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Collagen fibers and their orientation greatly influence an artery's mechanical characteristics, determining its transversely isotropic behavior. It is generally assumed that these fibers are deposited along a preferred direction to maximize the load bearing capacity of the vessel wall. This implies a large spatial variation in collagen orientation which can be reconstructed in numerical models using so-called reorientation algorithms. Until now, these algorithms have used the classical continuum mechanics modeling framework which requires knowledge of tissue-level parameters and the artery's stress-free reference state, which is inaccessible in a clinical context. We present an algorithm to compute the preferred fiber distribution compatible with the constrained mixture theory, which orients two collagen fiber families according to the loading experienced by the isotropic non-collagenous extracellular matrix, without requiring prior knowledge of the stress-free state. Because consensus is lacking whether stress or stretch is the determining factor behind the preferred fiber distribution, we implemented both approaches and compared the results with experimental microstructural data of an abdominal aorta. The stress-based algorithm was able to describe several experimentally observed transitions of the fiber distribution across the intima, media and adventitia. ispartof: International Journal For Numerical Methods In Biomedical Engineering vol:39 issue:4 ispartof: location:England status: Published online

Determining proper material parameters from clinical data remains a large, though unavoidable, challenge in patient-specific computational cardiovascular modeling. In an attempt to couple the clinical and modelling practice, this study investigated whether pulse wave velocity (PWV), a clinical arterial stiffness measure, can guide in determining appropriate parameter values for the Gasser-Ogden-Holzapfel (GOH) constitutive model. The reduction and uncertainty analysis was demonstrated on a cylindrical descending thoracic aorta model. Starting from discretized ranges of GOH parameters and using a full factorial design, the parameter sets yielding a physiological PWV (3.5-12.5 m/s) at diastolic pressure (80 mmHg; PWV80) were selected and their PWV at dicrotic notch pressure (110 mmHg; PWV110) was determined. These PWV measures were applied to determine the reduction of the 7D GOH parameter space, the 2D subspaces and the remaining uncertainty in case only PWV80 or both measurements are available. The resulting 12,032 parameter sets lead to a 7D parameter space reduction of ≥ 82.5 % using PWV80, which increased to 96.0 % when including PWV110, in particular at 3.5-8.5 m/s. A similar trend was observed for the remaining uncertainty and the 2D subspaces comprised of medial collagen fiber parameters, while scarce reductions were found for the adventitial and elastin parameters. In conclusion, PWV80 and PWV110 are complementary measures with the potential to reduce the GOH parameter space in arterial models, in particular for media- and collagen-related parameters. Moreover, this approach has the advantage that it allows the estimation of the remaining uncertainty after parameter space reduction. ispartof: Journal Of Biomechanics vol:149 ispartof: location:United States status: accepted

Mechanical characterization of articular cartilage and cell-seeded hydrogel constructs is a challenging task due to the complex biphasic behavior of these materials. Here we describe a step-by-step unconfined compression testing protocol for inverse mechanical characterization of these materials from sample preparation to parameter identification. Examples from our ongoing experiments on alginate hydrogel constructs and preserved and damaged cartilage explants obtained from human hip samples are presented.

Objective: Cerebral contusions (CC) represent a frequent lesion in traumatic brain injury, with potential morbidity from mass effect and tissue loss. Better understanding of the mechanical etiology will help to improve head protection. The goal of this study is to investigate the threshold for mechanical impact parameters to induce CC in an in vivo porcine controlled cortical impact model. Methods: Thirty-four adult male pigs underwent craniotomy and controlled cortical impact with a hemispherical tip on intact dura under general anesthesia. Peak impact depth varied between 1.1 and 12.6 mm, and impact velocity between 0.4 and 2.2 m/s while the dwell time was kept at 200 ms. Two days following impact, the animals underwent magnetic resonance (MR) imaging of the brain, and were subsequently sacrificed for brain extraction. CC damage was investigated by magnetic resonance imaging and histology. Results: All animals recovered from the impact without overt neurological deficit. Provoked injuries were histologically confirmed to be CC. Decreasing probability of cortical damage and white matter edema volume was observed with decreasing impact depth and velocity. No CC could be demonstrated below a product of impact depth and velocity of 0.8 mm*m/s, whereas the probability for CC was one third below 15 mm*m/s. The threshold for CC development as estimated from the current series of experiments, was situated at an impact depth of 2.0 mm and impact velocity of 0.4 m/s Conclusion: Mechanical thresholds for CC development could be explored in the current porcine controlled cortical impact model. Findings will be used to further refine a cerebral contusion porcine model with volumetric histology data in light of future finite element cerebral contusion validation studies.

