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Introduction: The neurobehavioral significance of white matter hyperintensities (WMHs) seen on magnetic resonance imaging after traumatic brain injury (TBI) remains unclear, especially in Veterans and Service Members with a history of mild TBI (mTBI). In this study, we investigate the relation between WMH, mTBI, age, and cognitive performance in a large multisite cohort from the Long-term Impact of Military-relevant Brain Injury Consortium-Chronic Effects of Neurotrauma Consortium., Materials and Methods: The neuroimaging and neurobehavioral assessments for 1,011 combat-exposed, post-9/11 Veterans and Service Members (age range 22-69 years), including those with a history of at least 1 mTBI (n = 813; median postinjury interval of 8 years) or negative mTBI history (n = 198), were examined., Results: White matter hyperintensities were present in both mTBI and comparison groups at similar rates (39% and 37%, respectively). There was an age-by-diagnostic group interaction, such that older Veterans and Service Members with a history of mTBI demonstrated a significant increase in the number of WMHs present compared to those without a history of mTBI. Additional associations between an increase in the number of WMHs and service-connected disability, insulin-like growth factor-1 levels, and worse performance on tests of episodic memory and executive functioning-processing speed were found., Conclusions: Subtle but important clinical relationships are identified when larger samples of mTBI participants are used to examine the relationship between history of head injury and radiological findings. Future studies should use follow-up magnetic resonance imaging and longitudinal neurobehavioral assessments to evaluate the long-term implications of WMHs following mTBI., (© Oxford University Press 2024.)

Mild traumatic brain injury (mTBI) is the most common form of brain injury. While most individuals recover from mTBI, roughly 20% experience persistent symptoms, potentially including reduced fine motor control. We investigate relationships between regional white matter organization and subcortical volumes associated with performance on the Grooved Pegboard (GPB) test in a large cohort of military Service Members and Veterans (SM&Vs) with and without a history of mTBI(s). Participants were enrolled in the Long-term Impact of Military-relevant Brain Injury Consortium-Chronic Effects of Neurotrauma Consortium. SM&Vs with a history of mTBI(s) ( n  = 847) and without mTBI ( n  = 190) underwent magnetic resonance imaging and the GPB test. We first examined between-group differences in GPB completion time. We then investigated associations between GPB performance and regional structural imaging measures (tractwise diffusivity, subcortical volumes, and cortical thickness) in SM&Vs with a history of mTBI(s). Lastly, we explored whether mTBI history moderated associations between imaging measures and GPB performance. SM&Vs with mTBI(s) performed worse than those without mTBI(s) on the non-dominant hand GPB test at a trend level ( p  < 0.1). Higher fractional anisotropy (FA) of tracts including the posterior corona radiata, superior longitudinal fasciculus, and uncinate fasciculus were associated with better GPB performance in the dominant hand in SM&Vs with mTBI(s). These findings support that the organization of several white matter bundles are associated with fine motor performance in SM&Vs. We did not observe that mTBI history moderated associations between regional FA and GPB test completion time, suggesting that chronic mTBI may not significantly influence fine motor control.

Objective: Use diffusion tensor imaging to investigate white matter microstructure attributable to mild TBI (mTBI) and/or posttraumatic stress disorder (PTSD)., Participants: Twenty-seven individuals with mTBI only, 16 with PTSD only, 42 with mTBI + PTSD, and 43 service members who sustained orthopedic injury., Design: Descriptive cross-sectional study., Main Measures: Clinical diffusion tensor imaging sequence to assess fractional anisotropy, mean, axial, and radial diffusivity within selected regions of interest., Results: Corrected analyses revealed a pattern of lower white matter integrity in the PTSD group for several scalar metrics. Regions affected included primarily right hemisphere areas of the internal capsule. These differences associated with the PTSD only cohort were observed in relation to all 3 comparison groups, while the mTBI + PTSD group did not exhibit any notable pattern of white matter abnormalities., Conclusion: Results suggest that lower resolution scan sequences are sensitive to post-acute abnormalities associated with PTSD, particularly in the right hemisphere. In addition, these findings suggest that ongoing PTSD symptoms are associated with differences in white matter diffusion that are more readily detected in a clinical scan sequence than mTBI abnormalities. Future studies are needed to prospectively assess service members prior to onset of injury to verify this pattern of results.

Background: White matter hyperintensities (WMHs) are foci of abnormal signal intensity in white matter regions seen with magnetic resonance imaging (MRI). WMHs are associated with normal ageing and have shown prognostic value in neurological conditions such as traumatic brain injury (TBI). The impracticality of manually quantifying these lesions limits their clinical utility and motivates the utilization of machine learning techniques for automated segmentation workflows., Methods: This study develops a concatenated random forest framework with image features for segmenting WMHs in a TBI cohort. The framework is built upon the Advanced Normalization Tools (ANTs) and ANTsR toolkits. MR (3D FLAIR, T2- and T1-weighted) images from 24 service members and veterans scanned in the Chronic Effects of Neurotrauma Consortium's (CENC) observational study were acquired. Manual annotations were employed for both training and evaluation using a leave-one-out strategy. Performance measures include sensitivity, positive predictive value, [Formula: see text] score and relative volume difference., Results: Final average results were: sensitivity = 0.68 ± 0.38, positive predictive value = 0.51 ± 0.40, [Formula: see text] = 0.52 ± 0.36, relative volume difference = 43 ± 26%. In addition, three lesion size ranges are selected to illustrate the variation in performance with lesion size., Conclusion: Paired with correlative outcome data, supervised learning methods may allow for identification of imaging features predictive of diagnosis and prognosis in individual TBI patients.