Numercial Investigations Of The Biomechanical Behavior Of Diffuse Brain Injuries

Traumatic brain injuries(TBIs) are most frequently injuries in road traffic accidents(RTAs), while about 40% of the victims were died from serious TBI among all the deaths associated with RTAs. TBIs induced fatalities and disabilities are also serious public economic problems in the modern society because of the huge costs fro TBI-related hospitalizations and the valued years of potential life lost. The mechanisms and tolerances of TBIs should be clearly understood, which forms fundamental knowledge for p rotection of human brain and reduction of the casualties in RTAs.Diffuse brain injuries(DBIs) are most common types of TBIs, and the serious DBIs are commonly associated with prolonged traumatic coma or death. In the last several decades, the studies on the biomechanical behavior of TBIs have been widely conducted by using biological materials, mechanical models and also mathematical models. Since head impact tests associated with TBIs could not be conducted via in vivo human body, therefore in vivo animal head impact experiments have been conducted for the investigation of DBIs based on the similar pathology of TBIs between humans and other mammals.The objective of this study was to investigate the biomechanical behavior and tolerances of DBIs via the application of in vivo rat head impact experimental data and the finite element(FE) model. A novel rat head FE model was developed and validated; intracranial dynamic responses of the rat head sustained DBIs were analyzed; tolerances of the cerebral c ell and axon injuries associated with DBIs were determined; risk functions of the cerebral cell and axon injuries in terms of intracranial dynamic responses were established via the analysis of the Logistic regression model, corresponding statistical toler ances were determined from injury risk functions; the possible translation of brain injury criteria between human and animals were discussed.Firstly, a novel rat head FE model was developed based on anatomical structures and inhomogeneous mechanical chara cteristic of rat brain. The FE model of the rat brain consists of 25 anatomic regions, including the corpus callosum, hippocampus, thalamus, hypothalamus, cingulated cortex, parietal region, temporal region, occipital region, cerebellum, brainstem, olfactory bulb, skull, meninx-cerebrospinal fluid, etc. Experimental measured mechanical properties were assigned to corresponding anatomical regions of the rat brain. The biofidelity of the rat head FE model were validated against the in vivo Dynamic Cortical Deformation(DCD) test.Then, in vivo rat head rotational impacts were reconstructed using the rat head FE model to investigate the intracranial dynamic responses associated with DBIs. The deformation of the brain tissue as well as the loading transformation were investigated based on FE modeling of relative skull-brain displacements. The performance of the rat head model were further validated via the comparison of relative skull-brain displacements between measured data and calculated values from FE simulat ions. The intracranial strain responses were determined as principal parameters for further studies on the biomechanical behavior of DBIs, based on the analysis of the effect of inhomogeneous brain mechanical characteristic on dynamic responses.The biomechanical behavior and tolerances of cerebral cell injuries associated with DBIs were further investigated. Twenty-four in vivo rat head rotational impact experiments were reconstructed using the rat head FE model; intracranial strain responses predicted by FE models were compared against experimental injury outcomes in terms of cerebral cellular damage; thresholds of cerebral cell injuries were determined with respect to the maximum principal strain(MPS) at the cortex and hippocampus regions, respectively; risk functions of the cerebral cell damage were formulated via the Logistic regression model, and thresholds for the 50% probability of the moderate or severe cell damage were determined by the logistic regression analysis with a MPS of 0.19 at the cortex, and a MPS of 0.15 at the hippocampus.The biomechanical behavior and tolerances of the diffuse axonal injury(DAI) were investigated based on FE reconstructions of twenty-six in vivo rat head rotational impact experiments. Region-specific studies were determined for further investigations of tolerances for DAI based on the comparison between the distribution of FE predicted strain responses and the distribution of experimental observed injured axons. Thresholds for DAI were determined in terms of injury indexes(MPS, the product of strain and strain rate, and the cu mulative strain damage measure- CSDM) in different regions of the corpus callosum. Risk functions of the axonal injuries in the frontal region of the corpus callosum were formulated in terms of calculated injury indexes. For the 50% probability of DAI in the frontal corpus callosum, the statistical thresholds determined by logistic regressions is 0.12 for the MPS, 110 s-1 for the product of strain and strain rate, and 17% for the CSDM.Finally, the possible translation of brain injury criteria between human and animals were discussed. The performance of a brain-mass-based scaling law(Holbourn law) for brain injury criteria were evaluated. Simulations using the rat head FE model and a human head FE model revealed that a simple scaling of rotational accelerations of the head may leading to a different brain injury pattern, and the Holbourn law has limits for the scaling of the acceleration duration. It is demonstrated that the translations between human and animals are necessary and feasible via the studies based on region-specific brain injury criteria.Conclusions of this study could be drawn as follows. The developed rat head FE model as well as the combination of FE simulat ions and in vivo animal experimental data are effective tools for the investigation of the biomechanical behavior of DBIs. Intracranial strain and strain-based dynamic parameters are validated as effective indexes for the prediction and evaluation of DBIs. Risk functions of DBIs were formulated, and the region-specific thresholds for the cerebral cell and axonal injuries associated with DBIs were determined via the logistic regression analysis.