A method for incorporating three-dimensional residual stretches/stresses into patient-specific finite element simulations of arteries

Experimental characterization of residual deformations in human descending thoracic aortas

The effect of residual stresses on the deformation of human aortas under pulsatile pressure is relevant. Experimental measurements of residual deformations are necessary to characterize residual stresses in human aortas. For this reason, an experimental study is carried out. In the present study, longitudinal and circumferential strips from descending thoracic aortas obtained from 21 donors, harvested during organ donation explant, underwent residual deformation measurements. The intact wall and the three separated layers were tested in both directions, resulting in 8 tests per donor, which gives a relevant set of experimental data for further studies. Results show significant residual deformations both in circumferential and longitudinal directions, which are compatible with a significantly compressed intima in the unloaded aorta. In particular, the measured mean effective curvature was -0.193 ± 0.064 (1/mm) for the circumferential strips and -0.076 ± 0.030 (1/mm) for longitudinal strips of the full wall. The effects of age and gender were also investigated.

Impact of residual stress on coronary plaque stress/strain calculations using optical coherence tomography image-based multi-layer models

Introduction

Mechanical stress and strain conditions play an important role in atherosclerosis plaque progression, remodeling and potential rupture and may be used in plaque vulnerability assessment for better clinical diagnosis and treatment decisions. Single layer plaque models without residual stress have been widely used due to unavailability of multi-layer image segmentation method and residual stress data. However, vessel layered structure and residual stress have large impact on stress/strain calculations and should be included in the models.

Methods

In this study, intravascular optical coherence tomography (OCT) data of coronary plaques from 10 patients were acquired and segmented to obtain the three-layer vessel structure using an in-house automatic segmentation algorithm. Multi- and single-layer 3D thin-slice biomechanical plaque models with and without residual stress were constructed to assess the impact of residual stress on stress/strain calculations.

Results

Our results showed that residual stress led to a more uniform stress distribution across the vessel wall, with considerable plaque stress/strain decrease on inner wall and increase on vessel out-wall. Multi-layer model with residual stress inclusion reduced inner wall maximum and mean plaque stresses by 38.57% and 59.70%, and increased out-wall maximum and mean plaque stresses by 572.84% and 432.03%.

Conclusion

These findings demonstrated the importance of multi-layer modeling with residual stress for more accurate plaque stress/strain calculations, which will have great impact in plaque cap stress calculation and plaque rupture risk assessment. Further large-scale studies are needed to validate our findings.

Regional biomechanical characterization of human ascending aortic aneurysms: Microstructure and biaxial mechanical response

The ascending thoracic aortic aneurysm (ATAA) is a permanent dilatation of the vessel with a high risk of adverse events, and shows heterogeneous properties. To investigate regional differences in the biomechanical properties of ATAAs, tissue samples were collected from 10 patients with tricuspid aortic valve phenotype and specimens from minor, anterior, major, and posterior regions were subjected to multi-ratio planar biaxial extension tests and second-harmonic generation (SHG) imaging. Using the data, parameters of a microstructure-motivated constitutive model were obtained considering fiber dispersion. SHG imaging showed disruptions in the organization of the layers. Structural and material parameters did not differ significantly between regions. The non-symmetric fiber dispersion model proposed by Holzapfel et al. [25] was used to fit the data. The mean angle of collagen fibers was negatively correlated between minor and anterior regions, and the parameter associated with collagen fiber stiffness was positively correlated between minor and major regions. Furthermore, correlations were found between the stiffness of the ground matrix and the mean fiber angle, and between the parameter associated with the collagen fiber stiffness and the out-of-plane dispersion parameter in the posterior and minor regions, respectively. The experimental data collected in this study contribute to the biomechanical data available in the literature on human ATAAs. Region-specific parameters for the constitutive models are fundamental to improve the current risk stratification strategies, which are mainly based on aortic size. Such investigations can facilitate the development of more advanced finite element models capable of capturing the regional heterogeneity of pathological tissues. STATEMENT OF SIGNIFICANCE: Tissue samples of human ascending thoracic aortic aneurysms (ATAA) were collected. Samples from four regions underwent multi-ratio planar biaxial extension tests and second-harmonic generation imaging. Region-specific parameters of a microstructure-motivated model considering fiber dispersion were obtained. Structural and material parameters did not differ significantly between regions, however, the mean fiber angle was negatively correlated between minor and anterior regions, and the parameter associated with collagen fiber stiffness was positively correlated between minor and major regions. Furthermore, correlations were found between the stiffness of the ground matrix and the mean fiber angle, and between the parameter associated with the collagen fiber stiffness and the out-of-plane dispersion parameter in the posterior and minor regions, respectively. This study provides a unique set of mechanical and structural data, supporting the microstructural influence on the tissue response. It may facilitate the development of better finite element models capable of capturing the regional tissue heterogeneity.

An updated Lagrangian constrained mixture model of pathological cardiac growth and remodelling

Progressive left ventricular (LV) growth and remodelling (G&R) is often induced by volume and pressure overload, characterized by structural and functional adaptation through myocyte hypertrophy and extracellular matrix remodelling, which are dynamically regulated by biomechanical factors, inflammation, neurohormonal pathways, etc. When prolonged, it can eventually lead to irreversible heart failure. In this study, we have developed a new framework for modelling pathological cardiac G&R based on constrained mixture theory using an updated reference configuration, which is triggered by altered biomechanical factors to restore biomechanical homeostasis. Eccentric and concentric growth, and their combination have been explored in a patient-specific human LV model under volume and pressure overload. Eccentric growth is triggered by overstretching of myofibres due to volume overload, i.e. mitral regurgitation, whilst concentric growth is driven by excessive contractile stress due to pressure overload, i.e. aortic stenosis. Different biological constituent's adaptations under pathological conditions are integrated together, which are the ground matrix, myofibres and collagen network. We have shown that this constrained mixture-motivated G&R model can capture different phenotypes of maladaptive LV G&R, such as chamber dilation and wall thinning under volume overload, wall thickening under pressure overload, and more complex patterns under both pressure and volume overload. We have further demonstrated how collagen G&R would affect LV structural and functional adaption by providing mechanistic insight on anti-fibrotic interventions. This updated Lagrangian constrained mixture based myocardial G&R model has the potential to understand the turnover processes of myocytes and collagen due to altered local mechanical stimuli in heart diseases, and in providing mechanistic links between biomechanical factors and biological adaption at both the organ and cellular levels. Once calibrated with patient data, it can be used for assessing heart failure risk and designing optimal treatment therapies. STATEMENT OF SIGNIFICANCE: Computational modelling of cardiac G&R has shown high promise to provide insight into heart disease management when mechanistic understandings are quantified between biomechanical factors and underlying cellular adaptation processes. The kinematic growth theory has been dominantly used to phenomenologically describe the biological G&R process but neglecting underlying cellular mechanisms. We have developed a constrained mixture based G&R model with updated reference by taking into account different mechanobiological processes in the ground matrix, myocytes and collagen fibres. This G&R model can serve as a basis for developing more advanced myocardial G&R models further informed by patient data to assess heart failure risk, predict disease progression, select the optimal treatment by hypothesis testing, and eventually towards a truly precision cardiology using in-silico models.

