hippocampal sclerosis in TLE and for generalized epilepsy in IGE. These imaging-transcriptomic signatures could potentially guide diagnosis or tailor therapeutic approaches to specific epilepsy syndromes.

De novo epilepsy after microsurgical resection of brain arteriovenous malformations

OBJECTIVE

Seizures are the second most common presenting symptom of brain arteriovenous malformations (bAVMs) after hemorrhage. Risk factors for preoperative seizures and subsequent seizure control outcomes have been well studied. There is a paucity of literature on postoperative, de novo seizures in initially seizure-naïve patients who undergo resection. Whereas this entity has been documented after craniotomy for a wide variety of neurosurgically treated pathologies including tumors, trauma, and aneurysms, de novo seizures after bAVM resection are poorly studied. Given the debilitating nature of epilepsy, the purpose of this study was to elucidate the incidence and risk factors associated with de novo epilepsy after bAVM resection.

METHODS

A retrospective review of patients who underwent resection of a bAVM over a 15-year period was performed. Patients who did not present with seizure were included, and the primary outcome was de novo epilepsy (i.e., a seizure disorder that only manifested after surgery). Demographic, clinical, and radiographic characteristics were compared between patients with and without postoperative epilepsy. Subgroup analysis was conducted on the ruptured bAVMs.

RESULTS

From a cohort of 198 patients who underwent resection of a bAVM during the study period, 111 supratentorial ruptured and unruptured bAVMs that did not present with seizure were included. Twenty-one patients (19%) developed de novo epilepsy. One-year cumulative rates of developing de novo epilepsy were 9% for the overall cohort and 8.5% for the cohort with ruptured bAVMs. There were no significant differences between the epilepsy and no-epilepsy groups overall; however, the de novo epilepsy group was younger in the cohort with ruptured bAVMs (28.7 ± 11.7 vs 35.1 ± 19.9 years; p = 0.04). The mean time between resection and first seizure was 26.0 ± 40.4 months, with the longest time being 14 years. Subgroup analysis of the ruptured and endovascular embolization cohorts did not reveal any significant differences. Of the patients who developed poorly controlled epilepsy (defined as Engel class III–IV), all had a history of hemorrhage and half had bAVMs located in the temporal lobe.

CONCLUSIONS

De novo epilepsy after bAVM resection occurs at an annual cumulative risk of 9%, with potentially long-term onset. Younger age may be a risk factor in patients who present with rupture. The development of poorly controlled epilepsy may be associated with temporal lobe location and a delay between hemorrhage and resection.

Topographic divergence of atypical cortical asymmetry and atrophy patterns in temporal lobe epilepsy

Temporal lobe epilepsy, a common drug-resistant epilepsy in adults, is primarily a limbic network disorder associated with predominant unilateral hippocampal pathology. Structural MRI has provided an in vivo window into whole-brain grey matter structural alterations in temporal lobe epilepsy relative to controls, by either mapping (i) atypical inter-hemispheric asymmetry; or (ii) regional atrophy. However, similarities and differences of both atypical asymmetry and regional atrophy measures have not been systematically investigated. Here, we addressed this gap using the multisite ENIGMA-Epilepsy dataset comprising MRI brain morphological measures in 732 temporal lobe epilepsy patients and 1418 healthy controls. We compared spatial distributions of grey matter asymmetry and atrophy in temporal lobe epilepsy, contextualized their topographies relative to spatial gradients in cortical microstructure and functional connectivity calculated using 207 healthy controls obtained from Human Connectome Project and an independent dataset containing 23 temporal lobe epilepsy patients and 53 healthy controls and examined clinical associations using machine learning. We identified a marked divergence in the spatial distribution of atypical inter-hemispheric asymmetry and regional atrophy mapping. The former revealed a temporo-limbic disease signature while the latter showed diffuse and bilateral patterns. Our findings were robust across individual sites and patients. Cortical atrophy was significantly correlated with disease duration and age at seizure onset, while degrees of asymmetry did not show a significant relationship to these clinical variables. Our findings highlight that the mapping of atypical inter-hemispheric asymmetry and regional atrophy tap into two complementary aspects of temporal lobe epilepsy-related pathology, with the former revealing primary substrates in ipsilateral limbic circuits and the latter capturing bilateral disease effects. These findings refine our notion of the neuropathology of temporal lobe epilepsy and may inform future discovery and validation of complementary MRI biomarkers in temporal lobe epilepsy.

Radiological identification of temporal lobe epilepsy using artificial intelligence: a feasibility study

Temporal lobe epilepsy is associated with MRI findings reflecting underlying mesial temporal sclerosis. Identifying these MRI features is critical for the diagnosis and management of temporal lobe epilepsy. To date, this process relies on visual assessment by highly trained human experts (e.g. neuroradiologists, epileptologists). Artificial intelligence is increasingly recognized as a promising aid in the radiological evaluation of neurological diseases, yet its applications in temporal lobe epilepsy have been limited. Here, we applied a convolutional neural network to assess the classification accuracy of temporal lobe epilepsy based on structural MRI. We demonstrate that convoluted neural networks can achieve high accuracy in the identification of unilateral temporal lobe epilepsy cases even when the MRI had been originally interpreted as normal by experts. We show that accuracy can be potentiated by employing smoothed grey matter maps and a direct acyclic graphs approach. We further discuss the foundations for the development of computer-aided tools to assist with the diagnosis of epilepsy.

Single-subject gray matter networks in temporal lobe epilepsy patients with hippocampal sclerosis

OBJECTIVE

Previous studies have demonstrated structural brain network abnormalities in patients with temporal lobe epilepsy (TLE) using cortical thickness or gray matter (GM) volume. However, no studies have applied single-subject GM network analysis. Here, we first applied an analysis of similarity-based single-subject GM networks to individual patients with TLE.

MATERIALS AND METHODS

We recruited 51 patients with TLE and unilateral hippocampal sclerosis (22 left, 29 right TLE) and 51 age- and gender- matched healthy controls. Single-subject structural networks were extracted from three-dimensional T1-weighted magnetic resonance images for each subject. In this method, nodes were defined as small cortical regions and edges representing connecting regions that have high statistical similarity. The constructed graphs were analyzed using the graph theoretical approach. The following global and local network properties were calculated: betweenness centrality, clustering coefficient, and characteristic path length. In addition, small world properties (normalized path length λ, normalized clustering coefficient γ, and small-world network value σ) were obtained and compared with those for the controls.

RESULTS

Although the small-world configurations were retained, impaired global clustering coefficient was observed in left and right TLE. At a regional level, patients with left TLE showed a widespread decrease of the clustering coefficient beyond the ipsilateral temporal lobe and a decreased characteristic path length in the ipsilateral temporal pole. On the other hand, patients with right TLE showed a localized decrease of the clustering coefficient in the ipsilateral temporal lobe.

CONCLUSIONS

Our findings suggest that global and local network properties disrupted and moved toward randomized networks in TLE patients in comparison to controls. This network alteration was more extensive in left TLE than in right TLE patients. Single-subject GM networks may contribute to a better understanding of the pathophysiology of TLE.

Atypical functional connectome hierarchy impacts cognition in temporal lobe epilepsy

OBJECTIVE

Drug-resistant temporal lobe epilepsy (TLE) is typically associated with hippocampal pathology. However, widespread network alterations are increasingly recognized and suggested to perturb cognitive function in multiple domains. Here we tested (1) whether TLE shows atypical cortical hierarchical organization, differentiating sensory and higher order systems; and (2) whether atypical hierarchy predicts cognitive impairment.

