Delayed brain development of Rolandic epilepsy profiled by deep learning-based neuroanatomic imaging

Structure-function interrelationships and associated neurotransmitter profiles in drug-naïve benign childhood epilepsy with central-temporal spikes patients

OBJECTIVES

To explore the interrelationships between structural and functional changes as well as the potential neurotransmitter profile alterations in drug-naïve benign childhood epilepsy with central-temporal spikes (BECTS) patients.

METHODS

Structural magnetic resonance imaging (sMRI) and resting-state functional MRI data from 20 drug-naïve BECTS patients and 33 healthy controls (HCs) were acquired. Parallel independent component analysis (P-ICA) was used to identify covarying components among gray matter volume (GMV) maps and fractional amplitude of low-frequency fluctuations (fALFF) maps. Furthermore, we explored the spatial correlations between GMV/fALFF changes derived from P-ICA and neurotransmitter maps in JuSpace toolbox.

RESULTS

A significantly positive correlation (p < 0.001) was identified between one structural component (GMV_IC6) and one functional component (fALFF_IC4), which showed significant group differences between drug-naïve BECTS patients and HCs (GMV_IC6: p < 0.01; fALFF_IC4: p < 0.001). GMV_IC6 showed increased GMV in the frontal lobe, temporal lobe, thalamus, and precentral gyrus as well as fALFF_IC4 had enhanced fALFF in the cerebellum in drug-naïve BECTS patients compared to HCs. Moreover, significant correlations between GMV alterations in GMV_IC6 and the serotonin (5HT1a: p < 0.001; 5HT2a: p < 0.001), norepinephrine (NAT: p < 0.001) and glutamate systems (mGluR5: p < 0.001) as well as between fALFF alterations in fALFF_IC4 and the norepinephrine system (NAT: p < 0.001) were detected.

CONCLUSION

The current findings suggest co-altered structural/functional components that reflect the correlation of language and motor networks as well as associated with the serotonergic, noradrenergic, and glutamatergic neurotransmitter systems.

CLINICAL RELEVANCE STATEMENT

The relationship between anatomical brain structure and intrinsic neural activity was evaluated using a multimodal fusion analysis and neurotransmitters which might provide an important window into the multimodal neural and underlying molecular mechanisms of benign childhood epilepsy with central-temporal spikes.

KEY POINTS

Structure-function relationships in drug-naïve benign childhood epilepsy with central-temporal spikes (BECTS) patients were explored. The interrelated structure-function components were found and correlated with the serotonin, norepinephrine, and glutamate systems. Co-altered structural/functional components reflect the correlation of language and motor networks and correlate with the specific neurotransmitter systems.

Combined diffusion tensor imaging and quantitative susceptibility mapping to characterize normal-appearing white matter in self-limited epilepsy with centrotemporal spikes

PURPOSE

In brain development, Myelination is the characteristic feature of white matter maturation, which plays an important role in efficient information transmitting. The white matter abnormality has been reported to be associated with self-limited epilepsy with centrotemporal spikes (SeLECTS). This study aimed to detect the altered white matter region in the SeLECTS patients by the combination of diffusion tensor imaging (DTI) and quantitative susceptibility mapping (QSM) technique.

METHODS

27 children with SeLECTS and 23 age- and gender-matched healthy children were enrolled. All participants were scanned with 3.0-T MRI to acquire the structure, diffusion and susceptibility-weighted data. The susceptibility and diffusion weighted data were processed to obtain quantitative susceptibility map and fraction anisotropy (FA) map. Then voxel-wise tract-based spatial statistics (TBSS) were used to analyze quantitative susceptibility and FA data.

RESULTS

Both DTI and QSM revealed extensive white matter alterations in the frontal, parietal, and temporal lobes in SeLECTS patients. The overlapped region of DTI and QSM analyses was located in the fiber tracts of the corona radiata. The FA values in this overlapped region were negatively correlated with the magnetic susceptibility values.

CONCLUSION

Our results suggest that TBSS-based QSM can be employed as a novel approach for characterizing alterations in white matter in SeLECTS. And the combination of QSM and DTI can provide a more comprehensive evaluation of white matter integrity by utilizing different biophysical features.

Cognitive development in children with new-onset Rolandic epilepsy and Rolandic discharges without seizures: Focusing on intelligence, visual perception, working memory and the role of parents' education

PURPOSE

Our aim was to assess intelligence, visual perception and working memory in children with new-onset Rolandic epilepsy (RE) and children with Rolandic discharges without seizures (RD).