A review on the biomechanical behaviour of the aorta

Large aortic aneurysm and acute and chronic aortic dissection are pathologies of the aorta requiring surgery. Recent advances in medical intervention have improved patient outcomes; however, a clear understanding of the mechanisms leading to aortic failure and, hence, a better understanding of failure risk, is still missing. Biomechanical analysis of the aorta could provide insights into the development and progression of aortic abnormalities, giving clinicians a powerful tool in risk stratification. The complexity of the aortic system presents significant challenges for a biomechanical study and requires various approaches to analyse the aorta. To address this, here we present a holistic review of the biomechanical studies of the aorta by categorising articles into four broad approaches, namely theoretical, in vivo, experimental and combined investigations. Experimental studies that focus on identifying mechanical properties of the aortic tissue are also included. By reviewing the literature and discussing drawbacks, limitations and future challenges in each area, we hope to present a more complete picture of the state-of-the-art of aortic biomechanics to stimulate research on critical topics. Combining experimental modalities and computational approaches could lead to more comprehensive results in risk prediction for the aortic system.

A novel constitutive model considering the role of elastic lamellae' structural heterogeneity in homogenizing transmural stress distribution in arteries

Understanding how the homeostatic stress state can be reached in arterial tissues can provide new insights into vascular physiology. Even though the function of maintaining homeostasis is often linked to the concentric layers of medial elastic lamellae, how the lamellae are capable of evenly distributing the stress transmurally remains to be understood. The recent microstructural study by Yu et al. (2018 J. R. Soc. Interface 15, 20180492) revealed that, circumferentially, lamellar layers closer to the lumen are wavier than the ones further away from it and, thus, experience more unfolding when subjected to blood pressure. Motivated by this peculiar finding, the current study, for the first time, proposes a novel approach to model elastic lamellae and such structural heterogeneity using the extensible worm-like chain model. When implemented into the material description of the conventional two-layer artery model, in which adventitial collagen is modelled using the inextensible worm-like chain model, it is demonstrated that structural heterogeneity in elastic lamellae plays an important role in dictating transmural stress distribution and, therefore, the homeostasis of the arterial wall.

A review of the characterizations of soft tissues used in human body modeling: Scope, limitations, and the path forward

Soft tissue material properties are vital to human body models that evaluate interactions between the human body and its environment. Such models evaluate internal stress/strain responses in soft tissues to investigate issues like pressure injuries. Numerous constitutive models and parameters have been used to represent mechanical behavior of soft tissues in biomechanical models under quasi-static loading. However, researchers reported that generic material properties cannot accurately represent specific target populations due to large inter-individual variability. Two challenges that exist are experimental mechanical characterization and constitutive modeling of biological soft tissues and personalization of constitutive parameters using non-invasive, non-destructive bedside testing methods. It is imperative to understand the scope and appropriate applications for reported material properties. Thus, the goal of this paper was to compile studies from which soft tissue material properties were obtained and categorize them by source of tissue samples, methods used to quantify deformation, and material models used to describe tissues. The collected studies displayed wide ranges of material properties, and factors that affected the properties included whether tissue samples were in vivo or ex vivo, from humans or animals, the body region tested, body position during in vivo studies, deformation measurements, and material models used to describe tissues. Because of the factors that affected reported material properties, it is clear that much progress has been made in understanding soft tissue responses to loading, yet there is a need to broaden the scope of reported soft tissue material properties and better match reported properties to appropriate human body models.

Fitting mechanical properties of the aortic wall and individual layers to experimental tensile tests including residual stresses

The authors have observed that a stress-strain curve for uniaxial tension of an aortic intact wall cannot be simply obtained by combining the strain energy functions of the three individual aortic layers - intima, media and adventitia - even taking into account the interaction among the three layers; the strain energy functions of the three layers are obtained fitting tensile tests on strips from the individual layers. Due to the layer separation, the residual stresses are released and thus they do not affect the stress-strain curves of the individual layers. The present study shows that it is instead possible to fit the intact wall experimental curves with the combination of the strain energy functions of the three individual layers if residual strains are added. The residual strains are used as optimization parameters with specific constraints and allowing for the buckling (wrinkling) of the intima under unpressurized condition of the aortic wall, as experimentally observed. By varying these parameters in the experimentally observed range of values, it is possible to find a solution with the combined responses of the individual layers matching the experimental stress-strain curves of the intact wall.

Residual strains in ascending thoracic aortic aneurysms: The effect of valve type, layer, and circumferential quadrant

The stress distribution in ascending thoracic aortic aneurysms is determined by the mechanical properties, geometry, loading conditions, and zero-stress state of the aneurysmal aorta. Our objective was to fully characterize the zero-stress state of the aneurysmal aorta in twelve tricuspid aortic valve patients and eight (age/aortic diameter-matched) bicuspid aortic valve patients, for which little data are available. Opening angles and residual stretches were measured for the intact wall and individual layers according to quadrant and were similar in the two patient groups. The intact-wall and medial opening angles were comparable; their circumferential but not their axial ones peaked in the left lateral quadrant, with non-significant regional differences in the other layers. The intima's circumferential opening angles were the highest of all layers (∼300 deg) and the adventitia's the lowest (∼165 deg), with lesser layer differences in the axial opening angles. Upon radially cutting aortic rings, the released circumferential residual stretches were tensile (of large magnitude) externally and compressive (of small magnitude) internally, unlike the axial residual stretches released when cutting intact-wall strips, whose magnitude was small externally and large internally. Nevertheless, large circumferential compressive residual stretches were released in the adventitia upon layer dissection, counteracting the large circumferential tensile stretches of the intact wall externally. Moreover, the large axial tensile residual stretches of the intima counteracted the large axial compressive stretches of the intact wall internally. These layer-specific residual stretches may moderate the in-vivo stress gradients across wall thickness, serving as a protective mechanism against aortic dissection or rupture.

