Hyperelastic modelling of arterial layers with distributed collagen fibre orientations

Computational prediction of Gore Excluder conformable endoprosthesis in the infrarenal aortic neck: results of the ACSSim study

BACKGROUND AND OBJECTIVE

The Gore® Excluder® Conformable (EXCC) device offers a less invasive and less risky alternative to open surgery and complex endovascular repair of abdominal aortic aneurysms for patients with hostile aortic neck anatomies. Indeed, its specific structure has sufficient conformability to prevent proximal sealing complications. Nevertheless, its mechanical behavior is more complex than the one of standard devices, and in complex anatomies, its deployment in the proximal neck of the aortic aneurysm remains difficult to predict. The aim of the present study was to develop and validate a digital twin of EXCC deployment that could accurately predict proximal endoprosthesis sealing.

METHODS

Twenty patients who underwent endovascular aortic aneurysm repair with the EXCC device for complex anatomies in one aortic center were selected. Endoprosthesis deployment in each aorta was simulated by the finite element (FE) method. We compared the positions predicted by the FE simulations with post-operative computed tomography angiography (CTA), focusing on the proximal axis angle, the stent center positions and stent-rings diameters through a principal component analysis.

RESULTS

A successful FE simulation of endoprosthesis deployment could be performed for each of the twenty patients. Relative diameter and vector mean deviations were 4.65 ± 3.85 % and 3.00 ± 1.41 mm, respectively. Axis angle mean deviation was 10.64 ± 5.09°. Outputs show satisfying agreement between numerical simulations and post-operative CTA. Mean proximal apposition was 81.64 ± 11.35 %. Minimal and maximal endoprosthesis appositions were 54.27 % and 95.11 %, respectively.

CONCLUSIONS

The FE model predicted accurately stent-graft positions in 20 patients presenting complex anatomies. High endoprosthesis appositions were observed. This shows the potential of computer simulation to anticipate endoprosthesis proximal sealing complications such as endoleaks and migration before intervention.

A review on finite element modelling of finger and hand mechanical behaviour in haptic interactions

Touch perception largely depends on the mechanical properties of the soft tissues of the glabrous skin of fingers and hands. The correct modelling of the stress-strain state of these tissues during the interaction with external objects can provide insights on the exteroceptual mechanisms of human touch, offering design guidelines for artificial haptic systems. However, devising correct models of the finger and hand at contact is a challenging task, due to the biomechanical complexity of human skin. This work presents an overview of the use of Finite Element analysis for studying the stress-strain state in the glabrous skin of the hand, under different loading conditions. We summarize existing approaches for the design and validation of Finite Element models of the soft tissues of the human finger and hand, evaluating their capability to provide results that are valuable in understanding tactile perception. The goal of our work is to serve as a reference and provide guidelines for those approaching this modelling method for the study of human haptic perception.

Mechanical characterization and constitutive law of porcine urethral tissues: a hyperelastic fiber model based on a physical approach

Lower urinary tract symptoms (LUTS), particularly urinary incontinence (UI), represent a significant global health challenge, affecting millions of patients worldwide. The artificial urinary sphincter (AUS) remains one of the most effective intervention for severe UI, with its design relying on a detailed understanding of the urethral biomechanics. Given the ethical and logistical constraints of using human tissue, porcine urethras, which share anatomical and mechanical similarities with human urethras, are widely employed in preclinical studies. This study investigates the uniaxial mechanical characterization of porcine urethral tissue under controlled conditions. Fresh porcine urethral samples were subjected to uniaxial tensile testing along both the longitudinal and circumferential directions to characterize their anisotropic mechanical properties. Experimental results were compared with existing datasets to validate findings. Additionally, conventional hyperelastic models were assessed to fit experimental results, and a novel anisotropic constitutive model with physical parameters was developed. This fiber model, which incorporates fiber modulus, volume, and orientation, uses a single set of parameters to predict behavior in both directions. It demonstrated improved accuracy, reaching the performance of the Gasser-Ogden-Holzapfel (GOH) model, with root mean square errors (RMSEs) of 9.24% and 12.98% in the circumferential and longitudinal directions, respectively. In contrast, the Yeoh and Ogden models were unable to fit both directions using a single set of parameters, yielding RMSEs values exceeding 30%. With its enhanced physical relevance, the fiber model having a more physical meaning holds promise for applications in the biomechanical analysis of fiber-composed soft tissues.

Assessing changes on large cerebral arteries in CADASIL: Preliminary insights from a case-control analysis

INTRODUCTION

Parent large brain arteries are intimately related to their offspring's small arteries. Whether the CADASIL phenotype is confined to small vessels is unclear, and the involvement of large arteries in CADASIL has not been systematically studied.

METHODS

We conducted a retrospective observational study with patients with CADASIL and randomly selected controls with acute lacunar stroke from the New York-Presbyterian Hospital/Columbia University Irving Medical Center Stroke Registry. We measured the diameters of both groups' basilar artery (BA) and intracranial internal carotid artery (ICA) on T2-weighted images. Z-scores of the arteries were calculated to derive a Brain Arterial Remodeling (BAR) score. We rated cervical ICA tortuosity as 0=no tortuosity, 1 = 45-90° deviation, and 2= >90°. Generalized linear models compared large artery characteristics, adjusting for demographics and clinical variables.

RESULTS

We matched 37 patients with CADASIL with 104 controls. Patients with CADASIL were less likely to be Hispanic/Latino (p < 0.001), hypertensive (p < 0.001), or current smokers (p = 0.02) but more likely to have a prior stroke (p < 0.001) than controls. In adjusted models, patients with CADASIL had larger BA diameters than controls (p = 0.002), but there were no differences in the right and left ICA diameters (p = 0.73, p = 0.88). There was a statistical trend for higher cervical ICA tortuosity in patients with CADASIL compared to controls (p = 0.08).

CONCLUSIONS

Traditionally considered a small-vessel disease, patients with CADASIL have larger BA diameters and possibly higher cervical ICA tortuosity than controls. Whether these changes are part of the NOTCH-3 mutation phenotype or influence the clinical course is uncertain but should be further investigated.