Planar biaxial testing is a popular experimental technique for characterizing and comparing biological soft tissues. A correct identification of the different stress states of the tissue sample is therefore essential. However, the difference between the zero-stress reference state and the sample state prior to the loading cycle caused by the mounting, preconditioning and preloading is often not considered. The importance of this difference, caused by prestretch, is investigated by simulating virtual planar biaxial experiments, either assuming an ideal test with a single deformation gradient or using finite element modeling to simulate a rake-based experiment. Multiple parameter fitting methods are used to estimate the material properties based on the available experimental data. These methods vary based on how they approximate the zero-stress state: either the prestretch is ignored, or the loads are zeroed after the preload has been reached, or the unknown prestretch values are included into the optimization function. The results reveal the high necessity of assessing the stress-free state when analyzing a planar biaxial test. The material fitting including the prestretch outperforms the other methods in terms of correctly describing the mechanical behavior of the tested material. It can be extended to correct for the boundary effects induced by the gripping mechanisms, providing a more accurate, yet more computationally expensive estimate of the material properties. ispartof: Journal Of The Mechanical Behavior Of Biomedical Materials vol:134 ispartof: location:Netherlands status: Published online

Computational investigations of how soft tissues grow and remodel are gaining more and more interest and several growth and remodeling theories have been developed. Roughly, two main groups of theories for soft tissues can be distinguished: kinematic-based growth theory and theories based on constrained mixture theory. Our goal was to apply these two theories on the same experimental data. Within the experiment, a pulmonary artery was exposed to systemic conditions. The change in diameter was followed-up over time. A mechanical and microstructural analysis of native pulmonary artery and pulmonary autograft was conducted. Whereas the kinematic-based growth theory is able to accurately capture the growth of the tissue, it does not account for the mechanobiological processes causing this growth. The constrained mixture theory takes into account the mechanobiological processes including removal, deposition and adaptation of all structural constituents, allowing us to simulate a changing microstructure and mechanical behavior.

Controlled cortical impact (CCI) on porcine brain is often utilized to investigate the pathophysiology and functional outcome of focal traumatic brain injury (TBI), such as cerebral contusion (CC). Using a finite element (FE) model of the porcine brain, the localized brain strain and strain rate resulting from CCI can be computed and compared to the experimentally assessed cortical lesion. This way, tissue-level injury metrics and corresponding thresholds specific for CC can be established. However, the variability and uncertainty associated with the CCI experimental parameters contribute to the uncertainty of the provoked cortical lesion and, in turn, of the predicted injury metrics. Uncertainty quantification via probabilistic methods (Monte Carlo simulation, MCS) requires a large number of FE simulations, which results in a time-consuming process. Following the recent success of machine learning (ML) in TBI biomechanical modeling, we developed an artificial neural network as surrogate of the FE porcine brain model to predict the brain strain and the strain rate in a computationally efficient way. We assessed the effect of several experimental and modeling parameters on four FE-derived CC injury metrics (maximum principal strain, maximum principal strain rate, product of maximum principal strain and strain rate, and maximum shear strain). Next, we compared the in silico brain mechanical response with cortical damage data from in vivo CCI experiments on pig brains to evaluate the predictive performance of the CC injury metrics. Our ML surrogate was capable of rapidly predicting the outcome of the FE porcine brain undergoing CCI. The now computationally efficient MCS showed that depth and velocity of indentation were the most influential parameters for the strain and the strain rate-based injury metrics, respectively. The sensitivity analysis and comparison with the cortical damage experimental data indicate a better performance of maximum principal strain and maximum shear strain as tissue-level injury metrics for CC. These results provide guidelines to optimize the design of CCI tests and bring new insights to the understanding of the mechanical response of brain tissue to focal traumatic brain injury. Our findings also highlight the potential of using ML for computationally efficient TBI biomechanics investigations. Frontiers ispartof: Frontiers In Bioengineering And Biotechnology vol:9 ispartof: location:Switzerland status: published