Inverse material parameter estimation of patient-specific finite element models at the carotid bifurcation: The impact of excluding the zero-pressure configuration and residual stress

The carotid bifurcation experiences a complex loading environment due to its anatomical structure. Previous in-vivo material parameter estimation methods often use simplified model geometries, isotropic hyperelastic constitutive equations or neglect key aspects of the vessel, such as the zero-pressure configuration or residual stress, all of which have independently been shown to alter the stress environment of the vessel wall. Characterizing the location of high stress in the vessel wall has often been proposed as a potential indicator of structural weakness. However, excluding the afore-mentioned zero-pressure configuration, residual stress and patient-specific material parameters can lead to an incorrect estimation of the true stress values observed, meaning that stress alone as a risk indicator of rupture is insufficient. In this study, we investigate how the estimated material parameters and overall stress distributions in geometries of carotid bifurcations, extracted from in-vivo MR images, alter with the inclusion of the zero-pressure configuration and residual stress. This approach consists of the following steps: (1) geometry segmentation and hexahedral meshing from in-vivo magnetic resonance images (MRI) at two known phases; (2) computation of the zero-pressure configuration and the associated residual stresses; (3) minimization of an objective function built on the difference between the stress states of an "almost true" stress field at two known phases and a "deformed" stress field by altering the input material parameters to determine patient-specific material properties; and (4) comparison of the stress distributions throughout these carotid bifurcations for all cases with estimated material parameters. This numerical approach provides insights into the need for estimation of both the zero-pressure configuration and residual stress for accurate material property estimation and stress analysis for the carotid bifurcation, establishing the reliability of stress as a rupture risk metric.

The Role of Layer-Specific Residual Stresses in Arterial Mechanics: Analysis via a Novel Modelling Framework

The existence of residual stresses in unloaded arteries has long been known. However, their effect is often neglected in experimental studies. Using a recently developed modelling framework, we aimed to investigate the role of residual stresses in the mechanical behaviour of the tri-layered wall of the pig thoracic aorta. The mechanical behaviour of the intact wall and isolated layers of n = 3 pig thoracic aortas was investigated via uniaxial tensile testing. After modelling the layer-specific mechanical data using a hyperelastic strain energy function, the layer-specific deformations in the unloaded vessel were estimated so that the mechanical response of the computationally assembled tri-layered flat wall would match that measured experimentally. Physiological tension–inflation of the cylindrical tri-layered vessel was then simulated, analysing changes in the distribution of stresses in the three layers when neglecting residual stresses. In the tri-layered model with residual stresses, layers exhibited comparable stresses throughout the physiological range of pressure. At 100 mmHg, intimal, medial, and adventitial circumferential load bearings were 16 $$\pm$$ ±  3%, 59 $$\pm$$ ± 4%, and 25 $$\pm$$ ± 2%, respectively. Adventitial stiffening at high pressures produced a shift in load bearing from the media to the adventitia. When neglecting residual stresses, in vivo stresses were highest at the intima and lowest at the adventitia. Consequently, the intimal and adventitial load bearings, 23 $$\pm$$ ± 2% and 18 $$\pm$$ ± 3% at 100 mmHg, were comparable at all pressures. Residual stresses play a crucial role in arterial mechanics guaranteeing a uniform distribution of stresses through the wall thickness. Neglecting these leads to incorrect interpretation of the layers’ role in arterial mechanics.

Toward Elucidating the Physiological Impacts of Residual Stresses in the Colorectum

Irritable bowel syndrome afflicts 10-20% of the global population, causing visceral pain with increased sensitivity to colorectal distension and normal bowel movements. Understanding and predicting these biomechanics will further advance our understanding of visceral pain and complement the existing literature on visceral neurophysiology. We recently performed a series of experiments at three longitudinal segments (colonic, intermediate, and rectal) of the distal 30 mm of colorectums of mice. We also established and fitted constitutive models addressing mechanical heterogeneity in both the through-thickness and longitudinal directions of the colorectum. Afferent nerve endings, strategically located within the submucosa, are likely nociceptors that detect concentrations of mechanical stresses to evoke the perception of pain from the viscera. In this study, we aim to: (1) establish and validate a method for incorporating residual stresses into models of colorectums, (2) predict the effects of residual stresses on the intratissue mechanics within the colorectum, and (3) establish intratissue distributions of stretches and stresses within the colorectum in vivo. To these ends we developed two-layered, composite finite element models of the colorectum based on our experimental evidence and validated our approaches against independent experimental data. We included layer- and segment-specific residual stretches/stresses in our simulations via the prestrain algorithm built into the finite element software febio. Our models and modeling approaches allow researchers to predict both organ and intratissue biomechanics of the colorectum and may facilitate better understanding of the underlying mechanical mechanisms of visceral pain.

Finite element analysis in clinical patients with atherosclerosis

Endovascular plaque composition is strongly related to stent strut stress and is responsible for strut fatigue, stent failure, and possible in-stent restenosis. To evaluate the effect of plaque on artery wall resistance to expansion we performed in silico analysis of atherosclerotic vessels. We generated finite element models from in vivo intravascular ultrasound virtual histology images to determine local artery surface stiffness and determined which plaque structures have the greatest influence. We validated the predictive capacity of our modeling approach by testing an atherosclerotic peripheral artery ex vivo with pressure-inflation testing at physiological pressures ranging from 10 to 200 mmHg. For this purpose, the in silico deformation of the arterial wall was compared to that observed ex vivo. We found that calcification had a positive effect on surface stiffness with fibrous plaque and necrotic core having negative effects. Additionally, larger plaque structures demonstrated significantly higher average surface stiffness and calcification located nearer the lumen was also shown to increase surface stiffness. Therefore, more developed plaques will have greater resistance to expansion and higher stent strut stress, with calcification located near the lumen further increasing stress in localized areas. Thus, it may be expected that such plaque structures may increase the likelihood of localized stent strut fracture.

A novel framework for quantifying the subject-specific three-dimensional residual stress field in the aortic wall

BACKGROUND

Quantification of subject-specific residual stress field remains a challenge that prohibits accurate stress analysis and refined understanding of the biomechanical behavior of the aortic wall.