METHODS

The participants in the study were 12 children with RE and 26 children with RD aged 4 to 10 years (all without medication and shortly after diagnosis) and 31 healthy controls. Their cognitive performance was assessed using the German versions of the Wechsler Preschool and Primary Scale of Intelligence (WPPSI-III), the Wechsler Intelligence Scale for Children (WISC-IV), the Developmental Test of Visual Perception-2 (DTVP-2), the Developmental Test of Visual Perception-Adolescent and Adult (DTVP-A) (each according to age) and the Word Order, Hand Movements and Spatial Memory subtests of the German version of the Kaufman Assessment Battery for Children (K-ABC).

RESULTS

The comparison of the entire group of children with RE/RD and the control group conducted in the first step of our analysis revealed a weaker performance of the children with RE/RD in all cognitive domains. Significant deficits, however, were found exclusively in the RD group. Compared to the controls, they performed significantly weaker regarding IQ (full scale IQ: p < 0.001; verbal IQ: p < 0.001; performance IQ: p = 0.002; processing speed: p = 0.005), visual perception (general visual perception: p = 0.005; visual-motor integration: p = 0.002) and working memory (WISC working memory: p = 0.002 and K-ABC Word Order (p = 0.010) and Hand Movements (p = 0.001) subtests. Also, the children without seizures scored significantly lower than those with seizures on the WISC Working Memory Index (p = 0.010) and on the K-ABC Word Order (p = 0.021) and Hand Movements (p = 0.027) subtests. Further analysis of our data demonstrated the particular importance of the family context for child development. Significant cognitive deficits were found only in children with RD from parents with lower educational levels. This group consistently scored lower compared to the control group regarding IQ (full scale IQ: p < 0.001; verbal IQ: p < 0.001; performance IQ: p = 0.012; processing speed: p = 0.034), visual perception (general visual perception: p = 0.018; visual-motor integration: p = 0.010) and auditory working memory (WISC working memory: p = 0.014). Furthermore, compared to the children with RE, they performed significantly weaker on verbal IQ (p = 0.020), auditory working memory consistently (WISC working memory: p = 0.027; K-ABC: Word Order: p = 0.046) as well as in one of the K-ABC spatial working memory subtests (Hand Movements: p = 0.029). Although we did not find significant deficits in children with new-onset RE compared to healthy controls, the performance of this group tended to be weaker more often. No statistically significant associations were observed between selected clinical markers (focus types: centrotemporal/other foci/laterality of foci and spread of Rolandic discharges) and cognitive test results. Except for spatial working memory, we also found no evidence that the age of our patients at the time of study participation was of significant importance to their cognitive performance.

CONCLUSIONS

Our study provides some evidence that children with Rolandic discharges, with and without seizures, may be at higher risk of cognitive impairment. In addition to medical care, we emphasise early differentiated psychosocial diagnostics to provide these children and their families with targeted support if developmental problems are present.

Quantitative susceptibility mapping shows lower brain iron content in children with childhood epilepsy with centrotemporal spikes

PURPOSE

The dysregulation of brain iron homeostasis is closely relevant to a multitude of chronic neurological disorders. This study employed quantitative susceptibility mapping (QSM) to detect and compare whole-brain iron content between childhood epilepsy with centrotemporal spikes (CECTS) children and typically developing children.

MATERIALS AND METHODS

32 children with CECTS and 25 age- and gender-matched healthy children were enrolled. All participants were imaged with 3.0-T MRI to acquire the structural and susceptibility-weighted data. The susceptibility-weighted data were processed using STISuite toolbox to obtain QSM. The magnetic susceptibility difference between the two groups was compared using voxel-wise and region of interest methods. Multivariable linear regression, controlling for age, were employed to investigate the associations between the brain magnetic susceptibility and age at onset.

RESULTS

Lower magnetic susceptibility was mainly observed in sensory- and motor-related brain regions in children with CECTS, including bilateral middle frontal gyrus, supplementary motor area, midcingulate cortex, paracentral lobule and precentral gyrus, the magnetic susceptibility of right paracentral lobule, right precuneus and left supplementary motor area were found to have positive correlation with the age at onset.

