Experimental and Numerical Analysis of Growth and Remodeling Phenomena in the Pulmonary Autograft

In several cardiac interventions, pulmonary arterial tissue is exposed to systemic conditions. One of these procedures is the Ross procedure, which replaces a diseased aortic valve with the patient's own pulmonary valve. A common complication hereby is the dilatation of this pulmonary autograft. Still, not all autografts fail and the decisive factor for autograft failure is not known. Several reinforcement strategies have been designed to counteract this dilatation, but none have proven to be consistently successful. A personalized macroporous mesh used to reinforce dilating aortic roots in Marfan patients might also bring a solution for this dilating autograft. The goal of this thesis is therefore to investigate the mechanical and microstructural changes that occur when a pulmonary artery is placed in aortic position as an autograft, and to assess the effect of a macroporous mesh that reinforces the autograft. To this end, a combined experimental and computational approach was applied. Two sets of experiments were conducted on sheep. Within these animal experiments, a segment of pulmonary artery was placed in aortic position. This pulmonary autograft was either reinforced with a macroporous mesh or left unreinforced in the control group. Six months after implantation, the sheep were sacrificed and the following tissues were harvested and subjected to planar biaxial testing: native aorta, native pulmonary artery, unreinforced pulmonary autograft, reinforced pulmonary autograft. The first set of animal experiments constisted of nine sheep, with two sheep serving as control group. Seventeen sheep were included in the second set of animal experiments, with eight sheep serving as control group. The mechanical behavior of the unreinforced autograft adapted to become more aorta-like in some samples whereas it retained its pulmonary artery character in other samples. Microstructurally, an increased collagen deposition, smooth muscle cell atrophy and a decrease in media thickness occured in the unreinforced pulmonary autograft. The mesh appeared to be nicely incorporated but a higher loss of smooth muscle cells was noticed in the reinforced pulmonary autograft. The follow-up MRIs, taken only in the second set of animal experiments, showed progressive dilatation of the autograft when leaving it unreinforced. The macroporous mesh around the pulmonary autograft decreased autograft dilatation, but also its compliance. A subset of animal experiments without macroporous reinforcement was reproduced in silico using different growth and remodeling models. The ability to reproduce the experimental outcome was evaluated for two types of models: models based on kinematic growth theory and models based on constrained mixture theory. The former decompose the deformation gradient into a growth and elastic deformation gradient, with growth either in the radial or circumferential direction. The constrained mixture theory represents an artery as a mixture of constituents with their own stress-free configuration, turnover rates and material properties, but are constrained to move together. The two constituents in this case are elastin and collagen. Elastin is assumed to remain constant whereas collagen continuously degrades and is deposited, influenced by the stretch felt by the collagen fibers. The kinematic growth model with circumferential growth as well as the constrained mixture models are capable of reproducing the progressive dilatation of the autograft. However, where the experiments show an initial steep increase in diameter followed by a slower increase, the model shows a linearly increasing diameter. As opposed to the kinematic growth models, the constrained mixture models are also able to reproduce the experimentally observed changes in mechanical behaviour and collagen fraction. In conclusion, the animal experiments showed adaptation of the mechanical behavior of the pulmonary artery when placed in aortic position. The macroporous mesh was also able to halt progressive dilatation of the autograft while retaining its microstructure. The two types of growth and remodeling models were capable of simulating the dilatation of the autograft, and the constrained mixture models were also capable of simulating changing mechanical behavior and microstructure. Nevertheless, more controlled experiments are needed to increase our understanding of autograft (mal)adaptation and to define more mechanobiologically substantiated constitutive relations.status: accepte

A chemomechanobiological model of the long-term healing response of arterial tissue to a clamping injury

International audienceVascular 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 futur

NUMERICAL STUDY OF THE ROLE OF SMOOTH MUSCLE CELLS IN ARTERIAL GROWTH AND REMODELING

Like all living tissue, arterial tissue grows and remodels under the impulse of altered mechanical loading. In arterial tissue, the smooth muscle cells (SMC) play an essential role in this process. These SMC can have either a contractile or a synthetic phenotype. In case of the former, changes in wall shear stress trigger transition from a contracted to a relaxed state, allowing the blood vessel to regulate blood flow on a short time scale (in the order of seconds). SMC with a synthetic phenotype produce extracellular matrix, in casu collagen, allowing for a continuous turnover of collagen content, which has a half-life of around 70 days. The balance between collagen production and degradation is an essential factor in the growth and remodeling process of arterial tissue. In this study, we numerically test the effect of the sensitivity and response rate of synthetic SMC on the remodeling process and compare with experimental data.status: publishe

How to measure the deformation during planar biaxial testing of biological soft tissue?

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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.status: publishe

Biomechanical evaluation of the (un)reinforced Ross procedure

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Determination of layer-specific properties from planar biaxial tests on intact aortic wall

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Determination of layer-specific material properties from planar biaxial tension tests and uniaxial tests on intact arterial wall

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Constrained mixture modeling affects material parameter identification from planar biaxial tests

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

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