Diffuse axonal injury (DAI) has been considered to be one of the main mechanisms leading to permanent disability in patients with traumatic brain injury (TBI) leading to disturbance in axonal function and neuronal damage. Conventional neuroimaging techniques such as computed tomography and magnetic resonance imaging (MRI) are useful in detection of macroscopic lesions. However, due to their lack of sensitivity, they are not sensitive enough to detect DAI. Diffusion-weighted (DW) MRI is a non-invasive imaging method that can be sensitive to subtle white matter (WM) alterations and it is capable of providing information about structural brain connectivity in vivo. The aim of the present research was to study microstructural WM abnormalities following TBI using DW-MRI and advanced analysis techniques e.g. high angular resolution diffusion imaging (HARDI). Patients with mild TBI (mTBI) and orthopedically injured (OI) patients that served as control subjects underwent brain imaging and clinical assessments during the TBICare study. Whole brain global and local WM abnormalities associated with DAI were investigated using diffusion tensor imaging analysis methods and probabilistic tractography. In addition, brain structural connectivity was evaluated following mTBI. Furthermore, the associations of WM alterations and structural network properties with the outcome were assessed.

Patients with mTBI showed lower anisotropy and higher diffusivity measures at acute or sub-acute, and chronic stages of mTBI compared with controls. These WM alterations were susceptible to the average fiber orientation. Additionally, structural network connectivity was altered only locally and no differences were found between patients and controls in the global network properties. However, WM alterations and network metrics were significantly associated with the outcome. This study highlighted that novel advanced HARDI methods are promising tools to detect WM alterations already at the early stage after mTBI. Furthermore, we showed that disruptions in structural brain networks are associated with outcome, and suggest that network properties in the acute/subacute stage are promising imaging biomarkers for prognostic purposes.