CONCLUSIONS

This study suggests that the potential iron deficiency in certain brain regions is associated with CECTS, which might be helpful for further illumination of potential pathogenesis mechanism of CECTS.

Predicting Antiseizure Medication Treatment in Children with Rare Tuberous Sclerosis Complex-Related Epilepsy Using Deep Learning

BACKGROUND AND PURPOSE

Tuberous sclerosis complex disease is a rare, multisystem genetic disease, but appropriate drug treatment allows many pediatric patients to have positive outcomes. The purpose of this study was to predict the effectiveness of antiseizure medication treatment in children with tuberous sclerosis complex-related epilepsy.

MATERIALS AND METHODS

We conducted a retrospective study involving 300 children with tuberous sclerosis complex-related epilepsy. The study included the analysis of clinical data and T2WI and FLAIR images. The clinical data consisted of sex, age of onset, age at imaging, infantile spasms, and antiseizure medication numbers. To forecast antiseizure medication treatment, we developed a multitechnique deep learning method called WAE-Net. This method used multicontrast MR imaging and clinical data. The T2WI and FLAIR images were combined as FLAIR3 to enhance the contrast between tuberous sclerosis complex lesions and normal brain tissues. We trained a clinical data-based model using a fully connected network with the above-mentioned variables. After that, a weighted-average ensemble network built from the ResNet3D architecture was created as the final model.

RESULTS

The experiments had shown that age of onset, age at imaging, infantile spasms, and antiseizure medication numbers were significantly different between the 2 drug-treatment outcomes (P < .05). The hybrid technique of FLAIR3 could accurately localize tuberous sclerosis complex lesions, and the proposed method achieved the best performance (area under the curve = 0.908 and accuracy of 0.847) in the testing cohort among the compared methods.

CONCLUSIONS

The proposed method could predict antiseizure medication treatment of children with rare tuberous sclerosis complex-related epilepsy and could be a strong baseline for future studies.

Atypical functional connectivity hierarchy in Rolandic epilepsy

Functional connectivity hierarchy is an important principle in the process of brain functional organization and an important feature reflecting brain development. However, atypical brain network hierarchy organization in Rolandic epilepsy have not been systematically investigated. We examined connectivity alteration with age and its relation to epileptic incidence, cognition, or underlying genetic factors in 162 cases of Rolandic epilepsy and 117 typically developing children, by measuring fMRI multi-axis functional connectivity gradients. Rolandic epilepsy is characterized by contracting and slowing expansion of the functional connectivity gradients, highlighting the atypical age-related change of the connectivity hierarchy in segregation properties. The gradient alterations are relevant to seizure incidence, cognition, and connectivity deficit, and development-associated genetic basis. Collectively, our approach provides converging evidence for atypical connectivity hierarchy as a system-level substrate of Rolandic epilepsy, suggesting this is a disorder of information processing across multiple functional domains, and established a framework for large-scale brain hierarchical research.

Language-related brain areas in childhood epilepsy with centrotemporal spikes studied with MEG

OBJECTIVE

Children with self-limited epilepsy with centrotemporal spikes (SeLECTS) typically indicate cognitive impairment with widespread speech impairment. We explored how epilepsy affects language-related brain areas and areas in their vicinity.

METHODS

Twenty-two children with SeLECTS and declined verbal comprehension (DVC), 21 with SeLECTS and normal verbal comprehension (NVC), and 23 healthy controls (HCs) underwent high-sampling magnetoencephalography recordings. According to a previous study, 24 language-related regions of interest were selected bilaterally, and the relative spectral power was estimated using a minimum norm estimate.

RESULTS

The highest mean power spectral density was observed in the delta band for the DVC group, in the theta band for the NVC group, and in the alpha band for HCs within language-specific brain regions. The distinctions between the DVC and NVC groups in the delta and theta frequency bands were primarily concentrated in the right linguistic brain area.

CONCLUSIONS

Children with SeLECTS may have developmental problems in language-related brain areas, with different developmental levels observed in the DVC, NVC, and HC groups. The DVC group could have inferior speech comprehension due to a more significant number of seizures and more left-sided spike locations.

SIGNIFICANCE

Children having SeLECTS showed impaired brain maturation, leading to associated language impairment.