METHODS

We studied 72 well-characterized drug-resistant TLE patients and 41 healthy controls, statistically matched for age and sex, using multimodal magnetic resonance imaging analysis and cognitive testing. To model cortical hierarchical organization in vivo, we used a bidirectional stepwise functional connectivity analysis tapping into the differentiation between sensory/unimodal and paralimbic/transmodal cortices. Linear models compared patients to controls. Finally, we assessed associations of functional anomalies to cortical atrophy and microstructural anomalies, as well as clinical and cognitive parameters.

RESULTS

Compared to controls, TLE presented with bidirectional disruptions of sensory-paralimbic functional organization. Stepwise connectivity remained segregated within paralimbic and salience networks at the top of the hierarchy, and sensorimotor and dorsal attention at the bottom. Whereas paralimbic segregation was associated with atypical cortical myeloarchitecture and hippocampal atrophy, dysconnectivity of sensorimotor cortices reflected diffuse cortical thinning. The degree of abnormal hierarchical organization in sensory-petal streams covaried, with broad cognitive impairments spanning sensorimotor, attention, fluency, and visuoconstructional ability and memory, and was more marked in patients with longer disease duration and Engel I outcome.

SIGNIFICANCE

Our findings show atypical functional integration between paralimbic/transmodal and sensory/unimodal systems in TLE. Differential associations with paralimbic microstructure and sensorimotor atrophy suggest that system-level imbalance likely reflects complementary structural processes, but ultimately accounts for a broad spectrum of cognitive impairments. Hierarchical contextualization of cognitive deficits promises to open new avenues for personalized counseling in TLE.

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.

Incorporation of quantitative MRI in a model to predict temporal lobe epilepsy surgery outcome

Quantitative volumetric brain MRI measurement is important in research applications, but translating it into patient care is challenging. We explore the incorporation of clinical automated quantitative MRI measurements in statistical models predicting outcomes of surgery for temporal lobe epilepsy. Four hundred and thirty-five patients with drug-resistant epilepsy who underwent temporal lobe surgery at Cleveland Clinic, Mayo Clinic and University of Campinas were studied. We obtained volumetric measurements from the pre-operative T1-weighted MRI using NeuroQuant, a Food and Drug Administration approved software package. We created sets of statistical models to predict the probability of complete seizure-freedom or an Engel score of I at the last follow-up. The cohort was randomly split into training and testing sets, with a ratio of 7:3. Model discrimination was assessed using the concordance statistic (C-statistic). We compared four sets of models and selected the one with the highest concordance index. Volumetric differences in pre-surgical MRI located predominantly in the frontocentral and temporal regions were associated with poorer outcomes. The addition of volumetric measurements to the model with clinical variables alone increased the model’s C-statistic from 0.58 to 0.70 (right-sided surgery) and from 0.61 to 0.66 (left-sided surgery) for complete seizure freedom and from 0.62 to 0.67 (right-sided surgery) and from 0.68 to 0.73 (left-sided surgery) for an Engel I outcome score. 57% of patients with extra-temporal abnormalities were seizure-free at last follow-up, compared to 68% of those with no such abnormalities (P-value = 0.02). Adding quantitative MRI data increases the performance of a model developed to predict post-operative seizure outcomes. The distribution of the regions of interest included in the final model supports the notion that focal epilepsies are network disorders and that subtle cortical volume loss outside the surgical site influences seizure outcome.

Automated analysis of cortical volume loss predicts seizure outcomes after frontal lobectomy

OBJECTIVE

Patients undergoing frontal lobectomy demonstrate lower seizure-freedom rates than patients undergoing temporal lobectomy and several other resective interventions. We attempted to utilize automated preoperative quantitative analysis of focal and global cortical volume loss to develop predictive volumetric indicators of seizure outcome after frontal lobectomy.

METHODS

Ninety patients who underwent frontal lobectomy were stratified based on seizure freedom at a mean follow-up time of 3.5 (standard deviation [SD] 2.5) years. Automated quantitative analysis of cortical volume loss organized by distinct brain region and laterality was performed on preoperative T1-weighted magnetic resonance imaging (MRI) studies. Univariate statistical analysis was used to select potential predictors of seizure freedom. Backward variable selection and multivariate logistical regression were used to develop models to predict seizure freedom.

RESULTS

Forty-eight of 90 (53.3%) patients were seizure-free at the last follow-up. Several frontal and extrafrontal brain regions demonstrated statistically significant differences in both volumetric cortical volume loss and volumetric asymmetry between the left and right sides in the seizure-free and non-seizure-free cohorts. A final multivariate logistic model utilizing only preoperative quantitative MRI data to predict seizure outcome was developed with a c-statistic of 0.846. Using both preoperative quantitative MRI data and previously validated clinical predictors of seizure outcomes, we developed a model with a c-statistic of 0.897.

SIGNIFICANCE

This study demonstrates that preoperative cortical volume loss in both frontal and extrafrontal regions can be predictive of seizure outcome after frontal lobectomy, and models can be developed with excellent predictive capabilities using preoperative MRI data. Automated quantitative MRI analysis can be quickly and reliably performed in patients with frontal lobe epilepsy, and further studies may be developed for integration into preoperative risk stratification.

Dynamic gray matter and intrinsic activity changes after epilepsy surgery

OBJECTIVES

To explore the dynamic changes of gray matter volume and intrinsic brain activity following anterior temporal lobectomy (ATL) in patients with unilateral mesial temporal lobe epilepsy (mTLE) who achieved seizure-free for 2 years.

MATERIALS AND METHODS

High-resolution T1-weighted MRI and resting-state functional MRI data were obtained in ten mTLE patients at five serial timepoints: before surgery, 3, 6, 12, and 24 months after surgery. The gray matter volume (GMV) and amplitude of low-frequency fluctuations (ALFF) were compared among the five scans to depict the dynamic changes after ATL.

RESULTS

After successful ATL, GMV decreased in several ipsilateral brain regions: ipsilateral insula, thalamus, and putamen showed gradual gray matter atrophy from 3 to 24 months, while ipsilateral superior temporal gyrus, middle temporal gyrus, inferior temporal gyrus, middle occipital gyrus, inferior occipital gyrus, caudate nucleus, lingual gyrus, and fusiform gyrus showed significant GMV decrease at 3 months follow-up, without further changes. Ipsilateral insula showed gradual ALFF decrease from 3 to 24 months after surgery. Ipsilateral superior temporal gyrus showed ALFF decrease at 3 months follow-up, without further changes. Ipsilateral thalamus and cerebellar vermis showed obvious ALFF increase after surgery.

CONCLUSIONS

Surgical resection may lead to a short-term reduction of gray matter volume and intrinsic brain activity in neighboring regions, while the progressive gray matter atrophy may be due to possible intrinsic mechanism of mTLE. Dynamic ALFF changes provide evidence that disrupted focal spontaneous activities were reorganized after successful surgery.

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.

Duration-dependent extensive volume and shape changes of mesolimbic structures in surgically treated unilateral patients with temporal lobe epilepsy

PURPOSE

Although surgical treatment of drug-resistant mesial temporal lobe epilepsy (MTLE) has proven efficacy, surgical referrals are often delayed. Knowledge of the abnormalities of mesolimbic structures beyond the hippocampus may be important for patients with MTLE because of its usefulness in the understanding of progressive disabilities in affected structures. This study aimed to identify volume and shape changes of mesolimbic structures in surgically treated patients with unilateral MTLE and their correlation with various clinical parameters.

METHODS

Twenty-four patients with unilateral MTLE (12 with left MTLE [LMTLE] and 12 with right MTLE [RMTLE]) who were surgically treated with standard temporal lobectomy, including amygdalohippocampectomy, and 24 age- and sex-matched healthy individuals were enrolled. Preoperatively, volumetric analysis using magnetic resonance imaging (MRI) of 27 mesolimbic substructures (11 from each hemisphere and 5 from the midline) was performed. We also investigated the three-dimensional morphometric differences of the mesolimbic structures between the unilateral MTLE and control groups using shape analyses.