Measuring alignment of structural proteins in engineered tissue constructs using polarized Raman spectroscopy

Measures of structural protein alignment within biological and engineered tissues are needed for improved understanding of their mechanical behavior and functionality. We advance our method of measuring protein alignment using polarized Raman spectroscopy (PRS). It provides a promising alternative to conventional microscopy-based methods as it is non-destructive and allows analysis of extracellular components without additional protein labeling. Previously, we used a machine learning-based alignment metric to compare the extent of alignment between various soft tissues. This study demonstrates that PRS can be successfully used to provide a sensitive measure of alignment in engineered tissues despite the challenges of water-dominated spectra, which have limited prior efforts. A framework for capturing spatial variation of the amplitude and angle of bulk protein alignment was developed. Engineered tissue constructs were generated using collagen type-I solutions seeded with mouse myoblast (C2C12) cells. Tissue alignment was introduced as samples contracted over 12 days of culture. PRS measures of alignment within three selected regions captured a 32% change in extent of alignment and a 30° change in angle between center and corner regions. A computational model was used to bridge between discrete fiber measures of alignment determined with standard immunofluorescence microscopy and our PRS technique. The model applied contraction strains within a hyperelastic continuum to model cell contraction, and model-derived alignment measures showed good agreement between microscopy and PRS measures. Overall, our study provides additional analysis tools for quantifying alignment with PRS and showed the high potential of this PRS technique to non-invasively measure spatial variation within engineered tissues. Such measurement tools are needed to engineer regional alignments aimed at capturing specific mechanical and functional capabilities.

Structure, Mechanics, and Mechanobiology of Fibrocartilage Pericellular Matrix Mediated by Type V Collagen

The pericellular matrix (PCM) is the immediate microniche surrounding cells in various tissues, regulating matrix turnover, cell-matrix interactions, and disease. This study elucidates the structure-mechanical properties and mechanobiology of the PCM in fibrocartilage, using the murine meniscus as the model. The fibrocartilage PCM is comprised of thin, randomly oriented collagen fibrils that entrap proteoglycans, contrasting with the densely packed, highly aligned collagen fibers in the bulk extracellular matrix (ECM). Compared to the ECM, the PCM exhibits lower modulus and greater isotropy, but has similar relative viscoelastic properties. In Col5a1+/- menisci, the reduction of collagen V results in thicker, more heterogeneous collagen fibrils, reduced modulus, loss of isotropy and faster viscoelastic relaxation in the PCM. Such altered PCM leads to impaired matrix-to-cell strain transmission, and in turn, disrupts mechanotransduction of meniscal cells, as illustrated by reduced calcium signaling activities and alters expression of matrix genes. In vitro, Col5a1+/- cells produce a weakened PCM with inferior properties and reduced protection of cells against tensile stretch. These findings highlight the PCM as a distinctive microstructure in fibrocartilage mechanobiology, underscoring a pivotal role of collagen V in PCM function. Targeting the PCM or its constituents offers potential for improving meniscus regeneration, osteoarthritis intervention and broader fibrocartilage-related therapies.

Hemodynamics in aortic dissections: A fluid-solid interaction study in an idealized dissection model with a false lumen side branch

Side-branches (SBs) emanating from the false lumen (FL) in Type-B aortic dissection (TBAD) has been shown to influence patency and FL growth, making FL hemodynamics crucial to understand. This study employs a strongly coupled Fluid-Solid interaction simulation to compare FL hemodynamics in four scenarios: (1) without SB (NSB), (2) single SB in FL (SB_FL), (3) single SB in FL with no re-entry tear (SB_FL_1T), and (4) single SB in true lumen (SB_TL). A pulsatile mass flow is imposed at the inlet, while 3-element windkessel models are applied at the outlets, ensuring equal total vascular resistance for all scenarios. While idealized in terms of geometry, the model incorporates residually stressed, externally supported and anisotropic tissue. Results demonstrate that SB presence leads to higher pressures in both TL and FL during systole, with the highest increase in systolic pressure when the SB emanates from the FL (∼6 mmHg vs ∼3 mmHg for SB_TL). A side branch in the FL reduces FL ejection fraction (FLEF) and leads to higher cycle-averaged transmembrane pressure (TMP¯), which however remains below 1 mmHg for all scenarios. NSB exhibits the highest dissected membrane displacement (∼8 mm), while SB_FL shows the lowest displacement across all planes (∼5.5 mm). These findings suggest that SBs in TBAD affect hemodynamics beyond an altered flow velocity field within the false lumen and, in a setting with maintained mass flow and total vascular resistance, leads to increased TL and FL pressures. The idealized nature of the geometry, however, is to be kept in mind when interpreting our data and extrapolating towards clinical reality.

Investigating the role of structural wall stress on aortic growth prognosis in acute uncomplicated type B aortic dissection

Objective False lumen expansion is a major factor that determines long-term survival of uncomplicated type B aortic dissection (TBAD). The objective of this study was to investigate whether structural wall stress distributions computed from patient-specific acute TBAD geometries can be used to predict aortic growth rates. Methods Three-dimensional (3D) computed tomography angiography (CTA) of 9 patients with acute uncomplicated TBAD were obtained at initial hospital admission and at their most recent follow-up visits. Patient-specific structural wall stress distributions were computed from the initial baseline CTA using a forward penalty method. Spatially varying blood pressure distributions, derived from computational fluid dynamics (CFD) simulations informed by patient-specific transthoracic echocardiography (TTE) and blood pressure (BP) measurements, were incorporated into the forward penalty stress analysis. Aortic growth rates were quantified and visualized within the 3D TBAD geometries using the initial baseline and follow-up scans. Linear mixed-effects regression analyses were performed to evaluate the spatial correlations between biomechanical markers (structural wall stress, wall shear stress, and pressure) and aortic growth rates. Results Utilizing initial baseline CTA, TTE, and BP data, the forward penalty analyses revealed hemodynamic and structural mechanics insights of acute uncomplicated TBADs. The linear mixed-effects model indicated that the fixed-effect association between structural wall stress and aortic growth rate distributions was statistically significant (p=0.039), which demonstrated that aortic segments experiencing high wall stress exhibited rapid growth. Fixed-effect associations were not significant when predicting growth rate using wall shear stress (p=0.86) or pressure (p=0.61) distributions. Significant Pearson correlation coefficients (p<0.05) were observed between structural wall stress and aortic growth rate in all patients. Conclusion High structural wall stress was associated with regions of high aortic growth rates, while false lumen thrombosis was associated with low wall stress. Structural wall stress derived from the forward penalty approach may be a novel predictor of aortic growth rate and failure of optimal medical therapy in acute TBAD.

Sensitivity analysis of the mechanical properties on atherosclerotic arteries rupture risk with an artificial neural network method

Considering the differences between individuals, in this paper, an uncertainty analysis model for predicting rupture risk of atherosclerotic arteries is established based on a back-propagation artificial neural network. The influence of isotropy and anisotropy on the rupture risk of atherosclerotic arteries is analyzed, and the results demonstrate the effectiveness of the artificial neural network in predicting the rupture risk. Moreover, the rupture risk of atherosclerotic arteries at different inflation sizes are simulated. This study contributes to a better understanding of the underlying mechanisms of atherosclerotic arteries rupture and promotes the advancement of artificial neural networks in atherosclerosis research.