A histologically motivated (HM) coefficient that establishes a link between tissue's microstructure and material model through histological data is used in the prediction of the mechanical properties of vaginal tissue that is subjected to multiaxial loading conditions. Therefore, the material parameters were based on an HM coefficient obtained from tensile testing and histological data of comparable tissues. Uniaxial tensile test data and histological data were collected from three groups of sheep at different time points in their life cycle, including virgins, pregnant, and parous ewes. From this data, a correlation between material parameters and histological data was obtained. Spherical indentation (ball burst [BB]) tests were then performed in specimens with similar tissue structure. The histological data of these samples were used in conjunction with the correlations already established for the uniaxial samples data, to define the material parameters of the BB samples. Mechanical properties of the BB specimens were predicted through basic histology and using finite element modeling (FEM) simulations, without direct mechanical measurements. The predicted force and displacement values of the FEM simulation displayed a good correlation with the experimental (BB) testing results. No fitting of the BB results was performed. In this way, the use of uniaxial tests coupled with useful histological information offers a promising approach to predicting macroscopic material behavior under multiaxial loading conditions in biomechanics.

The term "In Silico Trial" indicates the use of computer modelling and simulation to evaluate the safety and efficacy of a medical product, whether a drug, a medical device, a diagnostic product or an advanced therapy medicinal product. Predictive models are positioned as new methodologies for the development and the regulatory evaluation of medical products. New methodologies are qualified by regulators such as FDA and EMA through formal processes, where a first step is the definition of the Context of Use (CoU), which is a concise description of how the new methodology is intended to be used in the development and regulatory assessment process. As In Silico Trials are a disruptively innovative class of new methodologies, it is important to have a list of possible CoUs highlighting potential applications for the development of the relative regulatory science. This review paper presents the result of a consensus process that took place in the InSilicoWorld Community of Practice, an online forum for experts in in silico medicine. The experts involved identified 46 descriptions of possible CoUs which were organised into a candidate taxonomy of nine CoU categories. Examples of 31 CoUs were identified in the available literature; the remaining 15 should, for now, be considered speculative., Comment: Submitted to IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS

The regional dynamic mechanical properties of mouse, rat, pig, and human brain tissue were compared directly in this first-of-its-kind study. Our results suggest the use of pig or mouse brain tissue as suitable surrogates to characterise human brain tissue. The importance of this work is highlighted by the extensive use of constitutive data from animal brain tissue in traumatic brain injury research in the absence of human brain tissue data without any direct evidence supporting their use. Indentation force-relaxation experiments were performed on mouse, rat, pig, and human brains at 10/s strain rate up to 35% strain to determine the dynamic mechanical properties of brain tissue. Finite element models have become useful tools to investigate the biomechanics of traumatic brain injury - a global leading cause of death and disability and a risk factor for developing neurodegenerative diseases. However, these models require accurate constitutive data for brain tissue to produce reliable results. The results presented here provide validation for the use of pig and mouse brain tissue data in such models. Statement of Significance The significance of this work is underscored by the extensive use of animal brain tissue as a surrogate for human brain tissue without any direct evidence supporting the validity of their use. For the first time ever, we demonstrate that porcine and murine brain tissue can be used as surrogates for human brain tissue under dynamic loading conditions. These findings will allow researchers to select appropriate animal surrogates for human brain tissue under dynamic loading conditions. Furthermore, our findings support the use of animal surrogate data to improve the fidelity of computational models of the human brain, and provide experimental data to develop constitutive models of brain tissue.