RESULTS

Patients with LMTLE showed significant volume reductions in various ipsilateral mesolimbic (72.7%, 8/11) and contralateral structures (27.3%, 3/11). Patients with RMTLE had also significant reduced volumes in ipsilateral (63.6%, 7/11) and contralateral structures (73.3%, 3/11). Among the clinical parameters, only the duration of epilepsy had a statistically significant inverse correlation with the volumes of the hippocampus, parahippocampus, entorhinal cortex, cingulate, and corpus callosum. In the shape analysis of the bilateral hippocampus, amygdala, parahippocampus, and entorhinal cortex, after accounting for the effects of age and total intracranial volume, significant shape changes in the anterolateral area of the ipsilateral hippocampus were noted, which corresponds to the cornu ammonis (CA)1 and subiculum of the hippocampus.

CONCLUSIONS

The extensive volume reductions in the multiple mesolimbic structures and the substantial inverse correlation between the duration of epilepsy and the volumes of the various mesolimbic structures in our study supports that MTLE is not restricted to the hippocampus, but it progressively involves extensive mesolimbic structures. The duration-dependent atrophic changes in multiple subcortical structures seen in this study also suggest a positive role of early surgical intervention for patients with drug-resistant TLE.

Graph Theory Analysis of Functional Connectivity Combined with Machine Learning Approaches Demonstrates Widespread Network Differences and Predicts Clinical Variables in Temporal Lobe Epilepsy

Understanding how global brain networks are affected in epilepsy may elucidate the pathogenesis of seizures and its accompanying neurobehavioral comorbidities. We investigated functional changes within neural networks in temporal lobe epilepsy (TLE) using graph theory analysis of resting-state connectivity. Twenty-seven TLE presurgical patients (age 41.0 ± 12.3 years) and 85 age, gender, and handedness equivalent healthy controls (HCs; age 39.7 ± 16.9 years) were enrolled. Eyes-closed resting-state functional magnetic resonance image scans were analyzed to compare network properties and functional connectivity (FC) changes. TLE subjects showed significantly higher global efficiency, lower clustering coefficient ratio, and lower shortest path lengths ratio than HCs, as an indication of a more synchronized, yet less segregated network. A trend of functional reorganization with a shift of network hubs to the contralateral hemisphere was noted in TLE subjects. Support vector machine (SVM) with linear kernel was trained to separate between neural networks in TLE and HC subjects based on graph measurements. SVM analysis allowed separation between TLE and HC networks with 80.66% accuracy using eight features of graph measurements. Support vector regression (SVR) was used to predict neurocognitive performance from graph metrics. An SVR linear predictor showed discriminative prediction accuracy for four key neurocognitive variables in TLE (absolute R value range: 0.61-0.75). Despite TLE, our results showed both local and global network topology differences that reflect widespread alterations in FC in TLE. Network differences are discriminative between TLE and HCs using data-driven analysis and predicted severity of neurocognitive sequelae in our cohort.

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.

Altered effective connectivity network in patients with insular epilepsy: A high-frequency oscillations magnetoencephalography study

OBJECTIVE

The project aimed to determine the alterations in the effective connectivity (EC) neural network in patients with insular epilepsy based on interictal high-frequency oscillations (HFOs) from magnetoencephalography (MEG) data.

METHODS

We studied MEG data from 22 insular epilepsy patients and 20 normal subjects. Alterations in spatial pattern and connection properties of the patients with insular epilepsy were investigated in the entire brain network and insula-based network.

RESULTS

Analyses of the parameters of graph theory revealed the over-connectivity and small-world configuration of the global connectivity patterns observed in the patients. In the insula-based network, the insular cortex ipsilateral to the seizure onset displayed increased efferent and afferentEC. Left insular epilepsy featured strong connectivity with the bilateral hemispheres, whereas right insular epilepsy featured increased connectivity with only the ipsilateral hemisphere.

CONCLUSIONS

Patients with insular epilepsy display alterations in the EC network in terms of both whole-brain connectivity and the insula-based network during interictal HFOs.

SIGNIFICANCE

Alterations of interictal HFO-based networks provide evidence that epilepsy networks, instead of epileptic foci, play a key role in the complex pathophysiological mechanisms of insular epilepsy. The dysfunction of HFO networks may prove to be a novel promising biomarker and the cause of interictal brain dysfunctions in insular epilepsy.

Comparison of manual and automated fiber quantification tractography in patients with temporal lobe epilepsy

•

Tractography approaches showed moderate to good agreement for tract morphology.

•

Along- and whole-tract diffusivity was significantly correlated across approaches.

•

Whole-tract AFQ but not manual tract diffusivity correlated with clinical variables.

•

Absence of excellent agreement between approaches warrants caution.

Objective

To investigate the agreement between manually and automatically generated tracts from diffusion tensor imaging (DTI) in patients with temporal lobe epilepsy (TLE). Whole and along-the-tract diffusivity metrics and correlations with patient clinical characteristics were analyzed with respect to tractography approach.

Methods

We recruited 40 healthy controls and 24 patients with TLE who underwent conventional T1-weighted imaging and 60-direction DTI. An automated (Automated Fiber Quantification, AFQ) and manual (TrackVis) deterministic tractography approach was used to identify the uncinate fasciculus (UF) and parahippocampal white matter bundle (PHWM). Tract diffusion scalar metrics were analyzed with respect to agreement across automated and manual approaches (Dice Coefficient and Spearman correlations), to side of onset of epilepsy and patient clinical characteristics, including duration of epilepsy, age of onset and presence of hippocampal sclerosis.

Results

Across approaches the analysis of tract morphology similarity revealed Dice coefficients at moderate to good agreement (0.54 - 0.6) and significant correlations between diffusion values (Spearman's Rho=0.4–0.9). However, within bilateral PHWM, AFQ yielded significantly lower FA (left: Z = 4.4, p<0.001; right: Z = 5.1, p<0.001) and higher MD values (left: Z=-4.7, p<0.001; right: Z=-3.7, p<0.001) compared to the manual approach. Whole tract DTI metrics determined using AFQ were significantly correlated with patient characteristics, including age of epilepsy onset in FA (R = 0.6, p = 0.02) and MD of the ipsilateral PHWM (R=-0.6, p = 0.02), while duration of epilepsy corrected for age correlated with MD in ipsilateral PHWM (R = 0.7, p<0.01). Correlations between clinical metrics and diffusion values extracted using the manual whole tract technique did not survive correction for multiple comparisons. Both manual and automated along-the-tract analyses demonstrated significant correlations with patient clinical characteristics such as age of onset and epilepsy duration. The strongest and most widespread localized ipsi- and contralateral diffusivity alterations were observed in patients with left TLE and patients with HS compared to controls, while patients with right TLE and patients without HS did not show these strong effects.

Conclusions

Manual and AFQ tractography approaches revealed significant correlations in the reconstruction of tract morphology and extracted whole and along-tract diffusivity values. However, as non-identical methods they differed in the respective yield of significant results across clinical correlations and group-wise statistics. Given the absence of excellent agreement between manual and AFQ techniques as demonstrated in the present study, caution should be considered when using AFQ particularly when used without reference to benchmark manual measures.

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.

Relationship Between Seizure Frequency and Functional Abnormalities in Limbic Network of Medial Temporal Lobe Epilepsy

Background: We compared resting-state functional connectivity (RSFC) among limbic and temporal lobe regions between patients with medial temporal lobe epilepsy (mTLE) and healthy control subjects to identify imaging evidence of functional networks related to seizure frequency, age of seizure onset, and duration of epilepsy.

Methods: Twelve patients with drug-resistant, unilateral medial temporal lobe epilepsy and 12 healthy control subjects matched for age, sex, and handedness participated in the imaging experiments. We used network-based statistics to compare functional connectivity graphs in patients with mTLE and healthy controls to investigate the relationship between functional connectivity abnormalities and seizure frequency.