METHOD

This study presents a framework combining experiments, constitutive modeling, and computer simulation to quantify the subject-specific three-dimensional residual stress field of the aortic wall. The material properties and residual deformations were acquired from the same porcine aortic sample, so that the subject-specific residual stress field was quantified analytically. Consequently, a novel stress-driven tissue growth model was developed and incorporated in a finite element aortic model to recover the subject-specific residual stress with the help of analytical solution. We then evaluated the framework's efficacy by simulating the residual stress distribution in the aortic dissection (AD).

RESULT

Subject-specific residual stress field of the aortic sample was quantified analytically. No appreciable discrepancy was observed between the numerically simulated and analytically derived residual stress distributions, indicating the effectiveness of the tissue growth model. Errors arising from the numerically simulated circumferential opening angle and axial bending angle were within 5% relative to experimental results, highlighting that the framework was accurate in terms of subject-specific residual stress estimation. Finally, numerical simulations recovered the buckling behavior of the intimal flap of the dissected aorta and revealed the expansion of the false lumen and compression of the true lumen as the tear propagates circumferentially.

CONCLUSION

The proposed framework is effective in quantifying the three-dimensional subject-specific residual stress field and it is potentially applicable in more sophisticated scenarios involving residual stress.

Computation of a probabilistic and anisotropic failure metric on the aortic wall using a machine learning-based surrogate model

Scalar-valued failure metrics are commonly used to assess the risk of aortic aneurysm rupture and dissection, which occurs under hypertensive blood pressures brought on by extreme emotional or physical stress. To compute failure metrics under an elevated blood pressure, a classical patient-specific computer model consists of multiple computation steps involving inverse and forward analyses. These classical procedures may be impractical for time-sensitive clinical applications that require prompt feedback to clinicians. In this study, we developed a machine learning-based surrogate model to directly predict a probabilistic and anisotropic failure metric, namely failure probability (FP), on the aortic wall using aorta geometries at the systolic and diastolic phases. Ascending thoracic aortic aneurysm (ATAA) geometries of 60 patients were obtained from their CT scans, and biaxial mechanical testing data of ATAA tissues from 79 patients were collected. Finite element simulations were used to generate datasets for training, validation, and testing of the ML-surrogate model. The testing results demonstrated that the ML-surrogate can compute the maximum FP failure metric, with 0.42% normalized mean absolute error, in 1 s. To compare the performance of the ML-predicted probabilistic FP metric with other isotropic or deterministic metrics, a numerical case study was performed using synthetic "baseline" data. Our results showed that the probabilistic FP metric had more discriminative power than the deterministic Tsai-Hill metric, isotropic maximum principal stress, and aortic diameter criterion.

Multi-patient study for coronary vulnerable plaque model comparisons: 2D/3D and fluid-structure interaction simulations

Several image-based computational models have been used to perform mechanical analysis for atherosclerotic plaque progression and vulnerability investigations. However, differences of computational predictions from those models have not been quantified at multi-patient level. In vivo intravascular ultrasound (IVUS) coronary plaque data were acquired from seven patients. Seven 2D/3D models with/without circumferential shrink, cyclic bending and fluid–structure interactions (FSI) were constructed for the seven patients to perform model comparisons and quantify impact of 2D simplification, circumferential shrink, FSI and cyclic bending plaque wall stress/strain (PWS/PWSn) and flow shear stress (FSS) calculations. PWS/PWSn and FSS averages from seven patients (388 slices for 2D and 3D thin-layer models) were used for comparison. Compared to 2D models with shrink process, 2D models without shrink process overestimated PWS by 17.26%. PWS change at location with greatest curvature change from 3D FSI models with/without cyclic bending varied from 15.07% to 49.52% for the seven patients (average = 30.13%). Mean Max-FSS, Min-FSS and Ave-FSS from the flow-only models under maximum pressure condition were 4.02%, 11.29% and 5.45% higher than those from full FSI models with cycle bending, respectively. Mean PWS and PWSn differences between FSI and structure-only models were only 4.38% and 1.78%. Model differences had noticeable patient variations. FSI and flow-only model differences were greater for minimum FSS predictions, notable since low FSS is known to be related to plaque progression. Structure-only models could provide PWS/PWSn calculations as good approximations to FSI models for simplicity and time savings in calculation.

Evaluation of the role of peripheral artery plaque geometry and composition on stent performance

Peripheral stent fracture is a major precursor to restenosis of femoral artery atherosclerosis that has been treated with stent implantation. In this work, we validate a workflow for performing in silico stenting on a patient specific peripheral artery with heterogeneous plaque structure. Six human cadaveric femoral arteries were imaged ex vivo using intravascular ultrasound virtual histology (IVUS-VH) to obtain baseline vessel geometry and plaque structure. The vessels were then stented and the imaging repeated to obtain the stented vessel lumen area. Finite element (FE) models were then constructed using the IVUS-VH images, where the material property constants for each finite element were calculated using the proportions of each plaque component in the element, as identified by the IVUS-VH images. A virtual stent was deployed in each FE model, and the model lumen area was calculated and compared to the experimental lumen area to validate the modeling approach. The model was then used to compare stent performance for heterogeneous and homogeneous artery models, to determine whether plaque geometry or composition had added effects on stent performance. We found that the simulated lumen areas were similar to the corresponding experimental values, despite using generic material constants. Additionally, the heterogeneous and homogeneous lumen areas were also similar, implying that plaque geometry is a stronger predictor of stent expansion performance than plaque composition. Comparing stent stress and strain for heterogeneous and homogeneous models, it was found that stress from these two models had a strong linear correlation, while the strain correlation was weaker but still present. This implies that stent performance may be predicted with a simple homogeneous material models accounting for overall geometry of the plaque, providing that stent fatigue is calculated using stress criteria.

