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  • 1.
    Alvarez, Victor
    et al.
    KTH.
    Halldin, Peter
    KTH.
    Kleiven, Svein
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    The Influence of Neck Muscle Tonus and Posture on Brain Tissue Strain in Pedestrian Head Impacts2014In: 58th SAE Stapp Car Crash Conference, STAPP 2014, Vol. 58Article in journal (Refereed)
    Abstract [en]

    Pedestrians are one of the least protected groups in urban traffic and frequently suffer fatal head injuries. An important boundary condition for the head is the cervical spine, and it has previously been demonstrated that neck muscle activation is important for head kinematics during inertial loading. It has also been shown in a recent numerical study that a tensed neck musculature also has some influence on head kinematics during a pedestrian impact situation. The aim of this study was to analyze the influence on head kinematics and injury metrics during the isolated time of head impact by comparing a pedestrian with relaxed neck and a pedestrian with increased tonus. The human body Finite Element model THUMS Version 1.4 was connected to head and neck models developed at KTH and used in pedestrian-to-vehicle impact simulations with a generalized hood, so that the head would impact a surface with an identical impact response in all simulations. In order to isolate the influence of muscle tonus, the model was activated shortly before head impact so the head would have the same initial position prior to impact among different tonus. A symmetric and asymmetric muscle activation scheme that used high level of activation was used in order to create two extremes to investigate. It was found that for the muscle tones used in this study, the influence on the strain in the brain was very minor, in general about 1-14% change. A relatively large increase was observed in a secondary peak in maximum strains in only one of the simulated cases. 

  • 2.
    Alvarez, Victor S
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Kleiven, Svein
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Effect of pediatric growth on cervical spine kinematics and deformations in automotive crashes2018In: Journal of Biomechanics, ISSN 0021-9290, E-ISSN 1873-2380, Vol. 71, p. 76-83, article id S0021-9290(18)30075-7Article in journal (Refereed)
    Abstract [en]

    Finite element (FE) models are a powerful tool that can be used to understand injury mechanisms and develop better safety systems. This study aims to extend the understanding of pediatric spine biomechanics, where there is a paucity of studies available. A newly developed and continuously scalable FE model was validated and scaled to 1.5-, 3-, 6-, 10-, 14- and 18-year-old using a non-linear scaling technique, accounting for local topological changes. The oldest and youngest ages were also scaled using homogeneous geometric scaling. To study the effect of pediatric spinal growth on head kinematics and intervertebral disc strain, the models were exerted to 3.5 g acceleration pulse at the T1 vertebra to simulate frontal, rear and side impacts. It was shown that the head rotation increases with age, but is over predicted when geometrically scaling down from 18- to 1.5-year-old and under predicted when geometrically scaling up from 1.5- to 18-year-old. The strain in the disc, however, showed a clear decrease with age in side impact and for the upper cervical spine in rear impact, indicating a higher susceptibility for neck injury at younger ages. In the frontal impact, no clear age dependence could be seen, suggesting a large contribution from changed facet joint angles, and lower levels of strain, suggesting a lower risk of injury. The results also highlight the benefit of rearward facing children in a seat limiting head lateral motion.

  • 3. Beillas, Philippe
    et al.
    Giordano, Chiara
    Alvarez, Victor
    Li, Xiaogai
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Ying, Xingjia
    Chevalier, Marie-Christine
    Kirscht, Stefan
    Kleiven, Svein
    Development and performance of the PIPER scalable child human body models2016In: 14th International Conference on the Protection of Children in Cars, 2016Conference paper (Refereed)
  • 4. Beillas, Philippe
    et al.
    Lafon, Yoann
    Frechede, Bertrand
    Janak, Tomas
    Dupeux, Thomas
    Mear, Matthieu
    Kleiven, Svein
    Giordano, Chiara
    Alvarez, Victor
    Li, Xiaogai
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Chawla, Anoop
    Chhabra, A
    Paruchuri, S an Singh, S
    Kaushik, D
    Mukherjee, S
    Kumar, S
    Devane, K
    Mishra, K
    Machina, G
    Jolivet, Erwan
    Lemaire, Thomas
    Faure, François
    Gilles, Benjamin
    Vimont, Ulysse
    Lecomte, Christophe
    D3. 8 Final version of the personalization and positioning software tool with documentation. PIPER EU Project2017Report (Refereed)
  • 5. Beillas, Philippe
    et al.
    Wang, Xuguang
    Lafon, Yoann
    Frechede, Bertrand
    Janak, Tomas
    Dupeux, Thomas
    Mear, Matthieu
    Pacquaut, Guillaume
    Chevalier, Marie-Christine
    Le Ruyet, Anicet
    Eichene, Alexandre
    Theodorakos, Ilias
    Yin, Xingjia
    Gardegaront, M
    Collot, Jerome
    Petit, Philippe
    Eric, Song
    Moreau, Baptiste
    Kleiven, Svein
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Giordano, Chiara
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Strömbäck, Alvarez Victor
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Li, Xiaogai
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    et al,
    PIPER EU Project Final publishable summary2017Report (Refereed)
  • 6.
    Fahlstedt, Madelen
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Kleiven, Svein
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Li, Xiaogai
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Current Playground Surface Test Standards Underestimate Brain Injury Risk for Children2019In: Journal of Biomechanics, ISSN 0021-9290, E-ISSN 1873-2380Article in journal (Refereed)
    Abstract [en]

    Playgrounds surface test standards have been introduced to reduce the number of fatal and severe injuries. However, these test standards have several simplifications to make it practical, robust and cost-effective, such as the head is represented with a hemisphere, only the linear kinematics is evaluated and the body is excluded. Little is known about how these simplifications may influence the test results. The objective of this study was to evaluate the effect of these simplifications on global head kinematics and head injury prediction for different age groups. The finite element human body model PIPER was used and scaled to seven different age groups from 1.5 up to 18 years old, and each model was impacted at three different playground surface stiffness and three head impact locations. All simulations were performed in pairs, including and excluding the body. Linear kinematics and skull bone stress showed small influence if excluding the body while head angular kinematics and brain tissue strain were underestimated by the same simplification. The predicted performance of the three different playground surface materials, in terms of head angular kinematics and brain tissue strain, was also altered when including the body. A body and biofidelic neck need to be included, together with suitable head angular kinematics based injury thresholds, in future physical or virtual playground surface test standards to better prevent brain injuries.