Cardiac surgeries may expose pulmonary arterial tissue to systemic conditions, potentially resulting in failure of that tissue. Our goal was to quantitatively assess pulmonary artery adaptation due to changes in mechanical environment. In 17 sheep, we placed a pulmonary autograft in aortic position, with or without macroporous mesh reinforcement. It was exposed to systemic conditions for 6 months. All sheep underwent 3 ECG-gated MRI’s. Explanted tissue was subjected to mechanical and histological analysis. Results showed progressive dilatation of the unreinforced autograft, while reinforced autografts stabilized after two months. Some unreinforced pulmonary autograft samples displayed more aorta-like mechanical behavior with increased collagen deposition. The mechanical behavior of reinforced autografts was dominated by the mesh. The decrease in media thickness and loss of vascular smooth muscle cells was more pronounced in reinforced than in unreinforced autografts. In conclusion, altering the mechanical environment of a pulmonary artery causes changes in its mechano-biological properties. ispartof: Scientific Reports vol:10 issue:1 ispartof: location:England status: published

A reliable computational model of the human head is necessary for better understanding of the physical mechanisms of traumatic brain injury (TBI), car-crash investigation, development of protective head gear and advancement of dural replacement materials. The performance and biofidelity of these models depend largely on the material description of the different structures present in the head. One of these structures is the dura mater, the protective layer around the brain. We tested five human dura mater specimens, with samples at different locations, using planar biaxial tests. We describe the resulting stress-strain curves using both the anisotropic Gasser-Ogden-Holzapfel (GOH) model and the isotropic one-term Ogden model. The low-strain section of the curves is also described using a Neo-Hookean formulation. The obtained stress-strain curves reveal highly nonlinear but isotropic behaviour. A significant amount of inter- and intra-specimen variability is noticed, whereby the latter does not seem to be influenced by location. The GOH model achieves the best fit of the individual test data. A simple Neo-Hookean model can only be used with extreme caution, as it does not manage to capture the nonlinear effects present even at low strains.

OBJECTIVES Wrapping with various materials was an early treatment for aortic aneurysms. Wrapping with low-porosity vascular grafts has been associated with graft migration and vascular erosion. An alternative is to use a macroporous mesh (MPM) made of the same polymer (polyethylene terephalate). We compared the histological outcome 1 year after wrapping sheep aortas with low-porosity grafts versus MPM fabrics. METHODS The 2 different fabrics were wrapped around the aorta of 3 sheep. After 1 year the aortas were excised. The 2 wrapped segments of aorta were compared with each other and control aorta. Histological examinations and measurements were made of the layers of the aortic wall in 36 prespecified locations in each of the 3 sheep. RESULTS Both fabrics were consistently surrounded by foreign body reaction and well-vascularized fibrosis. This was more pronounced with the low-porosity vascular graft material which was poorly incorporated and caused buckling at the transition between wrapped and unwrapped aorta. Conversely, the MPM was fully incorporated, resulting in a composite mesh/biological aortic wall. There was reduction of medial thickness with both materials but it was locally more extreme due to the corrugations in the vascular graft material. The findings were consistent between sampled locations and were similar in the 3 animals. CONCLUSIONS The different porosity and rigidity of the materials influences their incorporation into the aortic wall. The incorporation of the pliable MPM precludes the complications of migration and erosion which are seen after wrapping with low-porosity prosthetic vascular graft material.

