Growth and remodeling of the dissected membrane in an idealized dissected aorta model

While transitioning from the acute to chronic phase, the wall of a dissected aorta often expands in diameter and adaptations in thickness and microstructure take place in the dissected membrane. Including the mechanisms, leading to these changes, in a computational model is expected to improve the accuracy of predictions of the long-term complications and optimal treatment timing of dissection patients. An idealized dissected wall was modeled to represent the elastin and collagen production and/or degradation imposed by stress- and inflammation-mediated growth and remodeling, using the homogenized constrained mixture theory. As no optimal growth and remodeling parameters have been defined for aortic dissections, a Latin hypercube sampling with 1000 parameter combinations was assessed for four inflammation patterns, with a varying spatial extent (full/local) and temporal evolution (permanent/transient). The dissected membrane thickening and microstructure was considered together with the diameter expansion over a period of 90 days. The highest success rate was found for the transient inflammation patterns, with about 15% of the samples leading to converged solutions after 90 days. Clinically observed thickening rates were found for 2-4% of the transient inflammation samples, which represented median total diameter expansion rates of about 5 mm/year. The dissected membrane microstructure showed an elastin decrease and, in most cases, a collagen increase. In conclusion, the model with the transient inflammation pattern allowed the reproduction of clinically observed dissected membrane thickening rates, diameter expansion rates and adaptations in microstructure, thus providing guidance in reducing the parameter space in growth and remodeling models of aortic dissections.

Uncertainty quantification of the wall thickness and stiffness in an idealized dissected aorta

Personalized treatment informed by computational models has the potential to markedly improve the outcome for patients with a type B aortic dissection. However, existing computational models of dissected walls significantly simplify the characteristic false lumen, tears and/or material behavior. Moreover, the patient-specific wall thickness and stiffness cannot be accurately captured non-invasively in clinical practice, which inevitably leads to assumptions in these wall models. It is important to evaluate the impact of the corresponding uncertainty on the predicted wall deformations and stress, which are both key outcome indicators for treatment optimization. Therefore, a physiology-inspired finite element framework was proposed to model the wall deformation and stress of a type B aortic dissection at diastolic and systolic pressure. Based on this framework, 300 finite element analyses, sampled with a Latin hypercube, were performed to assess the global uncertainty, introduced by 4 uncertain wall thickness and stiffness input parameters, on 4 displacement and stress output parameters. The specific impact of each input parameter was estimated using Gaussian process regression, as surrogate model of the finite element framework, and a δ moment-independent analysis. The global uncertainty analysis indicated minor differences between the uncertainty at diastolic and systolic pressure. For all output parameters, the 4th quartile contained the major fraction of the uncertainty. The parameter-specific uncertainty analysis elucidated that the material stiffness and relative thickness of the dissected membrane were the respective main determinants of the wall deformation and stress. The uncertainty analysis provides insight into the effect of uncertain wall thickness and stiffness parameters on the predicted deformation and stress. Moreover, it emphasizes the need for probabilistic rather than deterministic predictions for clinical decision making in aortic dissections.

Stiffness matters: Improved failure risk assessment of ascending thoracic aortic aneurysms

Objectives

Rupture and dissection are feared complications of ascending thoracic aortic aneurysms caused by mechanical failure of the wall. The current method of using the aortic diameter to predict the risk of wall failure and to determine the need for surgical resection lacks accuracy. Therefore, this study aims to identify reliable and clinically measurable predictors for aneurysm rupture or dissection by performing a personalized failure risk analysis, including clinical, geometrical, histologic, and mechanical data.

Methods

The study cohort consisted of 33 patients diagnosed with ascending aortic aneurysms without genetic syndromes. Uniaxial tensile tests until failure were performed to determine the wall strength. Material parameters were fitted against ex vivo planar biaxial data and in vivo pressure-diameter relationships at diastole and systole, which were derived from multiphasic computed tomography (CT) scans. Using the resulting material properties and in vivo data, the maximal in vivo stress at systole was calculated, assuming a thin-walled axisymmetric geometry. The retrospective failure risk was calculated by comparing the peak wall stress at suprasystolic pressure with the wall strength.

Results

The distensibility coefficient, reflecting aortic compliance and derived from blood pressure measurements and multiphasic CT scans, outperformed predictors solely based on geometrical features in assessing the risk of aneurysm failure.

Conclusions

In a clinical setting, multiphasic CT scans followed by the calculation of the distensibility coefficient are of added benefit in patient-specific, clinical decision-making. The distensibility derived from the aneurysm volume change has the best predictive power, as it also takes the axial stretch into account.