A backward pre-stressing algorithm for efficient finite element implementation of in vivo material and geometrical parameters into fibril-reinforced mixture models of articular cartilage

Classical continuum mechanics has been widely used for implementation of the material models of articular cartilage (AC) mainly with the aid of the finite element (FE) method, which, in many cases, considers the stress-free configuration as the initial configuration. On the contrary, the AC experimental tests typically begin with the pre-stressed state of both material and geometrical properties. Indeed, imposing the initial pre-stress onto AC models with the in vivo values as the initial state would result in nonphysiologically expansion of the FE mesh due to the soft nature of AC. This change in the model configuration can also affect the material behavior kinematically in the mixture models of cartilage due to the intrinsic compressibility of the tissue. Although several different fixed-point backward algorithms, as the most straightforward pre-stressing methods, have already been developed to incorporate these initial conditions into FE models iteratively, such methods focused merely on the geometrical parameters, and they omitted the material variations of the anisotropic mixture models of AC. To address this issue, we propose an efficient algorithm generalizing the backward schemes to restore stress-free conditions by optimizing both the involving variables, and we hypothesize that it can affect the results considerably. To this end, a comparative simulation was implemented on an advanced and validated multiphasic model by the new and conventional algorithms. The results are in support of the hypothesis, as in our illustrative general AC model, the material parameters experienced a maximum error of 16% comparing to the initial in vivo data when the older algorithm was employed, and it led to a maximum variation of 44% in the recorded stresses comparing to the results of the new method. We conclude that our methodology enhanced the model fidelity, and it is applicable in most of the existing FE solvers for future mixture studies with accurate stress distributions.

Reconstructing vascular homeostasis by growth-based prestretch and optimal fiber deposition

Computational modeling of cardiovascular biomechanics should generally start from a homeostatic state. This is particularly relevant for image-based modeling, where the reference configuration is the loaded in vivo state obtained from imaging. This state includes residual stress of the vascular constituents, as well as anisotropy from the spatially varying orientation of collagen and smooth muscle fibers. Estimation of the residual stress and fiber orientation fields is a formidable challenge in realistic applications. To help address this challenge, we herein develop a growth based Algorithm to recover a residual stress distribution in vascular domains such that the stress state in the loaded configuration is equal to a prescribed homeostatic stress distribution at physiologic pressure. A stress-driven fiber deposition process is included in the framework, which defines the distribution of the fiber alignments in the vascular homeostatic state based on a minimization procedure. Numerical simulations are conducted to test this two-stage homeostasis generation algorithm in both idealized and non-idealized geometries, yielding results that agree favorably with prior numerical and experimental data.

On the importance of tunica intima in the aging aorta: a three-layered in silico model for computing wall stresses in abdominal aortic aneurysms

Layer-specific experimental data for human aortic tissue suggest that, in aged arteries and arteries with non-atherosclerotic intimal thickening, the innermost layer of the aorta increases significantly its stiffness and thickness, becoming load-bearing. However, there are very few computational studies of abdominal aortic aneurysms (AAAs) that take into account the mechanical contribution of the three layers that comprise the aneurysmal tissue. In this paper, a three-layered finite element model is proposed from the simplest uniaxial stress state to geometrically parametrized models of AAAs with different asymmetry values. Comparisons are made between a three-layered artery wall and a mono-layered intact artery, which represents the complex behavior of the aggregate adventitia-media-intima in a single layer with averaged mechanical properties. Likewise, the response of our idealized geometries is compared with similar experimental and numerical models. Finally, the mechanical contributions of adventitia, media and intima are analyzed for the three-layered aneurysms through the evaluation of the mean stress absorption percentage. Results show the relevance and necessity of considering the inclusion of tunica intima in multi-layered models of AAAs for getting accurate results in terms of peak wall stresses and displacements.

A COUPLED EXPERIMENTAL AND NUMERICAL APPROACH TO CHARACTERIZE THE ANISOTROPIC MECHANICAL BEHAVIOR OF AORTIC TISSUES

Nowadays, the investigation of aortic wall biomechanics is a fundamental tool in clinical research and vascular prosthesis design. This study aims at analyzing the biomechanical behavior of aortic tissues using a coupled experimental and computational approach. Considering the typical fiber-reinforced configuration of aortic tissues, uni-axial tensile tests along six different loading directions were performed on specimens from pig aorta. Starting from the obtained experimental data, a suitable constitutive framework was defined and a methodology for the identification of the constitutive parameters was developed using the inverse analysis of mechanical tests. Transversal stretch versus loading stretch and nominal stress versus loading stretch curves were evaluated, showing the anisotropic and nonlinear mechanical behavior determined by tissue conformation with fibers distributed along preferential directions. In detail, experimental data showed different mechanical responses between longitudinal and circumferential directions, with a greater tissue stiffness along the longitudinal one. The reliability of the developed constitutive framework was evaluated by the comparison between experimental data and model results. The mentioned analysis can be considered as a useful tool for the development of reliable computational models, which allow a better understanding of the pathophysiology of cardiovascular diseases and can be applied for a proper planning of surgical procedures.

On the Relative Impact of Intraluminal Thrombus Heterogeneity on Abdominal Aortic Aneurysm Mechanics

Intraluminal thrombus (ILT) is present in the majority of abdominal aortic aneurysms (AAA) of a size warranting consideration for surgical or endovascular intervention. The rupture risk of AAAs is thought to be related to the balance of vessel wall strength and the mechanical stress caused by systemic blood pressure. Previous finite element analyses of AAAs have shown that ILT can reduce and homogenize aneurysm wall stress. These works have largely considered ILT to be homogeneous in mechanical character or have idealized a stiffness distribution through the thrombus thickness. In this work, we use magnetic resonance imaging (MRI) to delineate the heterogeneous composition of ILT in 7 AAAs and perform patient-specific finite element analysis under multiple conditions of ILT layer stiffness disparity. We find that explicit incorporation of ILT heterogeneity in the finite element analysis is unlikely to substantially alter major stress analysis predictions regarding aneurysm rupture risk in comparison to models assuming a homogenous thrombus, provided that the maximal ILT stiffness is the same between models. Our results also show that under a homogeneous ILT assumption, the choice of ILT stiffness from values common in the literature can result in significantly larger variations in stress predictions compared to the effects of thrombus heterogeneity.

Patient specific characterization of artery and plaque material properties in peripheral artery disease

Patient-specific finite element (FE) modeling of atherosclerotic plaque is challenging, as there is limited information available clinically to characterize plaque components. This study proposes that for the limited data available in vivo, material properties of plaque and artery can be identified using inverse FE analysis and either a simple neo-Hookean constitutive model or assuming linear elasticity provides sufficient accuracy to capture the changes in vessel deformation, which is the available clinical metric. To test this, 10 human cadaveric femoral arteries were each pressurized ex vivo at 6 pressure levels, while intravascular ultrasound (IVUS) and virtual histology (VH) imaging were performed during controlled pull-back to determine vessel geometry and plaque structure. The VH images were then utilized to construct FE models with heterogeneous material properties corresponding to the vessel plaque components. The constitutive models were then fit to each plaque component by minimizing the difference between the experimental and the simulated geometry using the inverse FE method. Additionally, we further simplified the analysis by assuming the vessel wall had a homogeneous structure, i.e. lumping artery and plaque as one tissue. We found that for the heterogeneous wall structure, the simulated and experimental vessel geometries compared well when the fitted neo-Hookean parameters or elastic modulus, in the case of linear elasticity, were utilized. Furthermore, taking the median of these fitted parameters then inputting these as plaque component mechanical properties in the finite element simulation yielded differences between simulated and experimental geometries that were on average around 2% greater (1.30-5.55% error range to 2.33-11.71% error range). For the homogeneous wall structure the simulated and experimental wall geometries had an average difference of around 4% although when the difference was calculated using the median fitted value this difference was larger than for the heterogeneous fits. Finally, comparison to uniaxial tension data and to literature constitutive models also gave confidence to the suitability of this simplified approach for patient-specific arterial simulation based on data that may be acquired in the clinic.