Importance of Considering Temporal Variations in Pulse Wave Velocity for Accurate Blood Pressure Prediction

PURPOSE

Continuous, cuffless blood pressure (BP) monitoring devices based on measuring pulse wave velocity (PWV) or pulse transit time (PTT) are emerging but are often plagued by large prediction errors. A key issue is that these techniques typically rely on a single PWV value, assuming a linear response and small arterial wall deformations. However, arterial response to BP is inherently nonlinear, with PWV varying over time [PWV(t)] by up to 50% during a cardiac cycle. This study evaluates the impact of assuming a single PWV on BP prediction accuracy.

METHOD

Using a Fluid-structure Interaction (FSI) testbed, we simulate the radial and common carotid arteries with the Holzapfel-Gasser-Ogden (HGO) constitutive model to capture nonlinear arterial behavior under a pulsatile physiological blood flow. Pressure data from FSI simulation are used as the ground truth, while inner area A(t) and two PWV values, at diastole and systole, serve as inputs to BP prediction models. Two models are tested: one using a single PWV value, emulating existing PWV-based BP prediction methods; another using the two PWV values to account for PWV(t).

RESULTS

The single-PWV BP model produced prediction errors of 17.44 mmHg and 6.57 mmHg for the radial and carotid arteries, respectively. The model incorporating two PWV values reduced these errors by 90.6% and 96.8%, respectively.

CONCLUSION

Relying on a single PWV in BP prediction models can lead to significant errors. To improve BP accuracy, future efforts should focus on incorporating PWV(t), or at least both diastolic and systolic PWV values, into these models.

3D velocity and pressure field reconstruction in the cardiac left ventricle via physics informed neural network from echocardiography guided by 3D color Doppler

Fluid dynamics of the heart chamber can provide critical biological cues for understanding cardiac health and disease and have the potential for supporting diagnosis and prognosis. However, directly acquiring fluid dynamics information from clinical imaging remains challenging, as they are often noisy and have limited resolution, preventing accurate detailed fluid dynamics analysis. Image-based flow simulations offer high detail but are typically difficult to align with clinical velocity measurements, and as a result, may not accurately depict true fluid dynamics. Inverse-computing velocity fields from images via intra-ventricular flow mapping (VFM) has been reported, but it can become inaccurate when faced with missing or noisy measurement data, which is common with modalities such as ultrasound. Here, we propose a physics-informed neural network (PINN) framework that can accurately reconstruct detailed 3D flow fields of the cardiac left ventricle within a localized time window, using supervision from color Doppler measurements, despite their low resolution and signal-to-noise ratio. This framework couples PINN solvers at consecutive time frames with discrete temporal numerical differentiation and is thus named the "Coupled Sequential Frame PINN" or CSF-PINN. We used image-based flow simulations of fetal and adult hearts to generate synthetic color Doppler velocity data at different spatial and temporal resolution for testing the framework. Results show that CSF-PINN can accurately predict high levels of fluid dynamics details, including flow patterns, intraventricular pressure gradients, vorticity structures, and energy losses. CSF-PINN outperforms vanilla PINN in both accuracy and computational efficiency, however, its accuracy is more limited for velocity-gradient-dependent parameters, such as vorticity and wall shear stress (WSS) magnitude. CSF-PINN's accuracy is maintained even when color Doppler velocity data are spatially and temporally sparse and noisy, and when complex motions of the mitral valve are modelled. These are scenarios in which previous methodologies, including image-based flow simulations and VFM, have struggled. Additionally, we propose a scheme for advancing fluid dynamics predictions to subsequent time windows by using training from the previous time window to initialize networks for the subsequent window, further minimizing errors.

Patient-specific coronary angioplasty simulations - A mixed-dimensional finite element modeling approach

Coronary angioplasty with stent implantation is the most frequently used interventional treatment for coronary artery disease. However, reocclusion within the stent, referred to as in-stent restenosis, occurs in up to 10% of lesions. It is widely accepted that mechanical loads on the vessel wall strongly affect adaptive and maladaptive mechanisms. Yet, the role of procedural and lesion-specific influence on restenosis risk remains understudied. Computational modeling of the stenting procedure can provide new mechanistic insights, such as local stresses, that play a significant role in tissue growth and remodeling. Previous simulation studies often featured simplified artery and stent geometries and cannot be applied to real-world examples. Realistic simulations were computationally expensive since they featured fully resolved stenting device models. The aim of this work is to develop and present a mixed-dimensional formulation to simulate the patient-specific stenting procedure with a reduced-dimensional beam model for the stent and 3D models for the artery. In addition to presenting the numerical approach, we apply it to realistic cases to study the intervention's mechanical effect on the artery and correlate the findings with potential high-risk locations for in-stent restenosis. We found that high artery wall stresses develop during the coronary intervention in severely stenosed areas and at the stent boundaries. Herewith, we lay the groundwork for further studies towards preventing in-stent restenosis after coronary angioplasty.

Modeling Techniques and Boundary Conditions in Abdominal Aortic Aneurysm Analysis: Latest Developments in Simulation and Integration of Machine Learning and Data-Driven Approaches

Research on abdominal aortic aneurysms (AAAs) primarily focuses on developing a clear understanding of the initiation, progression, and treatment of AAA through improved model accuracy. High-fidelity hemodynamic and biomechanical predictions are essential for clinicians to optimize preoperative planning and minimize therapeutic risks. Computational fluid dynamics (CFDs), finite element analysis (FEA), and fluid-structure interaction (FSI) are widely used to simulate AAA hemodynamics and biomechanics. However, the accuracy of these simulations depends on the utilization of realistic and sophisticated boundary conditions (BCs), which are essential for properly integrating the AAA with the rest of the cardiovascular system. Recent advances in machine learning (ML) techniques have introduced faster, data-driven surrogates for AAA modeling. These approaches can accelerate segmentation, predict hemodynamics and biomechanics, and assess disease progression. However, their reliability depends on high-quality training data derived from CFDs and FEA simulations, where BC modeling plays a crucial role. Accurate BCs can enhance ML predictions, increasing the clinical applicability. This paper reviews existing BC models, discussing their limitations and technical challenges. Additionally, recent advancements in ML and data-driven techniques are explored, discussing their current states, future directions, common algorithms, and limitations.