Drivers of vascular growth and remodeling: A computational framework to promote benign adaptation in the Ross procedure

In the sixties, Dr Donald Ross designed a surgical solution for young patients with aortic valve disease by using the patients' own pulmonary valve. The Ross procedure is the only aortic valve replacement technique that can restore long-term survival and preserve quality of life. The main failure mode of the Ross procedure is wall dilatation, potentially leading to valve regurgitation and leakage. Dilatation occurs due to the inability of the pulmonary autograft to adapt to the sudden increase in loading when exposing to aortic pressures. Previous experimental data has shown that a permanent external support wrapped around the artery can prevent the acute dilatation of the arterial wall. However, the textile support leads to stress-shielding phenomena due to the loss of mechanical wall compliance. We present a pragmatic and modular computational framework of arterial growth and remodeling predicting the long-term outcomes of cardiovascular tissue adaptation, with and without textile wrapping. The model integrates mean, systolic and diastolic pressures and assumes the resulting wall stresses to drive the biological remodeling rules. Rather than a single mean pressure or stress deviation from the homeostatic state, we demonstrate that only pulsatile stresses can predict available experimental results. Therefore, we suggest that a biodegradable external support could induce benign remodeling in the Ross procedure. Indeed, a biodegradable textile wrapped around the autograft fulfills the trade-off between prevention of acute dilatation on the one hand and recovery of arterial wall compliance on the other hand. After further validation, the computational framework can set the basis for the development of an actual biodegradable external support for the Ross procedure with optimized polymer mechanical properties and degradation behavior.

In Vivo Material Properties of Human Common Carotid Arteries: Trends and Sex Differences

INTRODUCTION

In vivo estimation of material properties of arterial tissue can provide essential insights into the development and progression of cardiovascular diseases. Furthermore, these properties can be used as an input to finite element simulations of potential medical treatments.

MATERIALS AND METHODS

This study uses non-invasively measured pressure, diameter and wall thickness of human common carotid arteries (CCAs) acquired in 103 healthy subjects. A non-linear optimization was performed to estimate material parameters of two different constitutive models: a phenomenological, isotropic model and a structural, anisotropic model. The effect of age, sex, body mass index and blood pressure on the parameters was investigated.

RESULTS AND CONCLUSION

Although both material models were able to model in vivo arterial behaviour, the structural model provided more realistic results in the supra-physiological domain. The phenomenological model predicted very high deformations for pressures above the systolic level. However, the phenomenological model has fewer parameters that were shown to be more robust. This is an advantage when only the physiological domain is of interest. The effect of stiffening with age, BMI and blood pressure was present for women, but not always for men. In general, sex had the biggest effect on the mechanical properties of CCAs. Stiffening trends with age, BMI and blood pressure were present but not very strong. The intersubject variability was high. Therefore, it can be concluded that finding a representative set of parameters for a certain age or BMI group would be very challenging. Instead, for purposes of patient-specific modelling of surgical procedures, we currently advise the use of patient-specific parameters.

Computational modeling reveals inflammation-driven dilatation of the pulmonary autograft in aortic position

The pulmonary autograft in the Ross procedure, where the aortic valve is replaced by the patient's own pulmonary valve, is prone to failure due to dilatation. This is likely caused by tissue degradation and maladaptation, triggered by the higher experienced mechanical loads in aortic position. In order to further grasp the causes of dilatation, this study presents a model for tissue growth and remodeling of the pulmonary autograft, using the homogenized constrained mixture theory and equations for immuno- and mechano-mediated mass turnover. The model outcomes, compared to experimental data from an animal model of the pulmonary autograft in aortic position, show that inflammation likely plays an important role in the mass turnover of the tissue constituents and therefore in the autograft dilatation over time. We show a better match and prediction of long-term outcomes assuming immuno-mediated mass turnover, and show that there is no linear correlation between the stress-state of the material and mass production. Therefore, not only mechanobiological homeostatic adaption should be taken into account in the development of growth and remodeling models for arterial tissue in similar applications, but also inflammatory processes.

How to implement constrained mixture growth and remodeling algorithms for soft biological tissues

Biological soft tissues are constantly adapting to their mechanical environment and remodel to restore certain mechanobiological homeostatic conditions. These effects can be modeled using the constrained mixture theory, that assumes degradation of material over time and the gradual replacement of extant material by newly deposited material. While this theory presents an elegant way to grasp phenomena of growth and remodeling in soft biological tissues, implementation difficulties may arise. Therefore, we give a detailed overview of the mathematical description of the constrained mixture theory and its homogenized equivalent, and present practical suggestions to numerically implement the theories. These implementations are thoroughly tested with multiple example growth and remodeling models. Results show a good correspondence between both theories, with the homogenized theory favored in terms of time efficiency. Results of a step time convergence study show the importance of choosing a small enough time step, especially when using the classical theory.

