Utilizing multiple scale models to improve predictions of extra-axial hemorrhage in the immature piglet

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• 作者：Gregory G. Scott ; Susan S. Margulies…
• 关键词：Subarachnoid space ; Microstructure ; Traumatic brain injury ; Finite element modeling ; Arachnoid trabeculae
• 刊名：Biomechanics and Modeling in Mechanobiology
• 出版年：2016
• 出版时间：October 2016
• 年：2016
• 卷：15
• 期：5
• 页码：1101-1119
• 全文大小：6,183 KB
• 刊物类别：Engineering
• 刊物主题：Theoretical and Applied Mechanics
  Biomedical Engineering
  Mechanics
  Biophysics and Biomedical Physics
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1617-7940
• 卷排序：15

文摘

Traumatic brain injury (TBI) is a leading cause of death and disability in the USA. To help understand and better predict TBI, researchers have developed complex finite element (FE) models of the head which incorporate many biological structures such as scalp, skull, meninges, brain (with gray/white matter differentiation), and vasculature. However, most models drastically simplify the membranes and substructures between the pia and arachnoid membranes. We hypothesize that substructures in the pia–arachnoid complex (PAC) contribute substantially to brain deformation following head rotation, and that when included in FE models accuracy of extra-axial hemorrhage prediction improves. To test these hypotheses, microscale FE models of the PAC were developed to span the variability of PAC substructure anatomy and regional density. The constitutive response of these models were then integrated into an existing macroscale FE model of the immature piglet brain to identify changes in cortical stress distribution and predictions of extra-axial hemorrhage (EAH). Incorporating regional variability of PAC substructures substantially altered the distribution of principal stress on the cortical surface of the brain compared to a uniform representation of the PAC. Simulations of 24 non-impact rapid head rotations in an immature piglet animal model resulted in improved accuracy of EAH prediction (to 94 % sensitivity, 100 % specificity), as well as a high accuracy in regional hemorrhage prediction (to 82–100 % sensitivity, 100 % specificity). We conclude that including a biofidelic PAC substructure variability in FE models of the head is essential for improved predictions of hemorrhage at the brain/skull interface.