Debasis Sahoo

Development and validation of an advanced anisotropic visco-hyperelastic human brain FE model

This paper proposes the implementation of fractional anisotropy and axonal fiber orientation from diffusion tensor imaging (DTI) of 12 healthy patients into an existing human FE head model to develop a more realistic brain model with advanced constitutive laws. Further, the brain behavior was validated in terms of brain strain against experimental data published by Hardy et al. (2001, 2007) and for brain pressure against Nahum et al. (1977) experimental impacts. A reasonable agreement was observed between the simulation and experimental data. Results showed the feasibility of integrating axonal direction information into FE analysis and established the context of computation of axonal elongation in case of head trauma.

Anisotropic composite human skull model and skull fracture validation against temporo-parietal skull fracture.

A composite material model for skull, taking into account damage is implemented in the Strasbourg University finite element head model (SUFEHM) in order to enhance the existing skull mechanical constitutive law. The skull behavior is validated in terms of fracture patterns and contact forces by reconstructing 15 experimental cases. The new SUFEHM skull model is capable of reproducing skull fracture precisely. The composite skull model is validated not only for maximum forces, but also for lateral impact against actual force time curves from PMHS for the first time. Skull strain energy is found to be a pertinent parameter to predict the skull fracture and based on statistical (binary logistical regression) analysis it is observed that 50% risk of skull fracture occurred at skull strain energy of 544.0mJ.

Brain injury tolerance limit based on computation of axonal strain

Traumatic brain injury (TBI) is the leading cause of death and permanent impairment over the last decades. In both the severe and mild TBIs, diffuse axonal injury (DAI) is the most common pathology and leads to axonal degeneration. Computation of axonal strain by using finite element head model in numerical simulation can enlighten the DAI mechanism and help to establish advanced head injury criteria. The main objective of this study is to develop a brain injury criterion based on computation of axonal strain. To achieve the objective a state-of-the-art finite element head model with enhanced brain and skull material laws, was used for numerical computation of real world head trauma. The implementation of new medical imaging data such as, fractional anisotropy and axonal fiber orientation from Diffusion Tensor Imaging (DTI) of 12 healthy patients into the finite element brain model was performed to improve the brain constitutive material law with more efficient heterogeneous anisotropic visco hyper-elastic material law. The brain behavior has been validated in terms of brain deformation against Hardy et al. (2001), Hardy et al. (2007), and in terms of brain pressure against Nahum et al. (1977) and Trosseille et al. (1992) experiments. Verification of model stability has been conducted as well. Further, 109 well-documented TBI cases were simulated and axonal strain computed to derive brain injury tolerance curve. Based on an in-depth statistical analysis of different intra-cerebral parameters (brain axonal strain rate, axonal strain, first principal strain, Von Mises strain, first principal stress, Von Mises stress, CSDM (0.10), CSDM (0.15) and CSDM (0.25)), it was shown that axonal strain was the most appropriate candidate parameter to predict DAI. The proposed brain injury tolerance limit for a 50% risk of DAI has been established at 14.65% of axonal strain. This study provides a key step for a realistic novel injury metric for DAI.

Development of skull fracture criterion based on real-world head trauma simulations using finite element head model.

The objective of this study was to enhance an existing finite element (FE) head model with composite modeling and a new constitutive law for the skull. The response of the state-of-the-art FE head model was validated in the time domain using data from 15 temporo-parietal impact experiments, conducted with postmortem human surrogates. The new model predicted skull fractures observed in these tests. Further, 70 well-documented head trauma cases were reconstructed. The 15 experiments and 70 real-world head trauma cases were combined to derive skull fracture injury risk curves. The skull internal energy was found to be the best candidate to predict skull failure based on an in depth statistical analysis of different mechanical parameters (force, skull internal energy), head kinematic-based parameter, the head injury criterion (HIC), and skull fracture correlate (SFC). The proposed tolerance limit for 50% risk of skull fracture was associated with 453mJ of internal energy. Statistical analyses were extended for individual impact locations (frontal, occipital and temporo-parietal) and separate injury risk curves were obtained. The 50% risk of skull fracture for each location: frontal: 481mJ, occipital: 457mJ, temporo-parietal: 456mJ of skull internal energy.

Finite element head model simulation and head injury prediction

Head injury is one of the most frequent causes of death and impairment sustained by pedestrians, cyclists, motorcyclists and vehicle occupants in road accidents, and accounts for approximately half of the road fatalities in the European Union (Mellor 2000). About 1.3 million people die each year as a result of road traffic crashes (WHO report 2012). Improved head injury assessment is now necessary to predict the potential risk of head injury under different impact conditions. In the context of head trauma biomechanics, computational modelling of head proved an efficient and promising tool to study the head trauma and to better predict head injury. In this study, 15 car–pedestrian accidents were selected from the Investigation of Vehicle Accidents in Changsha (IVAC) database for impact simulation between the Strasbourg University finite element head model (SUFEHM) and the validated finite element (FE) windscreen model. Head injury risk predictions and the windscreen fracture pattern obtained were verified with the literature to find the robust accuracy of this methodology. This study provides a realistic method for better assessment of head injury.

Head injury assessment of non-lethal projectile impacts: A combined experimental/computational method

The main objective of this study is to develop a methodology to assess this risk based on experimental tests versus numerical predictive head injury simulations. A total of 16 non-lethal projectiles (NLP) impacts were conducted with rigid force plate at three different ranges of impact velocity (120, 72 and 55m/s) and the force/deformation-time data were used for the validation of finite element (FE) NLP. A good accordance between experimental and simulation data were obtained during validation of FE NLP with high correlation value (>0.98) and peak force discrepancy of less than 3%. A state-of-the art finite element head model with enhanced brain and skull material laws and specific head injury criteria was used for numerical computation of NLP impacts. Frontal and lateral FE NLP impacts to the head model at different velocities were performed under LS-DYNA. It is the very first time that the lethality of NLP is assessed by axonal strain computation to predict diffuse axonal injury (DAI) in NLP impacts to head. In case of temporo-parietal impact the min-max risk of DAI is 0-86%. With a velocity above 99.2m/s there is greater than 50% risk of DAI for temporo-parietal impacts. All the medium- and high-velocity impacts are susceptible to skull fracture, with a percentage risk higher than 90%. This study provides tool for a realistic injury (DAI and skull fracture) assessment during NLP impacts to the human head.