Layer-specific fiber distribution in arterial tissue modeled as a constrained mixture

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.

Pulse wave velocity: A clinical measure to aid material parameter estimation in computational arterial biomechanics

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.

Contribution of collagen degradation and proteoglycan depletion to cartilage degeneration in primary and secondary osteoarthritis: an in silico study

OBJECTIVES

Current experimental approaches cannot elucidate the effect of maladaptive changes on the main cartilage constituents during the degeneration process in osteoarthritis (OA). In silico approaches, however, allow creating 'virtual knock-out' cases to elucidate these effects in a constituent-specific manner. We used such an approach to study the main mechanisms of cartilage degeneration in different mechanical loadings associated with the following OA etiologies: (1) physiological loading of degenerated cartilage, (2) injurious loading of healthy intact cartilage and (3) physiological loading of cartilage with a focal defect.

METHODS

We used the recently developed Cartilage Adaptive REorientation Degeneration (CARED) framework to simulate cartilage degeneration associated with primary and secondary OA (OA cases (1)-(3)). CARED incorporates numerical description of tissue-level cartilage degeneration mechanisms in OA, namely, collagen degradation, collagen reorientation, fixed charged density loss and tissue hydration increase following mechanical loading. We created 'virtual knock-out' scenarios by deactivating these degenerative processes one at a time in each of the three OA cases.

RESULTS

In the injurious loading of intact and physiological loading of degenerated cartilage, collagen degradation drives degenerative changes through fixed charge density loss and tissue hydration rise. In contrast, the two later mechanisms were more prominent in the focal defect cartilage model.

CONCLUSION

The virtual knock-out models reveal that injurious loading to intact cartilage and physiological loading to degenerated cartilage induce initial degenerative changes in the collagen network, whereas, in the presence of a focal cartilage defect, mechanical loading initially causes proteoglycans (PG) depletion, before changes in the collagen fibril network occur.

Unconfined Compression Experimental Protocol for Cartilage Explants and Hydrogel Constructs: From Sample Preparation to Mechanical Characterization

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.

Alterations in Human Mitral Valve Mechanical Properties Secondary to Left Ventricular Remodeling: A Biaxial Mechanical Study

Secondary mitral regurgitation occurs when a left ventricular problem causes leaking of the mitral valve. The altered left ventricular geometry changes the orientation of the subvalvular apparatus, thereby affecting the mechanical stress on the mitral valve. This in turn leads to active remodeling of the mitral valve, in order to compensate for the ventricular remodeling. In this study, a biomechanical analysis was performed on eight human mitral valves with secondary mitral regurgitation and ten healthy human mitral valves to better understand this pathophysiology and its effect on the mechanical properties of these tissues. Samples were obtained from the anterior and posterior leaflet and used for planar biaxial mechanical experiments. Uniaxial experiments were performed on four groups of mitral valve chords: anterior basal, anterior marginal, posterior basal and posterior marginal chords. The mechanical response of the mitral valve leaflets was fitted to the May-Newman and Yin constitutive model, whereas the material parameters of the third order Ogden model were determined for the chord samples. Next, stiffnesses calculated at low and high stress levels were statistically analyzed. Leaflet samples with secondary mitral regurgitation showed a small thickness increase and a change in anisotropy index compared to healthy control valves. Diseased leaflets were more compliant circumferentially and stiffer radially, resulting in anisotropic samples with the radial direction being stiffest. In addition, chord samples were slightly thicker and less stiff at high stress in secondary mitral regurgitation, when grouped per leaflet type and insertion region. These results confirm mechanical alterations due to the pathophysiological valvular changes caused by left ventricular remodeling. It is important that these changes in mechanical behavior are incorporated into computational models of the mitral valve.

Understanding Pulmonary Autograft Remodeling After the Ross Procedure: Stick to the Facts