Bridging veins (BVs) drain the blood from the cerebral cortex into dural sinuses. BVs have one end attached to the brain and the other to the superior sagittal sinus (SSS), which is attached to the skull. Relative movement between these two structures can cause BV to rupture producing acute subdural haematoma, a head injury with a mortality rate between 30 and 90%. A clear understanding of the BVs microstructure is required to increase the biofidelity of BV models when simulating head impacts. Twelve fresh BV samples draining in the superior sagittal sinus (SSS) from a single human cadaver were cut open along their length and placed on an inverted multiphoton microscope. To ensure that the BVs were aligned with the axial direction an in-house built, uniaxial tension set-up was used. Two scans were performed per sample. Before the first scan, a minor displacement was applied to align the tissue; then, a second scan was taken applying 50% strain. Each BV was scanned for a length of 5 mm starting from the drainage site into the SSS. Imaging was performed on a Zeiss LSM780 microscope with an 25[Formula: see text] water immersion objective (NA 0.8), coupled to a tunable MaiTai DS (Spectraphysics) pulsed laser with the wavelength set at 850 nm. Second harmonic and fluorescence signals were captured in forward and backward direction on binary GaAsP (BiG) detectors and stored as four colour Z-stacks. Prior to the calculation of the local orientations, acquired Z-stacks were denoised and enhanced to highlight fibrillar structures from the background. Then, for each Z-plane of the stack, the ImageJ plugin OrientationJ was used to extract the local 2D orientations of the fibres based on structure tensors. Two kinds of collagen architectures were seen. The most common (8[Formula: see text]12 samples) was single layered and had a uniform distribution of collagen. The less common (4[Formula: see text]12 samples) had 2 layers and 7 to 34 times thicker collagen bundles on the outer layer. Fibre angle analysis showed that collagen was oriented mainly along the axial direction of the vessel. The von Mises fittings showed that in order to describe the fibre distribution 3 components were needed with mean angles [Formula: see text] at [Formula: see text] 0.35, 0.21, [Formula: see text] 0.02 rad or [Formula: see text] 20.2[Formula: see text], 12.1[Formula: see text], [Formula: see text] 1.2[Formula: see text] relative to the vessel's axial direction which was also the horizontal scan direction. ispartof: BIOMECHANICS AND MODELING IN MECHANOBIOLOGY vol:19 issue:6 pages:2455-2489 ispartof: location:Germany status: published

As degenerative joint diseases such as osteoarthritis (OA) progress, the matrix constituents, particularly collagen fibrils and proteoglycans, become damaged, therefore deteriorating the tissue's mechanical properties. This study aims to further the understanding of the effect of degradation of the different cartilage constituents on the mechanical loading environment in early stage OA. To this end, intact, collagen- and proteoglycan-depleted cartilage plugs were cyclically loaded in axial compression using an experimental model simulating in vivo cartilage-on-cartilage contact conditions in a micro-MRI scanner. Depletion of collagen and proteoglycans was achieved through enzymatic degradation with collagenase and chondroitinase ABC, respectively. Using a displacement-encoded imaging sequence (DENSE), strains were computed and compared in intact and degraded samples. The results revealed that, while degradation with one or the other enzyme had little effect on the contact strains, degradation with a combination of both enzymes caused an increase in the means and variance of the transverse, axial and shear strains, particularly in the superficial zone of the cartilage. This effect indicates that the balance between cartilage matrix constituents plays an essential role in maintaining the mechanical properties of the tissue, and a disturbance in this balance leads to a decrease of the load bearing capacity associated with degenerative joint diseases such as OA. ispartof: JOURNAL OF THE MECHANICAL BEHAVIOR OF BIOMEDICAL MATERIALS vol:98 pages:383-394 ispartof: location:Netherlands status: published

A correct estimation of the material parameters from a planar biaxial test is crucial since they will affect the outcome of the finite element model in which they are used. In a virtual planar biaxial experiment, a difference can be noticed in the stress calculated from the force measured experimentally at the rakes and the actual stress at the center of the sample. As a consequence, a classic parameter fitting does not result in a correct estimation of the material parameters. This difference is caused by the boundary conditions of the set-up and is among others dependent on the sample material. To overcome this problem, a new parameter fitting procedure is proposed that takes this difference into account by calculating a finite element-based correction vector. This paper describes the methodology to apply this new parameter fitting procedure on real experimental data from a planar biaxial test using rakes. To this end, image processing is used to extract the experiment characteristics. This information is used to construct a finite element model. Two variations of the new parameter fitting procedure are investigated using two human aortic samples: a basic approach and an image-based approach. The performance of the method is assessed by the difference between the force measured at the rakes during the experiment and the force at the rakes obtained from the finite element simulation. Both approaches of the new parameter fitting procedure lead to an improved estimation of the sample behavior compared with the classic approach. ispartof: International Journal for Numerical Methods in Biomedical Engineering vol:35 issue:4 ispartof: location:England status: Published online

