Characterizing atherosclerotic tissues: in silico analysis of mechanical properties using intravascular ultrasound and inverse finite element methods.

Atherosclerosis is a prevalent cause of acute coronary syndromes that consists of lipid deposition inside the artery wall, creating an atherosclerotic plaque. Early detection may prevent the risk of plaque rupture. Nowadays, intravascular ultrasound (IVUS) is the most common medical imaging technology for atherosclerotic plaque detection. It provides an image of the section of the coronary wall and, in combination with new techniques, can estimate the displacement or strain fields. From these magnitudes and by inverse analysis, it is possible to estimate the mechanical properties of the plaque tissues and their stress distribution. In this paper, we presented a methodology based on two approaches to characterize the mechanical properties of atherosclerotic tissues. The first approach estimated the linear behavior under particular pressure. In contrast, the second technique yielded the non-linear hyperelastic material curves for the fibrotic tissues across the complete physiological pressure range. To establish and validate this method, the theoretical framework employed in silico models to simulate atherosclerotic plaques and their IVUS data. We analyzed different materials and real geometries with finite element (FE) models. After the segmentation of the fibrotic, calcification, and lipid tissues, an inverse FE analysis was performed to estimate the mechanical response of the tissues. Both approaches employed an optimization process to obtain the mechanical properties by minimizing the error between the radial strains obtained from the simulated IVUS and those achieved in each iteration. The second methodology was successfully applied to five distinct real geometries and four different fibrotic tissues, getting median R 2 of 0.97 and 0.92, respectively, when comparing the real and estimated behavior curves. In addition, the last technique reduced errors in the estimated plaque strain field by more than 20% during the optimization process, compared to the former approach. The findings enabled the estimation of the stress field over the hyperelastic plaque tissues, providing valuable insights into its risk of rupture.

A Cardiovascular Risk Optimization Program in People With Schizophrenia: A Pilot Randomized Controlled Clinical Trial.

BACKGROUND: Cardiovascular disease is one of the leading causes of premature death in people with schizophrenia. Some modifiable factors that have been implicated include unhealthy lifestyle, medication side effects, and physical comorbidities. The goal of this study was to assess the efficacy of a 6-month, multifactorial cardiovascular risk intervention to reduce cardiovascular risk (CVR) in people with schizophrenia. METHODS: We conducted a 2-arm, parallel, randomized clinical trial in a regional mental health center. Participants with at least 1 poorly controlled cardiovascular risk factor (CVRF) (hypertension, diabetes mellitus, hypercholesterolemia, or tobacco smoking) were randomly assigned to the intervention group or to a control group. The subjects in the intervention group received a patient-centered approach that included promoting a healthy lifestyle, pharmacological management of CVRFs, psychotropic drug optimization, and motivational follow-up [Programa d'optimització del RISc CArdiovascular (PRISCA)]. The main outcome was change in CVR as assessed using the Framingham-REGICOR function, after 6 months compared with the baseline in both groups. RESULTS: Forty-six participants were randomly assigned to the PRISCA group (n=23) or the control group (n=23). The most prevalent CVRFs at baseline were hypercholesterolemia (84.8%) and tobacco smoking (39.1%). The PRISCA group showed a significant reduction in the REGICOR score (-0.96%; 95% CI: -1.60 to -0.32, P=0.011) after 6 months (relative risk reduction of 20.9%), with no significant changes in the control group (0.21%; 95% CI: -0.47 to 0.89, P=0.706). In the PRISCA group, low-density lipoprotein cholesterol also decreased significantly (-27.14 mg/dL; 95% CI: -46.28 to -8.00, P=0.008). CONCLUSION: A patient-centered, multifactorial cardiovascular risk intervention improved CVR in people with schizophrenia after 6 months, which was achieved mainly by improving the lipid profile.

A Multimodal Scaffold for SDF1 Delivery Improves Cardiac Function in a Rat Subacute Myocardial Infarct Model.