Characterization of mechanical damage and viscoelasticity on aortas from guinea pigs subjected to hypoxia

To reliably assess the rupture risk of the aorta, along with the hazardousness of cardiovascular diseases and other extreme conditions or the effect of possible treatments, it is necessary to understand the influence of damage mechanisms along with the frequency and rate of mechanical loads. In particular, hypobaric hypoxia, an oxygen deficiency in the organism due to its low atmospheric partial pressure, is reported to alter the mechanical properties of blood vessels. In this work, we characterized the passive mechanical response of the aorta, seeking to capture the influence of hypoxia on their elastic, damage, and viscoelastic properties under ex-vivo conditions. The mechanical behavior of the aortic wall is described using an anisotropic hyperelastic model including two fiber families with asymmetric dispersion, along with an anisotropic damage model and an orthotropic viscoelastic model based on a reverse multiplicative decomposition of the deformation gradient. The constitutive model was experimentally calibrated from uniaxial-relaxation and biaxial-tensile test results, previously performed on thoracic aorta samples of guinea pigs. A group of guinea pigs subjected to hypoxia was contrasted with a normoxic (control) group. Cyclic-load stages of uniaxial tests were used to assess dissipation. Once the constitutive model was implemented and calibrated, its performance was evaluated via the numerical simulation of a bulge pressurization test to estimate energy dissipation and pressure associated with the onset of damage. Results indicated that hypoxia does not alter the visco-hyperelastic or damage behavior of the aorta. Besides, the pressure delivered by bulge-test simulations at the onset of damage on collagen fibers was representative of an arterial hypertensive condition.

Biomechanical and histomorphometric characterization of the melatonin treatment effect in the carotid artery subjected to hypobaric hypoxia

This study aims to assess the efficacy of melatonin in mitigating the adverse effects of hypobaric hypoxia on the cardiovascular system of neonatal lambs (30 days old). Two groups were considered for this purpose: (i) Melatonin-treated group (N = 5) and (ii) Control group (N = 6) without treatment. All subjects were exposed to hypobaric hypoxia during gestation and perinatal periods, with melatonin administered after birth. The study focused on the carotid artery, a known predictor of cardiovascular risk. Biomechanical tests, morphometric, and histological measurements were conducted, and a numerical model was developed based on the biomechanical data. Key findings showed remodeling effects: Firstly, a realignment of collagen fibers towards a longitudinal direction was observed with melatonin treatment, similar to non-hypoxic arteries. Second, changes in residual stress and ex-vivo luminal radius were noted, aiming to reduce wall stress and increase vascular resistance. These changes indicate an antihypertensive response, reducing the effects of increased blood pressure and flow due to hypobaric hypoxia. This study demonstrates that biomechanical and histomorphometric methodologies effectively assess the beneficial effects of melatonin treatment under hypobaric hypoxia exposure.

Layer-specific residual strains in human carotid arteries revealed under layer separation

Residual stresses are considered as a significant factor influencing the stress-states in arteries. These stresses are typically observed through opening angle of a radially cut artery segment, often regarded as a primary descriptor of their stress-free state. However, the experimental evidence regarding the stress-free states of different artery layers is scarce. In this study, two experimental protocols, each employing different layer-separating sequences, were performed on 17 human common carotid arteries; the differences between both protocols were found statistically insignificant. While the media exhibited opening behaviour (reduced curvature), a contrasting trend was observed for the adventitia curvature, indicating its closing behaviour. In addition to the different bending effect, length changes of both layers after separation were observed, namely shortening of the adventitia and elongation of the media. The results point out that not all the residual stresses are released after a radial cut but a significant portion of them is released only after the layer separation. Considering the different mechanical properties of layers, this may significantly change the stress distribution in arterial wall and should be considered in its biomechanical models.

Effect of melatonin on passive, ex-vivo biomechanical behavior of lamb esophagus

One of the purposes of tissue engineering is to offer therapeutic alternatives to treat various esophagus-related diseases. To develop viable esophageal replacements that are both mechanically and biologically compatible and to assess the impact of pharmacological treatments on esophageal tissue at the macro- and micro-structural levels, it is crucial to understand the biomechanical properties of the esophagus. In this study, we analyzed esophageal tissue samples from nine newborn lambs. Subjects were randomly separated into a control group (n = 5) and a melatonin-treated group (n = 4). The passive mechanical response of the esophagus was studied by performing in-vitro uniaxial tensile tests along longitudinal and circumferential directions. Samples were classified into three types: internal tissue (mucosa and submucosa layers), external tissue (external muscular layer), and integrated tissue (comprising all layers). Uniaxial stress versus stretch curves of each classification were used to determine mechanical properties that were statistically analyzed. Moreover, average experimental results were used to calibrate an anisotropic hyperelastic model. Stress-stretch curves from uniaxial tests showed a highly anisotropic behavior, with a higher stiffness along the longitudinal direction and internal tissue exhibiting the highest stiffness. To contrast the results obtained from mechanical testing, histological analysis of esophagus samples was carried out. Microstructural components were quantified and morphological measurements of the main zones were performed. No significant differences were found at the macro- and microstructural levels of the tissue, indicating that the supply of low doses of melatonin does not alter the biomechanical properties of the esophagus.

Robust super-structured porous hydrogel enables bioadaptive repair of dynamic soft tissue

Well-orchestrated integration of multiple contradictory properties into a single material is crucial for dynamic soft tissue defect repair but remains challenging. Bioinspired by diaphragm, we have successfully developed a robust super-structured porous hydrogel with anisotropic skeleton and asymmetric porous surfaces via integrated molding. Thanks to synergistic toughening of anisotropic structure and Hofmeister effect of amino acid, our hydrogel achieves high tensile strength (22.2 MPa) and elastic modulus (32.4 MPa) for strong mechanical support, while maintaining excellent toughness (61.9 MJ m-3) and fatigue threshold (5.6 kJ m-2) against dynamic stretching during the early healing phase. The mechanical properties of hydrogel gradually decrease during the late healing phase, minimizing its restriction on physiological movements. In addition, diaphragm defect repair models on female rabbits demonstrate asymmetric porous surfaces can simultaneously prevent visceral adhesion and promote defect healing. Therefore, our hydrogel opens an attractive avenue for the construction of biomimetically hierarchical materials to address the stringent requirements of dynamic tissue defect repair.

What does the slope of stress-stretch curves tell us about vascular tissue response?

