Dynamic changes in diffusion measures improve sensitivity in identifying patients with mild traumatic brain injury

• Published in: PloS one 2017-06, Vol.12 (6), p.e0178360-e0178360
• Main Authors: Thomas, Alexander W, Watts, Richard, Filippi, Christopher G, Nickerson, Joshua P, Andrews, Trevor, Lieberman, Gregory, Naylor, Magdalena R, Eppstein, Margaret J, Freeman, Kalev
• Format: Article
• Language: English
• Subjects: Adolescent; Adult; Anisotropy; Assessments; Biology and Life Sciences; Biomimetics; Brain; Brain Concussion - diagnosis; Brain injuries; Brain Injuries, Traumatic - diagnosis; Brain research; Cognition; Computational neuroscience; Concussion; Data acquisition; Data collection; Diffusion; Diffusion Magnetic Resonance Imaging; Edema; Emergencies; Emergency medical services; Female; Genetic algorithms; Head injuries; Health aspects; Heterogeneity; Humans; Imaging; Injuries; Integrity; Magnetic resonance imaging; Male; Mathematical analysis; Mathematical models; Medicine and Health Sciences; Middle Aged; Neuroimaging; Neurosciences; Patients; Programming; Psychiatry; Reproducibility of Results; Research and Analysis Methods; Sensitivity; Sensitivity and Specificity; Studies; Substantia alba; Surgery; Time measurement; Trauma; Traumatic brain injury; Variability; Variance; Young Adult
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0178360

The goal of this study was to investigate patterns of axonal injury in the first week after mild traumatic brain injury (mTBI). We performed a prospective cohort study of 20 patients presenting to the emergency department with mTBI, using 3.0T diffusion tensor MRI immediately after injury and again at 1 week post-injury. Corresponding data were acquired from 16 controls over a similar time interval. Fractional anisotropy (FA) and other diffusion measures were calculated from 11 a priori selected axon tracts at each time-point, and the change across time in each region was quantified for each subject. Clinical outcomes were determined by standardized neurocognitive assessment. We found that mTBI subjects were significantly more likely to have changes in FA in those 11 regions of interest across the one week time period, compared to control subjects whose FA measurements were stable across time. Longitudinal imaging was more sensitive to these subtle changes in white matter integrity than cross-sectional assessments at either of two time points, alone. Analyzing the sources of variance in our control population, we show that this increased sensitivity is likely due to the smaller within-subject variability obtained by longitudinal analysis with each subject as their own control. This is in contrast to the larger between-subject variability obtained by cross-sectional analysis of each individual subject to normalized data from a control group. We also demonstrated that inclusion of all a priori ROIs in an analytic model as opposed to measuring individual ROIs improves detection of white matter changes by overcoming issues of injury heterogeneity. Finally, we employed genetic programming (a bio-inspired computational method for model estimation) to demonstrate that longitudinal changes in FA have utility in predicting the symptomatology of patients with mTBI. We conclude concussive brain injury caused acute, measurable changes in the FA of white matter tracts consistent with evolving axonal injury and/or edema, which may contribute to post-concussive symptoms.