Adaptive Algorithms to Map how Brain Trauma Affects Anatomical Connectivity in Children

Deficits in white matter (WM) integrity occur following traumatic brain injury (TBI), and often persist long after the visible scars have healed. Heterogeneity in injury types and locations can complicate analyses, making it harder to discover common biomarkers for tracking recovery. Here we apply a newly developed adaptive connectivity method, EPIC (evolving partitions to improve connectomics) to identify differences in structural connectivity that persist longitudinally. This data comes from a longitudinal study, in which we scanned participants (aged 8-19 years) with anatomical and diffusion MRI in both the post-acute and chronic phases (1-6 months and 13-19 months post-injury). To identify patterns of abnormal connectivity, we trained a model on data from 32 TBI patients in the post-acute phase and 45 well-matched healthy controls, reducing an initial 68x68 connectivity matrix to a 14x14 matrix. We then applied this reduced parcellation to the chronic data in participants who had returned for their chronic assessment (21 TBI and 26 healthy controls) and tested for group differences. We found significant differences in two connections, comprising callosal fibers and long anterior-posterior fibers, with the TBI group showing increased fiber density relative to controls. Longitudinal analysis revealed that these were connections that were decreasing over time in the healthy controls, as is a common developmental phenomenon, but they were increasing in the TBI group. While we cannot definitively tell why this may occur with our current data, this study provides targets for longitudinal tracking, and poses questions for future investigation.