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

Metabolic connectivity as a predictor of surgical outcome in mesial temporal lobe epilepsy

OBJECTIVE

The study investigated metabolic connectivity (MC) differences between patients with unilateral drug-resistant mesial temporal lobe epilepsy (MTLE) with hippocampal sclerosis (HS) and healthy controls (HCs), based on [18 F]-fluorodeoxyglucose (FDG)-PET data. We focused on the MC changes dependent on the lateralization of the epileptogenic lobe and on correlations with postoperative outcomes.

METHODS

FDG-PET scans of 47 patients with unilateral MTLE with histopathologically proven HS and 25 HC were included in the study. All the patients underwent a standard anterior temporal lobectomy and were more than 2 years after the surgery. MC changes were compared between the two HS groups (left HS, right HS) and HC. Differences between the metabolic network of seizure-free and non-seizure-free patients after surgery were depicted afterward. Network changes were correlated with clinical characteristics.

RESULTS

The study showed widespread metabolic network changes in the HS patients as compared to HC. The changes were more extensive in the right HS than in the left HS. Unfavorable surgical outcomes were found in patients with decreased MC within the network including both the lesional and contralesional hippocampus, ipsilesional frontal operculum, and contralesional insula. Favorable outcomes correlated with decreased MC within the network involving both orbitofrontal cortices and the ipsilesional temporal lobe.

SIGNIFICANCE

There are major differences in the metabolic networks of left and right HS, with more extensive changes in right HS. The changes within the metabolic network could help predict surgical outcomes in patients with HS. MC may identify patients with potentially unfavorable outcomes and direct them to a more detailed presurgical evaluation.

PLAIN LANGUAGE SUMMARY

Metabolic connectivity is a promising method for metabolic network mapping. Metabolic networks in mesial temporal lobe epilepsy are dependent on lateralization of the epileptogenic lobe and could predict surgical outcomes.

Altered Metabolic Networks in Mesial Temporal Lobe Epilepsy with Focal to Bilateral Seizures

This study was designed to identify whether the metabolic network changes in mesial temporal lobe epilepsy (MTLE) patients with focal to bilateral tonic-clonic seizures (FBTCS) differ from changes in patients without FBTCS. This retrospective analysis enrolled 30 healthy controls and 54 total MTLE patients, of whom 27 had FBTCS. Fluorodeoxyglucose positron emission tomography (FDG-PET) data and graph theoretical analyses were used to examine metabolic connectivity. The differences in metabolic networks between the three groups were compared. Significant changes in both local and global network topology were evident in FBTCS+ patients as compared to healthy controls, with a lower assortative coefficient and altered betweenness centrality in 15 brain regions. While global network measures did not differ significantly when comparing FBTCS- patients to healthy controls, alterations in betweenness centrality were evident in 13 brain regions. Significantly altered betweenness centrality was also observed in four brain regions when comparing patients with and without FBTCS. The study revealed greater metabolic network abnormalities in MTLE patients with FBTCS as compared to FBTCS- patients, indicating the existence of distinct epileptogenic networks. These findings can provide insight into the pathophysiological basis of FBTCS.

Structural connectome alterations in anxious dogs: a DTI-based study

Anxiety and fear are dysfunctional behaviors commonly observed in domesticated dogs. Although dogs and humans share psychopathological similarities, little is known about how dysfunctional fear behaviors are represented in brain networks in dogs diagnosed with anxiety disorders. A combination of diffusion tensor imaging (DTI) and graph theory was used to investigate the underlying structural connections of dysfunctional anxiety in anxious dogs and compared with healthy dogs with normal behavior. The degree of anxiety was assessed using the Canine Behavioral Assessment & Research Questionnaire (C-BARQ), a widely used, validated questionnaire for abnormal behaviors in dogs. Anxious dogs showed significantly decreased clustering coefficient ([Formula: see text]), decreased global efficiency ([Formula: see text]), and increased small-worldness (σ) when compared with healthy dogs. The nodal parameters that differed between the anxious dogs and healthy dogs were mainly located in the posterior part of the brain, including the occipital lobe, posterior cingulate gyrus, hippocampus, mesencephalon, and cerebellum. Furthermore, the nodal degree ([Formula: see text]) of the left cerebellum was significantly negatively correlated with "excitability" in the C-BARQ of anxious dogs. These findings could contribute to the understanding of a disrupted brain structural connectome underlying the pathological mechanisms of anxiety-related disorders in dogs.