  • 7.
    Fahlstedt, Madelen
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Kleiven, Svein
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Li, Xiaogai
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    The Influence of the Body on Head Kinematics in Playground Falls for Different Age Groups2018In: Proceedings of International Research Council on Biomechanics of Injury (IRCOBI) Conference, 2018Conference paper (Refereed)
  • 8.
    Giordano, Chiara
    et al.
    KTH.
    Kleiven, Svein
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Development of an Unbiased Validation Protocol to Assess the Biofidelity of Finite Element Head Models used in Prediction of Traumatic Brain Injury2016In: SAE Technical Papers, SAE International , 2016, no NovemberConference paper (Refereed)
    Abstract [en]

    This study describes a method to identify laboratory test procedures and impact response requirements suitable for assessing the biofidelity of finite element head models used in prediction of traumatic brain injury. The selection of the experimental data and the response requirements were result of a critical evaluation based on the accuracy, reproducibility and relevance of the available experimental data. A weighted averaging procedure was chosen in order to consider different contributions from the various test conditions and target measurements based on experimental error. According to the quality criteria, 40 experimental cases were selected to be a representative dataset for validation. Based on the evaluation of response curves from four head finite element models, CORA was chosen as a quantitative method to compare the predicted time history response to the measured data. Optimization of the CORA global settings led to the recommendation of performing curve comparison on a fixed time interval of 0-30 ms for intracranial pressure and at least 0-40 ms for brain motion and deformation. The allowable maximum time shift was adjusted depending on the shape of the experimental curves (DMAX = 0.12 for intracranial pressure, DMAX = 0.40 for brain motion and DMAX = 0.25 for brain deformation). Finally, bigger penalization of ratings was assigned to curves with fundamentally incorrect shape compared to those having inaccuracies in amplitude or time shift (cubic vs linear). This rigorous approach is necessary to ensure confidence in the model results and progress in the usage of finite element head models for traumatic brain injury prediction. 

  • 9.
    Giordano, Chiara
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Kleiven, Svein
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Evaluation of Axonal Strain as a Predictor for Mild Traumatic Brain Injuries Using Finite Element Modeling2014In: 58th SAE Stapp Car Crash Conference, STAPP 2014Article in journal (Refereed)
    Abstract [en]

    Finite element (FE) models are often used to study the biomechanical effects of traumatic brain injury (TBI). Measures based on mechanical responses, such as principal strain or invariants of the strain tensor, are used as a metric to predict the risk of injury. However, the reliability of inferences drawn from these models depends on the correspondence between the mechanical measures and injury data, as well as the establishment of accurate thresholds of tissue injury. In the current study, a validated anisotropic FE model of the human head is used to evaluate the hypothesis that strain in the direction of fibers (axonal strain) is a better predictor of TBI than maximum principal strain (MPS), anisotropic equivalent strain (AESM) and cumulative strain damage measure (CSDM). An analysis of head kinematics-based metrics, such as head injury criterion (HIC) and brain injury criterion (BrIC), is also provided. Logistic regression analysis is employed to compare binary injury data (concussion/no concussion) with continuous strain/kinematics data. The threshold corresponding to 50% of injury probability is determined for each parameter. The predictive power (area under the ROC curve, AUC) is calculated from receiver operating characteristic (ROC) curve analysis. The measure with the highest AUC is considered to be the best predictor of mTBI.Logistic regression shows a statistical correlation between all the mechanical predictors and injury data for different regions of the brain. Peaks of axonal strain have the highest AUC and determine a strain threshold of 0.07 for corpus callosum and 0.15 for the brainstem, in agreement with previously experimentally derived injury thresholds for reversible axonal injury. For a data set of mild TBI from the national football league, the strain in the axonal direction is found to be a better injury predictor than MPS, AESM, CSDM, BrIC and HIC. 

  • 10.
    Gomez-Alvarez, Marcelo
    et al.
    Karolinska Inst, Dept Clin Sci Intervent & Technol, Unit Audiol, Alfred Nobels Alle 10, S-14183 Stockholm, Sweden..
    Gourevitch, Boris
    Sorbonne Univ Paris, Inst Pasteur, INSERM, Unite Genet & Physiol Audit, Paris, France.;CNRS, Paris, France..
    Felix, Richard A., II
    Washington State Univ, Vancouver, WA USA..
    Nyberg, Tobias
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Hernandez-Montiel, Hebert L.
    Univ Autonoma Queretaro, Clin Sistema Nervioso, Lab Neurobiol & Bioingn Celular, Santiago De Queretaro, Mexico..
    Magnusson, Anna K.
    Karolinska Inst, Dept Clin Sci Intervent & Technol, Unit Audiol, Alfred Nobels Alle 10, S-14183 Stockholm, Sweden..
    Temporal information in tones, broadband noise, and natural vocalizations is conveyed by differential spiking responses in the superior paraolivary nucleus2018In: European Journal of Neuroscience, ISSN 0953-816X, E-ISSN 1460-9568, Vol. 48, no 4, p. 2030-2049Article in journal (Refereed)
    Abstract [en]