The excellent clinical outcomes of the Ross procedure and previous histological studies suggest that the pulmonary autograft has the potential to offer young patients a permanent solution to aortic valve disease. We aim to study the early mechanobiological adaptation of the autograft. To this end, we have reviewed relevant existing animal models, including the canine models which enabled Donald N Ross to perform the first Ross procedure in a patient in 1967. Two research groups recently evaluated the isolated effect of systemic pressures on pulmonary arterial tissue in an ovine model of a pulmonary artery interposition graft in the descending aorta. While this model is ideal to study the artery's biological response and the effect of external support, it does not recreate the complex environment of the aortic root. The freestanding Ross procedure has been performed in pigs and sheep before. These studies offered valuable insights into leaflet growth and histological remodeling, yet may be less relevant to adults undergoing the Ross procedure, as pronounced autograft dilatation was achieved by using small, rapidly growing animals. Therefore, a large animal model remains needed to determine the ideal conditions and surgical technique to ensure long-term autograft remodeling and valve function. We set out to develop an ovine model of the Ross procedure performed as a freestanding root replacement, acknowledging that the sheep's specific anatomy and the setting of an animal laboratory would mandate several modifications in surgical strategy. This article describes the development, surgical technique and early outcomes of our animal model while highlighting opportunities for further research. ispartof: Annals Of Cardiothoracic Surgery vol:10 issue:4 pages:1-10 ispartof: location:China status: published

Traumatic brain injury (TBI) is an important cause of mortality and morbidity worldwide. Finite element models of the human head are used widely to simulate TBI loading scenar- ios, to improve the understanding of the mechanical pathogenesis of head trauma. The re- liability of such computational models depends strongly on the accuracy of the mechanical properties of the different components of the brain. Here, we address the shortage of high- quality data on the region-specific properties of human brain tissue at dynamic rates and under large deformation. We mechanically characterized 12 different regions of the human brain including cerebrum, cerebellum and brainstem through n = 595 force-relaxation ex- periments with a custom-built micro-indentation apparatus. We imposed up to 35% strain at 10/s strain rate, i.e. values representative for TBI. Pronounced differences in mechani- cal response were observed across the brain. This work both highlights and addresses the need to assign accurate, region-specific viscoelastic properties to different brain regions in finite element head models. ispartof: International Journal Of Engineering Science vol:155 status: Published online

Finite element modeling is often used in biomechanical engineering to evaluate medical devices, treatments and diagnostic tools. Using an adequate material model that describes the mechanical behavior of biological tissues is essential for a reliable outcome of the simulation. Pre-programmed material models for biological tissues are available in many finite element software packages. However, since these pre-programmed models are presented to the user as a black box, without the possibility to modify the material description, many researchers turn to implementing their own material formulations. This is a complex undertaking, requiring extensive knowledge while documentation is limited. This paper provides a detailed description, at the level of the biomedical engineer, of the implementation of a nonlinear hyperelastic material model using user subroutines in Abaqus®, in casuUANISOHYPER_INV and UMAT. The Gasser-Ogden-Holzapfel material model is used as an example, resulting in four implementation variations: the built-in implementation, a UANISOHYPER_INV formulation, a UMAT with analytical tangent stiffness formulation and a UMAT with numerical tangent stiffness formulation. In addition, three different element formulations are used: a continuum compressible, a continuum incompressible and a plane stress incompressible. All cases are thoroughly verified by applying a series of deformations on a single cube element and by simulating an extension-inflation experiment with non-homogeneous deformations and multiple elements. In these test cases, stresses, displacements, reaction forces, the required number of iterations and the total CPU time were compared. The results show that the four implementation variations are very similar, with total relative errors between 10-3 and 10-15, number of iterations that varied by maximum one iteration, and a comparable CPU time. In addition to this detailed overview, the user subroutines are added as supplementary material to this tutorial, which can be used as the ideal starting point for biomechanical engineers to implement their own material models at different levels of complexity. ispartof: Journal Of The Mechanical Behavior Of Biomedical Materials vol:110 ispartof: location:Netherlands status: Published online

