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

Structural brain network changes in patients with neurofibromatosis type 1: A retrospective study

We investigated the changes in structural connectivity (using diffusion tensor imaging [DTI]) and the structural covariance network based on structural volume using graph theory in patients with neurofibromatosis type 1 (NF1) compared to a healthy control group. We included 14 patients with NF1, according to international consensus recommendations, and 16 healthy individuals formed the control group. This was retrospectively observational study followed STROBE guideline. Both groups underwent brain magnetic resonance imaging including DTI and 3-dimensional T1-weighted imaging. We analyzed structural connectivity using DTI and Diffusion Spectrum Imaging Studio software and evaluated the structural covariance network based on the structural volumes using FreeSurfer and Brain Analysis Using Graph Theory software. There were no differences in the global structural connectivity between the 2 groups, but several brain regions showed significant differences in local structural connectivity. Additionally, there were differences between the global structural covariance networks. The characteristic path length was longer and the small-worldness index was lower in patients with NF1. Furthermore, several regions showed significant differences in the local structural covariance networks. We observed changes in structural connectivity and covariance networks in patients with NF1 compared to a healthy control group. We found that global structural efficiency is decreased in the brains of patients with NF1, and widespread changes in the local structural network were found. These results suggest that NF1 is a brain network disease, and our study provides direction for further research to elucidate the biological processes of NF1.

Brain networks and epilepsy development in patients with Alzheimer disease

INTRODUCTION

This study aimed to investigate the association between brain networks and epilepsy development in patients with Alzheimer disease (AD).

METHODS

We enrolled patients newly diagnosed with AD at our hospital who underwent three-dimensional T1-weighted magnetic resonance imaging at the time of AD diagnosis and included healthy controls. We obtained the cortical, subcortical, and thalamic nuclei structural volumes using FreeSurfer and applied graph theory to obtain the global brain network and intrinsic thalamic network based on the structural volumes using BRAPH.

RESULTS

We enrolled 25 and 56 patients with AD with and without epilepsy development, respectively. We also included 45 healthy controls. The global brain network differed between the patients with AD and healthy controls. The local efficiency (2.026 vs. 3.185, p = .048) and mean clustering coefficient (0.449 vs. 1.321, p = .024) were lower, whereas the characteristic path length (0.449 vs. 1.321, p = .048) was higher in patients with AD than in healthy controls. Both global and intrinsic thalamic networks were significantly different between AD patients with and without epilepsy development. In the global brain network, local efficiency (1.340 vs. 2.401, p = .045), mean clustering coefficient (0.314 vs. 0.491, p = .045), average degree (27.442 vs. 41.173, p = .045), and assortative coefficient (-0.041 vs. -0.011, p = .045) were lower, whereas the characteristic path length (2.930 vs. 2.118, p = .045) was higher in patients with AD with epilepsy development than in those without. In the intrinsic thalamic network, the mean clustering coefficient (0.646 vs. 0.460, p = .048) was higher, whereas the characteristic path length (1.645 vs. 2.232, p = .048) was lower in patients with AD with epilepsy development than in those without.

CONCLUSION

We found that the global brain network differs between patients with AD and healthy controls. In addition, we demonstrated significant associations between brain networks (both global brain and intrinsic thalamic networks) and epilepsy development in patients with AD.

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).

Alterations of the thalamic nuclei volumes and intrinsic thalamic network in patients with restless legs syndrome

We aimed to investigate the alterations of thalamic nuclei volumes and intrinsic thalamic network in patients with primary restless legs syndrome (RLS) compared to healthy controls. Seventy-one patients with primary RLS and 55 healthy controls were recruited. They underwent brain MRI using a three-tesla MRI scanner, including three-dimensional T1-weighted images. The intrinsic thalamic network was determined using graph theoretical analysis. The right and left whole thalamic volumes, and the right pulvinar inferior, left ventral posterolateral, left medial ventral, and left pulvinar inferior nuclei volumes in the patients with RLS were lower than those in healthy controls (0.433 vs. 0.447%, p = 0.034; 0.482 vs. 0.502%, p = 0.016; 0.013 vs. 0.015%, p = 0.031; 0.062 vs. 0.065%, p = 0.035; 0.001 vs. 0.001%, p = 0.034; 0.018 vs. 0.020%, p = 0.043; respectively). There was also a difference in the intrinsic thalamic network between the groups. The assortative coefficient in patients with RLS was higher than that in healthy controls (0.0318 vs. - 0.0358, p = 0.048). We demonstrated the alterations of thalamic nuclei volumes and intrinsic thalamic network in patients with RLS compared to healthy controls. These changes might be related to RLS pathophysiology and suggest the pivotal role of the thalamus in RLS symptoms.

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.