    Communication sounds across all mammals consist of multiple frequencies repeated in sequence. The onset and offset of vocalizations are potentially important cues for recognizing distinct units, such as phonemes and syllables, which are needed to perceive meaningful communication. The superior paraolivary nucleus (SPON) in the auditory brainstem has been implicated in the processing of rhythmic sounds. Here, we compared how best frequency tones (BFTs), broadband noise (BBN), and natural mouse calls elicit onset and offset spiking in the mouse SPON. The results demonstrate that onset spiking typically occurs in response to BBN, but not. BFT stimulation, while spiking at the sound offset occurs for both stimulus types. This effect of stimulus bandwidth on spiking is consistent with two of the established inputs to the SPON from the octopus cells (onset spiking) and medial nucleus of the trapezoid body (offset spiking). Natural mouse calls elicit two main spiking peaks. The first spiking peak, which is weak or absent with BFT stimulation, occurs most consistently during the call envelope, while the second spiking peak occurs at the call offset. This suggests that the combined spiking activity in the SPON elicited by vocalizations reflects the entire envelope, that is, the coarse amplitude waveform. Since the output from the SPON is purely inhibitory, it is speculated that, at the level of the inferior colliculus, the broadly tuned first peak may improve the signal-to-noise ratio of the subsequent, more call frequency-specific peak. Thus, the SPON may provide a dual inhibition mechanism for tracking phonetic boundaries in social-vocal communication.

  • 11. Kapeliotis, M.
    et al.
    Musigazi, G.
    Famaey, N.
    Depreitere, B.
    Kleiven, Svein
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Vander Sloten, J.
    Assessment of bridging vein rupture associated with acute subdural hematoma through finite elements analysis after biofidelic position adaptation2018In: Conference proceedings International Research Council on the Biomechanics of Injury, IRCOBI, International Research Council on the Biomechanics of Injury , 2018, p. 695-696Conference paper (Refereed)
  • 12.
    Kapeliotis, Markos
    et al.
    Katholieke Univ Leuven, Biomech Sect, Leuven, Belgium. usigazi, Gracia Umuhire; Depreitere, Bart.
    Musigazi, Gracia Umuhire
    Famaey, Nele
    Depreitere, Bart
    Kleiven, Svein
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Vander Sloten, Jos
    The sensitivity to inter-subject variability of the bridging vein entry angles for prediction of acute subdural hematoma2019In: Journal of Biomechanics, ISSN 0021-9290, E-ISSN 1873-2380, Vol. 92, p. 6-10Article in journal (Refereed)
    Abstract [en]

    Acute subdural hematoma (ASDH) is one of the most frequent traumatic brain injuries (TBIs) with high mortality rate. Bridging vein (BV) ruptures is a major cause of ASDH. The KTH finite element head model includes bridging veins to predict acute subdural hematoma due to BV rupture. In this model, BVs were positioned according to Oka et al. (1985). The aim of the current study is to investigate whether the location and entry angles of these BVs could be modelled using data from a greater statistical sample, and what the impact of this improvement would be on the model's predictive capability of BV rupture. From the CT angiogram data of 78 patients, the relative position of the bridging veins and their entry angles along the superior sagittal sinus was determined. The bridging veins were repositioned in the model accordingly. The performance of the model, w.r.t. BV rupture prediction potential was tested on simulations of full body cadaver head impact experiments. The experiments were simulated on the original version of the model and on three other versions which had updated BV positions according to mean, maximum and minimum entry angles. Even though the successful prediction rate between the models stayed the same, the location of the rupture site significantly improved for the model with the mean entry angles. Moreover, the models with maximum and minimum entry angles give an insight of how BV biovariability can influence ASDH. In order to further improve the successful prediction rate, more biofidelic data are needed both with respect to bridging vein material properties and geometry. Furthermore, more experimental data are needed in order to investigate the behaviour of FE head models in depth.

  • 13. Laksari, Kaveh
    et al.
    Kurt, Mehmet
    Babaee, Hessam
    Kleiven, Svein
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Camarillo, David
    Mechanistic Insights into Human Brain Impact Dynamics through Modal Analysis2018In: Physical Review Letters, ISSN 0031-9007, E-ISSN 1079-7114, Vol. 120Article in journal (Refereed)
    Abstract [en]

    Although concussion is one of the greatest health challenges today, our physical understanding of the cause of injury is limited. In this Letter, we simulated football head impacts in a finite element model and extracted the most dominant modal behavior of the brain’s deformation. We showed that the brain’s deformation is most sensitive in low frequency regimes close to 30 Hz, and discovered that for most subconcussive head impacts, the dynamics of brain deformation is dominated by a single global mode. In this Letter, we show the existence of localized modes and multimodal behavior in the brain as a hyperviscoelastic medium. This dynamical phenomenon leads to strain concentration patterns, particularly in deep brain regions, which is consistent with reported concussion pathology.

  • 14.
    Li, Xiaogai
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Kleiven, Svein
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Improved safety standards are needed to better protect younger children at playgrounds2018In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 8, no 1, article id 15061Article in journal (Refereed)
    Abstract [en]

    Playground-related traumatic brain injuries (TBIs) in children remain a considerable problem world-wide and current safety standards are being questioned due to historical reasons where the injury thresholds had been perpetuated from automobile industry. Here we investigated head injury mechanisms due to falls on playgrounds using a previously developed and validated age-scalable and positionable whole body child model impacted at front, back and side of the head simulating head-first falls from 1.59 meters (m). The results show that a playground material passing the current testing standards (HIC < 1000 and resultant linear acceleration <200g) resulted in maximum strain in the brain higher than known injury thresholds, thus not offering sufficient protection especially for younger children. The analysis highlights the age dependence of head injuries in children due to playground falls and the youngest have a higher risk of brain injury and skull fracture. Further, the results provide the first biomechanical evidence guiding age-dependent injury thresholds for playground testing standards. The results also have direct implications for novel designs of playground materials for a better protection of children from TBIs. Only making the playground material thicker and more compliant is not sufficient. This study represents the first initiative of using full body human body models of children as a new tool to improve playground testing standards and to better protect the children at playgrounds.