Results: Among mTLE patients, we found functional network abnormalities throughout the limbic system, but primarily in the hemisphere ipsilateral to the seizure focus. The RSFCs between ipsilateral hypothalamus and ventral anterior cingulate cortex and between ipsilateral subiculum and contralateral posterior cingulate cortex were highly correlated with seizure frequency.

Discussion: These findings suggest that in mTLE, changes in limbic networks ipsilateral to the epileptic focus are common. The pathological changes in connectivity between cingulate cortex, hypothalamus and subiculum ipsilateral to the seizure focus were correlated with increased seizure frequency.

Reduced Interhemispheric White Matter Asymmetries in Medial Temporal Lobe Epilepsy With Hippocampal Sclerosis

Mesial temporal lobe epilepsy (MTLE), one of the most common types of refractory focal epilepsy, has shown white matter abnormalities both within and beyond the temporal lobe. In particular, the white matter abnormalities in the ipsilateral hemisphere are more obvious than those in the contralateral hemisphere in MTLE, that is, the abnormalities present asymmetrical characteristics. However, very few studies have characterized the white matter microstructure asymmetry in MTLE patients specifically. Thus, we performed diffusion tensor imaging (DTI) to investigate the white matter microstructure asymmetries of patients with MTLE with unilateral hippocampal sclerosis (MTLE-HS). We enrolled 25 MTLE-HS (left MTLE-HS group, n = 13; right MTLE-HS group, n = 12) and 26 healthy controls (HC). DTI data were analyzed by tract-based spatial statistics (TBSS) to test the hemispheric differences across the entire white matter skeleton. We also conducted a two-sample paired t-test for 21 paired region of interests (ROIs) parceled on the basis of the ICBM-DTI-81 white-matter label atlas of bilateral hemispheres to test the hemispheric differences. An asymmetry index (AI) was calculated to further quantify the differences between the left and right paired-ROIs. It was found that the asymmetries of white matter skeletons were significantly lower in the MTLE-HS groups than in the HC group. In particular, the asymmetry traits were moderately reduced in the RMTLE-HS group and obviously reduced in the LMTLE-HS group. In addition, AI was significantly different in the RMTLE-HS group from the LMTLE-HS or HC group in the limbic system and superior longitudinal fasciculus (SLF). The current study found that the interhemispheric white matter asymmetries were significantly reduced in the MTLE-HS groups than in the HC group. The interhemispheric white matter asymmetries are distinctly affected in left and right MTLE-HS groups. The differences in AI among RMTLE-HS, LMTLE-HS, and HC involved the limbic system and SLF, which may have some pragmatic implications for the diagnosis of MTLE and differentiating LMTLE-HS from RMTLE-HS.

Metabolic covariance networks combining graph theory measuring aberrant topological patterns in mesial temporal lobe epilepsy

OBJECTIVE

We aimed to study the networks' mechanism of metabolic covariance networks in mesial temporal lobe epilepsy (mTLE), through examining the brain value of fluorine-18-fluorodeoxyglucose positron emission tomography (18 F-FDG-PET).

METHODS

18 F-FDG-PET images from 16 patients with mTLE were analyzed using local and global metabolic covariance network (MCN) approaches, including whole metabolic pattern analysis (WMPA), hippocampus-based (h-) MCN, whole brain (w-) MCN, and edge-based connectivity analysis (EBCA).

RESULTS

WMPA showed a typical ipsilateral hypometabolism and contralateral hypermetabolism pattern to epileptic zones in mTLE. h-MCN revealed decreased hippocampus-based synchronization in contralateral regions. w-MCN exhibited a disrupted metabolic network with globally increased small-world properties and regionally decreased nodal metrics in the ipsilateral hemisphere. Hippocampus (h)-EBCA and whole brain EBCA (w-EBCA) both detected a reduced-connectivity dominated metabolic covariant network. Moreover, the reduced interhemisphere connectivity seemingly played a major role in the aberrant epileptic topological pattern.

CONCLUSION

From a metabolic point of view, we demonstrated the damaging effects with reduced contralateral intranetwork metrics properties and the compensatory effects in contralateral intranetworks with increased network properties. However, the import role of significant reduced interhemisphere connection has rarely been reported in other mTLE studies. Taken together, 18 F-FDG-PET MCN analysis provides new evidence that the mTLE is a system neurological disorder with disrupted networks.

The Dilemma of the Chicken or the Egg-What Appears First in TLE-Seizures or Morphometric Changes in the Temporal Lobe?

Abnormal Temporal Lobe Morphology in Asymptomatic Relatives of Patients With Hippocampal Sclerosis: A Replication Study Yaakub SN, Barker GJ, Carr SJ, et al. Epilepsia. 2019;60(1):e1-e5. doi:10.1111/epi.14575. We investigated gray and white matter morphology in patients with mesial temporal lobe epilepsy with hippocampal sclerosis (mTLE + HS) and first-degree asymptomatic relatives of patients with mTLE+HS. Using T1-weighted magnetic resonance imaging (MRI), we sought to replicate previously reported findings of structural surface abnormalities of the anterior temporal lobe in asymptomatic relatives of patients with mTLE+HS in an independent cohort. We performed whole-brain MRI in 19 patients with mTLE+HS, 14 first-degree asymptomatic relatives of patients with mTLE+HS, and 32 healthy control participants. Structural alterations in patients and relatives compared to controls were assessed using automated hippocampal volumetry and cortical surface-based morphometry. We replicated previously reported cortical surface area contractions in the ipsilateral anterior temporal lobe in both patients and relatives compared to healthy controls, with asymptomatic relatives showing similar but less extensive changes than patients. These findings suggest morphologic abnormality in asymptomatic relatives of patients with mTLE+HS, suggesting an inherited brain structure endophenotype.

Temporal lobe epilepsy affects spatial organization of entorhinal cortex connectivity

Evidence for structural connectivity patterns within the medial temporal lobe derives primarily from postmortem histological studies. In humans and nonhuman primates, the parahippocampal gyrus (PHg) is subdivided into parahippocampal (PHc) and perirhinal (PRc) cortices, which receive input from distinct cortical networks. Likewise, their efferent projections to the entorhinal cortex (ERc) are distinct. The PHc projects primarily to the medial ERc (M-ERc). The PRc projects primarily to the lateral portion of the ERc (L-ERc). Both M-ERc and L-ERc, via the perforant pathway, project to the dentate gyrus and hippocampal (HC) subfields. Until recently, these neural circuits could not be visualized in vivo. Diffusion tensor imaging algorithms have been developed to segment gray matter structures based on probabilistic connectivity patterns. However, these algorithms have not yet been applied to investigate connectivity in the temporal lobe or changes in connectivity architecture related to disease processes. In this study, this segmentation procedure was used to classify ERc gray matter based on PRc, ERc, and HC connectivity patterns in 7 patients with temporal lobe epilepsy (TLE) without hippocampal sclerosis (mean age, 14.86 ± 3.34 years) and 7 healthy controls (mean age, 23.86 ± 2.97 years). Within samples paired t-tests allowed for comparison of ERc connectivity between epileptogenic and contralateral hemispheres. In healthy controls, there were no significant within-group differences in surface area, volume, or cluster number of ERc connectivity-defined regions (CDR). Likewise, in line with histology results, ERc CDR in the control group were well-organized, uniform, and segregated via PRc/PHc afferent and HC efferent connections. Conversely, in TLE, there were significantly more PRc and HC CDR clusters in the epileptogenic than the contralateral hemisphere. The surface area of the PRc CDR was greater, and that of the HC CDRs was smaller, in the epileptogenic hemisphere as well. Further, there was no clear delineation between M-ERc and L-ERc connectivity with PRc, PHc or HC in TLE. These results suggest a breakdown of the spatial organization of PHg-ERc-HC connectivity in TLE. Whether this breakdown is the cause or result of epileptic activity remains an exciting research question.