The Ross, or pulmonary autograft, procedure presents a fascinating mechanobiological scenario. Due to the common embryological origin of the aortic and pulmonary root, the conotruncus, several authors have hypothesized that a pulmonary autograft has the innate potential to remodel into an aortic phenotype once exposed to systemic conditions. Most of our understanding of pulmonary autograft mechanobiology stems from the remodeling observed in the arterial wall, rather than the valve, simply because there have been many opportunities to study the walls of dilated autografts explanted at reoperation. While previous histological studies provided important clues on autograft adaptation, a comprehensive understanding of its determinants and underlying mechanisms is needed so that the Ross procedure can become a widely accepted aortic valve substitute in select patients. It is clear that protecting the autograft during the early adaptation phase is crucial to avoid initiating a sequence of pathological remodeling. External support in the freestanding Ross procedure should aim to prevent dilatation while simultaneously promoting remodeling, rather than preventing dilatation at the cost of vascular atrophy. To define the optimal mechanical properties and geometry for external support, the ideal conditions for autograft remodeling and the timeline of mechanical adaptation must be determined. We aimed to rigorously review pulmonary autograft remodeling after the Ross procedure. Starting from the developmental, microstructural and biomechanical differences between the pulmonary artery and aorta, we review autograft mechanobiology in relation to distinct clinical failure mechanisms while aiming to identify unmet clinical needs, gaps in current knowledge and areas for further research. By correlating clinical and experimental observations of autograft remodeling with established principles in cardiovascular mechanobiology, we aim to present an up-to-date overview of all factors involved in extracellular matrix remodeling, their interactions and potential underlying molecular mechanisms.

Growth and remodeling in the pulmonary autograft: Computational evaluation using kinematic growth models and constrained mixture theory

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.

A Machine Learning Approach to Investigate the Uncertainty of Tissue-Level Injury Metrics for Cerebral Contusion

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.

Guide to mechanical characterization of articular cartilage and hydrogel constructs based on a systematic in silico parameter sensitivity analysis

Osteoarthritis is a whole joint disease with cartilage degeneration being an important manifestation. Tissue engineering treatment is a solution for repairing cartilage defects by implantation of chondrocyte-laden hydrogel constructs within the defect. In silico models have recently been introduced to simulate and optimize the design of these constructs. These models require accurate knowledge on the mechanical properties of the hydrogel constructs and cartilage explants, which are challenging to obtain due to their anisotropic structure and time-dependent behaviour. We performed a systematic in silico parameter sensitivity analysis to find the most efficient unconfined compression testing protocols for mechanical characterization of hydrogel constructs and cartilage explants, with a minimum number of tests but maximum identifiability of the material parameters. The construct and explant were thereby modelled as porohyperelastic and fibril-reinforced poroelastic materials, respectively. Three commonly used loading regimes were simulated in Abaqus (ramp, relaxation and dynamic loading) with varying compressive strain magnitudes and rates. From these virtual experiments, the resulting material parameters were obtained for each combination using a numerical inverse identification scheme. For hydrogels, maximum sensitivity to the different material parameters was found when using a single step ramp loading (20% compression with 10%/s rate) followed by 15 min relaxation. For cartilage explants, a two-stepped ramp loading (10% compression with 10%/s rate and 10% compression with 1%/s rate), each step followed by 15 min relaxation, yielded the maximum sensitivity to the different material parameters. With these protocols, the material parameters could be retrieved with the lowest amount of uncertainty (hydrogel: < 2% and cartilage: < 6%). These specific results and the overall methodology can be used to optimize mechanical testing protocols to yield reliable material parameters for in silico models of cartilage and hydrogel constructs.

Investigation of tissue level tolerance for cerebral contusion in a controlled cortical impact porcine model

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.

Back to the root: a large animal model of the Ross procedure

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.

Possible Contexts of Use for In Silico trials methodologies: a consensus- based review

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.

An in silico Framework of Cartilage Degeneration That Integrates Fibril Reorientation and Degradation Along With Altered Hydration and Fixed Charge Density Loss

Injurious mechanical loading of articular cartilage and associated lesions compromise the mechanical and structural integrity of joints and contribute to the onset and progression of cartilage degeneration leading to osteoarthritis (OA). Despite extensive in vitro and in vivo research, it remains unclear how the changes in cartilage composition and structure that occur during cartilage degeneration after injury, interact. Recently, in silico techniques provide a unique integrated platform to investigate the causal mechanisms by which the local mechanical environment of injured cartilage drives cartilage degeneration. Here, we introduce a novel integrated Cartilage Adaptive REorientation Degeneration (CARED) algorithm to predict the interaction between degenerative variations in main cartilage constituents, namely collagen fibril disorganization and degradation, proteoglycan (PG) loss, and change in water content. The algorithm iteratively interacts with a finite element (FE) model of a cartilage explant, with and without variable depth to full-thickness defects. In these FE models, intact and injured explants were subjected to normal (2 MPa unconfined compression in 0.1 s) and injurious mechanical loading (4 MPa unconfined compression in 0.1 s). Depending on the mechanical response of the FE model, the collagen fibril orientation and density, PG and water content were iteratively updated. In the CARED model, fixed charge density (FCD) loss and increased water content were related to decrease in PG content. Our model predictions were consistent with earlier experimental studies. In the intact explant model, minimal degenerative changes were observed under normal loading, while the injurious loading caused a reorientation of collagen fibrils toward the direction perpendicular to the surface, intense collagen degradation at the surface, and intense PG loss in the superficial and middle zones. In the injured explant models, normal loading induced intense collagen degradation, collagen reorientation, and PG depletion both on the surface and around the lesion. Our results confirm that the cartilage lesion depth is a crucial parameter affecting tissue degeneration, even under physiological loading conditions. The results suggest that potential fibril reorientation might prevent or slow down fibril degradation under conditions in which the tissue mechanical homeostasis is perturbed like the presence of defects or injurious loading.

