Neural functional connectivity in patients with periventricular nodular heterotopia-mediated epilepsy

Structural and functional abnormalities and cognitive profiles in older adults with early-onset and late-onset focal epilepsy

This study aimed to determine the patterns of changes in structure, function, and cognitive ability in early-onset and late-onset older adults with focal epilepsy (OFE). This study first utilized the deformation-based morphometry analysis to identify structural abnormalities, which were used as the seed region to investigate the functional connectivity with the whole brain. Next, a correlation analysis was performed between the altered imaging findings and neuropsychiatry assessments. Finally, the potential role of structural-functional abnormalities in the diagnosis of epilepsy was further explored by using mediation analysis. Compared with healthy controls (n = 28), the area of reduced structural volume was concentrated in the bilateral cerebellum, right thalamus, and right middle cingulate cortex, with frontal, temporal, and occipital lobes also affected in early-onset focal epilepsy (n = 26), while late-onset patients (n = 31) displayed cerebellar, thalamic, and cingulate atrophy. Furthermore, correlation analyses suggest an association between structural abnormalities and cognitive assessments. Dysfunctional connectivity in the cerebellum, cingulate cortex, and frontal gyrus partially mediates the relationship between structural abnormalities and the diagnosis of early-onset focal epilepsy. This study identified structural and functional abnormalities in early-onset and late-onset focal epilepsy and explored characters in cognitive performance. Structural-functional coupling may play a potential role in the diagnosis of epilepsy.

Localized activity alternations in periventricular nodular heterotopia-related epilepsy

OBJECTIVE

Periventricular nodular heterotopia (PNH) is a common type of heterotopia usually characterized by epilepsy. Previous studies have identified alterations in structural and functional connectivity related to this disorder, but its local functional neural basis has received less attention. The purpose of this study was to combine univariate analysis and a Gaussian process classifier (GPC) to assess local activity and further explore neuropathological mechanisms in PNH-related epilepsy.

METHODS

We used a 3.0-T scanner to acquire resting-state data and measure local regional homogeneity (ReHo) alterations in 38 patients with PNH-related epilepsy and 38 healthy controls (HCs). We first assessed ReHo alterations by comparing the PNH group to the HC group using traditional univariate analysis. Next, we applied a GPC to explore whether ReHo could be used to differentiate PNH patients from healthy patients at an individual level.

RESULTS

Compared to HCs, PNH-related epilepsy patients exhibited lower ReHo in the left insula extending to the putamen as well as in the subgenual anterior cingulate cortex (sgACC) extending to the orbitofrontal cortex (OFC) [p < 0.05, family-wise error corrected]. Both of these regions were also correlated with epilepsy duration. Furthermore, the ReHo GPC classification yielded a 76.32% accuracy (sensitivity = 71.05% and specificity = 81.58%) with p < 0.001 after permutation testing.

INTERPRETATION

Using the resting-state approach, we identified localized activity alterations in the left insula extending to the putamen and the sgACC extending to the OFC, providing pathophysiological evidence of PNH. These local connectivity patterns may provide a means to differentiate PNH patients from HCs.

A case-control study on the driving factors of childhood brain volume loss: What pediatricians must explore

BACKGROUND

The brain volume loss also known as brain atrophy is increasingly observed among children in the course of performing neuroimaging using CT scan and MRI brains. While severe forms of brain volume loss are frequently associated with neurocognitive changes due to effects on thought processing speed, reasoning and memory of children that eventually alter their general personality, most clinicians embark themselves in managing the neurological manifestations of brain atrophy in childhood and less is known regarding the offending factors responsible for developing pre-senile brain atrophy. It was therefore the goal of this study to explore the factors that drive the occurrence of childhood brain volume under the guidance of brain CT scan quantitative evaluation.

METHODS

This study was a case-control study involving 168 subjects with brain atrophy who were compared with 168 age and gender matched control subjects with normal brains on CT scan under the age of 18 years. All the children with brain CT scan were subjected to an intense review of their birth and medical history including laboratory investigation reports.

RESULTS

Results showed significant and influential risk factors for brain atrophy in varying trends among children including age between 14-17(OR = 1.1), male gender (OR = 1.9), birth outside facility (OR = 0.99), immaturity (OR = 1.04), malnutrition (OR = 0.97), head trauma (OR = 1.02), maternal alcoholism (OR = 1.0), antiepileptic drugs & convulsive disorders (OR = 1.0), radiation injury (OR = 1.06), space occupying lesions and ICP (OR = 1.01) and birth injury/asphyxia (OR = 1.02).

CONCLUSIONS

Pathological reduction of brain volume in childhood exhibits a steady trend with the increase in pediatric age, with space occupying lesions & intracranial pressure being the most profound causes of brain atrophy.

Using magnetic resonance fingerprinting to characterize periventricular nodular heterotopias in pharmacoresistant epilepsy

OBJECTIVE

We aimed to use a novel magnetic resonance fingerprinting (MRF) technique to examine in vivo tissue property characteristics of periventricular nodular heterotopia (PVNH). These characteristics were further correlated with stereotactic-electroencephalographic (SEEG) ictal onset findings.

METHODS

We included five patients with PVNH who had SEEG-guided surgery and at least 1 year of seizure freedom or substantial seizure reduction. High-resolution MRF scans were acquired at 3 T, generating three-dimensional quantitative T₁ and T₂  maps. We assessed the differences between T₁ and T₂  values from the voxels in the nodules located in the SEEG-defined seizure onset zone (SOZ) and non-SOZ, on -individual and group levels. Receiver operating characteristic analyses were performed to obtain the optimal classification performance. Quantification of SEEG ictal onset signals from the nodules was performed by calculating power spectrum density (PSD). The association between PSD and T₁ /T₂  values was further assessed at different frequency bands.

