Abstract

Neuroimaging biomarkers show promise for improving precision diagnosis and prognosis after mild traumatic brain injury (mTBI), but none has yet been adopted in routine clinical practice. Biophysical modeling of multishell diffusion MRI, using the neurite orientation dispersion and density imaging (NODDI) framework, may improve upon conventional diffusion tensor imaging (DTI) in revealing subtle patterns of underlying white matter microstructural pathology, such as diffuse axonal injury (DAI) and neuroinflammation, that are important for detecting mTBI and determining patient outcome. With a cross-sectional and longitudinal design, we assessed structural MRI, DTI and NODDI in 40 mTBI patients at 2 weeks and 6 months after injury and 14 matched control participants with orthopedic trauma but not suffering from mTBI at 2 weeks. Self-reported and performance-based cognitive measures assessing postconcussive symptoms, memory, executive functions and processing speed were investigated in post-acute and chronic phase after injury for the mTBI subjects. Machine learning analysis was used to identify mTBI patients with the best neuropsychological improvement over time and relate this outcome to DTI and NODDI biomarkers. In the cross-sectional comparison with the trauma control group at 2 weeks post-injury, mTBI patients showed decreased fractional anisotropy (FA) and increased mean diffusivity (MD) on DTI mainly in anterior tracts that corresponded to white matter regions of elevated free water fraction (FISO) on NODDI, signifying vasogenic edema. Patients showed decreases from 2 weeks to 6 months in white matter neurite density on NODDI, predominantly in posterior tracts. No significant longitudinal changes in DTI metrics were observed. The machine learning analysis divided the mTBI patients into two groups based on their recovery. Voxel-wise group comparison revealed associations between white matter orientation dispersion index (ODI) and FISO with degree and trajectory of improvement within the mTBI group. In conclusion, white matter FA and MD alterations early after mTBI might reflect vasogenic edema, as shown by elevated free water on NODDI. Longer-term declines in neurite density on NODDI suggest progressive axonal degeneration due to DAI, especially in tracts known to be integral to the structural connectome. Overall, these results show that the NODDI parameters appear to be more sensitive to longitudinal changes than DTI metrics. Thus, NODDI merits further study in larger cohorts for mTBI diagnosis, prognosis and treatment monitoring.