Widespread white matter DTI alterations in mesial temporal sclerosis independent of disease side

PURPOSE

The aim of this study was to evaluate white matter (WM) integrity in vivo in patients with unilateral mesial temporal sclerosis (MTS).

METHODS

Diffusion tensor imaging (DTI) findings from patients with left-sided MTS (L-MTS; N = 14) and right-sided MTS (R-MTS; N = 13), all taking antiepileptic medication, were compared with those from gender- and age-matched controls; DTI was performed along 30 noncollinear directions in a 1.5-T scanner. Tract-based spatial statistics (TBSS) analysis was performed by creating a WM skeleton; 5000-permutation-based inference (threshold, p < 0.05) was used to identify fractional anisotropy (FA) abnormalities. Mean (MD), radial (RD), and axial diffusivities (AD) were projected onto the mean FA skeleton.

RESULTS

Compared with the control groups, patients with MTS had decreased FA affecting widespread WM tracts as well as extensive areas with increased RD, bilaterally and independent of the disease side. Areas with decreased FA and increased RD overlapped substantially. There were no significant differences in DTI parameters between L-MTS and R-MTS patients.

CONCLUSION

Diffusion tensor imaging abnormalities were observed within and beyond the temporal lobe in patients with MTS. Patients with R- and L-MTS had extensive bilateral abnormalities in comparison to controls. These findings suggest that MTS pathobiology involves diffuse dysfunction of WM tracts, even in areas with no direct connections to the hippocampus.

Connectivity-based parcellation of the nucleus accumbens into core and shell portions for stereotactic target localization and alterations in each NAc subdivision in mTLE patients

The nucleus accumbens (NAc), an important target of deep brain stimulation for some neuropsychiatric disorders, is thought to be involved in epileptogenesis, especially the shell portion. However, little is known about the exact parcellation within the NAc, and its structural abnormalities or connections alterations of each NAc subdivision in temporal lobe epilepsy (TLE) patients. Here, we used diffusion probabilistic tractography to subdivide the NAc into core and shell portions in individual TLE patients to guide stereotactic localization of NAc shell. The structural and connection abnormalities in each NAc subdivision in the groups were then estimated. We successfully segmented the NAc in 24 of 25 controls, 14 of 16 left TLE patients, and 14 of 18 right TLE patients. Both left and right TLE patients exhibited significantly decreased fractional anisotropy (FA) and increased radial diffusivity (RD) in the shell, while there was no significant alteration in the core. Moreover, relatively distinct structural connectivity of each NAc subdivision was demonstrated. More extensive connection abnormalities were detected in the NAc shell in TLE patients. Our results indicate that neuronal degeneration and damage caused by seizure mainly exists in NAc shell and provide anatomical evidence to support the role of NAc shell in epileptogenesis. Remarkably, those NAc shell tracts with increased connectivities in TLE patients were found decreased in FA, which indicates disruption of fiber integrity. This finding suggests the regeneration of aberrant connections, a compensatory and repair process ascribed to recurrent seizures that constitutes part of the characteristic changes in the epileptic network.

Using machine learning to classify temporal lobe epilepsy based on diffusion MRI

BACKGROUND

It is common for patients diagnosed with medial temporal lobe epilepsy (TLE) to have extrahippocampal damage. However, it is unclear whether microstructural extrahippocampal abnormalities are consistent enough to enable classification using diffusion MRI imaging. Therefore, we implemented a support vector machine (SVM)-based method to predict TLE from three different imaging modalities: mean kurtosis (MK), mean diffusivity (MD), and fractional anisotropy (FA). While MD and FA can be calculated from traditional diffusion tensor imaging (DTI), MK requires diffusion kurtosis imaging (DKI).

METHODS

Thirty-two TLE patients and 36 healthy controls underwent DKI imaging. To measure predictive capability, a fivefold cross-validation (CV) was repeated for 1000 iterations. An ensemble of SVM models, each with a different regularization value, was trained with the subject images in the training set, and had performance assessed on the test set. The different regularization values were determined using a Bayesian-based method.

RESULTS

Mean kurtosis achieved higher accuracy than both FA and MD on every iteration, and had far superior average accuracy: 0.82 (MK), 0.68 (FA), and 0.51 (MD). Finally, the MK voxels with the highest coefficients in the predictive models were distributed within the inferior medial aspect of the temporal lobes.

CONCLUSION

These results corroborate our earlier publications which indicated that DKI shows more promise in identifying TLE-associated pathological features than DTI. Also, the locations of the contributory MK voxels were in areas with high fiber crossing and complex fiber anatomy. These traits result in non-Gaussian water diffusion, and hence render DTI less likely to detect abnormalities. If the location of consistent microstructural abnormalities can be better understood, then it may be possible in the future to identify the various phenotypes of TLE. This is important since treatment outcome varies dependent on type of TLE.

Neuroanatomical Changes in Brain Structures Related to Cognition in Epilepsy: An Update

Understanding the microanatomical changes in brain structures is necessary for developing innovative therapeutic approaches to prevent/delay the cognitive impairment in epilepsy. We review here the microanatomical changes in the brain structures related to cognition in epilepsy. Here, we have presented the changes in major brain structures related to cognition, which helps the clinicians understand epilepsy more clearly and also helps researchers develop new treatment procedures.

Disrupted Structural and Functional Networks and Their Correlation with Alertness in Right Temporal Lobe Epilepsy: A Graph Theory Study

Previous studies have shown that temporal lobe epilepsy (TLE) involves abnormal structural or functional connectivity in specific brain areas. However, limited comprehensive studies have been conducted on TLE associated changes in the topological organization of structural and functional networks. Additionally, epilepsy is associated with impairment in alertness, a fundamental component of attention. In this study, structural networks were constructed using diffusion tensor imaging tractography, and functional networks were obtained from resting-state functional MRI temporal series correlations in 20 right temporal lobe epilepsy (rTLE) patients and 19 healthy controls. Global network properties were computed by graph theoretical analysis, and correlations were assessed between global network properties and alertness. The results from these analyses showed that rTLE patients exhibit abnormal small-world attributes in structural and functional networks. Structural networks shifted toward more regular attributes, but functional networks trended toward more random attributes. After controlling for the influence of the disease duration, negative correlations were found between alertness, small-worldness, and the cluster coefficient. However, alertness did not correlate with either the characteristic path length or global efficiency in rTLE patients. Our findings show that disruptions of the topological construction of brain structural and functional networks as well as small-world property bias are associated with deficits in alertness in rTLE patients. These data suggest that reorganization of brain networks develops as a mechanism to compensate for altered structural and functional brain function during disease progression.

Distinctive Structural and Effective Connectivity Changes of Semantic Cognition Network across Left and Right Mesial Temporal Lobe Epilepsy Patients

Occurrence of language impairment in mesial temporal lobe epilepsy (mTLE) patients is common and left mTLE patients always exhibit a primary problem with access to names. To explore different neuropsychological profiles between left and right mTLE patients, the study investigated both structural and effective functional connectivity changes within the semantic cognition network between these two groups and those from normal controls. We found that gray matter atrophy of left mTLE patients was more severe than that of right mTLE patients in the whole brain and especially within the semantic cognition network in their contralateral hemisphere. It suggested that seizure attacks were rather targeted than random for patients with hippocampal sclerosis (HS) in the dominant hemisphere. Functional connectivity analysis during resting state fMRI revealed that subregions of the anterior temporal lobe (ATL) in the left HS patients were no longer effectively connected. Further, we found that, unlike in right HS patients, increased causal linking between ipsilateral regions in the left HS epilepsy patients cannot make up for their decreased contralateral interaction. It suggested that weakened contralateral connection and disrupted effective interaction between subregions of the unitary, transmodal hub of the ATL may be the primary cause of anomia in the left HS patients.