Altered metabolic-functional coupling in the epileptogenic network could predict surgical outcomes of mesial temporal lobe epilepsy

Objective

To investigate the relationship between glucose metabolism and functional activity in the epileptogenic network of patients with mesial temporal lobe epilepsy (MTLE) and to determine whether this relationship is associated with surgical outcomes.

Methods

¹⁸F-FDG PET and resting-state functional MRI (rs-fMRI) scans were performed on a hybrid PET/MR scanner in 38 MTLE patients with hippocampal sclerosis (MR-HS), 35 MR-negative patients and 34 healthy controls (HC). Glucose metabolism was measured using ¹⁸F-FDG PET standardized uptake value ratio (SUVR) relative to cerebellum; Functional activity was obtained by fractional amplitude of low-frequency fluctuation (fALFF). The betweenness centrality (BC) of metabolic covariance network and functional network were calculated using graph theoretical analysis. Differences in SUVR, fALFF, BC and the spatial voxel-wise SUVR-fALFF couplings of the epileptogenic network, consisting of default mode network (DMN) and thalamus, were evaluated by Mann-Whitney U test (using the false discovery rate [FDR] for multiple comparison correction). The top ten SUVR-fALFF couplings were selected by Fisher score to predict surgical outcomes using logistic regression model.

Results

The results showed decreased SUVR-fALFF coupling in the bilateral middle frontal gyrus (P_FDR = 0.0230, P_FDR = 0.0296) in MR-HS patients compared to healthy controls. Coupling in the ipsilateral hippocampus was marginally increased (P_FDR = 0.0802) in MR-HS patients along with decreased BC of metabolic covariance network and functional network (P_FDR = 0.0152; P_FDR = 0.0429). With Fisher score ranking, the top ten SUVR-fALFF couplings in regions from DMN and thalamic subnuclei could predict surgical outcomes with the best performance being a combination of ten SUVR-fALFF couplings with an AUC of 0.914.

Conclusion

These findings suggest that the altered neuroenergetic coupling in the epileptogenic network is associated with surgical outcomes of MTLE patients, which may provide insight into their pathogenesis and help with preoperative evaluation.

In vivo characterization of magnetic resonance imaging-based T1w/T2w ratios reveals myelin-related changes in temporal lobe epilepsy

Temporal lobe epilepsy (TLE) is the most common type of intractable epilepsy in adults. Although brain myelination alterations have been observed in TLE, it remains unclear how the myelination network changes in TLE. This study developed a novel method in characterization of myelination structural covariance network (mSCN) by T1-weighted and T2-weighted magnetic resonance imaging (MRI). The mSCNs were estimated in 42 left TLE (LTLE), 42 right TLE (RTLE) patients, and 41 healthy controls (HCs). The topology of mSCN was analyzed by graph theory. Voxel-wise comparisons of myelination laterality were also examined among the three groups. Compared to HC, both patient groups showed decreased myelination in frontotemporal regions, amygdala, and thalamus; however, the LTLE showed lower myelination in left medial temporal regions than RTLE. Moreover, the LTLE exhibited decreased global efficiency compared with HC and more increased connections than RTLE. The laterality in putamen was differently altered between the two patient groups: higher laterality at posterior putamen in LTLE and higher laterality at anterior putamen in RTLE. The putamen may play a transfer station role in damage spreading induced by epileptic seizures from the hippocampus. This study provided a novel workflow by combination of T1-weighted and T2-weighted MRI to investigate in vivo the myelin-related microstructural feature in epileptic patients first time. Disconnections of mSCN implicate that TLE is a system disorder with widespread disruptions at regional and network levels.