Epilepsy syndromes in cerebral palsy: varied, evolving and mostly self-limited

Seizures occur in approximately one-third of children with cerebral palsy. This study aimed to determine epilepsy syndromes in children with seizures and cerebral palsy due to vascular injury, anticipating that this would inform treatment and prognosis. We studied a population-based cohort of children with cerebral palsy due to prenatal or perinatal vascular injuries, born 1999-2006. Each child's MRI was reviewed to characterize patterns of grey and white matter injury. Children with syndromic or likely genetic causes of cerebral palsy were excluded, given their inherent association with epilepsy and our aim to study a homogeneous cohort of classical cerebral palsy. Chart review, parent interview and EEGs were used to determine epilepsy syndromes and seizure outcomes. Of 256 children, 93 (36%) had one or more febrile or afebrile seizures beyond the neonatal period and 87 (34%) had epilepsy. Children with seizures were more likely to have had neonatal seizures, have spastic quadriplegic cerebral palsy and function within Gross Motor Function Classification System level IV or V. Fifty-six (60%) children with seizures had electroclinical features of a self-limited focal epilepsy of childhood; we diagnosed these children with a self-limited focal epilepsy-variant given the current International League Against Epilepsy classification precludes a diagnosis of self-limited focal epilepsy in children with a brain lesion. Other epilepsy syndromes were focal epilepsy-not otherwise specified in 28, infantile spasms syndrome in 11, Lennox-Gastaut syndrome in three, genetic generalized epilepsies in two and febrile seizures in nine. No epilepsy syndrome could be assigned in seven children with no EEG. Twenty-one changed syndrome classification during childhood. Self-limited focal epilepsy-variant usually manifested with a mix of autonomic and brachio-facial motor features, and occipital and/or centro-temporal spikes on EEG. Of those with self-limited focal epilepsy-variant, 42/56 (75%) had not had a seizure for >2 years. Favourable seizure outcomes were also seen in some children with infantile spasms syndrome and focal epilepsy-not otherwise specified. Of the 93 children with seizures, at last follow-up (mean age 15 years), 61/91 (67%) had not had a seizure in >2 years. Children with cerebral palsy and seizures can be assigned specific epilepsy syndrome diagnoses typically reserved for normally developing children, those syndromes commonly being age-dependent and self-limited. Compared to typically developing children with epilepsy, self-limited focal epilepsy-variant occurs much more commonly in children with cerebral palsy and epilepsy. These findings have important implications for treatment and prognosis of epilepsy in cerebral palsy, and research into pathogenesis of self-limited focal epilepsy.

Imaging Genetics in Epilepsy: Current Knowledge and New Perspectives

Epilepsy is a neurological network disease with genetics playing a much greater role than was previously appreciated. Unfortunately, the relationship between genetic basis and imaging phenotype is by no means simple. Imaging genetics integrates multidimensional datasets within a unified framework, providing a unique opportunity to pursue a global vision for epilepsy. This review delineates the current knowledge of underlying genetic mechanisms for brain networks in different epilepsy syndromes, particularly from a neural developmental perspective. Further, endophenotypes and their potential value are discussed. Finally, we highlight current challenges and provide perspectives for the future development of imaging genetics in epilepsy.

Predicting brain age during typical and atypical development based on structural and functional neuroimaging

Exploring typical and atypical brain developmental trajectories is very important for understanding the normal pace of brain development and the mechanisms by which mental disorders deviate from normal development. A precise and sex-specific brain age prediction model is desirable for investigating the systematic deviation and individual heterogeneity of disorders associated with atypical brain development, such as autism spectrum disorders. In this study, we used partial least squares regression and the stacking algorithm to establish a sex-specific brain age prediction model based on T1-weighted structural magnetic resonance imaging and resting-state functional magnetic resonance imaging. The model showed good generalization and high robustness on four independent datasets with different ethnic information and age ranges. A predictor weights analysis showed the differences and similarities in changes in structure and function during brain development. At the group level, the brain age gap estimation for autistic patients was significantly smaller than that for healthy controls in both the ABIDE dataset and the healthy brain network dataset, which suggested that autistic patients as a whole exhibited the characteristics of delayed development. However, within the ABIDE dataset, the premature development group had significantly higher Autism Diagnostic Observation Schedule (ADOS) scores than those of the delayed development group, implying that individuals with premature development had greater severity. Using these findings, we built an accurate typical brain development trajectory and developed a method of atypical trajectory analysis that considers sex differences and individual heterogeneity. This strategy may provide valuable clues for understanding the relationship between brain development and mental disorders.