Ischemic heart disease is one of the leading causes of death worldwide. The efficient delivery of therapeutic growth factors could counteract the adverse prognosis of post-myocardial infarction (post-MI). In this study, a collagen hydrogel that is able to load and appropriately deliver pro-angiogenic stromal cell-derived factor 1 (SDF1) was physically coupled with a compact collagen membrane in order to provide the suture strength required for surgical implantation. This bilayer collagen-on-collagen scaffold (bCS) showed the suitable physicochemical properties that are needed for efficient implantation, and the scaffold was able to deliver therapeutic growth factors after MI. In vitro collagen matrix biodegradation led to a sustained SDF1 release and a lack of cytotoxicity in the relevant cell cultures. In vivo intervention in a rat subacute MI model resulted in the full integration of the scaffold into the heart after implantation and biocompatibility with the tissue, with a prevalence of anti-inflammatory and pro-angiogenic macrophages, as well as evidence of revascularization and improved cardiac function after 60 days. Moreover, the beneficial effect of the released SDF1 on heart remodeling was confirmed by a significant reduction in cardiac tissue stiffness. Our findings demonstrate that this multimodal scaffold is a desirable matrix that can be used as a drug delivery system and a scaffolding material to promote functional recovery after MI.

Modeling fatigue failure in soft tissue using a visco-hyperelastic model with discontinuous damage.

Soft tissue is susceptible to injury from single high-magnitude static loads and from repetitive low-magnitude fatigue loads. While many constitutive formulations have been developed and validated to model static failure in soft tissue, a modeling framework is not well-established for fatigue failure. Here we determined the feasibility of using a visco-hyperelastic damage model with discontinuous damage (strain energy-based damage criterion) to simulate low- and high-cycle fatigue failure in soft fibrous tissue. Cyclic creep data from six uniaxial tensile fatigue experiments of human medial meniscus were used to calibrate the specimen-specific material parameters. The model was able to successfully simulate all three characteristic stages of cyclic creep, and predict the number of cycles until tissue rupture. Mathematically, damage propagated under constant cyclic stress due to time-dependent viscoelastic increases in tensile stretch that in turn increased strain energy. Our results implicate solid viscoelasticity as a fundamental regulator of fatigue failure in soft tissue, where tissue with slow stress relaxation times will be more resistant to fatigue injury. In a validation study, the visco-hyperelastic damage model was able to simulate characteristic stress-strain curves of pull to failure experiments (static failure) when using material parameters curve fit to the fatigue experiments. For the first time, we've shown that a visco-hyperelastic discontinuous damage framework can model cyclic creep and predict material rupture in soft tissue, and may enable the reliable simulation of both fatigue and static failure behavior from a single constitutive formulation.

Coronary artery properties in atherosclerosis: A deep learning predictive model.

In this work an Artificial Neural Network (ANN) was developed to help in the diagnosis of plaque vulnerability by predicting the Young modulus of the core (E core ) and the plaque (E plaque ) of atherosclerotic coronary arteries. A representative in silico database was constructed to train the ANN using Finite Element simulations covering the ranges of mechanical properties present in the bibliography. A statistical analysis to pre-process the data and determine the most influential variables was performed to select the inputs of the ANN. The ANN was based on Multilayer Perceptron architecture and trained using the developed database, resulting in a Mean Squared Error (MSE) in the loss function under 10-7, enabling accurate predictions on the test dataset for E core and E plaque . Finally, the ANN was applied to estimate the mechanical properties of 10,000 realistic plaques, resulting in relative errors lower than 3%.

Is location a significant parameter in the layer dependent dissection properties of the aorta?

Proper characterisation of biological tissue is key to understanding the effect of the biomechanical environment in the physiology and pathology of the cardiovascular system. Aortic dissection in particular is a prevalent and sometimes fatal disease that still lacks a complete comprehension of its progression. Its development and outcome, however, depend on the location in the vessel. Dissection properties of arteries are frequently studied via delamination tests, such as the T-peel test and the mixed-mode peel test. So far, a study that performs both tests throughout different locations of the aorta, as well as dissecting several interfaces, is missing. This makes it difficult to extract conclusions in terms of vessel heterogeneity, as a standardised experimental procedure cannot be assured for different studies in literature. Therefore, both dissection tests have been here performed on healthy porcine aortas, dissecting three interfaces of the vessels, i.e., the intima-media, the media-adventitia and the media within itself, considering different locations of the aorta, the ascending thoracic aorta (ATA), the descending thoracic aorta and the infrarenal abdominal aorta (IAA). Significant differences were found for both, layers and location. In particular, dissection forces in the ATA were the highest and the separation of the intima-media interface required significantly the lowest force. Moreover, dissection in the longitudinal direction of the vessel generally required more force than in the circumferential one. These results emphasise the need to characterise aortic tissue considering the specific location and dissected layer of the vessel.