Abnormal metabolic connectivity in default mode network of right temporal lobe epilepsy

Aims

Temporal lobe epilepsy (TLE) is a common neurological disorder associated with the dysfunction of the default mode network (DMN). Metabolic connectivity measured by 18F-fluorodeoxyglucose Positron Emission Computed Tomography (18F-FDG PET) has been widely used to assess cumulative energy consumption and provide valuable insights into the pathophysiology of TLE. However, the metabolic connectivity mechanism of DMN in TLE is far from fully elucidated. The present study investigated the metabolic connectivity mechanism of DMN in TLE using 18F-FDG PET.

Method

Participants included 40 TLE patients and 41 health controls (HC) who were age- and gender-matched. A weighted undirected metabolic network of each group was constructed based on 14 primary volumes of interest (VOIs) in the DMN, in which Pearson's correlation coefficients between each pair-wise of the VOIs were calculated in an inter-subject manner. Graph theoretic analysis was then performed to analyze both global (global efficiency and the characteristic path length) and regional (nodal efficiency and degree centrality) network properties.

Results

Metabolic connectivity in DMN showed that regionally networks changed in the TLE group, including bilateral posterior cingulate gyrus, right inferior parietal gyrus, right angular gyrus, and left precuneus. Besides, significantly decreased (P < 0.05, FDR corrected) metabolic connections of DMN in the TLE group were revealed, containing bilateral hippocampus, bilateral posterior cingulate gyrus, bilateral angular gyrus, right medial of superior frontal gyrus, and left inferior parietal gyrus.

Conclusion

Taken together, the present study demonstrated the abnormal metabolic connectivity in DMN of TLE, which might provide further insights into the understanding the dysfunction mechanism and promote the treatment for TLE patients.

Nuclear imaging for localization and surgical outcome prediction in epilepsy: A review of latest discoveries and future perspectives

Background

Epilepsy is one of the most common neurological disorders. Approximately, one-third of patients with epilepsy have seizures refractory to antiepileptic drugs and further require surgical removal of the epileptogenic region. In the last decade, there have been many recent developments in radiopharmaceuticals, novel image analysis techniques, and new software for an epileptogenic zone (EZ) localization.

Objectives

Recently, we provided the latest discoveries, current challenges, and future perspectives in the field of positron emission tomography (PET) and single-photon emission computed tomography (SPECT) in epilepsy.

Methods

We searched for relevant articles published in MEDLINE and CENTRAL from July 2012 to July 2022. A systematic literature review based on the Preferred Reporting Items for Systematic Reviews and Meta-Analysis was conducted using the keywords "Epilepsy" and "PET or SPECT." We included both prospective and retrospective studies. Studies with preclinical subjects or not focusing on EZ localization or surgical outcome prediction using recently developed PET radiopharmaceuticals, novel image analysis techniques, and new software were excluded from the review. The remaining 162 articles were reviewed.

Results

We first present recent findings and developments in PET radiopharmaceuticals. Second, we present novel image analysis techniques and new software in the last decade for EZ localization. Finally, we summarize the overall findings and discuss future perspectives in the field of PET and SPECT in epilepsy.

Conclusion

Combining new radiopharmaceutical development, new indications, new techniques, and software improves EZ localization and provides a better understanding of epilepsy. These have proven not to only predict prognosis but also to improve the outcome of epilepsy surgery.

Metabolic connectivity is associated with seizure outcome in surgically treated temporal lobe epilepsies: A 18F-FDG PET seed correlation analysis

¹⁸F-FDG PET provides high sensitivity for the pre-surgical assessment of drug-resistant temporal lobe epilepsy (TLE). However, little is known about the metabolic connectivity of epileptogenic networks involved. This study therefore aimed to evaluate the association between metabolic connectivity and seizure outcome in surgically treated TLE.

