Xiaogai Li

Decompressive craniectomy causes a significant strain increase in axonal fiber tracts.

Decompressive craniectomy (DC) allows for the expansion of a swollen brain outside the skull and has the potential to reduce intracranial pressure. However, the stretching of axons may contribute to an unfavorable outcome in patients treated with DC. In this study, we present a method for quantifying and visualizing axonal fiber deformation during both the pre-craniectomy and post-craniectomy periods to provide more insight into the mechanical effects of this treatment on axonal fibers. The deformation of the brain tissue in the form of a Lagrangian finite strain tensor for the entire brain was obtained by a non-linear image registration method based on the CT scanning data sets of the patient. Axonal fiber tracts were extracted from diffusion-weighted images. Based on the calculated brain tissue strain tensor and the observed axonal fiber tracts, the deformation of axonal fiber tracts in the form of a first principal strain, axonal strain and axonal shear strain were quantified. The greatest axonal fiber displacement was predominantly located in the treated region of the craniectomy, accompanied by a large axonal deformation close to the skull edge of the craniectomy. The distortion (stretching or shearing) of axonal fibers in the treated area of the craniectomy may influence the axonal fibers in such a way that neurochemical events are disrupted. A quantitative model may clarify some of the potential problems with this treatment.

Influences of brain tissue poroelastic constants on intracranial pressure (ICP) during constant-rate infusion

A 3D finite element (FE) model has been developed to study the mean intracranial pressure (ICP) response during constant-rate infusion using linear poroelasticity. Due to the uncertainties in the poroelastic constants for brain tissue, the influence of each of the main parameters on the transient ICP infusion curve was studied. As a prerequisite for transient analysis, steady-state simulations were performed first. The simulated steady-state pressure distribution in the brain tissue for a normal cerebrospinal fluid (CSF) circulation system showed good correlation with experiments from the literature. Furthermore, steady-state ICP closely followed the infusion experiments at different infusion rates. The verified steady-state models then served as a baseline for the subsequent transient models. For transient analysis, the simulated ICP shows a similar tendency to that found in the experiments, however, different values of the poroelastic constants have a significant effect on the infusion curve. The influence of the main poroelastic parameters including the Biot coefficient , Skempton coefficient B, drained Youngs modulus E, Poissons ratio , permeability , CSF absorption conductance and external venous pressure was studied to investigate the influence on the pressure response. It was found that the value of the specific storage term is the dominant factor that influences the infusion curve, and the drained Youngs modulus E was identified as the dominant parameter second to . Based on the simulated infusion curves from the FE model, artificial neural network (ANN) was used to find an optimised parameter set that best fit the experimental curve. The infusion curves from both the FE simulation and using ANN confirmed the limitation of linear poroelasticity in modelling the transient constant-rate infusion.

Modeling of advanced combat helmet under ballistic impact

The use of combat helmets has greatly reduced penetrating injuries and saved lives of many soldiers. However, behind helmet blunt trauma (BHBT) has emerged as a serious injury type experienced by s ...

Numerical Impact Simulation of Gradually Increased Kinetic Energy Transfer Has the Potential To Break Up Folded Protein Structures Resulting in Cytotoxic Brain Tissue Edema

Although the consequences of traumatic brain injury (TBI) and its treatment have been improved, there is still a substantial lack of understanding the mechanisms. Numerical simulation of the impact can throw further lights on site and mechanism of action. A finite element model of the human head and brain tissue was used to simulate TBI. The consequences of gradually increased kinetic energy transfer was analyzed by evaluating the impact intracranial pressure (ICP), strain level, and their potential influences on binding forces in folded protein structures. The gradually increased kinetic energy was found to have the potential to break apart bonds of Van der Waals in all impacts and hydrogen bonds at simulated impacts from 6 m/s and higher, thereby superseding the energy in folded protein structures. Further, impacts below 6 m/s showed none or very slight increase in impact ICP and strain levels, whereas impacts of 6 m/s or higher showed a gradual increase of the impact ICP and strain levels reaching over 1000 KPa and over 30%, respectively. The present simulation study shows that the free kinetic energy transfer, impact ICP, and strain levels all have the potential to initiate cytotoxic brain tissue edema by unfolding protein structures. The definition of mild, moderate, and severe TBI should thus be looked upon as the same condition and separated only by a gradual severity of impact.

Three Dimensional Poroelastic Simulation of Brain Edema : Initial studies on intracranial pressure

Three Dimensional Poroelastic Simulation of Brain Edema : Initial Studies on Intracranial Pressure Using Comsol Multiphysics

The peculiar properties of the falx and tentorium in brain injury biomechanics

The influence of the falx and tentorium on brain injury biomechanics during impact was studied with finite element (FE) analysis. Three detailed 3D FE head models were created based on the images of a healthy, normal size head. Two of the models contained the addition of falx and tentorium with material properties from previously published experiments. Impact loadings from a reconstructed concussive case in a sport accident were applied to the two players involved. The results suggested that the falx and tentorium could induce large strains to the surrounding brain tissues, especially to the corpus callosum and brainstem. The tentorium seemed to constrain the motion of the cerebellum while inducing large strain in the brainstem in both players involved in the accident (one player had mainly coronal head rotation and the other had both coronal and transversal rotations). Since changed strain levels were observed in the brainstem and corpus callosum, which are classical sites for diffuse axonal injuries (DAI), we confirmed the importance of using accurate material properties for falx and tentorium in a FE head model when studying traumatic brain injuries.