We examined a group of 50 uniaxial stress-stretch curves obtained from human ascending aortic aneurysm tissues. The curves were believed to be associated with elastic response because the stress is monotonically increasing in all curves, and so is the slope. However, 26 curves exhibit exponential-like slope while the remaining 24 curves have sigmoid slopes. We hypothesized that the slope patterns stemmed from collage waviness distribution. A structural constitutive model was introduced to describe the responses. The model employed a unimodal density function to describe the waviness distribution, from which a two-phase response ensued. In the first phase the slope is quasi-exponential, and in the second phase the slope is sigmoid. The model fitted all 50 curves perfectly well. An exponential model was also introduced for a comparison. The model fitted the curves of quasi-exponential slope generally well, but performed worse over the curves of sigmoid slope. The work suggests that the slope may encode significant information about collagen waviness, and underscores a limitation of exponential-based models.

Mechanisms of aortic dissection: From pathological changes to experimental and in silico models

Aortic dissection continues to be responsible for significant morbidity and mortality, although recent advances in medical data assimilation and in experimental and in silico models have improved our understanding of the initiation and progression of the accumulation of blood within the aortic wall. Hence, there remains a pressing necessity for innovative and enhanced models to more accurately characterize the associated pathological changes. Early on, experimental models were employed to uncover mechanisms in aortic dissection, such as hemodynamic changes and alterations in wall microstructure, and to assess the efficacy of medical implants. While experimental models were once the only option available, more recently they are also being used to validate in silico models. Based on an improved understanding of the deteriorated microstructure of the aortic wall, numerous multiscale material models have been proposed in recent decades to study the state of stress in dissected aortas, including the changes associated with damage and failure. Furthermore, when integrated with accessible patient-derived medical data, in silico models prove to be an invaluable tool for identifying correlations between hemodynamics, wall stresses, or thrombus formation in the deteriorated aortic wall. They are also advantageous for model-guided design of medical implants with the aim of evaluating the deployment and migration of implants in patients. Nonetheless, the utility of in silico models depends largely on patient-derived medical data, such as chosen boundary conditions or tissue properties. In this review article, our objective is to provide a thorough summary of medical data elucidating the pathological alterations associated with this disease. Concurrently, we aim to assess experimental models, as well as multiscale material and patient data-informed in silico models, that investigate various aspects of aortic dissection. In conclusion, we present a discourse on future perspectives, encompassing aspects of disease modeling, numerical challenges, and clinical applications, with a particular focus on aortic dissection. The aspiration is to inspire future studies, deepen our comprehension of the disease, and ultimately shape clinical care and treatment decisions.

Cardiac Pulsatile Helical Deformation of the Thoracic Aorta Before and After Thoracic Endovascular Aortic Repair of Type B Dissections

PURPOSE

Type B aortic dissections propagate with either achiral (nonspiraling) or right-handed chiral (spiraling) morphology, have mobile dissection flaps, and are often treated with thoracic endovascular aortic repair (TEVAR). We aim to quantify cardiac-induced helical deformation of the true lumen of type B aortic dissections before and after TEVAR.

MATERIAL AND METHODS

Retrospective cardiac-gated computed tomography (CT) images before and after TEVAR of type B aortic dissections were used to construct systolic and diastolic 3-dimensional (3D) surface models, including true lumen, whole lumen (true+false lumens), and branch vessels. This was followed by extraction of true lumen helicity (helical angle, twist, and radius) and cross-sectional (area, circumference, and minor/major diameter ratio) metrics. Deformations between systole and diastole were quantified, and deformations between pre- and post-TEVAR were compared.

RESULTS

Eleven TEVAR patients (59.9±4.6 years) were included in this study. Pre-TEVAR, there were no significant cardiac-induced deformations of helical metrics; however, post-TEVAR, significant deformation was observed for the true lumen proximal angular position. Pre-TEVAR, cardiac-induced deformations of all cross-sectional metrics were significant; however, only area and circumference deformations remained significant post-TEVAR. There were no significant differences of pulsatile deformation from pre- to post-TEVAR. Variance of proximal angular position and cross-sectional circumference deformation decreased after TEVAR.

CONCLUSION

Pre-TEVAR, type B aortic dissections did not exhibit significant helical cardiac-induced deformation, indicating that the true and false lumens move in unison (do not move with respect to each other). Post-TEVAR, true lumens exhibited significant cardiac-induced deformation of proximal angular position, suggesting that exclusion of the false lumen leads to greater rotational deformations of the true lumen and lack of true lumen major/minor deformation post-TEVAR means that the endograft promotes static circularity. Population variance of deformations is muted after TEVAR, and dissection acuity influences pulsatile deformation while pre-TEVAR chirality does not.Clinical ImpactDescription of thoracic aortic dissection helical morphology and dynamics, and understanding the impact of thoracic endovascular aortic repair (TEVAR) on dissection helicity, are important for improving endovascular treatment. These findings provide nuance to the complex shape and motion of the true and false lumens, enabling clinicians to better stratify dissection disease. The impact of TEVAR on dissection helicity provides a description of how treatment alters morphology and motion, and may provide clues for treatment durability. Finally, the helical component to endograft deformation is important to form comprehensive boundary conditions for testing and developing new endovascular devices.

Regional Variation in Pulse Transit Time in the Upper Limb Arteries During Hypotensive and Non-hypotensive Lower Body Negative Pressure

PURPOSE

Pulse transit time (PTT) is crucial in developing non-invasive cuffless blood pressure (BP) measurement devices. Sympathetic activation, due to its effect on PTT, can lead to erroneous estimation of BP. Sympathetic activation might affect the PTT differentially depending on the site where PTT is measured in the upper limb. This study aimed to decipher regional variation in PTT in response to sympathetic activation in three segments of the upper limb arteries. Exposure to graded lower body negative pressure (LBNP) at hypotensive (-30 mmHg and -40 mmHg) and non-hypotensive (-10 mmHg and -20 mmHg) levels has been used to produce sympathetic activation.

METHODS

This was a pilot study. Ten healthy subjects were recruited for the study, and recordings were done. Carotid, brachial, and radial pulse waveforms were recorded simultaneously by tonometry, and the finger pulse waveform was recorded by photoplethysmography (PPG). LBNP was applied at -10 mmHg, -20 mmHg, -30 mmHg, and -40 mmHg for two minutes. Carotid-brachial PTT (cbPTT), brachial-radial PTT (brPTT), and radial-finger PTT (rfPTT) were calculated.

RESULTS

cbPTT did not show any significant change, whereas both brPTT (0.02679±0.00635 sec at baseline vs. 0.02027±0.00662 sec at hypotensive LBNP; p=0.0386) and rfPTT (0.00908±0.00350 sec at baseline vs. 0.00585±0.00211 sec at hypotensive LBNP; p=0.003) showed a significant decrease in response to hypotensive LBNP. rfPTT (0.00908±0.00350 at baseline vs. 0.00534±0.00249s at non-hypotensive LBNP; p=0.0257) also showed a significant decline in response to non-hypotensive LBNP as well.

