Accession Number : ADA619188

Title :   Combining the Finite Element Method with Structural Connectome-based Analysis for Modeling Neurotrauma: Connectome Neurotrauma Mechanics

Descriptive Note : Journal article

Corporate Author : ARMY RESEARCH LAB ABERDEEN PROVING GROUND MD

Personal Author(s) : Kraft, Reuben H ; McKee, Phillip J ; Dagro, Amy M ; Grafton, Scott T

Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a619188.pdf

Report Date : 16 Aug 2012

Pagination or Media Count : 16

Abstract : This article presents the integration of brain injury biomechanics and graph theoretical analysis of neuronal connections, or connectomics, to form a neurocomputational model that captures spatiotemporal characteristics of trauma. We relate localized mechanical brain damage predicted from biofidelic finite element simulations of the human head subjected to impact with degradation in the structural connectome for a single individual. The finite element model incorporates various length scales into the full head simulations by including anisotropic constitutive laws informed by diffusion tensor imaging. Coupling between the finite element analysis and network-based tools is established through experimentally-based cellular injury thresholds for white matter regions. Once edges are degraded, graph theoretical measures are computed on the damaged network. For a frontal impact, the simulations predict that the temporal and occipital regions undergo the most axonal strain and strain rate at short times (less than 24 hrs), which leads to cellular death initiation, which results in damage that shows dependence on angle of impact and underlying microstructure of brain tissue. The monotonic cellular death relationships predict a spatiotemporal change of structural damage. Interestingly, at 96 hrs post-impact, computations predict no network nodes were completely disconnected from the network, despite significant damage to network edges. At early times (tv24 hrs) network measures of global and local efficiency were degraded little; however, as time increased to 96 hrs the network properties were significantly reduced. In the future, this computational framework could help inform functional networks from physics-based structural brain biomechanics to obtain not only a biomechanics-based understanding of injury, but also neurophysiological insight.

Descriptors :   *BIOMECHANICS , *BRAIN DAMAGE , FINITE ELEMENT ANALYSIS , PATHOPHYSIOLOGY

Subject Categories : Anatomy and Physiology
      Medicine and Medical Research
      Operations Research
      Biomedical Instrumentation and Bioengineering

Distribution Statement : APPROVED FOR PUBLIC RELEASE