Comparative study of variations in mechanical stress and strain of human blood vessels: mechanical reference for vascular cell mechano-biology

The diseases of human blood vessels are closely associated with local mechanical variations. A better understanding of the quantitative correlation in mechanical environment between the current mechano-biological studies and vascular physiological or pathological conditions in vivo is crucial for evaluating numerous existing results and exploring new factors for disease discovery. In this study, six representative human blood vessels with known experimental measurements were selected, and their stress and strain variations in vessel walls under different blood pressures were analyzed based on nonlinear elastic theory. The results suggest that conventional mechano-biological experiments seeking the different biological expressions of cells at high/low mechanical loadings are ambiguous as references for studying vascular diseases, because distinct "site-specific" characteristics appear in different vessels. The present results demonstrate that the inner surface of the vessel wall does not always suffer the most severe stretch under high blood pressures comparing to the outer surface. Higher tension on the outer surface of aortas supports the hypothesis of the outside-in inflammation dominated by aortic adventitial fibroblasts. These results indicate that cellular studies at different mechanical niches should be "disease-specific" as well. The present results demonstrate considerable stress gradients across the wall thickness, which indicate micro-scale mechanical variations existing around the vascular cells, and imply that the physiological or pathological changes are not static processes confined within isolated regions, but are coupled with dynamic cell behaviors such as migration. The results suggest that the stress gradients, as well as the mechanical stresses and strains, are key factors constituting the mechanical niches, which may shed new light on "factor-specific" experiments of vascular cell mechano-biology.

A deep learning approach to estimate stress distribution: a fast and accurate surrogate of finite-element analysis

Structural finite-element analysis (FEA) has been widely used to study the biomechanics of human tissues and organs, as well as tissue-medical device interactions, and treatment strategies. However, patient-specific FEA models usually require complex procedures to set up and long computing times to obtain final simulation results, preventing prompt feedback to clinicians in time-sensitive clinical applications. In this study, by using machine learning techniques, we developed a deep learning (DL) model to directly estimate the stress distributions of the aorta. The DL model was designed and trained to take the input of FEA and directly output the aortic wall stress distributions, bypassing the FEA calculation process. The trained DL model is capable of predicting the stress distributions with average errors of 0.492% and 0.891% in the Von Mises stress distribution and peak Von Mises stress, respectively. This study marks, to our knowledge, the first study that demonstrates the feasibility and great potential of using the DL technique as a fast and accurate surrogate of FEA for stress analysis.

Estimation of in vivo constitutive parameters of the aortic wall using a machine learning approach

The patient-specific biomechanical analysis of the aorta requires the quantification of the in vivo mechanical properties of individual patients. Current inverse approaches have attempted to estimate the nonlinear, anisotropic material parameters from in vivo image data using certain optimization schemes. However, since such inverse methods are dependent on iterative nonlinear optimization, these methods are highly computation-intensive. A potential paradigm-changing solution to the bottleneck associated with patient-specific computational modeling is to incorporate machine learning (ML) algorithms to expedite the procedure of in vivo material parameter identification. In this paper, we developed an ML-based approach to estimate the material parameters from three-dimensional aorta geometries obtained at two different blood pressure (i.e., systolic and diastolic) levels. The nonlinear relationship between the two loaded shapes and the constitutive parameters are established by an ML-model, which was trained and tested using finite element (FE) simulation datasets. Cross-validations were used to adjust the ML-model structure on a training/validation dataset. The accuracy of the ML-model was examined using a testing dataset.

The role of tissue remodeling in mechanics and pathogenesis of abdominal aortic aneurysms

Arterial walls can be regarded as composite materials consisting of collagen fibers embedded in an elastic matrix and smooth muscle cells. Remodeling of the structural proteins has been shown to play a significant role in the mechanical behavior of walls during pathogenesis of abdominal aortic aneurysms (AAA). In this study, we systematically studied the change in the microstructure, histology and mechanics to link them to AAA disease progression. We performed biaxial extension tests, second-harmonic generation imaging and histology on 15 samples from the anterior part of AAA walls harvested during open aneurysm surgery. Structural data were gained by fitting to a bivariate von Mises distribution and yielded the mean fiber direction and in- and out-of-plane fiber dispersions of collagen. Mechanical and structural data were fitted to a recently proposed material model. Additionally, the mechanical data were used to derive collagen recruitment points in the obtained stress-stretch curves. We derived 14 parameters from histology such as smooth muscle cell-, elastin-, and abluminal adipocyte content. In total, 22 parameters were obtained and statistically evaluated. Based on the collagen recruitment points we were able to define three different stages of disease progression. Significant differences in elastin content, collagen orientation and adipocyte contents were discovered. Nerves entrapped inside AAA walls pointed towards a significant deposition of newly formed collagen abluminally, which we propose as neo-adventitia formation. We were able to discriminate two types of remodeled walls with a high collagen content - potentially safe and possibly vulnerable walls with a high adipocyte content inside the wall and significant amounts of inflammation. The study yielded a hypothesis for disease progression, derived from the systematic comparison of mechanical, microstructural and histological changes in AAAs. STATEMENT OF SIGNIFICANCE: Remodeling of the structural proteins plays an important role in the mechanical behavior of walls during pathogenesis of abdominal aortic aneurysms (AAA). We analyzed changes in the microstructure, histology and biomechanics of 15 samples from the anterior part of AAA walls and, for the first time, linked the results to three different stages of disease progression. We identified significant differences in elastin content, collagen orientation, adipocyte contents, and also a deposition of newly formed collagen forming a neoadventitia. We could discriminate two types of remodeled walls: (i) potentially safe and (ii) possibly vulnerable associated with inflammation and a high amount of adipocytes.