  • 15.
    Li, Xiaogai
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Sandler, Håkan
    Kleiven, Svein
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Infant skull fractures: Accident or abuse?: Evidences from biomechanical analysis using finite element head models2019In: Forensic science international, Vol. 294, p. 173-182Article in journal (Refereed)
    Abstract [en]

    Abusive Head Trauma (AHT) is considered by some authors to be a leading cause of traumatic death in children less than two years of age and skull fractures are commonly seen in cases of suspected AHT. Today, diagnosing whether the observed fractures are caused by abuse or accidental fall is still a challenge within both the medical and the legal communities and the central question is a biomechanical question: can the described history explain the observed fractures? Finite element (FE) analysis has been shown a valuable tool for biomechanical analysis accounting for detailed head geometry, advanced material modelling, and case-specific factors (e.g. head impact location, impact surface properties). Here, we reconstructed two well-documented suspected abuse cases (a 3- and a 4-month-old) using subject-specific FE head models. The models incorporate the anatomical details and age-dependent anisotropic material properties of infant cranial bones that reflect the grainy fibres radiating from ossification centres. The impact locations are determined by combining multimodality images. The results show that the skull fracture patterns in both cases of suspected abuse could be explained by the described accidental fall history, demonstrating the inherent potential of FE analysis for providing biomechanical evidence to aid forensic investigations. Increased knowledge of injury mechanisms in children may have enormous medico-legal implications world-wide. 

  • 16.
    Li, Xiaogai
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    von Holst, Hans
    Finite element modeling of decompressive craniectomy (DC) and its clinical validation2015In: ADVANCES IN BIOMEDICAL SCIENCE AND ENGINEERING, Vol. 2, no 1, p. 1-9Article in journal (Refereed)
    Abstract [en]

    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.

  • 17. Li, Y. Q.
    et al.
    Li, Xiaogai
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering. Southern Methodist University, United States.
    Gao, X. -L
    Modeling of advanced combat helmet under ballistic impact2015In: Journal of applied mechanics, ISSN 0021-8936, E-ISSN 1528-9036, Vol. 82, no 11, article id 111004Article in journal (Refereed)
    Abstract [en]

    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 soldiers in battlefields. BHBT results from nonpenetrating ballistic impacts and is often associated with helmet back face deformation (BFD). In the current study, a finite element-based computational model is developed for simulating the ballistic performance of the Advanced Combat Helmet (ACH), which is validated against the experimental data obtained at the Army Research Laboratory. Both the maximum value and time history of the BFD are considered, unlike existing studies focusing on the maximum BFD only. The simulation results show that the maximum BFD, the time history of the BFD, and the shape and size of the effective area of the helmet shell agree fairly well with the experimental findings. In addition, it is found that ballistic impacts on the helmet at different locations and in different directions result in different BFD values. The largest BFD value is obtained for a frontal impact, which is followed by that for a crown impact and then by that for a lateral impact. Also, the BFD value is seen to decrease as the oblique impact angle decreases. Furthermore, helmets of four different sizes - extra large, large, medium, and small - are simulated and compared. It is shown that at the same bullet impact velocity the small-size helmet has the largest BFD, which is followed by the medium-size helmet, then by the large-size helmet, and finally by the extra large-size helmet. Moreover, ballistic impact simulations are performed for an ACH placed on a ballistic dummy head form embedded with clay as specified in the current ACH testing standard by using the validated helmet model. It is observed that the BFD values as recorded by the clay in the head form are in good agreement with the experimental data.

  • 18.
    Meng, Shiyang
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Cernicchi, Alessandro
    Kleiven, Svein
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Halldin, Peter
    KTH.
    The biomechanical differences of shock absorption test methods in the US and European helmet standards2019In: International Journal of Crashworthiness, ISSN 1358-8265, E-ISSN 1754-2111, Vol. 24, no 4, p. 399-412Article in journal (Refereed)
    Abstract [en]

    Nowadays crash helmets are tested by dropping a free or unrestrained headform in Europe but a guided or restrained headform in the United States. It remains unclear whether the free fall and the guided fall produce similar impact kinematics that cause head injury. A ?nite element helmet model is developed and compared with experimental tests. The resulting head kinematics from virtual tests are input for a ?nite element head model to compute the brain tissue strain. The guided fall produces higher peak force and linear acceleration than the free fall. Eccentric impact in the free fall test induces angular head motion which directs some of the impact energy into rotational kinetic energy. Consequently, the brain tissue strain in the free fall test is up to 6.3 times more than that in the guided fall. This study recommends a supplemental procedure that records angular head motion in the free fall test.

  • 19.
    Meng, Shiyang
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Fahlstedt, Madelen
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Halldin, Peter
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    The effect of impact velocity angle on helmeted head impact severity: A rationale for motorcycle helmet impact test design2018In: Conference proceedings International Research Council on the Biomechanics of Injury, IRCOBI, International Research Council on the Biomechanics of Injury , 2018, p. 454-469Conference paper (Refereed)
    Abstract [en]

    The impact velocity angle determined by the normal and tangential velocity has been shown to be an important description of head impact conditions but can vary in real-world accidents. The objective of this paper was to investigate the effect of impact velocity angle on helmeted head impact severity indicated by the brain tissue strain. The human body model coupled with a validated motorcycle helmet model was propelled at a constant resultant velocity but varying angle relative to a rigid surface. Different body angles, impact directions and helmet designs have also been incorporated in the simulation matrix (n=300). The results show an influence of impact velocity angle on brain tissue strain response. By aggregating all simulation cases into different impact velocity angle groups, i.e., 15, 30, 45, 60 and 75 degrees, a 30- or 45-degree angle group give the highest median and inter-quartile range of the peak brain tissue strain. Comparisons of strain pattern and its peak value between individual cases give consistent results. The brain tissue strain is less sensitive to the body angle than to the velocity angle. The study suggests that UN/ECE 22.05 can be improved by increasing the current 'oblique' angle, i.e. 15 degrees inclined to vertical axis, to a level that can produce sufficient normal velocity component and hence angular head motion. This study also underline the importance of understanding post-impact head kinematics, and the need for further evaluation of human body models.