Hippocampus-associated causal network of structural covariance measuring structural damage progression in temporal lobe epilepsy

In mesial temporal lobe epilepsy (mTLE), the causal relationship of morphometric alterations between hippocampus and the other regions, that is, how the hippocampal atrophy leads to progressive morphometric alterations in the epileptic network regions remains largely unclear. In this study, a causal network of structural covariance (CaSCN) was proposed to map the causal effects of hippocampal atrophy on the network-based morphometric alterations in mTLE. It was hypothesized that if cross-sectional morphometric MRI data could be attributed temporal information, for example, by sequencing the data according to disease progression information, GCA would be a feasible approach for constructing a CaSCN. Based on a large cohort of mTLE patients (n = 108), the hippocampus-associated CaSCN revealed that the hippocampus and the thalamus were prominent nodes exerting causal effects (i.e., GM reduction) on other regions and that the prefrontal cortex and cerebellum were prominent nodes being subject to causal effects. Intriguingly, compensatory increased gray matter volume in the contralateral temporal region and post cingulate cortex were also detected. The method unraveled richer information for mapping network atrophy in mTLE relative to the traditional methods of stage-specific comparisons and structured covariance network. This study provided new evidence on the network spread mechanism in terms of the causal influence of hippocampal atrophy on progressive brain structural alterations in mTLE. Hum Brain Mapp 38:753-766, 2017. © 2016 Wiley Periodicals, Inc.

Age at onset and seizure frequency affect white matter diffusion coefficient in patients with mesial temporal lobe epilepsy

In mesial temporal lobe epilepsy with hippocampal sclerosis (MTLE-HS), structural abnormalities are present not only in the hippocampus but also in the white matter with ipsilateral predominance. Although the timing of epilepsy onset is commonly associated with clinical and semiological dissimilarities, limited data exist regarding white matter diffusion changes with respect to age at epilepsy onset. The aim of this study was to investigate diffusion changes in the white matter of patients with unilateral MTLE-HS with respect to clinical parameters and to compare them with an age- and sex-matched healthy control group. Apparent diffusion coefficients (ADCs) were derived using monoexponential approaches from 22 (11 early and 11 late age at onset) patients with unilateral MTLE-HS and 22 age- and sex-matched control subjects after acquiring diffusion-weighted images on a 3T MRI system. Data were analyzed using two-tailed t-tests and multiple linear regression models. In the group with early onset MTLE-HS, ADC was significantly elevated in the ipsilateral hemispheric (p=0.04) and temporal lobe white matter (p=0.01) compared with that in controls. These differences were not detectable in late onset MTLE-HS patients. Apparent diffusion coefficient of the group with early onset MTLE-HS was negatively related to age at epilepsy onset in the ipsilateral hemispheric white matter (p=0.03) and the uncinate fasciculus (p=0.03), while in patients with late onset MTLE-HS, ADC was no longer dependent on age at epilepsy onset itself but rather on the seizure frequency in the ipsilateral uncinate fasciculus (p=0.03). Such diffusivity pattern has been associated with chronic white matter degeneration, reflecting myelin loss and higher extracellular volume which are more pronounced in the frontotemporal regions and also depend on clinical features. In the group with early onset MTLE-HS, the timing of epilepsy seems to be the major cause of white matter abnormalities while in late onset disease, it has a secondary role in provoking diffusion changes.

Asymmetric Gray Matter Volume Changes Associated with Epilepsy Duration and Seizure Frequency in Temporal-Lobe-Epilepsy Patients with Favorable Surgical Outcome

Background and Purpose

This study aimed to estimate the changes in gray matter volume (GMV) and their hemispheric difference in patients with mesial temporal lobe epilepsy (MTLE) using a voxel-based morphometry (VBM) methodology, and to determine whether GMV changes are correlated with clinical features.

Methods

VBM analysis of brain MRI using statistical parametric mapping 8 (SPM8) was performed for 30 left MTLE (LMTLE) and 30 right MTLE (RMTLE) patients and 30 age- and sex-matched healthy controls. We also analyzed the correlations between GMV changes and clinical features of MTLE patients.

Results

In SPM8-based analyses, MTLE patients showed significant GMV reductions in the hippocampus ipsilateral to the epileptic focus, bilateral thalamus, and contralateral putamen in LMTLE patients. The GMV reductions were more extensive in the ipsilateral hippocampus, thalamus, caudate, putamen, uncus, insula, inferior temporal gyrus, middle occipital gyrus, cerebellum, and paracentral lobule in RMTLE patients. These patients also exhibited notable reductions of GMV in the contralateral hippocampus, thalamus, caudate, putamen, and inferior frontal gyrus. We observed that GMV reduction was positively correlated with several clinical features (epilepsy duration and seizure frequency in RMTLE, and history of febrile seizure in LMTLE) and negatively correlated with seizure onset age in both the RMTLE and LMTLE groups.

Conclusions

Our study revealed GMV decreases in the hippocampus and extrahippocampal regions. Furthermore, the GMV reduction was more extensive in the RMTLE group than in the LMTLE group, since it included the contralateral hemisphere in the former. This difference in the GMV reduction patterns between LMTLE and RMTLE may be related to a longer epilepsy duration and higher seizure frequency in the latter.

Increased MRI volumetric correlation contralateral to seizure focus in temporal lobe epilepsy

Quantification of volumetric correlation may be sensitive to disease alterations undetected by standard voxel based morphometry (VBM) such as subtle, synchronous alterations in regional volumes, and may provide complementary evidence of the structural impact of temporal lobe epilepsy (TLE) on the brain. The purpose of this study was to quantify differences of regional volumetric correlation in right (RTLE) and left (LTLE) TLE patients compared to healthy controls. A T1 weighted 3T MRI was acquired (1mm(3)) in 44 drug resistant unilateral TLE patients (n=26 RTLE, n=18 LTLE) and 44 individually age and gender matched healthy controls. Images were processed using a standard VBM framework and volumetric correlation was calculated across subjects in 90 regions and compared between patients and controls. Results were summarized across hemispheres and region groups. There was increased correlation involving the contralateral homologues of the seizure foci/network in the limbic, subcortical and temporal regions in both RTLE and LTLE. Outside these regions, results implied widespread correlated alterations across several contralateral lobes in LTLE, with more focal changes in RTLE. These findings complement previous volumetric studies in TLE describing more ipsilateral atrophy, by revealing subtle coordinated volumetric changes to identify a more widespread effect of TLE across the brain.

Subregional Mesiotemporal Network Topology Is Altered in Temporal Lobe Epilepsy

Temporal lobe epilepsy (TLE) is the most frequent drug-resistant epilepsy in adults and commonly associated with variable degrees of mesiotemporal atrophy on magnetic resonance imaging (MRI). Analyses of inter-regional connectivity have unveiled disruptions in large-scale cortico-cortical networks; little is known about the topological organization of the mesiotemporal lobe, the limbic subnetwork central to the disorder. We generated covariance networks based on high-resolution MRI surface-shape descriptors of the hippocampus, entorhinal cortex, and amygdala in 134 TLE patients and 45 age- and sex-matched controls. Graph-theoretical analysis revealed increased path length and clustering in patients, suggesting a shift toward a more regularized arrangement; findings were reproducible after split-half assessment and across 2 parcellation schemes. Analysis of inter-regional correlations and module participation showed increased within-structure covariance, but decreases between structures, particularly with regards to the hippocampus and amygdala. While higher clustering possibly reflects topological consequences of axonal sprouting, decreases in interstructure covariance may be a consequence of disconnection within limbic circuitry. Preoperative network parameters, specifically the segregation of the ipsilateral hippocampus, predicted long-term seizure freedom after surgery.