A homogenized constrained mixture model of restenosis and vascular remodelling after balloon angioplasty

Restenosis is one of the main adverse effects of the treatment of atherosclerosis through balloon angioplasty or stenting. During the intervention, the arterial wall is overstretched, causing a cascade of cellular events and subsequent neointima formation. This mechanical stimulus and its mechanobiological effects can be reproduced in biomechanical simulations. The aim of these models is to predict the long-term outcome of these procedures, to help increase the understanding of restenosis formation and to allow for in silico optimization of the treatment. We propose a predictive finite-element model of restenosis, using the homogenized constrained mixture modelling framework designed to model growth and remodelling in soft tissues. We compare the results with clinical observations in human coronary arteries and experimental findings in non-human primate models. We also explore the model's clinical relevance by testing its response to different balloon loads and to the use of drug-eluting balloons. The comparison of the results with experimental data shows the relevance of the model. We show its ability to predict both inward and outward remodelling as observed in vivo and we show the importance of an improved understanding of restenosis formation from a biomechanical point of view.

A Chemomechanobiological Model of the Long-Term Healing Response of Arterial Tissue to a Clamping Injury

Vascular clamping often causes injury to arterial tissue, leading to a cascade of cellular and extracellular events. A reliable in silico prediction of these processes following vascular injury could help us to increase our understanding thereof, and eventually optimize surgical techniques or drug delivery to minimize the amount of long-term damage. However, the complexity and interdependency of these events make translation into constitutive laws and their numerical implementation particularly challenging. We introduce a finite element simulation of arterial clamping taking into account acute endothelial denudation, damage to extracellular matrix, and smooth muscle cell loss. The model captures how this causes tissue inflammation and deviation from mechanical homeostasis, both triggering vascular remodeling. A number of cellular processes are modeled, aiming at restoring this homeostasis, i.e., smooth muscle cell phenotype switching, proliferation, migration, and the production of extracellular matrix. We calibrated these damage and remodeling laws by comparing our numerical results to in vivo experimental data of clamping and healing experiments. In these same experiments, the functional integrity of the tissue was assessed through myograph tests, which were also reproduced in the present study through a novel model for vasodilator and -constrictor dependent smooth muscle contraction. The simulation results show a good agreement with the in vivo experiments. The computational model was then also used to simulate healing beyond the duration of the experiments in order to exploit the benefits of computational model predictions. These results showed a significant sensitivity to model parameters related to smooth muscle cell phenotypes, highlighting the pressing need to further elucidate the biological processes of smooth muscle cell phenotypic switching in the future.

How to implement user-defined fiber-reinforced hyperelastic materials in finite element software

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.

Mechanical characterization of squid giant axon membrane sheath and influence of the collagenous endoneurium on its properties

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 [Formula: see text], 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.

Reinforcing the pulmonary artery autograft in the aortic position with a textile mesh: a histological evaluation

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 < 0.05). A fibrotic sheet, variable in thickness and containing fibroblasts, neovessels and foreign body giant cells, was incorporated in the mesh. Histological examination of the reinforced autograft and the adjacent aorta revealed thinning of the vessel wall due to atrophy of the smooth muscle cells. Potential spaces between the vessel wall and the mesh were filled with oedema.

CONCLUSIONS

Reinforcing an interposition pulmonary autograft in the descending aorta with a macroporous mesh showed promising results in limiting autograft dilatation in this sheep model. Histological evaluation revealed atrophy of the smooth muscle cell and consequently thinning of the vessel wall within the mesh support.

Combined enzymatic degradation of proteoglycans and collagen significantly alters intratissue strains in articular cartilage during cyclic compression

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.

Development of an improved parameter fitting method for planar biaxial testing using rakes

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.

Cartilage-on-cartilage contact: effect of compressive loading on tissue deformations and structural integrity of bovine articular cartilage

OBJECTIVE

This study aims to characterize the deformations in articular cartilage under compressive loading and link these to changes in the extracellular matrix constituents described by magnetic resonance imaging (MRI) relaxation times in an experimental model mimicking in vivo cartilage-on-cartilage contact.

DESIGN

Quantitative MRI images, T₁, T₂ and T_1ρ relaxation times, were acquired at 9.4T from bovine femoral osteochondral explants before and immediately after loading. Two-dimensional intra-tissue displacement and strain fields under cyclic compressive loading (350N) were measured using the displacement encoding with stimulated echoes (DENSE) method. Changes in relaxation times in response to loading were evaluated against the deformation fields.

RESULTS

Deformation fields showed consistent patterns among all specimens, with maximal strains at the articular surface that decrease with tissue depth. Axial and transverse strains were maximal around the center of the contact region, whereas shear strains were minimal around the contact center but increased towards contact edges. A decrease in T₂ and T_1ρ was observed immediately after loading whereas the opposite was observed for T₁. No correlations between cartilage deformation patterns and changes in relaxation times were observed.

CONCLUSIONS

Displacement encoding combined with relaxometry by MRI can noninvasively monitor the cartilage biomechanical and biochemical properties associated with loading. The deformation fields reveal complex patterns reflecting the depth-dependent mechanical properties, but intra-tissue deformation under compressive loading does not correlate with structural and compositional changes. The compacting effect of cyclic compression on the cartilage tissue was revealed by the change in relaxation time immediately after loading.

Cartilage defect location and stiffness predispose the tibiofemoral joint to aberrant loading conditions during stance phase of gait

OBJECTIVES

The current study quantified the influence of cartilage defect location on the tibiofemoral load distribution during gait. Furthermore, changes in local mechanical stiffness representative for matrix damage or bone ingrowth were investigated. This may provide insights in the mechanical factors contributing to cartilage degeneration in the presence of an articular cartilage defect.

METHODS

The load distribution following cartilage defects was calculated using a musculoskeletal model that included tibiofemoral and patellofemoral joints with 6 degrees-of-freedom. Circular cartilage defects of 100 mm2 were created at different locations in the tibiofemoral contact geometry. By assigning different mechanical properties to these defect locations, softening and hardening of the tissue were evaluated.

RESULTS

Results indicate that cartilage defects located at the load-bearing area only affect the load distribution of the involved compartment. Cartilage defects in the central part of the tibia plateau and anterior-central part of the medial femoral condyle present the largest influence on load distribution. Softening at the defect location results in overloading, i.e., increased contact pressure and compressive strains, of the surrounding tissue. In contrast, inside the defect, the contact pressure decreases and the compressive strain increases. Hardening at the defect location presents the opposite results in load distribution compared to softening. Sensitivity analysis reveals that the surrounding contact pressure, contact force and compressive strain alter significantly when the elastic modulus is below 7 MPa or above 18 MPa.

CONCLUSION

Alterations in local mechanical behavior within the high load bearing area resulted in aberrant loading conditions, thereby potentially affecting the homeostatic balance not only at the defect but also at the tissue surrounding and opposing the defect. Especially, cartilage softening predisposes the tissue to loads that may contribute to accelerated risk of cartilage degeneration and the initiation or progression towards osteoarthritis of the whole compartment.

How important is sample alignment in planar biaxial testing of anisotropic soft biological tissues? A finite element study

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.

Comparison of in vivo vs. ex situ obtained material properties of sheep common carotid artery

Patient-specific biomechanical modelling can improve preoperative surgical planning. This requires patient-specific geometry as well as patient-specific material properties as input. The latter are, however, still quite challenging to estimate in vivo. This study focuses on the estimation of the mechanical properties of the arterial wall. Firstly, in vivo pressure, diameter and thickness of the arterial wall were acquired for sheep common carotid arteries. Next, the animals were sacrificed and the tissue was stored for mechanical testing. Planar biaxial tests were performed to obtain experimental stress-stretch curves. Finally, parameters for the hyperelastic Mooney-Rivlin and Gasser-Ogden-Holzapfel (GOH) material model were estimated based on the in vivo obtained pressure-diameter data as well as on the ex situ experimental stress-stretch curves. Both material models were able to capture the in vivo behaviour of the tissue. However, in the ex situ case only the GOH model provided satisfactory results. When comparing different fitting approaches, in vivo vs. ex situ, each of them showed its own advantages and disadvantages. The in vivo approach estimates the properties of the tissue in its physiological state while the ex situ approach allows to apply different loadings to properly capture the anisotropy of the tissue. Both of them could be further enhanced by improving the estimation of the stress-free state, i.e. by adding residual circumferential stresses in vivo and by accounting for the flattening effect of the tested samples ex vivo. • Competing interests: none declared • Word count: 4716.