CONCLUSION

The current study reveals that in upper limb arteries, PTT response to LBNP shows regional variation with an accentuation of response from proximal to distal segments.

Bridging biomechanics with neuropathological and neuroimaging insights for mTBI understanding through multiscale and multiphysics computational modeling

Mild traumatic brain injury (mTBI) represents a significant public health challenge in modern society. An in-depth analysis of the injury mechanisms, pathological forms, and assessment criteria of mTBI has underscored the pivotal role of craniocerebral models in comprehending and addressing mTBI. Research indicates that although existing finite element craniocerebral models have made strides in simulating the macroscopic biomechanical responses of the brain, they still fall short in accurately depicting the complexity of mTBI. Consequently, this paper emphasizes the necessity of integrating biomechanics, neuropathology, and neuroimaging to develop multiscale and multiphysics craniocerebral models, which are crucial for precisely capturing microscopic injuries, establishing pathological mechanical indicators, and simulating secondary and long-term brain functional impairments. The comprehensive analysis and in-depth discussion presented in this paper offer new perspectives and approaches for understanding, diagnosing, and preventing mTBI, potentially contributing to alleviating the global burden of mTBI.

Hyperelastic meniscal material characterization via inverse parameter identification for knee arthroscopic simulations

Understanding the complex behavior of menisci is of growing interest in many fields including sports medicine, surgical simulation, and implant design. The selection of an appropriate material model and accurate model parameters contribute to identifying the degree of degeneration of the meniscus. Incorporating patient-specific material parameters could further improve the safe handling of tissue during probing in knee arthroscopy simulations, supporting more informed intraoperative decision-making. The objective of this study is to identify hyperelastic material parameters of individual human menisci based on an inverse parameter identification approach using optimization and demonstrate a real-time interactive surgical simulation using identified parameters. Mechanical tests were conducted in indentation of the anterior, mid-body, and posterior regions of five lateral and medial menisci to obtain experimental force-displacement data. An inverse parameter identification based on these tests and finite element (FE) models was employed to minimize the differences between the experimental and simulated force. The region-specific FE models considered the predominant collagen fiber orientation of the meniscus. Anisotropic hyperelastic material parameters were optimized using a particle swarm optimization algorithm. Finally, the optimized parameters were used in simulation open framework architecture (SOFA) and demonstrated a real-time probe-meniscus interaction during the arthroscopic meniscus examination. The optimized values revealed subject-specific characteristics, along with anatomical and regional variations, with high shear modulus observed in the anterior region of the medial meniscus (0.76 ± 0.28 MPa for 1 mm indentation). Additionally, an increase in shear modulus was observed with increased indentation depth (p<0.05 except for the mid-body of the medial meniscus).

An Electromechanical Model-Based Study on the Dosage Effects of Ranolazine in Treating Failing HCM Cardiomyocyte

Background and Objective

Hypertrophic cardiomyopathy (HCM) is associated with a significant risk of progression to heart failure (HF). Extensive experimental and clinical research has highlighted the therapeutic benefits of ranolazine in alleviating electrophysiological abnormalities and arrhythmias in the context of HCM and HF. Despite these findings, there is a shortage of studies examining the electromechanical responses of failing HCM cardiomyocytes to ranolazine and the impact of ranolazine dosage on outcomes across varying degrees of HF. This study aims to systematically address these issues.

Methods

A computational modeling approach was utilized to quantify alterations in electromechanical variables within failing HCM cardiomyocytes subsequent to ranolazine treatment. The model parameters were calibrated against extant literature data to delineate the spectrum of HF severities and the changes in ion channels following the administration of various doses of ranolazine.

Results

The inhibition of the augmented late Na+ current in failing HCM cardiomyocyte with an adequate amount of ranolazine was found to be effective in alleviating electrophysiological abnormalities (e.g., prolongation of action potential (AP), Ca2+ overload in diastole), which contributed to improving the diastolic function of the cardiomyocyte, albeit with a modest negative effect on the systolic function. A threshold drug dose was identified for achieving a significant normalization of the overall electromechanical profile. The threshold drug dose for effective therapy was observed to be contingent upon the severity of HF and the status of certain key ion channels. Furthermore, it was determined that an increase of the drug dose beyond the threshold did not yield substantial additional improvements in the principal electromechanical variables.

Conclusions

The study demonstrated the presence of a threshold dose of ranolazine for effective treatment of failing HCM cardiomyocyte, and further established that this threshold is influenced by the severity of HF and the functional status of key ion channels. These findings may serve as theoretical evidence for comprehending the mechanisms underlying ranolazine's therapeutic efficacy in treating failing HCM hearts. Moreover, the study underscores the potential clinical value of personalized dosing strategies.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12195-025-00842-5.

Ex-vivo mechano-structural characterization of fresh diseased human esophagus

The esophagus, the tube-like organ responsible for transporting food from the pharynx to the stomach, operates as a highly mechanical structure, exhibiting complex contraction and distension patterns triggered by neurological impulses. Despite the critical role of mechanics in its function and the need for high-fidelity models of esophageal transport, mechanical characterization studies of human esophagus remain relatively scarce. In addition to the paucity of studies in human specimens, the available results are often scattered in terms of methodology and scope, making it difficult to compare findings across studies and thereby limiting their use in computational models. In this work, we present a detailed passive-mechanical and structural characterization of the esophageal muscular layers, excised from short esophageal segments obtained from live patients with varied clinical presentations. Specifically, we conducted uniaxial and planar biaxial extension tests on the smooth muscle layers, complemented by pre- and post-testing structural characterization via histological imaging. Unlike existing studies, our experimental results on passive behavior are discussed in the context of physiological relevance (e.g., physiological stretches, and activity-inhibiting pathologies), providing valuable insights that guide the subsequent modeling of the esophagus' mechanical response. As such, this work provides new insights into the passive properties of the fresh human esophagus, expands the existing database of mechanical parameters for computational modeling, and lays the foundation for future studies on active mechanical properties. STATEMENT OF SIGNIFICANCE: Understanding the mechanical properties of the esophagus is crucial for developing accurate models of its function and suitable replacements. This study provides insights into the passive mechanical behavior of fresh human esophageal tissue, enhancing our understanding of how it responds to stretching under physiological conditions. By characterizing the properties of different esophageal layers, obtained from esophagectomy specimens with various presentations, and considering their relevance to both normal and abnormal functioning, this work addresses the gap in ex-vivo human esophagus studies. The findings emphasize the importance of contextually analyzing experimental results within physiological parameters and suggest avenues for future research to further refine our understanding of esophageal mechanics, paving the way for improved diagnostic and therapeutic approaches in managing esophageal disorders.