  • 20.
    Montanino, Annaclauida
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Deryckere, Astrid
    Laboratory of Developmental Neurobiology, Department of Biology, KU Leuven, Leuven, Belgium.
    Famaey, Nele
    Biomechanics section, KU Leuven, Leuven, Belgium.
    Seuntjens, Eve
    Laboratory of Developmental Neurobiology, Department of Biology, KU Leuven, Leuven, Belgium.
    Kleiven, Svein
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Mechanical characterization of squid giant axon membrane sheath and influence of the collagenous endoneurium on its properties2019In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 9, no 1, article id 8969Article in journal (Refereed)
    Abstract [en]

    To understand traumas to the nervous system, the relation between mechanical load and functional impairment needs to be explained. Cellular-level computational models are being used to capture the mechanism behind mechanically-induced injuries and possibly predict these events. However, uncertainties in the material properties used in computational models undermine the validity of their predictions. For this reason, in this study the squid giant axon was used as a model to provide a description of the axonal mechanical behavior in a large strain and high strain rate regime (ε=10%,ε⋅=1s−1), which is relevant for injury investigations. More importantly, squid giant axon membrane sheaths were isolated and tested under dynamic uniaxial tension and relaxation. From the lumen outward, the membrane sheath presents: an axolemma, a layer of Schwann cells followed by the basement membrane and a prominent layer of loose connective tissue consisting of fibroblasts and collagen. Our results highlight the load-bearing role of this enwrapping structure and provide a constitutive description that could in turn be used in computational models. Furthermore, tests performed on collagen-depleted membrane sheaths reveal both the substantial contribution of the endoneurium to the total sheath’s response and an interesting increase in material nonlinearity when the collagen in this connective layer is digested. All in all, our results provide useful insights for modelling the axonal mechanical response and in turn will lead to a better understanding of the relationship between mechanical insult and electrophysiological outcome.

  • 21.
    Montanino, Annaclauida
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Kleiven, Svein
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Utilizing a Structural Mechanics Approach to Assess the Primary Effects of Injury Loads Onto the Axon and Its Components2018In: Frontiers in Neurology, ISSN 1664-2295, E-ISSN 1664-2295, Vol. 9, no 643, p. 1-12Article in journal (Refereed)
    Abstract [en]

    Diffuse axonal injury (DAI) occurs as a result of the transmission of rapid dynamic loads from the head to the brain and specifically to its neurons. Despite being one of the most common and most deleterious types of traumatic brain injury (TBI), the inherent cell injury mechanism is yet to be understood. Experimental observations have led to the formulation of different hypotheses, such as mechanoporation of the axolemma and microtubules (MTs) breakage. With the goal of singling out the mechanical aspect of DAI and to resolve the ambiguity behind its injury mechanism, a composite finite element (FE) model of a representative volume of an axon was developed. Once calibrated and validated against published experimental data, the axonal model was used to simulate injury scenarios. The resulting strain distributions along its components were then studied in dependence of strain rate and of typical modeling choices such as the applied MT constraints and tau proteins failure. Results show that oversimplifying the MT bundle kinematic entails a systematic attenuation (cf = 2.33) of the computed maximum MT strain. Nevertheless, altogether, results support the hypothesis of axolemma mechanoporation as a cell-injury trigger. Moreover, for the first time the interconnection between the axolemma and the MT bundle is shown to play a role in damage localization. The proposed FE axonal model is a valuable tool to understand the axonal injury mechanism from a mechanical perspective and could be used in turn for the definition of well-informed injury criteria at the tissue and organ level.

