Intrinsic hippocampal and thalamic networks in temporal lobe epilepsy with hippocampal sclerosis according to drug response

Aberrant functional connectivity associated with drug response in patients with newly diagnosed epilepsy

OBJECTIVE

To analyze the local functional activity and connectivity features of the brain associated with drug response inpatients newly diagnosed with epilepsy (NDE) who are naïve to anti-seizure medication (ASM).

METHODS

Recruited patients, underwent functional magnetic resonance imaging at baseline, and were assigned to the well-controlled (WC, n = 28) or uncontrolled (UC, n = 11) groups based on their response to ASM. Healthy participants were included in the control group (HC, n = 29). The amplitudes of low-frequency fluctuation (ALFF) and fractional ALFF (fALFF) were used to measure local functional activity, and voxel-wise degree centrality (DC) and seed-based functional connectivity (FC) were used to evaluate the connecting intensity of the brain areas.

RESULTS

Compared to the HC and WC groups, the UC group had higher ALFF values in the left posterior central gyrus (PoCG.L) and left inferior temporal gyrus (ITG.L) and higher DC in the bilateral PoCG (Gaussian random field correction, voxel-level P < 0.001, and cluster-level P < 0.05). Both PoCG and ITG.L in the UC group showed stronger FC with multiple brain regions, mainly located in the occipital and temporal lobes, compared to the HC or WC group, while the WC group showed decreased or similar FC compared to the HC group.

INTERPRETATION

Excessive enhancement of brain functional activity or connecting intensity in ASM-naïve patients with NDE may be associated with a higher risk of poor drug response.

Increased coherence predicts medical refractoriness in patients with temporal lobe epilepsy on monotherapy

Among patients with epilepsy, 30-40% experience recurrent seizures even after adequate antiseizure medications therapies, making them refractory. The early identification of refractory epilepsy is important to provide timely surgical treatment for these patients. In this study, we analyze interictal electroencephalography (EEG) data to predict drug refractoriness in patients with temporal lobe epilepsy (TLE) who were treated with monotherapy at the time of the first EEG acquisition. Various EEG features were extracted, including statistical measurements and interchannel coherence. Feature selection was performed to identify the optimal features, and classification was conducted using different classifiers. Functional connectivity and graph theory measurements were calculated to identify characteristics of refractory TLE. Among the 48 participants, 34 (70.8%) were responsive, while 14 (29.2%) were refractory over a mean follow-up duration of 38.5 months. Coherence feature within the gamma frequency band exhibited the most favorable performance. The light gradient boosting model, employing the mutual information filter-based feature selection method, demonstrated the highest performance (AUROC = 0.821). Compared to the responsive group, interchannel coherence displayed higher values in the refractory group. Interestingly, graph theory measurements using EEG coherence exhibited higher values in the refractory group than in the responsive group. Our study has demonstrated a promising method for the early identification of refractory TLE utilizing machine learning algorithms.

Structural connectivity as a predictive factor for responsiveness to levetiracetam treatment in epilepsy

PURPOSE

To investigate whether structural connectivity or glymphatic system function is a potential predictive factor for levetiracetam (LEV) response in patients with newly diagnosed epilepsy.

METHODS

We enrolled patients with newly diagnosed epilepsy who were administered LEV as initial monotherapy and underwent diffusion tensor imaging (DTI) at diagnosis. We categorized the patients into drug response. We used graph theory to calculate the network measures for structural connectivity based on the DTI scans in patients with epilepsy. Additionally, we evaluated glymphatic system function by calculating the DTI analysis along the perivascular space (DTI-ALPS) index based on DTI scans.

RESULTS

We enrolled 84 patients with epilepsy. The clinical factors and DTI-ALPS index did not differ between the groups. However, some of the structural connectivity measures significantly differ between the groups. The poor responders exhibited a higher mean clustering coefficient, global efficiency, and small-worldness index than the good responders (p = 0.003, p = 0.048, and p = 0.038, respectively). In the receiver operating characteristic curve analysis, the mean clustering coefficient exhibited the highest performance in predicting the responsiveness to LEV (area under the curve of 0.677). In the multiple logistic regression analysis, the mean clustering coefficient of the structural connectivity measures was the only significant predictor of LEV response (p = 0.014). Furthermore, in the survival analysis, the mean clustering coefficient was the only significant predictor of LEV response (p = 0.026).

CONCLUSION

We demonstrated that structural connectivity is a potential predictive factor for responsiveness to LEV treatment in patients with newly diagnosed epilepsy.

Structural brain network analysis in occipital lobe epilepsy

BACKGROUND

This study aimed to analyze the structural brain network in patients with occipital lobe epilepsy (OLE) and investigate the differences in structural brain networks between patients with OLE and healthy controls.

