Dataset Information

Developmental divergence of structural brain networks as an indicator of future cognitive impairments in childhood brain injury: Executive functions.

ABSTRACT: Brain insults during childhood can perturb the already non-linear trajectory of typical brain maturation. The diffuse effects of injury can be modelled using structural covariance networks (SCN), which change as a function of neurodevelopment. However, SCNs are estimated at the group-level, limiting applicability to predicting individual-subject outcomes. This study aimed to measure the divergence of the brain networks in paediatric traumatic brain injury (pTBI) patients and controls, and investigate relationships with executive functioning (EF) at 24 months post-injury. T1-weighted MRI acquired acutely in 78 child survivors of pTBI and 33 controls underwent 3D-tissue segmentation to estimate cortical thickness (CT) across 68 atlas-based regions-of-interest (ROIs). Using an 'add-one-patient' approach, we estimate a developmental divergence index (DDI). Our approach adopts a novel analytic framework in which age-appropriate reference networks to calculate the DDI were generated from control participants from the ABIDE dataset using a sliding-window approach. Divergence from the age-appropriate SCN was related to reduced EF performance and an increase in behaviours related to executive dysfunctions. The DDI measure showed predictive value with regard to executive functions, highlighting that early imaging can assist in prognosis for cognition.

SUBMITTER: King DJ

PROVIDER: S-EPMC6996014 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Developmental divergence of structural brain networks as an indicator of future cognitive impairments in childhood brain injury: Executive functions.

King Daniel J DJ Seri Stefano S Beare Richard R Catroppa Cathy C Anderson Vicki A VA Wood Amanda G AG

Developmental cognitive neuroscience 20200121

Brain insults during childhood can perturb the already non-linear trajectory of typical brain maturation. The diffuse effects of injury can be modelled using structural covariance networks (SCN), which change as a function of neurodevelopment. However, SCNs are estimated at the group-level, limiting applicability to predicting individual-subject outcomes. This study aimed to measure the divergence of the brain networks in paediatric traumatic brain injury (pTBI) patients and controls, and invest ...[more]

PMID: 32072940

Similar Datasets

Project description:Paediatric traumatic brain injury (pTBI) results in inconsistent changes to regional morphometry of the brain across studies. Structural-covariance networks represent the degree to which the morphology (typically cortical-thickness) of cortical-regions co-varies with other regions, driven by both biological and developmental factors. Understanding how heterogeneous regional changes may influence wider cortical network organization may more appropriately capture prognostic information in terms of long term outcome following a pTBI. The current study aimed to investigate the relationships between cortical organisation as measured by structural-covariance, and long-term cognitive impairment following pTBI. T1-weighted magnetic resonance imaging (MRI) from n = 83 pTBI patients and 33 typically developing controls underwent 3D-tissue segmentation using Freesurfer to estimate cortical-thickness across 68 cortical ROIs. Structural-covariance between regions was estimated using Pearson's correlations between cortical-thickness measures across 68 regions-of-interest (ROIs), generating a group-level 68 × 68 adjacency matrix for patients and controls. We grouped a subset of patients who underwent executive function testing at 2-years post-injury using a neuropsychological impairment (NPI) rule, defining impaired- and non-impaired subgroups. Despite finding no significant reductions in regional cortical-thickness between the control and pTBI groups, we found specific reductions in graph-level strength of the structural covariance graph only between controls and the pTBI group with executive function (EF) impairment. Node-level differences in strength for this group were primarily found in frontal regions. We also investigated whether the top n nodes in terms of effect-size of cortical-thickness reductions were nodes that had significantly greater strength in the typically developing brain than n randomly selected regions. We found that acute cortical-thickness reductions post-pTBI are loaded onto regions typically high in structural covariance. This association was found in those patients with persistent EF impairment at 2-years post-injury, but not in those for whom these abilities were spared. This study posits that the topography of post-injury cortical-thickness reductions in regions that are central to the typical structural-covariance topology of the brain, can explain which patients have poor EF at follow-up.

Dataset Information

Developmental divergence of structural brain networks as an indicator of future cognitive impairments in childhood brain injury: Executive functions.

Publications

Developmental divergence of structural brain networks as an indicator of future cognitive impairments in childhood brain injury: Executive functions.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets