Hemodynamics and wall shear metrics in a pulmonary autograft: Comparing a fluid-structure interaction and computational fluid dynamics approach.

OBJECTIVE: In young patients, aortic valve disease is often treated by placement of a pulmonary autograft (PA) which adapts to its new environment through growth and remodeling. To better understand the hemodynamic forces acting on the highly distensible PA in the acute phase after surgery, we developed a fluid-structure interaction (FSI) framework and comprehensively compared hemodynamics and wall shear-stress (WSS) metrics with a computational fluid dynamic (CFD) simulation. METHODS: The FSI framework couples a prestressed non-linear hyperelastic arterial tissue model with a fluid model using the in-house coupling code CoCoNuT. Geometry, material parameters and boundary conditions are based on in-vivo measurements. Hemodynamics, time-averaged WSS (TAWSS), oscillatory shear index (OSI) and topological shear variation index (TSVI) are evaluated qualitatively and quantitatively for 3 different sheeps. RESULTS: Despite systolic-to-diastolic volumetric changes of the PA in the order of 20 %, the point-by-point correlation of TAWSS and OSI obtained through CFD and FSI remains high (r > 0.9, p < 0.01) for TAWSS and (r > 0.8, p < 0.01) for OSI). Instantaneous WSS divergence patterns qualitatively preserve similarities, but large deformations of the PA leads to a decrease of the correlation between FSI and CFD resolved TSVI (r < 0.7, p < 0.01). Moderate co-localization between FSI and CFD is observed for low thresholds of TAWSS and high thresholds of OSI and TSVI. CONCLUSION: FSI might be warranted if we were to use the TSVI as a mechano-biological driver for growth and remodeling of PA due to varying intra-vascular flow structures and near wall hemodynamics because of the large expansion of the PA.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

An improved parameter fitting approach of a planar biaxial test including the experimental prestretch.

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.

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.

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.