  • 22.
    Panzer, Matthew B.
    et al.
    Univ Virginia, Ctr Appl Biomech, Charlottesville, VA USA..
    Giudice, J. Sebastian
    Univ Virginia, Ctr Appl Biomech, Charlottesville, VA USA..
    Caudillo, Adrian
    Univ Virginia, Ctr Appl Biomech, Charlottesville, VA USA..
    Mukherjee, Sayak
    Univ Virginia, Ctr Appl Biomech, Charlottesville, VA USA..
    Kong, Kevin
    Univ Virginia, Ctr Appl Biomech, Charlottesville, VA USA..
    Cronin, Duane S.
    Univ Waterloo, Waterloo, ON, Canada..
    Barker, Jeffrey
    Univ Waterloo, Waterloo, ON, Canada..
    Gierczycka, Donata
    Univ Waterloo, Waterloo, ON, Canada..
    Bustamante, Michael
    Univ Waterloo, Waterloo, ON, Canada..
    Bruneau, David
    Univ Waterloo, Waterloo, ON, Canada..
    Corrales, Miguel
    Univ Waterloo, Waterloo, ON, Canada..
    Halldin, Peter
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Fahlstedt, Madelen
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Arnesen, Marcus
    Jungstedt, Erik
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Fibre- and Polymer Technology, Biocomposites. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Centres, Wallenberg Wood Science Center.
    Gayzik, F. Scott
    Wake Forest Univ, Bowman Gray Sch Med, Winston Salem, NC USA..
    Stitzel, Joel D.
    Wake Forest Univ, Bowman Gray Sch Med, Winston Salem, NC USA..
    Decker, William
    Wake Forest Univ, Bowman Gray Sch Med, Winston Salem, NC USA..
    Baker, Alex M.
    Wake Forest Univ, Bowman Gray Sch Med, Winston Salem, NC USA..
    Ye, Xin
    Wake Forest Univ, Bowman Gray Sch Med, Winston Salem, NC USA..
    Brown, Philip
    Wake Forest Univ, Bowman Gray Sch Med, Winston Salem, NC USA..
    NUMERICAL CROWDSOURCING OF NFL FOOTBALL HELMETS2018In: Journal of Neurotrauma, ISSN 0897-7151, E-ISSN 1557-9042, Vol. 35, no 16, p. A148-A148Article in journal (Other academic)
  • 23.
    Robinson, Yohan
    et al.
    Uppsala University Hospital, Uppsala, Sweden.
    Lison Almkvist, Viktor
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Olerud, Claes
    Uppsala University Hospital, Uppsala, Sweden.
    Halldin, Peter
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Fahlstedt, Madelen
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Finite Element Analysis of Long Posterior Transpedicular Instrumentation for Cervicothoracic Fractures Related to Ankylosing Spondylitis2018In: Global Spine Journal, ISSN 2192-5682, E-ISSN 2192-5690Article in journal (Refereed)
  • 24.
    Saeedimasine, M.
    et al.
    Karolinska Inst, Dept Biosci & Nutr, Huddinge, Sweden..
    Montanino, Annaclauida
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH).
    Kleiven, Svein
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Villa, A.
    Karolinska Inst, Dept Biosci & Nutr, Huddinge, Sweden..
    Impact of lipid composition and ion channel on the mechanical behavior of axonal membranes: a molecular simulation study2019In: European Biophysics Journal, ISSN 0175-7571, E-ISSN 1432-1017, Vol. 48, p. S99-S99Article in journal (Other academic)
  • 25.
    Saeedimasine, Marzieh
    et al.
    Department of Biosciences and Nutrition, Karolinska Institutet, Huddinge, Sweden.
    Montanino, Annaclaudia
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Kleiven, Svein
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Villa, Alessandra
    Department of Biosciences and Nutrition, Karolinska Institutet, Huddinge, Sweden.
    Role of lipid composition on the structural and mechanical features of axonal membranes: a molecular simulation study2019In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 18, p. 27-39Article in journal (Refereed)
    Abstract [en]

    The integrity of cellular membranes is critical for the functionality of axons. Failure of the axonal membranes (plasma membrane and/or myelin sheath) can be the origin of neurological diseases. The two membranes differ in the content of sphingomyelin and galactosylceramide lipids. We investigate the relation between lipid content and bilayer structural-mechanical properties, to better understand the dependency of membrane properties on lipid composition. A sphingomyelin/phospholipid/cholesterol bilayer is used to mimic a plasma membrane and a galactosylceramide/phospholipid/cholesterol bilayer to mimic a myelin sheath. Molecular dynamics simulations are performed at atomistic and coarse-grained levels to characterize the bilayers at equilibrium and under deformation. For comparison, simulations of phospholipid and phospholipid/cholesterol bilayers are also performed. The results clearly show that the bilayer biomechanical and structural features depend on the lipid composition, independent of the molecular models. Both galactosylceramide or sphingomyelin lipids increase the order of aliphatic tails and resistance to water penetration. Having 30% galactosylceramide increases the bilayers stiffness. Galactosylceramide lipids pack together via sugar-sugar interactions and hydrogen-bond phosphocholine with a correlated increase of bilayer thickness. Our findings provide a molecular insight on role of lipid content in natural membranes.

  • 26.
    Sahandifar, Pooya
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Kleiven, Svein
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Studying the age effect on fall induced hip fracture using an orthotropic continuum damage model2018In: Conference proceedings International Research Council on the Biomechanics of Injury, IRCOBI, International Research Council on the Biomechanics of Injury , 2018, p. 733-734Conference paper (Refereed)
  • 27.
    von Holst, Hans
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering. Section of Neurosurgery, Division of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden .
    Li, Xiaogai
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Higher impact energy in traumatic brain injury interferes with noncovalent and covalent bonds resulting in cytotoxic brain tissue edema as measured with computational simulation2015In: Acta Neurochirurgica, ISSN 0001-6268, E-ISSN 0942-0940, Vol. 157, no 4, p. 639-648Article in journal (Refereed)
    Abstract [en]

    Cytotoxic brain tissue edema is a complicated secondary consequence of ischemic injury following cerebral diseases such as traumatic brain injury and stroke. To some extent the pathophysiological mechanisms are known, but far from completely. In this study, a hypothesis is proposed in which protein unfolding and perturbation of nucleotide structures participate in the development of cytotoxic edema following traumatic brain injury (TBI). An advanced computational simulation model of the human head was used to simulate TBI. The consequences of kinetic energy transfer following an external dynamic impact were analyzed including the intracranial pressure (ICP), strain level, and their potential influences on the noncovalent and covalent bonds in folded protein structures. The result shows that although most of the transferred kinetic energy is absorbed in the skin and three bone layers, there is a substantial amount of energy reaching the gray and white matter. The kinetic energy from an external dynamic impact has the theoretical potential to interfere not only with noncovalent but also covalent bonds when high enough. The induced mechanical strain and pressure may further interfere with the proteins, which accumulate water molecules into the interior of the hydrophobic structures of unfolded proteins. Simultaneously, the noncovalent energy-rich bonds in nucleotide adenosine-triphosphates may be perturbed as well. Based on the analysis of the numerical simulation data, the kinetic energy from an external dynamic impact has the theoretical potential to interfere not only with noncovalent, but also with covalent bonds when high enough. The subsequent attraction of increased water molecules into the unfolded protein structures and disruption of adenosine-triphosphate bonds could to some extent explain the etiology to cytotoxic edema.

