Alterations of structural connectivity and structural co-variance network in focal cortical dysplasia

Efficient organisation of the contralateral hemisphere connectome is associated with improvement in intelligence quotient after paediatric epilepsy surgery

OBJECTIVE

Aims of epilepsy surgery in childhood include optimising seizure control and facilitating cognitive development. Predicting which children will improve cognitively is challenging. We investigated the association of the pre-operative structural connectome of the contralateral non-operated hemisphere with improvement in intelligence quotient (IQ) post-operatively.

METHODS

Consecutive children who had undergone unilateral resective procedures for epilepsy at a single centre were retrospectively identified. We included those with pre-operative volume T1-weighted non-contrast brain magnetic resonance imaging (MRI), no visible contralateral MRI abnormalities, and both pre-operative and two years post-operative IQ assessment. The MRI of the hemisphere contralateral to the side of resection was anatomically parcellated into 34 cortical regions and the covariance of cortical thickness between regions was used to create binary and weighted group connectomes.

RESULTS

Eleven patients with a post-operative IQ increase of at least 10 points at two years were compared with twenty-four patients with no change in IQ score. Children who gained at least 10 IQ points post-operatively had a more efficiently structured contralateral hemisphere connectome with higher global efficiency (0.74) compared to those whose IQ did not change at two years (0.58, p = 0.014). This was consistent across thresholds and both binary and weighted networks. There were no statistically significant group differences in age, sex, age at onset of epilepsy, pre-operative IQ, mean cortical thickness, side or site of procedure, two year post-operative Engel scores or use of anti-seizure medications between the two groups.

CONCLUSIONS

Surgical procedures to reduce or stop seizures may allow children with an efficiently structured contralateral hemisphere to achieve their cognitive potential.

Advances in Neuroimaging and Multiple Post-Processing Techniques for Epileptogenic Zone Detection of Drug-Resistant Epilepsy

Among the approximately 20 million patients with drug-resistant epilepsy (DRE) worldwide, the vast majority can benefit from surgery to minimize seizure reduction and neurological impairment. Precise preoperative localization of epileptogenic zone (EZ) and complete resection of the lesions can influence the postoperative prognosis. However, precise localization of EZ is difficult, and the structural and functional alterations in the brain caused by DRE vary by etiology. Neuroimaging has emerged as an approach to identify the seizure-inducing structural and functional changes in the brain, and magnetic resonance imaging (MRI) and positron emission tomography (PET) have become routine noninvasive imaging tools for preoperative evaluation of DRE in many epilepsy treatment centers. Multimodal neuroimaging offers unique advantages in detecting EZ, especially in improving the detection rate of patients with negative MRI or PET findings. This approach can characterize the brain imaging characteristics of patients with DRE caused by different etiologies, serving as a bridge between clinical and pathological findings and providing a basis for individualized clinical treatment plans. In addition to the integration of multimodal imaging modalities and the development of special scanning sequences and image post-processing techniques for early and precise localization of EZ, the application of deep machine learning for extracting image features and deep learning-based artificial intelligence have gradually improved diagnostic efficiency and accuracy. These improvements can provide clinical assistance for precisely outlining the scope of EZ and indicating the relationship between EZ and functional brain areas, thereby enabling standardized and precise surgery and ensuring good prognosis. However, most existing studies have limitations imposed by factors such as their small sample sizes or hypothesis-based study designs. Therefore, we believe that the application of neuroimaging and post-processing techniques in DRE requires further development and that more efficient and accurate imaging techniques are urgently needed in clinical practice. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 2.

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.

Focal epilepsy without overt epileptogenic lesions: no evidence of microstructural brain tissue damage in multi-parametric quantitative MRI

Background and purpose

In patients with epilepsies of structural origin, brain atrophy and pathological alterations of the tissue microstructure extending beyond the putative epileptogenic lesion have been reported. However, in patients without any evidence of epileptogenic lesions on diagnostic magnetic resonance imaging (MRI), impairment of the brain microstructure has been scarcely elucidated. Using multiparametric quantitative (q) magnetic resonance imaging MRI, we aimed to investigate diffuse impairment of the microstructural tissue integrity in MRI-negative focal epilepsy patients.