Aberrant topological patterns of brain structural network in temporal lobe epilepsy

OBJECTIVE

Although altered large-scale brain network organization in patients with temporal lobe epilepsy (TLE) has been shown using morphologic measurements such as cortical thickness, these studies, have not included critical subcortical structures (such as hippocampus and amygdala) and have had relatively small sample sizes. Here, we investigated differences in topological organization of the brain volumetric networks between patients with right TLE (RTLE) and left TLE (LTLE) with unilateral hippocampal atrophy.

METHODS

We performed a cross-sectional analysis of 86 LTLE patients, 70 RTLE patients, and 116 controls. RTLE and LTLE groups were balanced for gender (p = 0.64), seizure frequency (Mann-Whitney U test, p = 0.94), age (p = 0.39), age of seizure onset (p = 0.21), and duration of disease (p = 0.69). Brain networks were constructed by thresholding correlation matrices of volumes from 80 cortical/subcortical regions (parcellated with Freesurfer v5.3 https://surfer.nmr.mgh.harvard.edu/) that were then analyzed using graph theoretical approaches.

RESULTS

We identified reduced cortical/subcortical connectivity including bilateral hippocampus in both TLE groups, with the most significant interregional correlation increases occurring within the limbic system in LTLE and contralateral hemisphere in RTLE. Both TLE groups demonstrated less optimal topological organization, with decreased global efficiency and increased local efficiency and clustering coefficient. LTLE also displayed a more pronounced network disruption. Contrary to controls, hub nodes in both TLE groups were not distributed across whole brain, but rather found primarily in the paralimbic/limbic and temporal association cortices. Regions with increased centrality were concentrated in occipital lobes for LTLE and contralateral limbic/temporal areas for RTLE.

SIGNIFICANCE

These findings provide first evidence of altered topological organization of the whole brain volumetric network in TLE, with disruption of the coordinated patterns of cortical/subcortical morphology.

Functional substrate for memory function differences between patients with left and right mesial temporal lobe epilepsy associated with hippocampal sclerosis

OBJECTIVE

Little is known about the functional substrate for memory function differences in patients with left or right mesial temporal lobe epilepsy (mTLE) associated with hippocampal sclerosis (HS) from an electrophysiological perspective. To characterize these differences, we hypothesized that hippocampal theta connectivity in the resting-state might be different between patients with left and right mTLE with HS and be correlated with memory performance.

METHODS

Resting-state hippocampal theta connectivity, identified via whole-brain magnetoencephalography, was evaluated. Connectivity and memory function in 41 patients with mTLE with HS (left mTLE=22; right mTLE=19) were compared with those in 46 age-matched healthy controls and 28 patients with focal cortical dysplasia (FCD) but without HS.

RESULTS

Connectivity between the right hippocampus and the left middle frontal gyrus was significantly stronger in patients with right mTLE than in patients with left mTLE. Moreover, this connectivity was positively correlated with delayed verbal recall and recognition scores in patients with mTLE. Patients with left mTLE had greater delayed recall impairment than patients with right mTLE and FCD. Similarly, delayed recognition performance was worse in patients with left mTLE than in patients with right mTLE and FCD. No significant differences in memory function between patients with right mTLE and FCD were detected. Patients with right mTLE showed significantly stronger hippocampal theta connectivity between the right hippocampus and left middle frontal gyrus than patients with FCD and left mTLE.

CONCLUSION

Our results suggest that right hippocampal-left middle frontal theta connectivity could be a functional substrate that can account for differences in memory function between patients with left and right mTLE. This functional substrate might be related to different compensatory mechanisms against the structural hippocampal lesions in left and right mTLE groups. Given the positive correlation between connectivity and delayed verbal memory function, hemispheric-specific hippocampal-frontal theta connectivity assessment could be useful as an electrophysiological indicator of delayed verbal memory function in patients with mTLE with HS.

Network analysis for a network disorder: The emerging role of graph theory in the study of epilepsy

Recent years have witnessed a paradigm shift in the study and conceptualization of epilepsy, which is increasingly understood as a network-level disorder. An emblematic case is temporal lobe epilepsy (TLE), the most common drug-resistant epilepsy that is electroclinically defined as a focal epilepsy and pathologically associated with hippocampal sclerosis. In this review, we will summarize histopathological, electrophysiological, and neuroimaging evidence supporting the concept that the substrate of TLE is not limited to the hippocampus alone, but rather is broadly distributed across multiple brain regions and interconnecting white matter pathways. We will introduce basic concepts of graph theory, a formalism to quantify topological properties of complex systems that has recently been widely applied to study networks derived from brain imaging and electrophysiology. We will discuss converging graph theoretical evidence indicating that networks in TLE show marked shifts in their overall topology, providing insight into the neurobiology of TLE as a network-level disorder. Our review will conclude by discussing methodological challenges and future clinical applications of this powerful analytical approach.

Predicting the laterality of temporal lobe epilepsy from PET, MRI, and DTI: A multimodal study

Pre-surgical evaluation of patients with temporal lobe epilepsy (TLE) relies on information obtained from multiple neuroimaging modalities. The relationship between modalities and their combined power in predicting the seizure focus is currently unknown. We investigated asymmetries from three different modalities, PET (glucose metabolism), MRI (cortical thickness), and diffusion tensor imaging (DTI; white matter anisotropy) in 28 left and 30 right TLE patients (LTLE and RTLE). Stepwise logistic regression models were built from each modality separately and from all three combined, while bootstrapped methods and split-sample validation verified the robustness of predictions. Among all multimodal asymmetries, three PET asymmetries formed the best predictive model (100% success in full sample, >95% success in split-sample validation). The combinations of PET with other modalities did not perform better than PET alone. Probabilistic classifications were obtained for new clinical cases, which showed correct lateralization for 7/7 new TLE patients (100%) and for 4/5 operated patients with discordant or non-informative PET reports (80%). Metabolism showed closer relationship with white matter in LTLE and closer relationship with gray matter in RTLE. Our data suggest that metabolism is a powerful modality that can predict seizure laterality with high accuracy, and offers high value for automated predictive models. The side of epileptogenic focus can affect the relationship of metabolism with brain structure. The data and tools necessary to obtain classifications for new TLE patients are made publicly available.

Increased Intrinsic Connectivity of the Default Mode Network in Temporal Lobe Epilepsy: Evidence from Resting-State MEG Recordings

The electrophysiological signature of resting state oscillatory functional connectivity within the default mode network (DMN) during spike-free periods in temporal lobe epilepsy (TLE) remains unclear. Using magnetoencephalographic (MEG) recordings, this study investigated how the connectivity within the DMN was altered in TLE, and we examined the effect of lateralized TLE on functional connectivity. Sixteen medically intractable TLE patients and 22 controls participated in this study. Whole-scalp 306-channel MEG epochs without interictal spikes generated from both MEG and EEG data were analyzed using a minimum norm estimate (MNE) and source-based imaginary coherence analysis. With this processing, we obtained the cortical activation and functional connectivity within the DMN. The functional connectivity was increased between DMN and the right medial temporal (MT) region at the delta band and between DMN and the bilateral anterior cingulate cortex (ACC) regions at the theta band. The functional change was associated with the lateralization of TLE. The right TLE showed enhanced DMN connectivity with the right MT while the left TLE demonstrated increased DMN connectivity with the bilateral MT. There was no lateralization effect of TLE upon the DMN connectivity with ACC. These findings suggest that the resting-state functional connectivity within the DMN is reinforced in temporal lobe epilepsy during spike-free periods. Future studies are needed to examine if the altered functional connectivity can be used as a biomarker for treatment responses, cognitive dysfunction and prognosis in patients with TLE.

