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Background and Objective: Epilepsy is associated with alterations in the structural framework of the cerebral network. The aim of this study was to measure the potential of global metrics of network architecture derived from resting state functional MRI to capture the impact of epilepsy on the developing brain., Methods: Pediatric patients were retrospectively identified with: 1. Focal epilepsy; 2. Brain MRI at 3 Tesla, including resting state functional MRI; 3. Full scale IQ measured by a pediatric neuropsychologist. The cerebral cortex was parcellated into approximately 700 gray matter network nodes. The strength of a connection between two nodes was defined as the correlation between their resting BOLD signal time series. The following global network metrics were then calculated: clustering coefficient, transitivity, modularity, path length, and global efficiency. Epilepsy duration was used as an index for the cumulative impact of epilepsy on the brain., Results: 45 patients met criteria (age: 4-19 years). After accounting for age of epilepsy onset, epilepsy duration was inversely related to IQ ( p : 0.01). Epilepsy duration predicted by a machine learning algorithm on the basis of the five global network metrics was highly correlated with actual epilepsy duration (r: 0.95; p : 0.0001). Specifically, modularity and to a lesser extent path length and global efficiency were independently associated with epilepsy duration., Conclusions: We observed that a machine learning algorithm accurately predicted epilepsy duration based on global metrics of network architecture derived from resting state fMRI. These findings suggest that network metrics have the potential to form the basis for statistical models that translate quantitative imaging data into patient-level markers of cognitive deterioration.

Objective: To study magnetic resonance imaging (MRI) correlates of novel (new-onset) psychiatric disorders (NPD) after traumatic brain injury (TBI) and orthopedic injury (OI)., Method: Participants were 7 to 17 years of age at the time of hospitalization for either TBI or OI. The study used a prospective, longitudinal, controlled design with standardized psychiatric assessments conducted at baseline (reflecting pre-injury function) and 3 months post-injury. MRI assessments including diffusion tensor imaging (DTI)-derived fractional anisotropy (FA), volumetric measures of gray and white matter regions, volumetric measures of lesions, and cortical thickness were conducted. Injury severity was assessed by standard clinical scales. The outcome measure was the presence of an NPD identified during the first 3 months after injury., Results: There were 88 participants (TBI, 44; OI, 44). NPD occurred more frequently in the TBI (21/44; 48%) versus the OI (6/44; 14%) group (Fisher's exact test, p = .001). NPD in TBI participants was not related to injury severity. Multivariate analysis of covariance of the relationship between FA in hypothesized regions of interest (bilateral frontal and temporal lobes, bilateral centrum semiovale, bilateral uncinate fasciculi) and NPD and group (TBI versus OI) was significant, and both variables (NPD, p < .05; group, p < .001) were jointly significantly related to FA. NPD was not significantly related to volumetric measures of white or gray matter structures, volumetric measures of lesions, or cortical thickness measures., Conclusions: Lowered white matter integrity may be more important in the pathophysiology of NPD than indices of gray matter or white matter atrophic changes, macroscopic lesions, and injury severity., (Copyright © 2012 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.)