METHODS

Patients with OLE and healthy controls with normal brain MRI findings were enrolled. They underwent diffusion tensor imaging using a 3.0T MRI scanner, and we computed the network measures of global and local structural networks in patients with OLE and healthy controls using the DSI studio program. We compared network measures between the groups.

RESULTS

We enrolled 23 patients with OLE and 42 healthy controls. There were significant differences in the global structural network between patients with OLE and healthy controls. The assortativity coefficient (-0.0864 vs. -0.0814, p = 0.0214), mean clustering coefficient (0.0061 vs. 0.0064, p = 0.0203), global efficiency (0.0315 vs. 0.0353, p = 0.0086), and small-worldness index (0.0001 vs. 0.0001, p = 0.0175) were lower, whereas the characteristic path length (59.2724 vs. 53.4684, p = 0.0120) was higher in patients with OLE than those in the healthy controls. There were several nodes beyond the occipital lobe that showed significant differences in the local structural network between the groups. In addition, the assortativity coefficient was negatively correlated with the duration of epilepsy (r=-0.676, p = 0.001).

Excessively increased thalamocortical connectivity and poor initial antiseizure medication response in epilepsy patients

Objectives

The network mechanism underlying the initial response to antiseizure medication in epilepsy has not been revealed yet. Given the central role of the thalamus in the brain network, we conducted a case-control study to investigate the association between thalamic connectivity and medication response.

Methods

We recruited 39 patients with newly diagnosed and medication-naïve epilepsy of genetic or unknown etiology, including 26 with a good response (GR group) and 13 with a poor response (PR group), and 26 matched healthy participants (control group). We measured the gray matter density (GMD) and the amplitude of low-frequency fluctuation (ALFF) of bilateral thalami. We then set each thalamus as the seed region of interest (ROI) to calculate voxel-wise functional connectivity (FC) and assessed ROI-wise effective connectivity (EC) between the thalamus and targeted regions.

Results

We found no significant difference between groups in the GMD or ALFF of bilateral thalami. However, we observed that the FC values of several circuits connecting the left thalamus and the cortical areas, including the bilateral Rolandic operculum, the left insula, the left postcentral gyrus, the left supramarginal gyrus, and the left superior temporal gyrus, differed among groups (False Discovery Rate correction, P < 0.05), with a higher value in the PR group than in the GR group and/or the control group (Bonferroni correction, P < 0.05). Similarly, both the outflow and the inflow EC in each thalamocortical circuit were higher in the PR group than in the GR group and the control group, although these differences did not remain statistically significant after applying the Bonferroni correction (P < 0.05). The FC showed a positive correlation with the corresponding outflow and inflow ECs for each circuit.

Conclusion

Our finding suggested that patients with stronger thalamocortical connectivity, potentially driven by both thalamic outflowing and inflowing information, may be more likely to respond poorly to initial antiseizure medication.

Thalamic nuclei volumes and intrinsic thalamic network in patients with occipital lobe epilepsy

INTRODUCTION

This study aimed to investigate the alterations in individual thalamic nuclei volumes in patients with occipital lobe epilepsy (OLE) compared with those of healthy controls, and to analyze the intrinsic thalamic network based on these volumes using graph theory.

METHODS

Thirty adult patients with newly diagnosed OLE and 42 healthy controls were retrospectively enrolled (mean age, 33.8 ± 17.0 and 32.2 ± 6.6 years, respectively). The study participants underwent brain magnetic resonance imaging with three-dimensional T1-weighted imaging. The right and left total thalamic and individual thalamic nuclei volumes were obtained using the FreeSurfer program. Then, the intrinsic thalamic network was calculated based on the individual thalamic nuclei volumes and graph theory using a BRAPH program.

RESULTS

There were no differences in the right and left whole-thalamic volumes between the two groups (0.445% vs. 0.469%, p = .142 and 0.481% vs. 0.490%, p = .575, respectively). However, significant differences were observed in the volumes of several thalamic nuclei between the two groups. The right medial geniculate and right suprageniculate nuclei volumes were increased (0.0077% vs. 0.0064%, p = .0003 and 0.0013% vs. 0.0010%, p = .0004, respectively), whereas the right and left parafascicular nuclei volumes were decreased in patients with OLE compared with those in healthy controls (0.0038% vs. 0.0048%, p < .0001 and 0.0037% vs. 0.0045%, p = .0001, respectively). There were no differences in the network measures regarding intrinsic thalamic network between the two groups.

CONCLUSION

We successfully demonstrated the alterations in individual thalamic nuclei volumes, especially the increased medial geniculate and suprageniculate, and decreased parafascicular nuclei volumes in patients with OLE compared with those of healthy controls despite no changes in the whole-thalamic volumes. These findings suggest an important role of the thalamus in the epileptic network of OLE.