Constitutive neural networks for main pulmonary arteries: discovering the undiscovered

Accurate modeling of cardiovascular tissues is crucial for understanding and predicting their behavior in various physiological and pathological conditions. In this study, we specifically focus on the pulmonary artery in the context of the Ross procedure, using neural networks to discover the most suitable material model. The Ross procedure is a complex cardiac surgery where the patient's own pulmonary valve is used to replace the diseased aortic valve. Ensuring the successful long-term outcomes of this intervention requires a detailed understanding of the mechanical properties of pulmonary tissue. Constitutive artificial neural networks offer a novel approach to capture such complex stress-strain relationships. Here, we design and train different constitutive neural networks to characterize the hyperelastic, anisotropic behavior of the main pulmonary artery. Informed by experimental biaxial testing data under various axial-circumferential loading ratios, these networks autonomously discover the inherent material behavior, without the limitations of predefined mathematical models. We regularize the model discovery using cross-sample feature selection and explore its sensitivity to the collagen fiber distribution. Strikingly, we uniformly discover an isotropic exponential first-invariant term and an anisotropic quadratic fifth-invariant term. We show that constitutive models with both these terms can reliably predict arterial responses under diverse loading conditions. Our results provide crucial improvements in experimental data agreement, and enhance our understanding into the biomechanical properties of pulmonary tissue. The model outcomes can be used in a variety of computational frameworks of autograft adaptation, ultimately improving the surgical outcomes after the Ross procedure.

A waviness-centered damage model for collagenous soft tissues

This article presents a damage model for collagenous tissue under monotonic loading. Given that the true stretch of collagen fibers is not uniform and is regulated by fiber waviness, we postulate that damage commences from more stretched (i.e. straighter) fibers and progresses to less stretched (i.e. wavier) ones. The complicated nonlinear response is regarded as the outcome of two competing mechanisms: the recruitment of wavy intact fibers and the loss of taut functioning fibers. The progression of damage is modeled by an evolving damage front in the waviness domain. A power law is proposed for the evolution of damage front. The model was fitted to four groups of published uniaxial and biaxial tests data of vascular tissues. Spot-on fits were observed in all groups.

Assessment of Aortic Dissection Remodeling With Patient-Specific Fluid-Structure Interaction Models

Aortic dissection leads to late complications due tochronic degeneration and dilatation of the false lumen. This study examines the interaction between hemodynamics and long-term remodeling of a patient's aortic dissection, tracked from pre-dissection to the chronic phase using CT angiography. Fluid-structure interaction models with tissue prestress, external support, and anisotropic properties were used to analyze hemodynamic markers. Each aortic wall layer had distinct thicknesses and material properties. The boundary conditions were guided by in vitro 4D-flow MRI and the patient's blood pressure. Aortic dilatation was most significant distal to the left subclavian artery, reaching 6 cm in the chronic phase. Simulations quantified the flow jet velocity through the entry tear, which peaked at 185 cm/s in the subacute phase and decreased to 123 to 133 cm/s in the chronic phase, corresponding to an increased entry tear size. Flow jet impingement on the false lumen resulted in a localized pressure increase of 11 and 2 mmHg in the subacute and chronic phases, with wall shear stress reaching 4 Pa. These hemodynamic changes appear to be the main drivers of aortic growth and morphological changes. Despite moderate overall flap movement, in-plane displacement increased from 0.6 to 1.8 mm as disease progressed, which was associated with an overall increase in aortic diameter. Simulations with a significant reduction in flap stiffness during the subacute phase resulted in increased flap motion up to 9.5 mm. Although these results are based on a single patient, they suggest a strong relationship between hemodynamics and aortic growth.

Equilibrium mechanical properties of the human uterus in tension and compression

A successful pregnancy relies on the proper cellular, biochemical, and mechanical functions of the uterus. A comprehensive understanding of nonpregnant and pregnant uterine mechanical properties is key to understanding different obstetric and gynecological disorders such as preterm birth, placenta accreta, uterine rupture, leiomyoma, adenomyosis, and endometriosis. This study sought to characterize the macro-scale equilibrium material behaviors of the human uterus in nonpregnancy and late pregnancy under both compressive and tensile loading. Forty four human uterine specimens from 16 patients (8 nonpregnant [NP] and 8 pregnant [PG]) were tested using spherical indentation and uniaxial tension coupled with digital image correlation (DIC). A three-strain level incremental load-hold protocol was applied to both tests. A microstructurally-inspired material model considering fiber architecture was applied to this dataset. Inverse finite element analysis (IFEA) was then performed to generate a single set of mechanical parameters to describe compressive and tensile behaviors. The freeze-thaw effect on uterine mechanical properties was also evaluated. For this cohort of tissue samples, the fiber network of the PG uterus was more extensible than in the NP tissue. The initial fiber stiffness and ground substance compressibility were similar between NP and PG uterine tissue. Lastly, a single freeze-thaw cycle did not systematically alter the mechanical behavior of the human uterus under indentation.

What about the mechanical behaviour and modelling of arteries in radial direction?

Understanding the physiological behaviour of arteries in the radial direction is crucial for establishing a reference point to detect and analyse pathological changes. In this study, the influence of the radial component of the aorta will be investigated by performing experimental tests on porcine aortic tissue in the three main directions of the aorta: circumferential, longitudinal and radial. The results obtained in all directions will be analysed and compared in order to contribute to a comprehensive understanding of the healthy behaviour of the vessel. Our results demonstrate that the aorta exhibits nonlinear behaviour under compression and tensile loading in the radial direction. Moreover, tissue stiffening progresses more prominently under compression compared to tensile loading. We have found that the tensile stiffness in the ATA is higher compared to the other two regions examined. The Neo-Hookean and Demiray models were selected to describe the isotropic contribution when fitting the uniaxial response of the circumferential and longitudinal samples using the GOH model. Neo-Hookean model fall short (R2=0.235) in accurately replicating the observed behaviour of the aorta in the radial direction and Demiray model showing better fitting results (R2=0.994).