The constrained mixture theory is an elegant way to incorporate the phenomenon of residual stresses in patient-specific finite element models of arteries. This theory assumes an in vivo reference geometry, obtained from medical imaging, and constituent-specific deposition stretches in the assumed reference state. It allows to model residual stresses and prestretches in arteries without the need for a stress-free reference configuration, most often unknown in patient-specific modeling. A finite element (FE) model requires material parameters, which are classically obtained by fitting the constitutive model to experimental data. The characterization of arterial tissue is often based on planar biaxial test data, to which nonlinear elastic fiber-reinforced material parameters are fitted. However, the introduction of the constrained mixture theory requires an adapted approach to parameter fitting. Therefore, we introduce an iterative fitting method, alternating between nonlinear least squares parameter optimization and an FE prestressing algorithm to obtain the correct constrained mixture material state during the mechanical test. We verify the method based on numerically constructed planar biaxial test data sets, containing ground truth sets of material parameters. The results show that the method converges to the correct parameter sets in just a few iterations. Next, the iterative fitting approach is applied to planar biaxial test data of ovine pulmonary artery tissue. The obtained results demonstrate a convergence towards constrained mixture compatible parameters, which differ significantly from classically obtained parameters. We show that this new modeling approach yields in vivo wall stresses similar to when using classically obtained parameters. However, due to the numerous advantages of constrained mixture modeling, our fitting method is relevant to obtain compatible material parameters, that may not be confused with parameters obtained in a classical way. ispartof: Journal of the Mechanical Behavior of Biomedical Materials vol:95 pages:124-135 ispartof: location:Netherlands status: published

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 $$({\boldsymbol{\varepsilon }}={\bf{10}}{\boldsymbol{ \% }},\,\mathop{{\boldsymbol{\varepsilon }}}\limits^{\cdot }={\bf{1}}{{\boldsymbol{s}}}^{-{\bf{1}}})$$ ( ε = 10 % , ε ⋅ = 1 s − 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.

Finite element models of biomedical applications increasingly use anisotropic hyperelastic material formulations. Appropriate material parameters are essential for a reliable outcome of these simulations, which is why planar biaxial testing of soft biological tissues is gaining importance. However, much is still to be learned regarding the ideal methodology for performing this type of test and the subsequent parameter fitting procedure. This paper focuses on the effect of an unknown sample orientation or a mistake in the sample orientation in a planar biaxial test using rakes. To this end, finite element simulations were conducted with various degrees of misalignment. Variations to the test method and subsequent fitting procedures are compared and evaluated. For a perfectly aligned sample and for a slightly misaligned sample, the parameters of the Gasser-Ogden-Holzapfel model can be found to a reasonable accuracy using a planar biaxial test with rakes and a parameter fitting procedure that takes into account the boundary conditions. However, after a certain threshold of misalignment, reliable parameters can no longer be found. The level of this threshold seems to be material dependent. For a sample with unknown sample orientation, material parameters could theoretically be obtained by increasing the degrees of freedom along which test data is obtained, e.g. by adding the data of a rail shear test. However, in the situation and the material model studied here, the inhomogeneous boundary conditions of the test set-ups render it impossible to obtain the correct parameters, even when using the parameter fitting method that takes into account boundary conditions. To conclude, it is always important to carefully track the sample orientation during harvesting and preparation and to minimize the misalignment during mounting. For transversely isotropic samples with an unknown orientation, we advise against parameter fitting based on a planar biaxial test, even when combined with a rail shear test. ispartof: J Mech Behav Biomed Mater vol:88 pages:201-216 ispartof: location:Netherlands status: published

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. ispartof: JOURNAL OF BIOMECHANICS vol:92 pages:6-10 ispartof: location:United States status: published