METHODS

The study included 107 right-handed patients that had undergone a presurgical interictal ¹⁸F-FDG PET assessment followed by an anterior temporal lobectomy and were classified according to seizure outcome 2 years after surgery. Metabolic connectivity was evaluated by seed correlation analysis in left and right epilepsy patients with a Class Engel IA or > IA outcome and compared to age-, sex- and handedness-matched healthy controls.

RESULTS

Increased metabolic connectivity was observed in the >IA compared to the IA group within the operated temporal lobe (respective clusters of 7.5 vs 3.3 cm³ and 2.6 cm³ vs 2.2 cm³ in left and right TLE), and to a lower extent with the contralateral temporal lobe (1.2 vs 0.7 cm³ and 1.7 cm³ vs 0.7 cm³ in left and right TLE). Seed correlations provided added value for the estimated individual performance of seizure outcome over the group comparisons in left TLE (AUC of 0.74 vs 0.67).

CONCLUSION

Metabolic connectivity is associated with outcome in surgically treated TLE with a strengthened epileptogenic connectome in patients with non-free-seizure outcomes. The added value of seed correlation analysis in left TLE underlines the importance of evaluating metabolic connectivity in network related diseases.

Individual Brain Metabolic Connectome Indicator Based on Jensen-Shannon Divergence Similarity Estimation Predicts Seizure Outcomes of Temporal Lobe Epilepsy

Objective: We aimed to use an individual metabolic connectome method, the Jensen-Shannon Divergence Similarity Estimation (JSSE), to characterize the aberrant connectivity patterns and topological alterations of the individual-level brain metabolic connectome and predict the long-term surgical outcomes in temporal lobe epilepsy (TLE).

Methods: A total of 128 patients with TLE (63 females, 65 males; 25.07 ± 12.01 years) who underwent Positron emission tomography (PET) with 18F-fluorodeoxyglucose (FDG) imaging were enrolled. Patients were classified either as experiencing seizure recurrence (SZR) or seizure free (SZF) at least 1 year after surgery. Each individual’s metabolic brain network was ascertained using the proposed JSSE method. We compared the similarity and difference in the JSSE network and its topological measurements between the two groups. The two groups were then classified by combining the information from connection and topological metrics, which was conducted by the multiple kernel support vector machine. The validation was performed using the nested leave-one-out cross-validation strategy to confirm the performance of the methods.

Results: With a median follow-up of 33 months, 50% of patients achieved SZF. No relevant differences in clinical features were found between the two groups except age at onset. The proposed JSSE method showed marked degree reductions in IFGoperc.R, ROL. R, IPL. R, and SMG. R; and betweenness reductions in ORBsup.R and IOG. R; meanwhile, it found increases in the degree analysis of CAL. L and PCL. L, and in the betweenness analysis of PreCG.R, IOG. R, PoCG.R, PCL. L and PCL.R. Exploring consensus significant metabolic connections, we observed that the most involved metabolic motor networks were the INS-TPOmid.L, MTG. R-SMG. R, and MTG. R-IPL.R pathways between the two groups, and yielded another detailed individual pathological connectivity in the PHG. R-CAU.L, PHG. R-HIP.L, TPOmid.L-LING.R, TPOmid.L-DCG.R, MOG. R-MTG.R, MOG. R-ANG.R, and IPL. R-IFGoperc.L pathways. These aberrant functional network measures exhibited ideal classification performance in predicting SZF individuals from SZR ones at a sensitivity of 75.00%, a specificity of 92.79%, and an accuracy of 83.59%.

Conclusion: The JSSE method indicator can identify abnormal brain networks in predicting an individual’s long-term surgical outcome of TLE, thus potentially constituting a clinically applicable imaging biomarker. The results highlight the biological meaning of the estimated individual brain metabolic connectome.

