Finite element model predictions of intracranial hemorrhage from non-impact, rapid head rotations in the piglet.

Published

Journal Article

Clinicians are charged with the significant task of distinguishing between accidental and inflicted head trauma. Oftentimes this distinction is straightforward, but many times probabilities of injuries from accidental scenarios are unknown making the differential diagnosis difficult. For example, it is unknown whether intracranial hemorrhage (IH) can occur at a location other than a focal contact site following a low height fall. To create a foundation for predicting regional IH in infants, we sought to identify the biomechanical response and injury threshold best able to predict IH in 3-5 day old piglets. First, finite element (FE) model simulations of in situ animal studies were performed to ascertain the optimal representation of the pia-arachnoid complex, cerebrospinal fluid and cortical vasculature (PCC) for predicting brain strain and brain/skull displacement. Second, rapid head rotations resulting in various degrees of IH were simulated (n=24) to determine the biomechanical predictor and injury threshold most closely correlated with IH. FE models representing the PCC with either spring connectors or solid elements between the brain and skull resulted in peak brain strain and brain/skull displacement similar to measured values in situ. However, when predicting IH, the spring connector representation of the PCC had the best predictive capability for IH with a sensitivity of 80% and a specificity of 85% when ≥ 1% of all spring connectors had at least a peak strain of 0.31 mm/mm. These findings and reported methodology will be used in the development of a human infant FE model to simulate real-world falls and identify injury thresholds for predicting IH in infants.

Full Text

Duke Authors

Cited Authors

  • Coats, B; Eucker, SA; Sullivan, S; Margulies, SS

Published Date

  • May 2012

Published In

Volume / Issue

  • 30 / 3

Start / End Page

  • 191 - 200

PubMed ID

  • 22239917

Pubmed Central ID

  • 22239917

Electronic International Standard Serial Number (EISSN)

  • 1873-474X

Digital Object Identifier (DOI)

  • 10.1016/j.ijdevneu.2011.12.009

Language

  • eng

Conference Location

  • England