Consequences of the dynamic triple peak impact factor in traumatic brain injury as measured with numerical simulation

There is a lack of knowledge about the direct neuromechanical consequences in traumatic brain injury (TBI) at the scene of accident. In this study we use a finite element model of the human head to study the dynamic response of the brain during the first milliseconds after the impact with velocities of 10, 6, and 2 meters/second (m/s), respectively. The numerical simulation was focused on the external kinetic energy transfer, intracranial pressure (ICP), strain energy density and first principal strain level, and their respective impacts to the brain tissue. We show that the oblique impacts of 10 and 6 m/s resulted in substantial high peaks for the ICP, strain energy density, and first principal strain levels, however, with different patterns and time frames. Also, the 2 m/s impact showed almost no increase in the above mentioned investigated parameters. More importantly, we show that there clearly exists a dynamic triple peak impact factor to the brain tissue immediately after the impact regardless of injury severity associated with different impact velocities. The dynamic triple peak impacts occurred in a sequential manner first showing strain energy density and ICP and then followed by first principal strain. This should open up a new dimension to better understand the complex mechanisms underlying TBI. Thus, it is suggested that the combination of the dynamic triple peak impacts to the brain tissue may interfere with the cerebral metabolism relative to the impact severity thereby having the potential to differentiate between severe and moderate TBI from mild TBI.

The importance of nonlinear tissue modelling in finite element simulations of infant head impacts

Despite recent efforts on the development of finite element (FE) head models of infants, a model capable of capturing head responses under various impact scenarios has not been reported. This is hypothesized partially attributed to the use of simplified linear elastic models for soft tissues of suture, scalp and dura. Orthotropic elastic constants are yet to be determined to incorporate the direction-specific material properties of infant cranial bone due to grain fibres radiating from the ossification centres. We report here on our efforts in advancing the above-mentioned aspects in material modelling in infant head and further incorporate them into subject-specific FE head models of a newborn, 5- and 9-month-old infant. Each model is subjected to five impact tests (forehead, occiput, vertex, right and left parietal impacts) and two compression tests. The predicted global head impact responses of the acceleration–time impact curves and the force–deflection compression curves for different age groups agree well with the experimental data reported in the literature. In particular, the newly developed Ogden hyperelastic model for suture, together with the nonlinear modelling of scalp and dura mater, enables the models to achieve more realistic impact performance compared with linear elastic models. The proposed approach for obtaining age-dependent skull bone orthotropic material constants counts both an increase in stiffness and decrease in anisotropy in the skull bone—two essential biological growth parameters during early infancy. The profound deformation of infant head causes a large stretch at the interfaces between the skull bones and the suture, suggesting that infant skull fractures are likely to initiate from the interfaces; the impact angle has a profound influence on global head impact responses and the skull injury metrics for certain impact locations, especially true for a parietal impact.

Performances of the PIPER scalable child human body model in accident reconstruction

Human body models (HBMs) have the potential to provide significant insights into the pediatric response to impact. This study describes a scalable/posable approach to perform child accident reconstructions using the Position and Personalize Advanced Human Body Models for Injury Prediction (PIPER) scalable child HBM of different ages and in different positions obtained by the PIPER tool. Overall, the PIPER scalable child HBM managed reasonably well to predict the injury severity and location of the children involved in real-life crash scenarios documented in the medical records. The developed methodology and workflow is essential for future work to determine child injury tolerances based on the full Child Advanced Safety Project for European Roads (CASPER) accident reconstruction database. With the workflow presented in this study, the open-source PIPER scalable HBM combined with the PIPER tool is also foreseen to have implications for improved safety designs for a better protection of children in traffic accidents.

Finite Element Modeling of Decompressive Craniectomy (DC) and its Clinical Validation

Decompressive craniectomy (DC) is a reliable neurosurgical approach to reduce a pathologically increased intracranial pressure after neurological diseases such as severe traumatic brain injury (TBI) and stroke. The procedure has substantially reduced the mortality rate but at the expense of increased neurological cognitive impairments. Finite Element (FE) modeling in the past decades has become an important tool to develop innovative treatment strategies in various areas of the clinical neuroscience field. The aim of this study was to develop patient-specific FE models to simulate DC surgery and validate the models against patients’ clinical data. The FE models were created based on the Computed Tomography (CT) images of six patients treated with DC. Brain tissue was modeled as poroelastic material. To validate the model prediction, the motion of brain surface at the DC area from the simulation was compared with the measured values from medical images which were derived from image registration. The results from the computational simulations gave a reliable prediction of brain surface motion at DC area for all the six patients evaluated. Both the deformation pattern and the quantitative values of the brain surface displacement from the model simulation were found in good agreement with measured values from medical images. The developed FE model and its validation in this study is a prerequisite for future investigations aiming at finding optimal treatment for a specific patient which hopefully will significantly improve patients’ outcome.