Fabrication of human myocardium using multidimensional modelling of engineered tissues.

Biofabrication of human tissues has seen a meteoric growth triggered by recent technical advancements such as human induced pluripotent stem cells (hiPSCs) and additive manufacturing. However, generation of cardiac tissue is still hampered by lack of adequate mechanical properties and crucially by the often unpredictable post-fabrication evolution of biological components. In this study we employ melt electrowriting (MEW) and hiPSC-derived cardiac cells to generate fibre-reinforced human cardiac minitissues. These are thoroughly characterized in order to build computational models and simulations able to predict their post-fabrication evolution. Our results show that MEW-based human minitissues display advanced maturation 28 post-generation, with a significant increase in the expression of cardiac genes such as MYL2, GJA5, SCN5A and the MYH7/MYH6 and MYL2/MYL7 ratios. Human iPSC-cardiomyocytes are significantly more aligned within the MEW-based 3D tissues, as compared to conventional 2D controls, and also display greater expression of C×43. These are also correlated with a more mature functionality in the form of faster conduction velocity. We used these data to develop simulations capable of accurately reproducing the experimental performance. In-depth gauging of the structural disposition (cellular alignment) and intercellular connectivity (C×43) allowed us to develop an improved computational model able to predict the relationship between cardiac cell alignment and functional performance. This study lays down the path for advancing in the development ofin silicotools to predict cardiac biofabricated tissue evolution after generation, and maps the route towards more accurate and biomimetic tissue manufacture.

Mathematical modelling of endovascular drug delivery: Balloons versus stents.

The most common treatment for obstructive coronary artery disease (CAD) is the implantation of a permanent drug-eluting stent (DES). Not only has this permanency been associated with delayed healing of the artery, but it also poses challenges when treating subsequent re-narrowing due to in-stent restenosis (ISR). Drug-coated balloons (DCBs) provide a potential solution to each of these issues. While their use has been primarily limited to treating ISR, in recent years, DCBs have emerged as an attractive potential alternative to DESs for the treatment of certain de novo lesions. However, there remain a number of concerns related to the safety and efficacy of these devices. Firstly, unlike DESs, DCBs necessitate a very short drug delivery window, favouring a higher drug loading. Secondly, while the majority of coronary DCBs in Europe are coated with paclitaxel, the potential mortality signal raised with paclitaxel DCBs in peripheral interventions has shifted efforts towards the development of limus-eluting balloons. The purpose of this paper is to provide a computational model that allows drug delivery from DCBs and DESs to be investigated and compared. We present a comprehensive computational framework that employs a 2D-axisymmetric geometry, incorporates two nonlinear phases of drug binding (specific and non-specific) and includes the influence of diffusion and advection, within a multilayer arterial wall. We utilise this framework to (i) simulate drug delivery from different types of balloon platform; (ii) explore the influence of DCB application time; (iii) elucidate the importance on release kinetics of elevated pressure during DCB application; (iv) compare DCB delivery of two different drugs (sirolimus and paclitaxel) and; (v) compare simulations of DESs versus DCBs. Key measures of comparison are related to safety (drug content in tissue, DC) and efficacy (specific binding site saturation, %SBSS) markers. Our results highlight the pros and cons of each device in terms of DC and %SBSS levels achieved and, moreover, indicate the potential for designing a DCB that gives rise to sufficiently similar safety and efficacy indicators as current commercial DESs.

Biomechanical characterization and constitutive modeling of the layer-dissected residual strains and mechanical properties of abdominal porcine aorta.

We analyze the residual stresses and mechanical properties of layer-dissected infrarenal abdominal aorta (IAA). We measured the axial pre-stretch and opening angle and performed uniaxial tests to study and compare the mechanical behavior of both intact and layer-dissected porcine IAA samples under physiological loads. Finally, some of the most popular anisotropic hyperelastic constitutive models (GOH and microfiber models) were proposed to estimate the mechanical properties of the abdominal aorta by least-square fitting of the recorded in-vitro uniaxial test results. The results show that the residual stresses are layer dependent. In all cases, we found that the OA in the media layer is lower than in the whole artery, the intima and the adventitia. For the axial pre-stretch, we found that the adventitia and the media were slightly stretched in the environment of the intact arterial strip, whereas the intima appears to be compressed. Regarding the mechanical properties, the media seems to be the softest layer over the whole deformation domain showing high anisotropy, while the intima and adventitia exhibit considerable stiffness and a lower anisotropy response. Finally, all the hyperelastic anisotropic models considered in this study provided a reasonable approximation of the experimental data. The GOH model showed the best fitting.