Metabolic Brain Network and Surgical Outcome in Temporal Lobe Epilepsy: A Graph Theoretical Study Based on 18F-fluorodeoxyglucose PET

Drug-resistant temporal lobe epilepsy (TLE) is a potential candidate for surgery; however, nearly one-third subjects had a poor surgical prognosis. We studied the underlying neuromechanism related to the surgical prognosis using graph theory based on metabolic brain network. Sixty-four unilateral TLE subjects with preoperative ¹⁸F-fluorodeoxyglucose (FDG) PET scanning were retrospectively enrolled and divided into Ia (Engel class Ia, n = 32) and non-Ia (Engel class Ib-IV, n = 32) groups according to more than 3-year follow-up after unilateral anterior temporal lobectomy (ATL). The metabolic brain network was constructed and the changed metabolic connectivity of Ia and non-Ia was detected compared with 15 matched healthy controls (HCs). Further, the network properties, including small-worldness and global efficiency, were calculated and hub nodes were also identified for the 3 groups respectively. Non-Ia group exhibited increased connectivity between contralateral fusiform gyrus and contralateral lingual gyrus; while Ia showed decreased connectivity mainly among bilateral frontal, temporal and parietal cortex. Graph theoretical analysis revealed that non-Ia group showed increased small-worldness (35%<s < 55%, P ≤ 0.05) compared to HCs; and elevated global efficiency (P = 0.05) and decreased L_p (P = 0.05) compared to Ia group. Ia group showed reduced C_p (55%<s < 63%, P < 0.05) and increased small-worldness (35%<s < 37%, P < 0.05) compared to HCs; Furthermore, disrupted hub nodes distribution pattern with the midcingulate gyrus disappeared, was also found in non-Ia group compared with the Ia group. All those results revealed that elevated network integration and metabolic connectivity, redistributed hub nodes pattern is associated with ongoing postoperative seizures in subjects with intractable TLE.

Neurobehavioural comorbidities of epilepsy: towards a network-based precision taxonomy

Cognitive and behavioural comorbidities are prevalent in childhood and adult epilepsies and impose a substantial human and economic burden. Over the past century, the classic approach to understanding the aetiology and course of these comorbidities has been through the prism of the medical taxonomy of epilepsy, including its causes, course, characteristics and syndromes. Although this 'lesion model' has long served as the organizing paradigm for the field, substantial challenges to this model have accumulated from diverse sources, including neuroimaging, neuropathology, neuropsychology and network science. Advances in patient stratification and phenotyping point towards a new taxonomy for the cognitive and behavioural comorbidities of epilepsy, which reflects the heterogeneity of their clinical presentation and raises the possibility of a precision medicine approach. As we discuss in this Review, these advances are informing the development of a revised aetiological paradigm that incorporates sophisticated neurobiological measures, genomics, comorbid disease, diversity and adversity, and resilience factors. We describe modifiable risk factors that could guide early identification, treatment and, ultimately, prevention of cognitive and broader neurobehavioural comorbidities in epilepsy and propose a road map to guide future research.

18F-FDG-PET glucose hypometabolism pattern in patients with epileptogenic hypothalamic hamartoma

Epileptogenic hypothalamic hamartoma is characterized by intractable gelastic seizures. A systematic analysis of the overall brain metabolic pattern in patients with hypothalamic hamartoma (HH) could facilitate the understanding of the epileptic brain network and the associated brain damage effects of HH. In this study, we retrospectively evaluated 27 patients with epileptogenic HH (8 female patients; age, 2-33 years) by using ¹⁸F-fluorodeoxyglucose-positron emission tomography. The correlations among tomography result, seizure type, sex, and structural magnetic resonance imaging were assessed. Whole metabolic patterns and voxel-based morphometry findings were assessed by group analysis with healthy controls. Assessment of the whole metabolic pattern in patients with HH revealed several regional metabolic reductions in the cerebrum and an overall metabolic reduction in the cerebellum. In addition, areas showing hypometabolism in the neocortex were more widely distributed ipsilaterally than contralaterally to the HH. Reductions in glucose metabolism and gray matter volume in the neocortex were predominant ipsilateral to the HH. In conclusion, the glucose hypometabolism pattern in patients with epileptogenic HH involved the neocortex, subcortical regions, and cerebellum. The characteristics of glucose hypometabolism differed across seizure type and sex. Reductions in glucose metabolism and structural changes may be based on different mechanisms, but both are likely to occur ipsilateral to the HH in the neocortex. We hypothesized that the dentato-rubro-thalamic tract and cerebro-ponto-cerebellar tract, which are responsible for intercommunication between the cerebral cortex, subcortical regions, and cerebellar regions, may be involved in a pathway related to seizure propagation, particularly gelastic seizures, in patients with HH.

