Browsing by Author "Ji, Songbai"

Now showing 1 - 3 of 3
  • Thumbnail Image
    Item
    Group-wise evaluation and comparison of white matter fiber strain and maximum principal strain in sports-related concussion
    (Mary Ann Liebert, 2015-04-01) Ji, Songbai; Zhao, Wei; Ford, James C.; Beckwith, Jonathan G.; Bolander, Richard P.; Greenwald, Richard M.; Flashman, Laura A.; Paulsen, Keith D.; McAllister, Thomas W.; Department of Psychiatry, IU School of Medicine
    Sports-related concussion is a major public health problem in the United States and yet its biomechanical mechanisms remain unclear. In vitro studies demonstrate axonal elongation as a potential injury mechanism; however, current response-based injury predictors (e.g., maximum principal strain, ε(ep)) typically do not incorporate axonal orientations. We investigated the significance of white matter (WM) fiber orientation in strain estimation and compared fiber strain (ε(n)) with ε(ep) for 11 athletes with a clinical diagnosis of concussion. Geometrically accurate subject-specific head models with high mesh quality were created based on the Dartmouth Head Injury Model (DHIM), which was successfully validated (performance categorized as "good" to "excellent"). For WM regions estimated to be exposed to high strains using a range of injury thresholds (0.09-0.28), substantial differences existed between ε(n) and ε(ep) in both distribution (Dice coefficient of 0.13-0.33) and extent (∼ 5-10-fold differences), especially at higher threshold levels and higher rotational acceleration magnitudes. For example, an average of 3.2% vs. 29.8% of WM was predicted above an optimal threshold of 0.18 established from an in vivo animal study using ε(n) and ε(ep), respectively, with an average Dice coefficient of 0.14. The distribution of WM regions with high ε(n) was consistent with typical heterogeneous patterns of WM disruptions in diffuse axonal injury, and the group-wise extent at the optimal threshold matched well with the percentage of WM voxels experiencing significant longitudinal changes of fractional anisotropy and mean diffusivity (3.2% and 3.44%, respectively) found from a separate independent study. These results suggest the significance of incorporating WM microstructural anisotropy in future brain injury studies.
  • Thumbnail Image
    Item
    Head impact accelerations for brain strain-related responses in contact sports: a model-based investigation
    (Springer, 2014-10) Ji, Songbai; Zhao, Wei; Li, Zhigang; McAllister, Thomas W.; Psychiatry, School of Medicine
    Both linear (alin) and rotational (arot) accelerations contribute to head impacts on the field in contact sports; however, they are often isolated in injury studies. It is critical to evaluate the feasibility of estimating brain responses using isolated instead of full degrees-of-freedom (DOFs) accelerations. In this study, we investigated the sensitivities of regional brain strain-related responses to resultant alin and arot as well as the relative contributions of these acceleration components to the responses via random sampling and linear regression using parameterized, triangulated head impacts with kinematic variable values based on on-field measurements. Two independently established and validated finite element models of the human head were employed to evaluate model consistency and dependency in results: the Dartmouth Head Injury Model (DHIM) and Simulated Injury Monitor (SIMon). For the majority of the brain, volume-weighted regional peak strain, strain rate, and von Mises stress accumulated from the simulation significantly correlated to the product of the magnitude and duration of arot, or effectively, the rotational velocity, but not to alin. Responses from arot-only were comparable to the full-DOFs counterparts especially when normalized by injury-causing thresholds (e.g., volume fractions of large differences virtually diminished (i.e., <1%) at typical difference percentage levels of 1–4% on average). These model-consistent results support the inclusion of both rotational acceleration magnitude and duration into kinematics-based injury metrics, and demonstrate the feasibility of estimating strain-related responses from isolated arot for analyses of strain-induced injury relevant to contact sports without significant loss of accuracy, especially for the cerebrum.
  • Thumbnail Image
    Item
    White Matter Injury Susceptibility via Fiber Strain Evaluation Using Whole-Brain Tractography
    (Mary Ann Leibert, 2016-10-15) Zhao, Wei; Ford, James C.; Flashman, Laura A.; McAllister, Thomas W.; Ji, Songbai; Psychiatry, School of Medicine
    Microscale brain injury studies suggest axonal elongation as a potential mechanism for diffuse axonal injury (DAI). Recent studies have begun to incorporate white matter (WM) structural anisotropy in injury analysis, with initial evidence suggesting improved injury prediction performance. In this study, we further develop a tractography-based approach to analyze fiber strains along the entire lengths of fibers from voxel- or anatomically constrained whole-brain tractography. This technique potentially extends previous element- or voxel-based methods that instead utilize WM fiber orientations averaged from typically coarse elements or voxels. Perhaps more importantly, incorporating tractography-based axonal structural information enables assessment of the overall injury risks to functionally important neural pathways and the anatomical regions they connect, which is not possible with previous methods. A DAI susceptibility index was also established to quantify voxel-wise WM local structural integrity and tract-wise damage of individual neural pathways. This “graded” injury susceptibility potentially extends the commonly employed treatment of injury as a simple binary condition. As an illustration, we evaluate the DAI susceptibilities of WM voxels and transcallosal fiber tracts in three idealized head impacts. Findings suggest the potential importance of the tractography-based approach for injury prediction. These efforts may enable future studies to correlate WM mechanical responses with neuroimaging, cognitive alteration, and concussion, and to reveal the relative vulnerabilities of neural pathways and identify the most vulnerable ones in real-world head impacts.