RESULTS

Individual-level analysis showed T₁ was significantly higher in SOZ voxels than non-SOZ voxels (p < .05), with an average 73% classification accuracy. Group-level analysis also showed higher T₁ was significantly associated with SOZ voxels (p < .001). At the optimal cutoff (normalized T₁ of 1.1), a 76% accuracy for classifying SOZ nodules from non-SOZ nodules was achieved. T₁  values were significantly associated with ictal onset PSD at the ultraslow, θ, β, γ, and ripple bands (p < .05). T₂  values were significantly associated with PSD only at the ultraslow band (p < .05).

SIGNIFICANCE

Quantitative MRF measures, especially T₁ , can provide additional noninvasive information to separate nodules in SOZ and non-SOZ. The T₁ and T₂ tissue property changes carry electrophysiological underpinnings relevant to the epilepsy, as shown by their significant positive associations with power changes during the SEEG seizure onset. The use of MRF as a supplementary noninvasive tool may improve presurgical evaluation for patients with PVNH and pharmacoresistant epilepsy.

Regional and remote connectivity patterns in focal extratemporal lobe epilepsy

Background

Focal epilepsy accounts for most epilepsy cases, and frontal lobe epilepsy (FLE) accounts for the largest proportion of cases of extratemporal epilepsy syndrome. The epileptogenic zone is usually not easy to locate, contributing to a lack of imaging studies. The objective of this study was to evaluate functional connectivity patterns to explore the underlying pathological mechanisms of this disorder.

Methods

Forty-three patients with focal extratemporal epilepsy [mean age ± standard deviation (SD): 29.51±8.04 years, 19 males] and the same number of healthy controls (mean age ± SD: 29.56±8.02 years, 19 males) were recruited to undergo functional magnetic resonance imaging. Mean regional homogeneity (ReHo) was measured, and regions showing significant alterations in ReHo in patients were identified to examine functional connectivity (FC). In particular, FC within the default mode network (DMN) in patients was analyzed.

Results

Patients with extratemporal lobe epilepsy showed significantly higher ReHo in the bilateral precentral gyrus, and lower ReHo in frontal-cerebellum regions than healthy controls [P<0.05, Gaussian random field (GRF)-corrected]. FC analysis based on regions of interest showed significantly higher connectivity in the frontoparietal-insula region and lowered FC in the frontal-cerebellum regions (P<0.05, GRF-corrected). Altered FC within DMN was also demonstrated (P<0.05, GRF-corrected).

Conclusions

Analyses of ReHo and FC based on regions of interest suggest epilepsy-related neural networks are located mainly in frontal regions in extratemporal lobe epilepsy. These findings reveal disruptions of interactions and connectivity of large-scale neural networks and frontotemporal-cerebellar regions, suggesting connectivity-based pathophysiology.

Incidence and risk factors associated with the development of epilepsy in patients with intracranial alveolar echinococcosis

Parasitic infection remains a critical health problem in Ganzi Tibetan Autonomous Prefecture of China. The association of epilepsy and intracranial alveolar echinococcosis (IAE) is still largely unclear. This study primarily aimed to assess both the incidence and possible risk factors of epilepsy in patients with IAE. According to the occurrence of seizures, patients were separated into two different groups consisting of patients with epilepsy and those without epilepsy. Univariate and multivariate logistic regression analysis was used to identify the potential risk factors associated with the development of epilepsy in patients with IAE. A total of 97 patients (42 women, 55 men; age 19-76 years) were enrolled. Epilepsy was observed in almost 20 % of patients with IAE. The use of anti-seizure medications was not standardized, as 83.3 % of female patients of childbearing age used sodium valproate. It was observed that cortical lesions (hazard ratio (HR) = 29.740, P = 0.006) were significantly associated with development of epilepsy. In addition, epilepsy had no significant effect on the overall survival rate of patients with IAE.

Brain functional connectivity patterns in focal cortical dysplasia related epilepsy

OBJECTIVE

Focal cortical dysplasia (FCD) appears to be strongly associated with intractable epilepsy. Although patients with FCD are candidates for epilepsy surgery, gray matter structural abnormalities can extend beyond the primary lesion, which makes surgery less effective. The objective of this study was to evaluate functional connectivity patterns in epilepsy associated with FCD to explore the underlying pathological mechanism of this disorder.

METHODS

A total of 34 patients (14 men) with FCD and epilepsy [mean age ± standard deviation (SD), 24.5 ± 9.8 years; range, 8-47 years] and 34 age-matched healthy controls (14 men, 24.6 ± 9.7 years) underwent functional magnetic resonance imaging. Independent component analysis (ICA), seed-based functional connectivity, and graph theory were applied to analyze functional connectivity patterns in the brain.

RESULTS

Patients showed more connections among dorsal attention network, anterior default mode network, and sensorimotor brain networks than healthy controls based on ICA. Analysis of connectivity between regions of interest (ROIs) showed greater functional connectivity in patients between frontal and temporal regions, but lower connectivity between the cerebellum and frontal regions. The normalized characteristic path length was significantly higher in group of patients, but the two groups showed no significant differences in global or regional efficiency, clustering coefficient or characteristic path length.

CONCLUSIONS

Analysis of ICA-derived and ROI-based functional connectivity suggests that disrupted interactions and dysconnectivity in large-scale neural networks and frontotemporal-cerebellar regions may contribute to underlying pathological mechanisms in FCD-related epilepsy.