Methods

27 MRI-negative patients with focal epilepsy (mean age 33.1 ± 14.2 years) and 27 matched healthy control subjects underwent multiparametric qMRI including T1, T2, and PD mapping at 3 T. After tissue segmentation based on synthetic anatomies, mean qMRI parameter values were extracted from the cerebral cortex, the white matter (WM) and the deep gray matter (GM) and compared between patients and control subjects. Apart from calculating mean values for the qMRI parameters across the respective compartments, voxel-wise analyses were performed for each tissue class.

Results

There were no significant differences for mean values of quantitative T1, T2, and PD obtained from the cortex, the WM and the deep GM between the groups. Furthermore, the voxel-wise analyses did not reveal any clusters indicating significant differences between patients and control subjects for the qMRI parameters in the respective compartments.

Conclusions

Based on the employed methodology, no indication for an impairment of the cerebral microstructural tissue integrity in MRI-negative patients with focal epilepsy was found in this study. Further research will be necessary to identify relevant factors and mechanisms contributing to microstructural brain tissue damage in various subgroups of patients with epilepsy.

Application of data harmonization and tract-based spatial statistics reveals white matter structural abnormalities in pediatric patients with focal cortical dysplasia

Our study assessed diffusion tensor imaging (DTI) metrics of fractional anisotropy (FA), mean diffusivity (MD), and radial diffusivity (RD) in pediatric subjects with epilepsy secondary to Focal Cortical Dysplasia (FCD) to improve our understanding of structural network changes associated with FCD related epilepsy. We utilized a data harmonization (DH) approach to minimize confounding effects induced by MRI protocol differences. We also assessed correlations between DTI metrics and neurocognitive measures of the fluid reasoning index (FRI), verbal comprehension index (VCI), and visuospatial index (VSI). Data (n = 51) from 23 FCD patients and 28 typically developing controls (TD) scanned clinically on either 1.5T, 3T, or 3T-wide-bore MRI were retrospectively analyzed. Tract-based spatial statistics (TBSS) with threshold-free cluster enhancement and permutation testing with 100,000 permutations were used for statistical analysis. To account for imaging protocol differences, we employed non-parametric data harmonization prior to permutation testing. Our analysis demonstrates that DH effectively removed MRI protocol-based differences typical in clinical acquisitions while preserving group differences in DTI metrics between FCD and TD subjects. Furthermore, DH strengthened the association between DTI metrics and neurocognitive indices. Fractional anisotropy, MD, and RD metrics showed stronger correlation with FRI and VSI than VCI. Our results demonstrate that DH is an integral step to reduce the confounding effect of MRI protocol differences during the analysis of white matter tracts and highlights biological differences between FCD and healthy control subjects. Characterization of white matter changes associated with FCD-related epilepsy may better inform prognosis and treatment approaches.

Early suppression of excitability in subcortical band heterotopia modifies epileptogenesis in rats

Malformations of cortical development represent a major cause of epilepsy in childhood. However, the pathological substrate and dynamic changes leading to the development and progression of epilepsy remain unclear. Here, we characterized an etiology-relevant rat model of subcortical band heterotopia (SBH), a diffuse type of cortical malformation associated with drug-resistant seizures in humans. We used longitudinal electrographic recordings to monitor the age-dependent evolution of epileptiform discharges during the course of epileptogenesis in this model. We found both quantitative and qualitative age-related changes in seizures properties and patterns, accompanying a gradual progression towards a fully developed seizure pattern seen in adulthood. We also dissected the relative contribution of the band heterotopia and the overlying cortex to the development and age-dependent progression of epilepsy using timed and spatially targeted manipulation of neuronal excitability. We found that an early suppression of neuronal excitability in SBH slows down epileptogenesis in juvenile rats, whereas epileptogenesis is paradoxically exacerbated when excitability is suppressed in the overlying cortex. However, in rats with active epilepsy, similar manipulations of excitability have no effect on chronic spontaneous seizures. Together, our data support the notion that complex developmental alterations occurring in both the SBH and the overlying cortex concur to creating pathogenic circuits prone to generate seizures. Our study also suggests that early and targeted interventions could potentially influence the course of these altered developmental trajectories, and favorably modify epileptogenesis in malformations of cortical development.