Self-adhesive hydrogel meshes reduce tissue incorporation and mechanical behavior versus microgrips self-fixation: a preclinical study.

PURPOSE: Atraumatic mesh fixation for abdominal hernia repair has been developed to avoid the disadvantages of classical fixation with sutures, which is considered a cause of chronic pain and discomfort. This study was designed to analyze, in the short and medium term, the biological and mechanical behavior of two self-fixing meshes compared to that of a polypropylene (PP) mesh fixed with a cyanoacrylate (CA) tissue adhesive. METHODS: Partial abdominal wall defects (6 × 4 cm) were created in New Zealand rabbits (n = 36) and repaired using a self-adhesive hydrogel mesh (Adhesix™), a self-gripping mesh (ProGrip™) or a PP mesh fixed with CA (Surgipro™ CA). After 14 and 90 days, the host tissue incorporation, macrophage response and biomechanical strength were examined. RESULTS: At 14 and 90 days, the ProGrip and Surgipro CA meshes showed good host tissue incorporation; however, the Adhesix implants presented poor integration, seroma formation and a higher degree of shrinkage. The Adhesix hydrogel was completely reabsorbed at 14 days, whereas ProGrip microhooks were observed at all study times. The macrophage response was higher in the ProGrip and Surgipro CA groups at 14 and 90 days, respectively, and decreased over time. At 90 days, the ProGrip implants showed the highest tensile strength values and the Adhesix implants showed the highest failure stretch. CONCLUSION: Meshes with mechanical microgrip self-fixation (ProGrip) show better biological and mechanical behavior than those with adhesive hydrogel (Adhesix) in a preclinical model of abdominal hernia repair in rabbits.

Effects of the Haemodynamic Stimulus on the Location of Carotid Plaques Based on a Patient-Specific Mechanobiological Plaque Atheroma Formation Model.

In this work, we propose a mechanobiological atheroma growth model modulated by a new haemodynamic stimulus. To test this model, we analyse the development of atheroma plaques in patient-specific bifurcations of carotid arteries for a total time of 30 years. In particular, eight geometries (left or right carotid arteries) were segmented from clinical images and compared with the solutions obtained computationally to validate the model. The influence of some haemodynamical stimuli on the location and size of plaques is also studied. Plaques predicted by the mechanobiological models using the time average wall shear stress (TAWSS), the oscillatory shear index (OSI) and a new index proposed in this work are compared. The new index predicts the shape index of the endothelial cells as a combination of TAWSS and OSI values and was fitted using data from the literature. The mechanobiological model represents an evolution of the one previously proposed by the authors. This model uses Navier-Stokes equations to simulate blood flow along the lumen in the transient mode. It also employs Darcy's law and Kedem-Katchalsky equations for plasma and substance flow across the endothelium using the three-pore model. The mass balances of all the substances that have been considered in the model are implemented by convection-diffusion-reaction equations, and finally the growth of the plaques has been computed. The results show that by using the new mechanical stimulus proposed in this study, prediction of plaques is, in most cases, better than only using TAWSS or OSI with a minimal and maximal errors on stenosis ratio of 2.77 and 32.89 %, respectively. However, there are a few geometries in which haemodynamics cannot predict the location of plaques, and other biological or genetic factors would be more relevant than haemodynamics. In particular, the model predicts correctly eleven of the fourteen plaques presented in all the geometries considered. Additionally, a healthy geometry has been computed to check that plaque is not developed with the model in this case.

Influence of vessel curvature and plaque composition on drug transport in the arterial wall following drug-eluting stent implantation.