Off-Label use of Stretchable Polytetrafluoroethylene: Overexpansion of Synthetic Shunts

Purpose

To describe our experience with balloon dilatation and stenting of modified systemic-to-pulmonary artery (PA) shunts in relation to an assessment and interpretation of the mechanical properties of thin-walled expandable polytetrafluoroethylene (ePTFE) stretch vascular grafts.

Methods

Our pediatric cardiology/cardiac surgery database was reviewed to identify all infants and children with a modified systemic-to-PA shunt who underwent cardiac catheterization. Reports and images were reviewed. Thin-walled stretchable and regular Gore-Tex® vascular grafts were mechanically compared using tensiometry.

Results

11 patients underwent dilatation or stenting procedures of a systemic-to-PA shunt. No major complications occurred and none of our patients died during or due to this intervention. High pressures in balloons and stents with diameters larger than the graft were used. Shunt diameters and oxygen saturation levels increased from 2.05 ± 1.25 mm to 4.75 ± 0.88 mm and with 12 ± 6.8%, respectively. In 6 patients re-catheterizations were performed. Four patients died, all with patent shunts. The fail-stress and the fail-strain in the circumferential direction of the stretchable graft were significantly higher than in the non-stretchable graft.

Conclusions

Dilatation and stenting of stenosed modified systemic-to-PA shunts is feasible and safe. Dilatation and stenting of these shunts to calibers larger than those provided by the manufacturer is possible. Results of our technical study posit a great advantage for the use of the thin-walled stretch configuration of ePTFE.

GPGPU-based explicit finite element computations for applications in biomechanics: the performance of material models, element technologies, and hardware generations

Finite element (FE) simulations are increasingly valuable in assessing and improving the performance of biomedical devices and procedures. Due to high computational demands such simulations may become difficult or even infeasible, especially when considering nearly incompressible and anisotropic material models prevalent in analyses of soft tissues. Implementations of GPGPU-based explicit FEs predominantly cover isotropic materials, e.g. the neo-Hookean model. To elucidate the computational expense of anisotropic materials, we implement the Gasser-Ogden-Holzapfel dispersed, fiber-reinforced model and compare solution times against the neo-Hookean model. Implementations of GPGPU-based explicit FEs conventionally rely on single-point (under) integration. To elucidate the expense of full and selective-reduced integration (more reliable) we implement both and compare corresponding solution times against those generated using underintegration. To better understand the advancement of hardware, we compare results generated using representative Nvidia GPGPUs from three recent generations: Fermi (C2075), Kepler (K20c), and Maxwell (GTX980). We explore scaling by solving the same boundary value problem (an extension-inflation test on a segment of human aorta) with progressively larger FE meshes. Our results demonstrate substantial improvements in simulation speeds relative to two benchmark FE codes (up to 300[Formula: see text] while maintaining accuracy), and thus open many avenues to novel applications in biomechanics and medicine.

In vivo evidence of significant levator ani muscle stretch on MR images of a live childbirth

OBJECTIVE

Vaginal childbirth is believed to be a significant risk factor for the development of pelvic floor dysfunction later in life. Previous studies have explored the use of medical imaging and simulations of childbirth to determine the stretch in the levator ani muscle. A report in 2012 has recorded magnetic resonance images of a live childbirth of a 24 year old woman giving birth vaginally for the second time, using a 1.0 Tesla open, high-field scanner. Our objective was to determine the stretch ratios in the levator muscle using these magnetic resonance images of live childbirth.

STUDY DESIGN

Three-dimensional magnetic resonance image sequences were obtained to visualize coronal and axial planes before and after the childbirth. These images were obtained before the expulsion phase without pushing and were used to reconstruct the levator muscle and the fetal head in 3 dimensions. The fetal head was approximated to be an ellipsoid, and it is assumed that its middle section is visible in dynamic magnetic resonance images. Assuming incompressibility, the full deformation field of the fetal head is then calculated. Real-time cine magnetic resonance images were acquired for the during the expulsion phase, occurring over 2 contractions in the midsagittal plane. The levator muscle stretch is estimated using a custom program. The program calculates points of contact between the fetal head ellipsoid and the levator ani muscle model as the head descends down the birth canal and moves them orthogonal to its surface. Circumferential stretch was calculated to represent the extension needed to allow the passage of the fetal head.