Networks Underlie Temporal Onset of Dysplasia-Related Epilepsy: A MELD Study

OBJECTIVE

The purpose of this study was to evaluate if focal cortical dysplasia (FCD) co-localization to cortical functional networks is associated with the temporal distribution of epilepsy onset in FCD.

METHODS

International (20 center), retrospective cohort from the Multi-Centre Epilepsy Lesion Detection (MELD) project. Patients included if >3 years old, had 3D pre-operative T1 magnetic resonance imaging (MRI; 1.5 or 3 T) with radiologic or histopathologic FCD after surgery. Images processed using the MELD protocol, masked with 3D regions-of-interest (ROI), and co-registered to fsaverage_sym (symmetric template). FCDs were then co-localized to 1 of 7 distributed functional cortical networks. Negative binomial regression evaluated effect of FCD size, network, histology, and sulcal depth on age of epilepsy onset. From this model, predictive age of epilepsy onset was calculated for each network.

RESULTS

Three hundred eighty-eight patients had median age seizure onset 5 years (interquartile range [IQR] = 3-11 years), median age at pre-operative scan 18 years (IQR = 11-28 years). FCDs co-localized to the following networks: limbic (90), default mode (87), somatomotor (65), front parietal control (52), ventral attention (32), dorsal attention (31), and visual (31). Larger lesions were associated with younger age of onset (p = 0.01); age of epilepsy onset was associated with dominant network (p = 0.04) but not sulcal depth or histology. Sensorimotor networks had youngest onset; the limbic network had oldest age of onset (p values <0.05).

INTERPRETATION

FCD co-localization to distributed functional cortical networks is associated with age of epilepsy onset: sensory neural networks (somatomotor and visual) with earlier onset, and limbic latest onset. These variations may reflect developmental differences in synaptic/white matter maturation or network activation and may provide a biological basis for age-dependent epilepsy onset expression. ANN NEUROL 2022;92:503-511.

Expedited epilepsy surgery prior to drug resistance in children: a frontier worth crossing?

Epilepsy surgery is an established safe and effective treatment for selected candidates with drug-resistant epilepsy. In this opinion piece, we outline the clinical and experimental evidence for selectively considering epilepsy surgery prior to drug resistance. Our rationale for expedited surgery is based on the observations that, 1) a high proportion of patients with lesional epilepsies (e.g. focal cortical dysplasia, epilepsy associated tumours) will progress to drug-resistance, 2) surgical treatment of these lesions, especially in non-eloquent areas of brain, is safe, and 3) earlier surgery may be associated with better seizure outcomes. Potential benefits beyond seizure reduction or elimination include less exposure to anti-seizure medications (ASM), which may lead to improved developmental trajectories in children and optimize long-term neurocognitive outcomes and quality of life. Further, there exists emerging experimental evidence that brain network dysfunction exists at the onset of epilepsy, where continuing dysfunctional activity could exacerbate network perturbations. This in turn could lead to expanded seizure foci and contribution to the comorbidities associated with epilepsy. Taken together, we rationalize that epilepsy surgery, in carefully selected cases, may be considered prior to drug resistance. Lastly, we outline the path forward, including the challenges associated with developing the evidence base and implementing this paradigm into clinical care.