  • 28.
    Xia, Qingling
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering. Chongqing University.
    Infrared Neural Modulation: Photothermal Effects on Cortex Neurons Using Infrared Laser Heating2018Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    It would be of great value to have a precise and non-damaging neuromodulation technique in the field of basic neuroscience research and for clinical treatment of neurological diseases. Infrared neural modulation (INM) is a new modulation modality developed in the last decade, which uses pulsed or continues infrared (IR) light with a wavelength of 1200 to 2200 nm to directly alter neural signals. INM includes both infrared neural stimulation (INS) and infrared neural inhibition (INI). INM is widely investigated for use on peripheral nerves, cochlear nerve fibers, cardiac cells, and the central nervous system. This technique holds the advantages of contact-free and high spatiotemporal precision compared to the traditional electrical stimulation. It does not depend on genetic modification and exogenous absorbers as other optical techniques, such as the optogenetic technique and the enhanced near-infrared neural stimulation (e-NIR). These advantages make INM a viable technique for research and clinical applications. The primary mechanism of the INM is believed to be a photothermal effect, where the IR laser energy absorbed by water leads to a rapid local temperature change. However, so far the details of the mechanism of action potential (AP) generation and inhibition remain elusive. Another issueis that the cells may be endangeredbythe heat exposure, consequently triggering a physiologicalmalfunction or even permanent damage.These concernshave hindered the transfer of the INM technique to the clinical therapy.Therefore, the general aim of this study was to improve the understanding of the details of how INM affects the cells. Laser parameters for safe and efficient stimulation were investigated on the basis of being useful for clinical applications. A tailored heating model and in vitro INM experiments on cortex neurons were used to reach this goal.The first paper was a feasibility study. A 1550nm laser with a beam spot diameter of around 6 mm was used to irradiate the rat cortex neurons, which were seeded on multi-electrode arrays (MEA) and formed well-connected networks. A heating model based on an estimated laser beam (standard Gaussian distribution) was used to simulate temperaturechanges. The damage signal ratio (DSR),based on the temperature,was calculated to predict the heat damage. The average spike rate of all the working electrodes from two MEAs was used to evaluate the degree of theinhibition of the neural networks. Results IVshowed that it is possible to use the 1550 nm laser to safely inhibit the neural network activity and that the degree of the INI is dependent on the power of the laser.The second paper wasan application and mechanism study. The aim of this study was to investigate the safety, efficiency, and cellular mechanism of INI. The same laser as in paper Iwas used in this study. A 20 X objective was used to decrease the beam spot diameteraround 240 μm. The measured laser profile (high order Gaussian beam) was used in the heating model to predict the temperature. The model was verified by local temperature measurements viamicropipette. The action potential rates, measured by the MEA electrodes, were quantified for different temperatures. Bicuculline was added to the cortex neuron cultures to induce hyperexcitation of the neural network. The results showed that the INI is temperature dependent and that the temperature needs to be less than 46 °C at 30 s laser irradiation for safe inhibition. The IR laser couldalso be used to inhibit the hyperexcitedactivity. The degree of inhibition, for the assessed subpopulation of neurons, was better correlated with the action potential amplitude than the width of it and INIcan be accomplished without inhibitory synapses

  • 29.
    Xia, Qingling
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering. Chongqing University.
    Nyberg, Tobias
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Inhibition of Cortical Neural Networks Using Infrared LaserManuscript (preprint) (Other academic)
  • 30.
    Xia, Qingling
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering. Chongqing University.
    Nyberg, Tobias
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Photothermal Inhibition of Cortex Neurons Activity by Infrared Laser2018In: World Congress on Medical Physics and Biomedical Engineering 2018, 2018, Vol. 68/3, p. 99-104Conference paper (Refereed)
    Abstract [en]

    Some brain diseases are caused by neurons being abnormally excited, such as Parkinson’s disease (PD) and epilepsy. The aim of this study was to investigate the feasibility and the efficacy of infrared laser irradiation for inhibiting neuronal network activity. We cultured rat cortex neurons, forming neural networks with spontaneous neural activity, on multi-electrode arrays (MEAs). To inhibit the activity of the networks we irradiated the neurons using different intensity of 1550 nm infrared laser light. A temperature model was created using COMSOL Multiphysics software to predict the temperature change at different laser intensity irradiation. Our initial result shows that the wavelength of 1550 nm infrared laser can be used to inhibit the network activity of cultivated rat cortex neurons directly and reversibly. The degrees of network inhibition can be manipulated by changing the laser intensity. The optical thermal effect is considered the primary mechanism during infrared neural inhibition (INI). These results demonstrate that INI could potentially be useful in the treatment of neurological disorders and that temperature may play an important role in INI.

  • 31.
    Zhou, Zhou
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Li, Xiaogai
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Kleiven, Svein
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Biomechanics of acute subdural hematoma in the elderly: A fluid-structure interaction study2019In: Journal of Neurotrauma, ISSN 0897-7151, E-ISSN 1557-9042, Vol. 36, no 13, p. 2099-2108Article in journal (Refereed)
    Abstract [en]

    Acute subdural hematoma (ASDH) due to bridging vein (BV) rupture is a frequent and lethal head injury, especially in the elderly. Brain atrophy has been hypothesized to be a primary pathogenesis associated with the increased risk of ASDH in the elderly. Though decades of biomechanical endeavours have been made to elucidate the potential mechanisms, a thorough explanation for this hypothesis appears lacking. Thus, a recently improved finite element head model, in which the brain-skull interface was modelled using a fluid-structure interaction (FSI) approach with special treatment of the cerebrospinal fluid as arbitrary Lagrangian-Eulerian fluid formulation, is used to partially address this understanding gap. Models with various degrees of atrophied brains and thereby different subarachnoid thicknesses are generated and subsequently exposed to experimentally determined loadings known to cause ASDH or not. The results show significant increases in the cortical relative motion and BV strain in the atrophied brain, which consequently exacerbates the ASDH risk in the elderly. Results of this study are suggested to be considered while developing age-adapted protecting strategies for the elderly in the future.