Finite element simulation of three dimensional residual stress in the aortic wall using an anisotropic tissue growth model

Residual stress is believed to play a significant role in the in vivo stress state of the arterial wall, but quantifying residual stress in vivo is challenging. Based on the well-known assumptions that residual stress is a result of heterogeneous arterial growth and that it homogenizes the transmural distribution of arterial wall stress, we propose a new anisotropic tissue growth model for the aorta to recover the three-dimensional residual stress field in a bi-layer human aortic wall. Finite element simulations showed that the predicted residual stress magnitude with this method are within the documented range for human aorta. Particularly, the homeostatic inter-layer stress difference is identified as a key parameter to quantify the opening angle. To the authors' knowledge, this is the first finite element study employing anisotropic growth of aortic tissue in a bi-layer model to generate three-dimensional residual stress field, and the resultant opening angle can match with the experiments. A parametric study found that inter-layer stress homogeneity, arterial blood pressure, axial pre-stretch, and material stiffness strongly affect the residual stress field.

On the computation of in vivo transmural mean stress of patient-specific aortic wall

It is well known that residual deformations/stresses alter the mechanical behavior of arteries, e.g., the pressure-diameter curves. In an effort to enable personalized analysis of the aortic wall stress, approaches have been developed to incorporate experimentally derived residual deformations into in vivo loaded geometries in finite element simulations using thick-walled models. Solid elements are typically used to account for "bending-like" residual deformations. Yet, the difficulty in obtaining patient-specific residual deformations and material properties has become one of the biggest challenges of these thick-walled models. In thin-walled models, fortunately, static determinacy offers an appealing prospect that allows for the calculation of the thin-walled membrane stress without patient-specific material properties. The membrane stress can be computed using forward analysis by enforcing an extremely stiff material property as penalty treatment, which is referred to as the forward penalty approach. However, thin-walled membrane elements, which have zero bending stiffness, are incompatible with the residual deformations, and therefore, it is often stated as a limitation of thin-walled models. In this paper, by comparing the predicted stresses from thin-walled models and thick-walled models, we demonstrate that the transmural mean stress is approximately the same for the two models and can be readily obtained from in vivo clinical images without knowing the patient-specific material properties and residual deformations. Computation of patient-specific mean stress can be greatly simplified by using the forward penalty approach, which may be clinically valuable.

A machine learning approach as a surrogate of finite element analysis-based inverse method to estimate the zero-pressure geometry of human thoracic aorta

Advances in structural finite element analysis (FEA) and medical imaging have made it possible to investigate the in vivo biomechanics of human organs such as blood vessels, for which organ geometries at the zero-pressure level need to be recovered. Although FEA-based inverse methods are available for zero-pressure geometry estimation, these methods typically require iterative computation, which are time-consuming and may be not suitable for time-sensitive clinical applications. In this study, by using machine learning (ML) techniques, we developed an ML model to estimate the zero-pressure geometry of human thoracic aorta given 2 pressurized geometries of the same patient at 2 different blood pressure levels. For the ML model development, a FEA-based method was used to generate a dataset of aorta geometries of 3125 virtual patients. The ML model, which was trained and tested on the dataset, is capable of recovering zero-pressure geometries consistent with those generated by the FEA-based method. Thus, this study demonstrates the feasibility and great potential of using ML techniques as a fast surrogate of FEA-based inverse methods to recover zero-pressure geometries of human organs.

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.

The influence of fiber dispersion on the mechanical response of aortic tissues in health and disease: a computational study

Changes in the structural components of aortic tissues have been shown to play a significant role in the pathogenesis of aortic degeneration. Therefore, reliable stress analyses require a suitable and meaningful constitutive model that captures micro-structural changes. As recent data show, in-plane and out-of-plane collagen fiber dispersions vary significantly between healthy and aneurysmatic aortic walls. The aim of this study is to computationally investigate the influence of fiber dispersion on the mechanical response of aortic tissues in health and disease. In particular, the influence of three different fiber dispersions is studied: (i) non-rotationally symmetric dispersion, the most realistic assumption for aortic tissues; (ii) transversely isotropic dispersion, a special case; (iii) perfectly aligned fibers (no dispersion in either plane), another special case. Explicit expressions for the stress and elasticity tensors as needed for the implementation in a finite element code are provided. Three representative numerical examples are studied: planar biaxial extension, inflation of residually stressed and pre-stretched aortic segments and inflation of an idealized abdominal aortic aneurysm (AAA) geometry. For the AAA geometry the case of isotropic dispersion is additionally analyzed. Documented structural and mechanical parameters are taken from human aortas (healthy media/adventitia and AAA). The influence of fiber dispersions upon magnitudes and distributions of stresses and deformations are presented and analyzed. Stresses vary significantly, especially in the AAA case, where material stiffening is significantly influenced by fiber dispersion. The results highlight the need to incorporate the structural differences into finite element simulations to obtain more accurate stress predictions. Additionally, results show the capability of one constitutive model to represent different scenarios of aortic micro-structures allowing future studies of collagen reorientation during disease progression.

Effects of Residual Stress, Axial Stretch, and Circumferential Shrinkage on Coronary Plaque Stress and Strain Calculations: A Modeling Study Using IVUS-Based Near-Idealized Geometries

Accurate stress and strain calculations are important for plaque progression and vulnerability assessment. Models based on in vivo data often need to form geometries with zero-stress/strain conditions. The goal of this paper is to use IVUS-based near-idealized geometries and introduce a three-step model construction process to include residual stress, axial shrinkage, and circumferential shrinkage and investigate their impacts on stress and strain calculations. In Vivo intravascular ultrasound (IVUS) data of human coronary were acquired for model construction. In Vivo IVUS movie data were acquired and used to determine patient-specific material parameter values. A three-step modeling procedure was used to make our model: (a) wrap the zero-stress vessel sector to obtain the residual stress; (b) stretch the vessel axially to its length in vivo; and (c) pressurize the vessel to recover its in vivo geometry. Eight models were constructed for our investigation. Wrapping led to reduced lumen and cap stress and increased out boundary stress. The model with axial stretch, circumferential shrink, but no wrapping overestimated lumen and cap stress by 182% and 448%, respectively. The model with wrapping, circumferential shrink, but no axial stretch predicted average lumen stress and cap stress as 0.76 kPa and -15 kPa. The same model with 10% axial stretch had 42.53 kPa lumen stress and 29.0 kPa cap stress, respectively. Skipping circumferential shrinkage leads to overexpansion of the vessel and incorrect stress/strain calculations. Vessel stiffness increase (100%) leads to 75% lumen stress increase and 102% cap stress increase.

