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      Modeling the mechanics of axonal fiber tracts using the embedded finite element method.

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          Abstract

          A subject-specific human head finite element model with embedded axonal fiber tractography obtained from diffusion tensor imaging was developed. The axonal fiber tractography finite element model was coupled with the volumetric elements in the head model using the embedded element method. This technique enables the calculation of axonal strains and real-time tracking of the mechanical response of the axonal fiber tracts. The coupled model was then verified using pressure and relative displacement-based (between skull and brain) experimental studies and was employed to analyze a head impact, demonstrating the applicability of this method in studying axonal injury. Following this, a comparison study of different injury criteria was performed. This model was used to determine the influence of impact direction on the extent of the axonal injury. The results suggested that the lateral impact loading is more dangerous compared to loading in the sagittal plane, a finding in agreement with previous studies. Through this analysis, we demonstrated the viability of the embedded element method as an alternative numerical approach for studying axonal injury in patient-specific human head models.

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          Author and article information

          Journal
          Int J Numer Method Biomed Eng
          International journal for numerical methods in biomedical engineering
          Wiley-Blackwell
          2040-7947
          2040-7939
          May 2017
          : 33
          : 5
          Affiliations
          [1 ] Department of Mechanical and Nuclear Engineering, The Pennsylvania State University, University Park, PA 16802, USA.
          [2 ] Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA.
          Article
          10.1002/cnm.2823
          27502006
          b8eba7bc-173c-4f80-8d25-9b4e698984bb
          History

          axonal fiber network,axonal injury,diffusion tensor imaging,embedded element method,finite element model,tractography

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