  • 32.
    Zhou, Zhou
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Li, Xiaogai
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Kleiven, Svein
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Fluid–structure interaction simulation of the brain–skull interface for acute subdural haematoma prediction2018In: Biomechanics and Modeling in Mechanobiology, ISSN 1617-7959, E-ISSN 1617-7940, Vol. 18, no 1, p. 155-173Article in journal (Refereed)
    Abstract [en]

    Traumatic brain injury is a leading cause of disability and mortality. Finite element-based head models are promising tools for enhanced head injury prediction, mitigation and prevention. The reliability of such models depends heavily on adequate representation of the brain–skull interaction. Nevertheless, the brain–skull interface has been largely simplified in previous three-dimensional head models without accounting for the fluid behaviour of the cerebrospinal fluid (CSF) and its mechanical interaction with the brain and skull. In this study, the brain–skull interface in a previously developed head model is modified as a fluid–structure interaction (FSI) approach, in which the CSF is treated on a moving mesh using an arbitrary Lagrangian–Eulerian multi-material formulation and the brain on a deformable mesh using a Lagrangian formulation. The modified model is validated against brain–skull relative displacement and intracranial pressure responses and subsequently imposed to an experimentally determined loading known to cause acute subdural haematoma (ASDH). Compared to the original model, the modified model achieves an improved validation performance in terms of brain–skull relative motion and is able to predict the occurrence of ASDH more accurately, indicating the superiority of the FSI approach for brain–skull interface modelling. The introduction of the FSI approach to represent the fluid behaviour of the CSF and its interaction with the brain and skull is crucial for more accurate head injury predictions.

  • 33.
    Zhou, Zhou
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Li, Xiaogai
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Kleiven, Svein
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Shah, Chirag S.
    Hardy, Warren N.
    A Reanalysis of Experimental Brain Strain Data: Implication for Finite Element Head Model Validation2019In: SAE Technical Papers, SAE International , 2019, Vol. 2019, article id NovemberConference paper (Refereed)
    Abstract [en]

    Relative motion between the brain and skull and brain deformation are biomechanics aspects associated with many types of traumatic brain injury (TBI). Thus far, there is only one experimental endeavor (Hardy et al., 2007) reported brain strain under loading conditions commensurate with levels that were capable of producing injury. Most of the existing finite element (FE) head models are validated against brain-skull relative motion and then used for TBI prediction based on strain metrics. However, the suitability of using a model validated against brain-skull relative motion for strain prediction remains to be determined. To partially address the deficiency of experimental brain deformation data, this study revisits the only existing dynamic experimental brain strain data and updates the original calculations, which reflect incremental strain changes. The brain strain is recomputed by imposing the measured motion of neutral density target (NDT) to the NDT triad model. The revised brain strain and the brain-skull relative motion data are then used to test the hypothesis that an FE head model validated against brain-skull relative motion does not guarantee its accuracy in terms of brain strain prediction. To this end, responses of brain strain and brain-skull relative motion of a previously developed FE head model (Kleiven, 2007) are compared with available experimental data. CORrelation and Analysis (CORA) and Normalized Integral Square Error (NISE) are employed to evaluate model validation performance for both brain strain and brain-skull relative motion. Correlation analyses (Pearson coefficient) are conducted between average cluster peak strain and average cluster peak brain-skull relative motion, and also between brain strain validation scores and brain-skull relative motion validation scores. The results show no significant correlations, neither between experimentally acquired peaks nor between computationally determined validation scores. These findings indicate that a head model validated against brain-skull relative motion may not be sufficient to assure its strain prediction accuracy. It is suggested that a FE head model with intended use for strain prediction should be validated against the experimental brain deformation data and not just the brain-skull relative motion.

  • 34.
    Zhou, Zhou
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Li, Xiaogai
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Kleiven, Svein
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Shah, C.S.
    Hardy, W.N.
    A reanalysis of experimental brain strain data: implication for finite element head model validation2018In: Stapp Car Crash Journal, ISSN 1532-8546, Vol. 62, p. 293-318Article in journal (Refereed)
    Abstract [en]

    Relative motion between the brain and skull and brain deformation are biomechanics aspects associated with many types of traumatic brain injury (TBI). Thus far, there is only one experimental endeavor (Hardy et al., 2007) reported brain strain under loading conditions commensurate with levels that were capable of producing injury. Most of the existing finite element (FE) head models are validated against brain-skull relative motion and then used for TBI prediction based on strain metrics. However, the suitability of using a model validated against brain-skull relative motion for strain prediction remains to be determined. To partially address the deficiency of experimental brain deformation data, this study revisits the only existing dynamic experimental brain strain data and updates the original calculations, which reflect incremental strain changes. The brain strain is recomputed by imposing the measured motion of neutral density target (NDT) to the NDT triad model. The revised brain strain and the brain-skull relative motion data are then used to test the hypothesis that an FE head model validated against brainskull relative motion does not guarantee its accuracy in terms of brain strain prediction. To this end, responses of brain strain and brain-skull relative motion of a previously developed FE head model (Kleiven, 2007) are compared with available experimental data. CORrelation and Analysis (CORA) and Normalized Integral Square Error (NISE) are employed to evaluate model validation performance for both brain strain and brain-skull relative motion. Correlation analyses (Pearson coefficient) are conducted between average cluster peak strain and average cluster peak brain-skull relative motion, and also between brain strain validation scores and brain-skull relative motion validation scores. The results show no significant correlations, neither between experimentally acquired peaks nor between computationally determined validation scores. These findings indicate that a head model validated against brain-skull relative motion may not be sufficient to assure its strain prediction accuracy. It is suggested that a FE head model with intended use for strain prediction should be validated against the experimental brain deformation data and not just the brain-skull relative motion.

1 - 34 of 34
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