Mesial temporal lobe epilepsy with hippocampal sclerosis is a network disorder with altered cortical hubs

OBJECTIVE

Electrophysiologic hubs within the large-scale functional networks in mesial temporal lobe epilepsy (mTLE) with hippocampal sclerosis (HS) have not been investigated. We hypothesized that mTLE with HS has different resting-state network hubs in their large-scale functional networks compared to the hubs in healthy controls (HC). We also hypothesized that the hippocampus would be a functional hub in mTLE patients with HS.

METHODS

Resting-state functional networks, identified by using magnetoencephalography (MEG) signals in the theta, alpha, beta, and gamma frequency bands, were evaluated. Networks in 44 mTLE patients with HS (left mTLE = 22; right mTLE = 22) were compared with those in 46 age-matched HC. We investigated betweenness centrality at the source-level MEG network.

RESULTS

The main network hubs were at the pole of the left superior temporal gyrus in the beta band, the pole of the left middle temporal gyrus in the beta and gamma bands, left hippocampus in the theta and alpha bands, and right posterior cingulate gyrus in all four frequency bands in mTLE patients; all of which were different from the main network hubs in HC. Only patients with left mTLE showed profound differences from HC at the left hippocampus in the alpha band.

SIGNIFICANCE

Our analysis of resting-state MEG signals shows that altered electrophysiologic functional hubs in mTLE patients reflect pathophysiologic brain network reorganization. Because we detected network hubs in both hippocampal and extrahippocampal areas, it is probable that mTLE is a large-scale network disorder rather than a focal disorder. The hippocampus was a network hub in left mTLE but not in right mTLE patients, which may be due to intrinsic functional and structural asymmetries between left and right mTLE patients. The evaluation of cortical hubs, even in the spike-free resting-state, could be a clinical diagnostic marker of mTLE with HS.

Magnetic resonance imaging and histology correlation in the neocortex in temporal lobe epilepsy

OBJECTIVE

To investigate the histopathological correlates of quantitative relaxometry and diffusion tensor imaging (DTI) and to determine their efficacy in epileptogenic lesion detection for preoperative evaluation of focal epilepsy.

METHODS

We correlated quantitative relaxometry and DTI with histological features of neuronal density and morphology in 55 regions of the temporal lobe neocortex, selected from 13 patients who underwent epilepsy surgery. We made use of a validated nonrigid image registration protocol to obtain accurate correspondences between in vivo magnetic resonance imaging and histology images.

RESULTS

We found T1 to be a predictor of neuronal density in the neocortical gray matter (GM) using linear mixed effects models with random effects for subjects. Fractional anisotropy (FA) was a predictor of neuronal density of large-caliber neurons only (pyramidal cells, layers 3 and 5). Comparing multivariate to univariate mixed effects models with nested variables demonstrated that employing T1 and FA together provided a significantly better fit than T1 or FA alone in predicting density of large-caliber neurons. Correlations with clinical variables revealed significant positive correlations between neuronal density and age (rs  = 0.726, pfwe  = 0.021). This study is the first to relate in vivo T1 and FA values to the proportion of neurons in GM.

INTERPRETATION

Our results suggest that quantitative T1 mapping and DTI may have a role in preoperative evaluation of focal epilepsy and can be extended to identify GM pathology in a variety of neurological disorders.

Functional network alterations and their structural substrate in drug-resistant epilepsy

The advent of MRI has revolutionized the evaluation and management of drug-resistant epilepsy by allowing the detection of the lesion associated with the region that gives rise to seizures. Recent evidence indicates marked chronic alterations in the functional organization of lesional tissue and large-scale cortico-subcortical networks. In this review, we focus on recent methodological developments in functional MRI (fMRI) analysis techniques and their application to the two most common drug-resistant focal epilepsies, i.e., temporal lobe epilepsy related to mesial temporal sclerosis and extra-temporal lobe epilepsy related to focal cortical dysplasia. We put particular emphasis on methodological developments in the analysis of task-free or “resting-state” fMRI to probe the integrity of intrinsic networks on a regional, inter-regional, and connectome-wide level. In temporal lobe epilepsy, these techniques have revealed disrupted connectivity of the ipsilateral mesiotemporal lobe, together with contralateral compensatory reorganization and striking reconfigurations of large-scale networks. In cortical dysplasia, initial observations indicate functional alterations in lesional, peri-lesional, and remote neocortical regions. While future research is needed to critically evaluate the reliability, sensitivity, and specificity, fMRI mapping promises to lend distinct biomarkers for diagnosis, presurgical planning, and outcome prediction.

Clinical correlates of graph theory findings in temporal lobe epilepsy

PURPOSE

Temporal lobe epilepsy (TLE) is considered a brain network disorder, additionally representing the most common form of pharmaco-resistant epilepsy in adults. There is increasing evidence that seizures in TLE arise from abnormal epileptogenic networks, which extend beyond the clinico-radiologically determined epileptogenic zone and may contribute to the failure rate of 30-50% following epilepsy surgery. Graph theory allows for a network-based representation of TLE brain networks using several neuroimaging and electrophysiologic modalities, and has potential to provide clinicians with clinically useful biomarkers for diagnostic and prognostic purposes.

METHODS

We performed a review of the current state of graph theory findings in TLE as they pertain to localization of the epileptogenic zone, prediction of pre- and post-surgical seizure frequency and cognitive performance, and monitoring cognitive decline in TLE.

RESULTS

Although different neuroimaging and electrophysiologic modalities have yielded occasionally conflicting results, several potential biomarkers have been characterized for identifying the epileptogenic zone, pre-/post-surgical seizure prediction, and assessing cognitive performance. For localization, graph theory measures of centrality have shown the most potential, including betweenness centrality, outdegree, and graph index complexity, whereas for prediction of seizure frequency, measures of synchronizability have shown the most potential. The utility of clustering coefficient and characteristic path length for assessing cognitive performance in TLE is also discussed.

CONCLUSIONS

Future studies integrating data from multiple modalities and testing predictive models are needed to clarify findings and develop graph theory for its clinical utility.

White matter microstructure complements morphometry for predicting verbal memory in epilepsy

Verbal memory is the most commonly impaired cognitive domain in patients with temporal lobe epilepsy (TLE). Although damage to the hippocampus and adjacent temporal lobe structures is known to contribute to memory impairment, little is known of the relative contributions of white versus gray matter structures, or whether microstructural versus morphometric measures of temporal lobe pathology are stronger predictors of impairment. We evaluate whether measures of temporal lobe pathology derived from diffusion tensor imaging (DTI; microstructural) versus structural MRI (sMRI; morphometric) contribute the most to memory performances in TLE, after controlling for hippocampal volume (HCV). DTI and sMRI were performed on 26 patients with TLE and 35 controls. Verbal memory was measured with the Logical Memory (LM) subtest of the Wechsler Memory Scale-III. Hierarchical regression analyses were performed to examine unique contributions of DTI and sMRI measures to verbal memory with HCV entered in block 1. In patients, impaired recall was associated with increased mean diffusivity (MD) of multiple fiber tracts that project through the temporal lobes. In addition, increased MD of the left cortical and bilateral pericortical white matter was associated with impaired recall. After controlling for left HCV, only microstructural measures of white matter pathology contributed to verbal recall. The best predictive model included left HCV and MD of the left inferior longitudinal fasciculus (ILF) and pericortical white matter beneath the left entorhinal cortex. This model explained 60% of the variance in delayed recall and revealed that MD of the left ILF was the strongest predictor. These data reveal that white matter microstructure within the temporal lobe can be used in conjunction with left HCV to enhance the prediction of verbal memory impairment, and speak to the complementary nature of DTI and sMRI for understanding cognitive dysfunction in epilepsy and possibly other memory disorders.