Estimation of in vivo mechanical properties of the aortic wall: A multi-resolution direct search approach

The patient-specific biomechanical analysis of the aorta requires in vivo mechanical properties of individual patients. Existing approaches for estimating in vivo material properties often demand high computational cost and mesh correspondence of the aortic wall between different cardiac phases. In this paper, we propose a novel multi-resolution direct search (MRDS) approach for estimation of the nonlinear, anisotropic constitutive parameters of the aortic wall. Based on the finite element (FE) updating scheme, the MRDS approach consists of the following three steps: (1) representing constitutive parameters with multiple resolutions using principal component analysis (PCA), (2) building links between the discretized PCA spaces at different resolutions, and (3) searching the PCA spaces in a 'coarse to fine' fashion following the links. The estimation of material parameters is achieved by minimizing a node-to-surface error function, which does not need mesh correspondence. The method was validated through a numerical experiment by using the in vivo data from a patient with ascending thoracic aortic aneurysm (ATAA), the results show that the number of FE iterations was significantly reduced compared to previous methods. The approach was also applied to the in vivo CT data from an aged healthy human patient, and using the estimated material parameters, the FE-computed geometry was well matched with the image-derived geometry. This novel MRDS approach may facilitate the personalized biomechanical analysis of aortic tissues, such as the rupture risk analysis of ATAA, which requires fast feedback to clinicians.

Microstructure and mechanics of healthy and aneurysmatic abdominal aortas: experimental analysis and modelling

Soft biological tissues such as aortic walls can be viewed as fibrous composites assembled by a ground matrix and embedded families of collagen fibres. Changes in the structural components of aortic walls such as the ground matrix and the embedded families of collagen fibres have been shown to play a significant role in the pathogenesis of aortic degeneration. Hence, there is a need to develop a deeper understanding of the microstructure and the related mechanics of aortic walls. In this study, tissue samples from 17 human abdominal aortas (AA) and from 11 abdominal aortic aneurysms (AAA) are systematically analysed and compared with respect to their structural and mechanical differences. The collagen microstructure is examined by analysing data from second-harmonic generation imaging after optical clearing. Samples from the intact AA wall, their individual layers and the AAA wall are mechanically investigated using biaxial stretching tests. A bivariate von Mises distribution was used to represent the continuous fibre dispersion throughout the entire thickness, and to provide two independent dispersion parameters to be used in a recently proposed material model. Remarkable differences were found between healthy and diseased tissues. The out-of-plane dispersion was significantly higher in AAA when compared with AA tissues, and with the exception of one AAA sample, the characteristic wall structure, as visible in healthy AAs with three distinct layers, could not be identified in AAA samples. The collagen fibres in the abluminal layer of AAAs lost their waviness and exhibited rather straight and thick struts of collagen. A novel set of three structural and three material parameters is provided. With the structural parameters fixed, the material model was fitted to the mechanical experimental data, giving a very satisfying fit although there are only three material parameters involved. The results highlight the need to incorporate the structural differences into finite-element simulations as otherwise simulations of AAA tissues might not be good predictors for the actual in vivo stress state.

A new inverse method for estimation of in vivo mechanical properties of the aortic wall

The aortic wall is always loaded in vivo, which makes it challenging to estimate the material parameters of its nonlinear, anisotropic constitutive equation from in vivo image data. Previous approaches largely relied on either computationally expensive finite element models or simplifications of the geometry or material models. In this study, we investigated a new inverse method based on aortic wall stress computation. This approach consists of the following two steps: (1) computing an "almost true" stress field from the in vivo geometries and loading conditions, (2) building an objective function based on the "almost true" stress fields, constitutive equations and deformation relations, and estimating the material parameters by minimizing the objective function. The method was validated through numerical experiments by using the in vivo data from four ascending aortic aneurysm (AsAA) patients. The results demonstrated that the method is computationally efficient. This novel approach may facilitate the personalized biomechanical analysis of aortic tissues in clinical applications, such as in the rupture risk analysis of ascending aortic aneurysms.

A general framework for application of prestrain to computational models of biological materials

It is often important to include prestress in computational models of biological tissues. The prestress can represent residual stresses (stresses that exist after the tissue is excised from the body) or in situ stresses (stresses that exist in vivo, in the absence of loading). A prestressed reference configuration may also be needed when modeling the reference geometry of biological tissues in vivo. This research developed a general framework for representing prestress in finite element models of biological materials. It is assumed that the material is elastic, allowing the prestress to be represented via a prestrain. For prestrain fields that are not compatible with the reference geometry, the computational framework provides an iterative algorithm for updating the prestrain until equilibrium is satisfied. The iterative framework allows for enforcement of two different constraints: elimination of distortion in order to address the incompatibility issue, and enforcing a specified in situ fiber strain field while allowing for distortion. The framework was implemented as a plugin in FEBio (www.febio.org), making it easy to maintain the software and to extend the framework if needed. Several examples illustrate the application and effectiveness of the approach, including the application of in situ strains to ligaments in the Open Knee model (simtk.org/home/openknee). A novel method for recovering the stress-free configuration from the prestrain deformation gradient is also presented. This general purpose theoretical and computational framework for applying prestrain will allow analysts to overcome the challenges in modeling this important aspect of biological tissue mechanics.

A microstructurally inspired damage model for early venous thrombus

Accumulative damage may be an important contributor to many cases of thrombotic disease progression. Thus, a complete understanding of the pathological role of thrombus requires an understanding of its mechanics and in particular mechanical consequences of damage. In the current study, we introduce a novel microstructurally inspired constitutive model for thrombus that considers a non-uniform distribution of microstructural fibers at various crimp levels and employs one of the distribution parameters to incorporate stretch-driven damage on the microscopic level. To demonstrate its ability to represent the mechanical behavior of thrombus, including a recently reported Mullins type damage phenomenon, we fit our model to uniaxial tensile test data of early venous thrombus. Our model shows an agreement with these data comparable to previous models for damage in elastomers with the added advantages of a microstructural basis and fewer model parameters. We submit that our novel approach marks another important step toward modeling the evolving mechanics of intraluminal thrombus, specifically its damage, and hope it will aid in the study of physiological and pathological thrombotic events.