In the last decade, many computational models have been developed to describe the transport of drug eluted from stents and the subsequent uptake into arterial tissue. Each of these models has its own set of limitations: for example, models typically employ simplified stent and arterial geometries, some models assume a homogeneous arterial wall, and others neglect the influence of blood flow and plasma filtration on the drug transport process. In this study, we focus on two common limitations. Specifically, we provide a comprehensive investigation of the influence of arterial curvature and plaque composition on drug transport in the arterial wall following drug-eluting stent implantation. The arterial wall is considered as a three-layered structure including the subendothelial space, the media and the adventitia, with porous membranes separating them (endothelium, internal and external elastic lamina). Blood flow is modelled by the Navier-Stokes equations, while Darcy's law is used to calculate plasma filtration through the porous layers. Our findings demonstrate that arterial curvature and plaque composition have important influences on the spatiotemporal distribution of drug, with potential implications in terms of effectiveness of the treatment. Since the majority of computational models tend to neglect these features, these models are likely to be under- or over-estimating drug uptake and redistribution in arterial tissue.

Unraveling the multilayer mechanical response of aorta using layer-specific residual stresses and experimental properties.

To test the capability of the multilayer model, we used previously published layer-specific experimental data relating to the axial pre-stretch, the opening angle, the fiber distribution obtained by polarized light microscopy measurements, and the uniaxial and biaxial response of the porcine descending and abdominal aorta. We fitted the mechanical behavior of each arterial layer using Gasser, Holzapfel and Ogden strain energy function using the dispersion parameter κ as phenomenological parameter obtained during the fitting procedure or computed from the experimental fiber distribution. A multilayer finite element model of the whole aorta with the dimensions of the circumferential and longitudinal strips were then built using layer-specific material parameters previously fitted. This model was used to capture the whole aorta response under uniaxial and biaxial stress states and to reproduce the response of the whole aorta to internal pressure. Our results show that a model based on a multilayer structure without residual stresses is unable to render the uniaxial and biaxial mechanical response of the aorta (R2=0.6954 and R2=0.8582 for descending thoracic aorta (DTA) and infrarenal abdominal aorta (IAA), respectively). Only an appropriate multilayer model that includes layer-specific residual stresses can reproduce the response of the whole aorta (R2=0.9787 and R2=0.9636 for DTA and IAA respectively). In addition, a multilayer model without residual stresses produces the same stress distribution as a monolayer model without residual stresses where the maximal value of circumferential and longitudinal stresses appears at the inner radius of the intima. Finally, if layer-specific residual stresses are not available, there is less error the stress distribution using a monolayer model with residual stresses that a multilayer model without residual stresses.

How does stent expansion alter drug transport properties of the arterial wall?

Stents have become the most successful device to treat advanced atherosclerotic lesions. However, one of the main issues with these interventions is the development of restenosis. The coating of stents with antiproliferative substances to reduce this effect is now standard, although such drugs can also delay re-endothelialization of the intima. The drug release strategy is therefore a key determinant of drug-eluting stent efficacy. Many mathematical models describing drug transport in arteries have been developed and, usually separately, models describing the mechanics of arterial tissue have been devised. However, the literature is lacking a comprehensive model that adequately takes into account both the mechanical deformation of the porous arterial wall and the resulting impact on drug transport properties. In this paper, we provide the most comprehensive study to date of the effect of stent mechanical expansion on the drug transport properties of a three-layer arterial wall. Our model incorporates the state-of-the art description of the mechanical properties of arterial tissue though an anisotropic, hyperelastic material model and includes a nonlinear saturable binding model to describe drug transport in the arterial wall. We establish relationships between mechanical force generated through device expansion and alteration in diffusion within the arterial wall and perform simulations to elucidate the impact of such alterations in spatio-temporal drug release and tissue uptake. Mechanical deformation of the arterial wall results in modified drug transport properties and tissue drug concentrations, highlighting the importance of coupling solid mechanics with drug transport.

Mathematical modelling of the restenosis process after stent implantation.

The stenting procedure has evolved to become a highly successful technique for the clinical treatment of advanced atherosclerotic lesions in arteries. However, the development of in-stent restenosis remains a key problem. In this work, a novel two-dimensional continuum mathematical model is proposed to describe the complex restenosis process following the insertion of a stent into a coronary artery. The biological species considered to play a key role in restenosis development are growth factors, matrix metalloproteinases, extracellular matrix, smooth muscle cells and endothelial cells. Diffusion-reaction equations are used for modelling the mass balance between species in the arterial wall. Experimental data from the literature have been used in order to estimate model parameters. Moreover, a sensitivity analysis has been performed to study the impact of varying the parameters of the model on the evolution of the biological species. The results demonstrate that this computational model qualitatively captures the key characteristics of the lesion growth and the healing process within an artery subjected to non-physiological mechanical forces. Our results suggest that the arterial wall response is driven by the damage area, smooth muscle cell proliferation and the collagen turnover among other factors.