Distinct limbic connectivity in left and right benign mesial temporal lobe epilepsy: Evidence from a resting state functional MRI study

Background

Functional connectivity (FC) studies showed that pharmaco-resistant mesial temporal lobe epilepsy (MTLE) affects not only the limbic system, but also several extra-limbic regions, including areas belonging to resting state networks. Less is known about FC in subjects with benign MTLE (i.e., sensitive to antiseizure medication, bMTLE).

Aim and methods

We evaluated FC of hippocampus and amygdala in subjects with bMTLE, distinguished based on the epileptic focus lateralization. We enrolled 19 patients (10 with left and 9 with right bMTLE) and 10 age-matched healthy subjects. Connectivity was investigated at rest by using a seed-based regression analyses approach with four regions of interest (left and right hippocampus, left and right amygdala). Patients were also tested with a neuropsychological battery and their scores were correlated with fMRI data.

Results and conclusions

Our study documented an asymmetrical disruption of FC in bMTLE, in relation to the side of the focus. Right subjects only exhibited limited altered connections, while left subjects—who performed worse in verbal memory tests—showed a wide bilateral hypoconnectivity of hippocampus and amygdala with areas belonging to language and memory network. The strength of FC between left limbic areas and language and memory network correlated with better performances in verbal memory tests. Moreover, we observed an increased FC with areas of default mode network, more pronounced in left subjects, a possible attempt to compensate cognitive deficit but without effectiveness.

We believe that these findings could help to better characterize bMTLE, in which a dysfunction of limbic connectivity is detectable despite well-controlled epilepsy.

Intrinsic Thalamic Network in Temporal Lobe Epilepsy With Hippocampal Sclerosis According to Surgical Outcomes

Background: The aim of this study was to identify the differences of intrinsic amygdala, hippocampal, or thalamic networks according to surgical outcomes in temporal lobe epilepsy (TLE) patients with hippocampal sclerosis (HS).

Methods: We enrolled 69 pathologically confirmed TLE patients with HS. All patients had pre-operative three-dimensional T1-weighted MRI using a 3.0 T scanner. We obtained the structural volumes of the amygdala nuclei, hippocampal subfields, and thalamic nuclei. Then, we investigated the intrinsic networks based on volumes of these structures using structural covariance and graph theoretical analysis.

Results: Of the 69 TLE patients with HS, 21 patients (42.1%) had poor surgical outcomes, whereas 40 patients (57.9%) had good surgical outcomes. The volumes in the amygdala nuclei, hippocampal subfields, and thalamic nuclei were not different according to surgical outcome. In addition, the intrinsic amygdala and hippocampal networks were not different between the patients with poor and good surgical outcomes. However, there was a significant difference in the intrinsic thalamic network in the ipsilateral hemisphere between them. The eccentricity and small-worldness index were significantly increased, whereas the characteristic path length was decreased in the patients with poor surgical outcomes compared to those with good surgical outcomes.

Conclusion: We successfully demonstrated significant differences in the intrinsic thalamic network in the ipsilateral hemisphere between TLE patients with HS with poor and good surgical outcomes. This result suggests that the pre-operative intrinsic thalamic network can be related with surgical outcomes in TLE patients with HS.

Effects of seizure burden on structural global brain networks in patients with unilateral hippocampal sclerosis

BACKGROUND AND PURPOSE

Temporal lobe epilepsy secondary to hippocampal sclerosis is related to epileptogenic networks rather than a focal epileptogenic source. Graph-theoretical gray and white matter networks may help to identify alterations within these epileptogenic networks.

METHODS

Twenty-seven patients with hippocampal sclerosis and 14 controls underwent magnetic resonance imaging, including 3D-T1, fluid-attenuated inversion recovery, and diffusion tensor imaging. Subject-specific structural gray and white matter network properties (normalized path length, clustering, and small-worldness) were reconstructed. Group differences and differences between those with higher and lower seizure burden (<4 vs. ≥4 average monthly seizures in the last year) in network parameters were evaluated. Additionally, correlations between network properties and disease-related variables were calculated.

RESULTS

All patients with hippocampal sclerosis as one group did not have altered gray or white matter network properties (all p > .05). Patients with lower seizure burden had significantly lower gray matter small-worldness and normalized clustering compared to controls and those with higher seizure burden (all p < .04). A higher number of monthly seizures was significantly associated with increased gray and white matter small-worldness, indicating a more rigid network.

CONCLUSION

Overall, there were no differences in network properties in this group of patients with hippocampal sclerosis. However, patients with lower seizure burden had significantly lower gray matter network indices, indicating a more random organization. The correlation between higher monthly seizures and a more rigid network is driven by those with higher seizure burden, who presented a more rigid network compared to those with a lower seizure burden.