Disturbance of functional and effective connectivity of the salience network involved in attention deficits in right temporal lobe epilepsy

The salience network (SN) acts as a switch that generates transient control signals to regulate the executive control network (ECN) and the default mode network (DMN) and has been implicated in cognitive processes. Temporal lobe epilepsy (TLE) is usually accompanied by different types of cognitive deficits, but whether it is associated with dysfunctional connectivity of the SN remains unknown. To address this, thirty-six patients with right TLE (rTLE) and thirty-six healthy controls (HCs) were recruited for the present study. All of the participants were subjected to attention network test (ANT) and resting-state functional resonance imaging (rs-fMRI) scanning. The patient group showed deficits in attention performance. Moreover, the functional connectivity (FC) and effective connectivity (EC) were analyzed based on key SN hubs (the anterior cingulate cortex (ACC) and the bilateral anterior insula (AI)). When compared with those in the HC group, the ACC showed increased FC with the left middle frontal gyrus and the left precentral gyrus, and the right AI showed decreased FC with the right precuneus and the right superior occipital gyrus in the patient group. The EC analysis revealed an increased inflow of information from the left middle temporal gyrus to the ACC and the right AI and an increased outflow of information from the bilateral AI to the left middle frontal gyrus. Furthermore, in the correlation analysis, the abnormal EC from the right AI to the left middle temporal gyrus was positively correlated with the executive control effect. These findings demonstrated aberrant modulation of the SN in rTLE, which was particularly characterized by dysfunctional connectivity between the SN and key brain regions in the DMN and ECN. Elucidation of this effect may further contribute to the comprehensive understanding of the neural mechanisms of the SN in regard to attention deficits in patients with TLE.

Brain metabolic characteristics distinguishing typical and atypical benign epilepsy with centro-temporal spikes

OBJECTIVES

Atypical benign epilepsy with centro-temporal spikes (BECTS) have less favorable outcomes than typical BECTS, and thus should be accurately identified for adequate treatment. We aimed to investigate the glucose metabolic differences between typical and atypical BECTS using ¹⁸F-fluorodeoxyglucose positron emission tomography ([¹⁸F]FDG PET) imaging, and explore whether these differences can help distinguish.

METHODS

Forty-six patients with typical BECTS, 31 patients with atypical BECTS and 23 controls who underwent [¹⁸F]FDG PET examination were retrospectively involved. Absolute asymmetry index (|AI|) was applied to evaluate the severity of metabolic abnormality. Glucose metabolic differences were investigated among typical BECTS, atypical BECTS, and controls by using statistical parametric mapping (SPM). Logistic regression analyses were performed based on clinical, PET, and hybrid features.

RESULTS

The |AI| was found significantly higher in atypical BECTS than in typical BECTS (p = 0.040). Atypical BECTS showed more hypo-metabolism regions than typical BECTS, mainly located in the fronto-temporo-parietal cortex. The PET model had significantly higher area under the curve (AUC) than the clinical model (0.91 vs. 0.70, p = 0.006). The hybrid model had the highest sensitivity (0.90), specificity (0.85), and accuracy (0.87) of all three models.