RESULTS

Starting from a position in the preexpulsion phase, the levator muscle experiences a maximum circumferential stretch of 248% on the posterior-medial portion of the levator ani muscle, as shown in previously published finite element simulations. However, the maximal stretch was notably less than that predicted by finite element models. This is because our baseline 3-dimensional model of the levator muscle is created from images taken shortly before expulsion and thus is already in a stretched state. Furthermore, the finite element models are created from images of a healthy nulliparous woman, while this study uses images from a para 2 woman.

CONCLUSION

This study is the first attempt to estimate the stretch in levator ani muscle using magnetic resonance images of a live childbirth. The stretch was significant and the locations corroborate with previous findings of finite element models.

Planar biaxial testing of soft biological tissue using rakes: A critical analysis of protocol and fitting process

Mechanical characterization of soft biological tissue is becoming more and more prevalent. Despite the growing use of planar biaxial testing for soft tissue characterization, testing conditions and subsequent data analysis have not been standardized and vary widely. This also influences the quality of the result of the parameter fitting. Moreover, the testing conditions and data analysis are often not or incompletely reported, which impedes the proper comparison of parameters obtained from different studies. With a focus on planar biaxial tests using rakes, this paper investigates varying testing conditions and varying data analysis methods and their effect on the quality of the parameter fitting results. By means of a series of finite element simulations, aspects such as number of rakes, rakes׳ width, loading protocol, constitutive model, material stiffness and anisotropy are evaluated based on the degree of homogeneity of the stress field, and on the correlation between the experimentally obtained stress and the stress derived from the constitutive model. When calculating the aforementioned stresses, different definitions of the section width and deformation gradient are used in literature, each of which are looked into. Apart from this degree of homogeneity and correlation, also the effect on the quality of the parameter fitting result is evaluated. The results show that inhomogeneities can be reduced to a minimum for wise choices of testing conditions and analysis methods, but never completely eliminated. Therefore, a new parameter optimization procedure is proposed that corrects for the inhomogeneities in the stress field and induces significant improvements to the fitting results. Recommendations are made for best practice in rake-based planar biaxial testing of soft biological tissues and subsequent parameter fitting, and guidelines are formulated for reporting thereof in publications.

Biomechanical and biochemical properties of the thoracic aorta in warmblood horses, Friesian horses, and Friesians with aortic rupture

Background

Thoracic aortic rupture and aortopulmonary fistulation are rare conditions in horses. It mainly affects Friesian horses. Intrinsic differences in biomechanical properties of the aortic wall might predispose this breed. The biomechanical and biochemical properties of the thoracic aorta were characterized in warmblood horses, unaffected Friesian horses and Friesians with aortic rupture in an attempt to unravel the underlying pathogenesis of aortic rupture in Friesian horses. Samples of the thoracic aorta at the ligamentum arteriosum (LA), mid thoracic aorta (T1) and distal thoracic aorta (T2) were obtained from Friesian horses with aortic rupture (A), nonaffected Friesian (NA) and warmblood horses (WB). The biomechanical properties of these samples were determined using uniaxial tensile and rupture assays. The percentages of collagen and elastin (mg/mg dry weight) were quantified.

Results

Data revealed no significant biomechanical nor biochemical differences among the different groups of horses. The distal thoracic aorta displayed an increased stiffness associated with a higher collagen percentage in this area and a higher load-bearing capacity compared to the more proximal segments.

Conclusions

Our findings match reported findings in other animal species. Study results did not provide evidence that the predisposition of the Friesian horse breed for aortic rupture can be attributed to altered biomechanical properties of the aortic wall.

Electronic supplementary material

The online version of this article (doi:10.1186/s12917-015-0597-0) contains supplementary material, which is available to authorized users.

Arterial Vasoreactivity is Equally Affected by In Vivo Cross-Clamping with Increasing Loads in Young and Middle-Aged Mice Aortas

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.

Non-invasive, energy-based assessment of patient-specific material properties of arterial tissue

The mechanical properties of human biological tissue vary greatly. The determination of arterial material properties should be based on experimental data, i.e. diameter, length, intramural pressure, axial force and stress-free geometry. Currently, clinical data provide only non-invasively measured pressure-diameter data for superficial arteries (e.g. common carotid and femoral artery). The lack of information forces us to take into account certain assumptions regarding the in situ configuration to estimate material properties in vivo. This paper proposes a new, non-invasive, energy-based approach for arterial material property estimation. This approach is compared with an approach proposed in the literature. For this purpose, a simplified finite element model of an artery was used as a mock experimental situation. This method enables exact knowledge of the actual material properties, thereby allowing a quantitative evaluation of material property estimation approaches. The results show that imposing conditions on strain energy can provide a good estimation of the material properties from the non-invasively measured pressure and diameter data.