Detecting cerebral palsy in neonatal stroke children: GNN-based detection considering the structural organization of basal ganglia

International audienceAs a long-term consequence of neonatal arterial ischaemic stroke (NAIS), the presence of cerebral palsy (CP) depends on the structural integrity of brain areas, especially of basal ganglia. Yet, it remains challenging to establish an early diagnosis of CP from a conventional structural MRI. In this study, we introduce a graph neural network-based classification for the recognition of NAIS children and mainly for the detection of children with CP among the NAIS ones. From the structural MRI of 68 children aged 7 years old and their corresponding segmentation of basal ganglia, we construct graphs where nodes represent structures, carrying on node and edge attributes structural information (volumes, distances). The classification accuracy achieved by the proposed method is of 86% for the detection of NAIS and of 89% for the detection of CP among neonatal stroke children

Mu rhythm: State of the art with special focus on cerebral palsy

International audienceVarious specific early rehabilitation strategies are proposed to decrease functional disabilities in patients with cerebral palsy (CP). These strategies are thought to favour the mechanisms of brain plasticity that take place after brain injury. However, the level of evidence is low. Markers of brain plasticity would favour validation of these rehabilitation programs. In this paper, we consider the study of mu rhythm for this goal by describing the characteristics of mu rhythm in adults and children with typical development, then review the current literature on mu rhythm in CP. Mu rhythm is composed of brain oscillations recorded by electroencephalography (EEG) or magnetoencephalography (MEG) over the sensorimotor areas. The oscillations are characterized by their frequency, topography and modulation. Frequency ranges within the alpha band (∼10 Hz, mu alpha) or beta band (∼20 Hz, mu beta). Source location analyses suggest that mu alpha reflects somatosensory functions, whereas mu beta reflects motor functions. Event-related desynchronisation (ERD) followed by event-related (re-)synchronisation (ERS) of mu rhythm occur in association with a movement or somatosensory input. Even if the functional role of the different mu rhythm components remains incompletely understood, their maturational trajectory is well described. Increasing age from infancy to adolescence is associated with increasing ERD as well as increasing ERS. A few studies characterised mu rhythm in adolescents with spastic CP and showed atypical patterns of modulation in most of them. The most frequent findings in patients with unilateral CP are decreased ERD and decreased ERS over the central electrodes, but atypical topography may also be found. The patterns of modulations are more variable in bilateral CP. Data in infants and young children with CP are lacking and studies did not address the questions of intra-individual reliability of mu rhythm modulations in patients with CP nor their modification after motor learning. Better characterization of mu rhythm in CP, especially in infants and young children, is warranted before considering this rhythm as a potential neurophysiological marker of brain plasticity

Hand function after neonatal stroke: A graph model based on basal ganglia and thalami structure

Introduction: Neonatal arterial ischemic stroke (NAIS) is a common model to study the impact of a unilateral early brain insult on developmental brain plasticity and the appearance of long-term outcomes. Motor difficulties that may arise are typically related to poor function of the affected (contra-lesioned) hand, but surprisingly also of the ipsilesional hand. Although many longitudinal studies after NAIS have shown that predicting the occurrence of gross motor difficulties is easier, accurately predicting hand motor function (for both hands) from morphometric MRI remains complicated. The hypothesis of an association between the structural organization of the basal ganglia (BG) and thalamus with hand motor function seems intuitive given their key role in sensorimotor function. Neuroimaging studies have frequently investigated these structures to evaluate the correlation between their volumes and motor function following early brain injury. However, the results have been controversial. We hypothesize the involvement of other structural parameters. Method: The study involves 35 children (mean age 7.3 years, SD 0.4) with middle cerebral artery NAIS who underwent a structural T1-weighted 3D MRI and clinical examination to assess manual dexterity using the Box and Blocks Test (BBT). Graphs are used to represent high-level structural information of the BG and thalami (volumes, elongations, distances) measured from the MRI. A graph neural network (GNN) is proposed to predict children’s hand motor function through a graph regression. To reduce the impact of external factors on motor function (such as behavior and cognition), we calculate a BBT score ratio for each child and hand. Results: The results indicate a significant correlation between the score ratios predicted by our method and the actual score ratios of both hands (p < 0.05), together with a relatively high accuracy of prediction (mean L1 distance < 0.03). The structural information seems to have a different influence on each hand’s motor function. The affected hand’s motor function is more correlated with the volume, while the ‘unaffected’ hand function is more correlated with the elongation of the structures. Experiments emphasize the importance of considering the whole macrostructural organization of the basal ganglia and thalami networks, rather than the volume alone, to predict hand motor function. Conclusion: There is a significant correlation between the structural characteristics of the basal ganglia/thalami and motor function in both hands. These results support the use of MRI macrostructural features of the basal ganglia and thalamus as an early biomarker for predicting motor function in both hands after early brain injury

Hand function after neonatal stroke: a graph model based on basal ganglia and thalami structure

International audienceIntroduction: Neonatal arterial ischemic stroke (NAIS) is a common model to study the impact of a unilateral early brain insult on developmental brain plasticity and the appearance of long-term outcomes. Motor difficulties that may arise are typically related to poor function of the affected (contra-lesioned) hand, but surprisingly also of the ipsilesional hand. Although many longitudinal studies after NAIS have shown that predicting the occurrence of gross motor difficulties is easier, accurately predicting hand motor function (for both hands) from morphometric MRI remains complicated. The hypothesis of an association between the structural organization of the basal ganglia (BG) and thalamus with hand motor function seems intuitive, given their key role in sensorimotor function. Neuroimaging studies have frequently investigated these structures to evaluate the correlation between their volumes and motor function following early brain injury. However, the results have been controversial. We hypothesize the involvement of other structural parameters.Method: The study involves 35 children (mean age 7.3 years, SD 0.4) with middle cerebral artery NAIS who underwent a structural T1-weighted 3D MRI and clinical examination to assess manual dexterity using the Box and Blocks Test (BBT). Graphs are used to represent high-level structural information of the BG and thalami (volumes, elongations, distances) measured from the MRI. A graph neural network (GNN) is proposed to predict children’s hand motor function through a graph regression. To reduce the impact of external factors on motor function (such as behavior and cognition), we calculate a BBT score ratio for each child and hand.Results: The results indicate a significant correlation between the score ratios predicted by our method and the actual score ratios of both hands (p < 0.05), together with a relatively high accuracy of prediction (mean L1 distance < 0.03). The structural information seems to have a different influence on each hand’s motor function. The affected hand’s motor function is more correlated with the volume, while the ‘unaffected’ hand function is more correlated with the elongation of the structures. Experiments emphasize the importance of considering the whole macrostructural organization of the basal ganglia and thalami networks, rather than the volume alone, to predict hand motor function.Conclusion: There is a significant correlation between the structural characteristics of the basal ganglia/thalami and motor function in both hands. These results support the use of MRI macrostructural features of the basal ganglia and thalamus as an early biomarker for predicting motor function in both hands after early brain injury

Added value of high-resolution electrical source imaging of ictal activity in children with structural focal epilepsy

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Assessing spino-cortical proprioceptive processing in childhood unilateral cerebral palsy with corticokinematic coherence.

To develop an electrophysiological marker of proprioceptive spino-cortical tracts integrity based on corticokinematic coherence (CKC) in young children with unilateral cerebral palsy (UCP), in whom behavioral measures are not applicable.info:eu-repo/semantics/publishe