CONCLUSIONS

Atypical BECTS showed more widespread and severe hypo-metabolism than typical BECTS, depending on which the two groups can be well distinguished. The combination of metabolic characteristics and clinical variables has the potential to be used clinically to distinguish between typical and atypical BECTS.

KEY POINTS

• Distinguishing between typical and atypical BECTS is very important for the formulation of treatment regimens in clinical practice. • Atypical BECTS showed more widespread and severe hypo-metabolism than typical BECTS, mainly located in the fronto-temporo-parietal cortex. • The logistic regression model based on PET outperformed that based on clinical characteristics in classification of typical and atypical BECTS, and the hybrid model achieved the best classification performance.

Alterations in the metabolic networks of temporal lobe epilepsy patients: A graph theoretical analysis using FDG-PET

OBJECTIVE

The aim of this study is to investigate changes in metabolic networks based on fluorodeoxyglucose positron emission tomography (FDG-PET) in patients with drug-resistant temporal lobe epilepsy (TLE) (with and without hippocampal sclerosis [HS]) when compared with healthy controls.

METHODS

We retrospectively enrolled 30 patients with drug-resistant temporal lobe epilepsy (17 patients with HS and 13 patients without HS) and 39 healthy controls. All subjects underwent interictal FDG-PET scans, which were analyzed to obtain metabolic connectivity using graph theoretical analysis. We investigated the differences in metabolic connectivity between patients with drug-resistant TLE (with and without HS) and healthy controls.

RESULTS

When compared with healthy controls, TLE patients with HS showed alterations of global and local metabolic connectivity. When considering global connectivity, TLE patients with HS had a decreased average degree with increased modularity. When considering local connectivity, TLE patients with HS displayed alterations of betweeness centrality in widespread regions. However, there were no alterations of global metabolic connectivity in TLE patients without HS when compared with healthy controls. In addition, when compared to TLE patients without HS, TLE patients with HS had increased modularity.

SIGNIFICANCE

Our study demonstrates more severe alterations in metabolic networks based on FDG-PET in TLE patients with HS than in those without HS and healthy controls. This may represent distinct epileptic networks in TLE patients with HS versus those without HS, although both are drug-resistant focal epilepsy.

Rosiglitazone polarizes microglia and protects against pilocarpine-induced status epilepticus

Aims

Activated microglia have been found in the forebrains and hippocampi of temporal lobe epilepsy (TLE) patients and status epileptic (SE) animal models. The peroxisome proliferator‐activated receptor γ (PPAR γ) agonist rosiglitazone has been shown to prevent microglial activation. However, its role in pilocarpine‐induced status epilepticus remains unknown. We aimed to examine the effect of the PPAR γ agonist rosiglitazone in protecting against pilocarpine‐induced status epileptic resulting from over‐activation and to explore phenotypic changes in microglia as the underlying mechanism.

Methods

Male C57BL/6 mice were assigned to three groups: the control group, pilocarpine‐induced (SE) group, and rosiglitazone‐treated (SE+Rosi) group. Status epileptic mice were administered 300 mg/kg pilocarpine via intraperitoneal injection. SE+Rosi mice were administered rosiglitazone (0.1 mg/kg, i.p.) after SE. Flow cytometry, immunofluorescence staining, and quantitative real‐time PCR were used to examine the activation of and phenotypic changes in microglia in the brain and to evaluate neuroinflammation.

Results

We found that the expression of proinflammatory CD86 and iNOS was increased and that the expression of antiinflammatory CD206 and Arg‐1 was decreased in the brains of pilocarpine‐induced SE mice compared to control mice. The mRNA levels of proinflammatory and antiinflammatory cytokines were not significantly changed in the brain. Rosiglitazone treatment significantly inhibited the proinflammatory polarization of microglia and rescued neuron loss in the temporal lobe and hippocampi of the brain after SE.

Conclusion

Rosiglitazone reverses microglial polarization in the brains of SE mice and also affords neuroprotection against pilocarpine‐induced status epilepticus without inducing significant changes in brain inflammation.

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.