The Ross procedure is a surgical procedure where a diseased aortic valve is replaced by the person's own pulmonary valve. The proximal segment of the pulmonary artery is thereby placed in aortic position and therefore suddenly exposed to a sevenfold increase in blood pressure. Excessive dilatation of this pulmonary autograft is a common complication and has excited interest about mechanobiological adaptation in such situations. Mathematical modelling of growth and remodelling is a relevant approach to improve insights into this phenomenon. We introduced an algorithm that models the continuous degradation and deposition of extracellular matrix in an artery according to the constrained mixture theory. To compute temporal variations of collagen and elastin mass and to deduce related mechanical properties of the remodelled artery, we discretized time and defined a finite number of cohorts for each collagen fiber family. The degradation and production rates of each cohort were mediated by the difference between ambient and homeostatic stress within each fiber cohort. We applied the algorithm to predict the adaptation of a pulmonary autograft over an extended period and compared the results to experimental data obtained in sheep. We were able to consistently reproduce the experimentally observed remodeling effects such as dilatation and delayed collagen fiber recruitment. Our simulations revealed how elastin takes up the excessive stress in overstretched regions of the tissue. In conclusion, the algorithm yields very promising results regarding autograft adaptation in overstretched conditions. Future work will focus on other situations of vascular adaptation where growth-related deformations will be considered. ispartof: ZAMM-Zeitschrift fur Angewandte Mathematik und Mechanik vol:98 issue:12 pages:2239-2257 status: published

A commonly heard concern in the Ross procedure, where a diseased aortic valve is replaced by the patient's own pulmonary valve, is the possibility of pulmonary autograft dilatation. We performed a biomechanical investigation of the use of a personalized external aortic root support or exostent as a possibility for supporting the autograft. In ten sheep a short length of pulmonary artery was interposed in the descending aorta, serving as a simplified version of the Ross procedure. In seven of these cases, the autograft was supported by an external mesh or so-called exostent. Three sheep served as control, of which one was excluded from the mechanical testing. The sheep were sacrificed six months after the procedure. Samples of the relevant tissues were obtained for subsequent mechanical testing: normal aorta, normal pulmonary artery, aorta with exostent, pulmonary artery with exostent, and pulmonary artery in aortic position for six months. After mechanical testing, the material parameters of the Gasser-Ogden-Holzapfel model were determined for the different tissue types. Stress-strain curves of the different tissue types show significantly different mechanical behavior. At baseline, stress-strain curves of the pulmonary artery are lower than aortic stress-strain curves, but at the strain levels at which the collagen fibers are recruited, the pulmonary artery behaves stiffer than the aorta. After being in aortic position for six months, the pulmonary artery tends towards aorta-like behavior, indicating that growth and remodeling processes have taken place. When adding an exostent around the pulmonary autograft, the mechanical behavior of the composite artery (exostent + artery) differs from the artery alone, the non-linearity being more evident in the former. ispartof: Journal of the Mechanical Behavior of Biomedical Materials vol:78 pages:164-174 ispartof: location:Netherlands status: published

Purpose: To compensate for the lack of haptic feedback by surgical robots, limitation of exerted forces could be implemented. The limits should be based on the observed relationship between tissue load and induced damage. This study examines whether age-related changes influence this relationship. Methods: Descending thoracic aortas of male C57BL/6J mice of 10, 25 and 40 weeks were clamped in vivo (no clamp, 0.5N or 2.0N) for 2 min. Functional integrity was tested in vitro by studying endothelium-dependent and -independent vasoreactivity. Results: Endothelium-dependent relaxation deteriorated with increased clamping force at all ages. Clamping did not influence endothelium-independent vasodilation. Age (10, 25 and 40 weeks) did not significantly impact on the effect of clamping on endothelium-dependent and independent vasoreactivity. Conclusions: Within the tested conditions, mechanical clamping induces damage to the vascular endothelium, but not to the smooth muscle cells. Age has no effect on the obtained results in mice from 10 to 40 weeks old.

OBJECTIVES The Ross procedure involves replacing a patient’s diseased aortic valve with their own pulmonary valve. The most common failure mode is dilatation of the autograft. Various strategies to reinforce the autograft have been proposed. Personalized external aortic root support has been shown to be effective in stabilizing the aortic root in Marfan patients. In this study, the use of a similar external mesh to support a pulmonary artery autograft was evaluated. METHODS The pulmonary artery was translocated as an interposition autograft in the descending thoracic aortas of 10 sheep. The autograft was reinforced with a polyethylene terephthalate mesh (n = 7) or left unreinforced (n = 3). After 6 months, a computed tomography scan was taken, and the descending aorta was excised and histologically examined using the haematoxylin–eosin and Elastica van Gieson stains. RESULTS The autograft/aortic diameter ratio was 1.59 in the unreinforced group but much less in the reinforced group (1.11) (P