Inactivation of carbapenem-resistant Klebsiella pneumoniae by photo-Fenton: Residual effect, gene evolution and modifications with citric acid and persulfate.

The photo-Fenton process application to eliminate carbapenem-resistant Klebsiella pneumoniae, an antibiotic-resistant priority pathogen, was evaluated. Initially, reagents concentration effect was tested and under suitable conditions (5 mg L-1 of Fe2+ and 50 mg L-1 of H2O2) complete bacteria inactivation by action of hydroxyl radical and UVA plus hydrogen peroxide was achieved at 120 min. The process presented a strong residual disinfecting effect when light was turned off at only 20 min. Besides, the cultivability of treated K. pneumoniae in a selective medium containing carbapenem antibiotics was considered. bla-KPC, gene responsible for the resistance, evolution was also assessed. The bacteria response to carbapenem antibiotics was higher as the treatment time increased. In turn, bla-KPC gene remained when K. pneumoniae was completely inactivated (120 min); nevertheless, treatment times longer than 120 min diminished bla-KPC presence. Finally, the photo-Fenton process and its modifications (citric acid addition or persulfate anion instead hydrogen peroxide) were applied to a real hospital wastewater in Colombia. In such complex matrix, the conventional photo-Fenton system reached a moderate disinfection (∼3.5 log-units at 300 min). Meanwhile, in presence of citric acid total inactivation was completed at the same time. Interestingly, the H2O2 substitution by persulfate strongly accelerated the microorganism elimination, achieving the 6-log-units reduction after only 60 min of process action. Thus, the effective elimination of K. pneumoniae from water by the modified photo-Fenton evidenced the potential applicability of this process to limit the proliferation of antibiotic resistant bacteria.

Failure damage mechanical properties of thoracic and abdominal porcine aorta layers and related constitutive modeling: phenomenological and microstructural approach.

Despite increasing experimental and analytical efforts to investigate the irreversible effects of arterial tissue failure, the underlying mechanisms are still poorly understood. The goal of this study was to characterize the failure properties of the intact wall and each separated layer (intima, media, and adventitia) of the descending thoracic and infrarenal abdominal aorta and to test the hypothesis that the failure properties of layer-separated tissue depend on the location of the aorta. To test this hypothesis, we performed uniaxial tests to study the mechanical behavior of both intact and layer-separated porcine aortic tissue samples taken from descending thoracic and infrarenal abdominal aorta until complete failure. The fracture stress is higher in the infrarenal abdominal aorta than in the equivalent descending thoracic aorta. It was also found that the extrapolation of the elastic mechanical properties from the physiological to the supra-physiological regime for characterizing the mechanical response of the aorta would be inappropriate. Finally, we report values of constitutive parameters using phenomenological and microstructural damage models based on continuum damage mechanics theory. The phenomenological damage model gives an excellent fit to the experimental data compared to the microstructural damage model. Although the fitting results of the phenomenological model are better, the microstructural models can include physically motivated aspects obtained from experiments.

On the use of machine learning techniques for the mechanical characterization of soft biological tissues.

Motivated by the search for new strategies for fitting a material model, a new approach is explored in the present work. The use of numerical and complex algorithms based on machine learning techniques such as support vector machines for regression, bagged decision trees, and artificial neural networks is proposed for solving the parameter identification of constitutive laws for soft biological tissues. First, the mathematical tools were trained with analytical uniaxial data (circumferential and longitudinal directions) as inputs, and their corresponding material parameters of the Gasser, Ogden, and Holzapfel strain energy function as outputs. The train and test errors show great efficiency during the training process in finding correlations between inputs and outputs; besides, the correlation coefficients were very close to 1. Second, the tool was validated with unseen observations of analytical circumferential and longitudinal uniaxial data. The results show an excellent agreement between the prediction of the material parameters of the strain energy function and the analytical curves. Finally, data from real circumferential and longitudinal uniaxial tests on different cardiovascular tissues were fitted; thus, the material model of these tissues was predicted. We found that the method was able to consistently identify model parameters, and we believe that the use of these numerical tools could lead to an improvement in the characterization of soft biological tissues.