Computational modeling of vascular tissue damage for the development of safe interventional devices

During intravascular procedures, medical devices interact mechanically with vascular tissue. The device design faces a trade-off: although a high bending stiffness improves its maneuvrability and deliverability, it may also trigger excessive supra-physiological loading that may result in tissue damage. In particular, the collagen fibers in vascular walls are load-bearing but may rupture on a microscopic scale due to mechanical interaction. When the mechanical load increases even further, tissue rupture or puncture occurs. To mitigate tissue damage, the current work focusses on the development of computational Finite Element (FE) based models wherein state-of-the-art constitutive tissue models are applied toward the design of safe devices. Several experiments are presented for tissue characterization in which device-mimicking indenters are pressed onto a porcine tissue. In these experiments, the Mullins effect, which is related to tissue damage, is observed. Consequently, the mechanical behavior of tissue, including the evolution of damage-induced energy dissipation, is accurately described by adopting a hyperelastic model incorporating the damage approach by Weisbecker et al. (2012). From the experimentally validated computational model, a novel design criterion is established, which allows for safe device development. Furthermore, an energy density criterion for the onset of puncture is proposed. With these tools, several frequently used work-horse guidewires are numerically evaluated.

Fluid-structure interaction analysis for abdominal aortic aneurysms: the role of multi-layered tissue architecture and intraluminal thrombus

Introduction

Abdominal aortic aneurysm (AAA) is a life-threatening disease marked by localized dilatations of the infrarenal aortic wall. While clinical guidelines often use the aneurysm diameter as an indicator for surgical intervention, this metric alone may not reliably predict rupture risks, underscoring the need for detailed biomechanical analyses to improve risk assessments.

Methods

We investigate the effects of the multi-layered tissue architecture and the intraluminal thrombus (ILT) on the wall stress distribution of AAA. Using fluid-structure interaction, we analyze the biomechanical responses of fusiform and saccular AAAs under three conditions: without ILT, with ILT but no tissue degradation, and with both ILT and tissue degradation.

Results

The findings show that the media is the primary load-bearing layer, and the multi-layered model yields a more accurate stress profile than the single-layered tissue model. The ILT substantially reduces overall stress levels in the covered tissue, although its impact on the location of peak stress varies across different scenarios. Media degradation increases the stress in the intima and adventitia, but the cushioning effect of ILT largely mitigates this impact.

Discussion

The results underscore the importance of incorporating the multi-layered tissue architecture and ILT in patient-specific analyses of AAA. These factors may improve the predictive capabilities of biomechanical assessments for rupture risk.

Interaction of a self-expandable stent with the arterial wall in the presence of hypocellular and calcified plaques

Self-expandable stents manufactured from nitinol alloys are commonly utilized alongside traditional balloon-expandable stents to provide scaffolding to stenosed arteries. However, a significant limitation hampering stent efficacy is restenosis, triggered by neointimal hyperplasia and resulting in the loss of gain in lumen size, post-intervention. In this study, a nonlinear finite element model was developed to simulate stent crimping and expansion and its interaction with the surrounding vessel in the presence of a plaque. The main aim was to determine contact pressures and forces induced at the interface between an artery wall with hypocellular and calcified plaques and an expanded stent. The results demonstrated the drawbacks of plaque calcification, which triggered a sharp contact pressure and radial force surge at the interface as well as a significant rise in von Mises stress within the vessel, potentially leading to rupture and restenosis. A regression line was then established to relate hypocellular and calcified plaques. The adjusted coefficient of determination indicated a good correlation between contact pressures for calcified and hypocellular plaque models. Regarding the directionality of wall properties, contact pressure and force observations were not significantly different between isotropic and anisotropic arteries. Moreover, variations in friction coefficients did not substantially affect the interfacial contact pressures.

A multiphasic model for determination of mouse ascending thoracic aorta mass transport properties with and without aneurysm

Thoracic aortic aneurysms (TAAs) are associated with aortic wall remodeling that affects transmural transport or the movement of fluid and solute across the wall. In previous work, we used a Fbln4E57K/E57K (MU) mouse model to investigate transmural transport changes as a function of aneurysm severity. We compared wild-type (WT), MU with no aneurysm (MU-NA), MU with aneurysm (MU-A), and MU with an additional genetic mutation that led to increased aneurysm penetrance (MU-XA). We found that all aneurysmal aortas (MU-A and MU-XA) had lower fluid flux compared to WT. Non-aneurysmal aortas (MU-NA) had higher 4 kDa FITC-dextran solute flux than WT, but aneurysmal MU-A and MU-XA aortas had solute fluxes similar to WT. Our experimental results could not isolate competing factors, such as changes in aortic geometry and solid material properties among these mouse models, to determine how intrinsic transport properties change with aneurysm severity. The objective of this study is to use biphasic and multiphasic models to identify changes in transport material properties. Our biphasic model indicates that hydraulic permeability is significantly decreased in the severe aneurysm model (MU-XA) compared to non-aneurysmal aortas (MU-NA). Our multiphasic model shows that effective solute diffusivity is increased in MU-NA aortas compared to all others. Our findings reveal changes in intrinsic transport properties that depend on aneurysm severity and are important for understanding the movement of fluids and solutes that may play a role in the diagnosis, progression, or treatment of TAA.

The Influence of Material Properties and Wall Thickness on Predicted Wall Stress in Ascending Aortic Aneurysms: A Finite Element Study

PURPOSE

Finite element analysis (FEA) has been used to predict wall stress in ascending thoracic aortic aneurysm (ATAA) in order to evaluate risk of dissection or rupture. Patient-specific FEA requires detailed information on ATAA geometry, loading conditions, material properties, and wall thickness. Unfortunately, measuring aortic wall thickness and mechanical properties non-invasively poses a significant challenge, necessitating the use of non-patient-specific data in most FE simulations. This study aimed to assess the impact of employing non-patient-specific material properties and wall thickness on ATAA wall stress predictions.

METHODS

FE simulations were performed on 13 ATAA geometries reconstructed from computed tomography angiography (CTA) images. Patient-specific material properties and wall thicknesses were made available from a previous study where uniaxial tensile testing was performed on tissue samples obtained from the same patients. The ATAA wall models were discretised with hexahedral elements and prestressed. For each ATAA model, FE simulations were conducted using patient-specific material properties and wall thicknesses, and group-mean values derived from all tissue samples included in the same experimental study. Literature-based material property and wall thickness were also obtained from the literature and applied to 4 representative cases. Additional FE simulations were performed on these 4 cases by employing group-mean and literature-based wall thicknesses.

RESULTS

FE simulations using the group-mean material property produced peak wall stresses comparable to those obtained using patient-specific material properties, with a mean deviation of 7.8%. Peak wall stresses differed by 20.8% and 18.7% in patients with exceptionally stiff or compliant walls, respectively. Comparison to results using literature-based material properties revealed larger discrepancies, ranging from 5.4% to 28.0% (mean 20.1%). Bland-Altman analysis showed significant discrepancies in areas of high wall stress, where wall stress obtained using patient-specific and literature-based properties differed by up to 674 kPa, compared to 227 kPa between patient-specific and group-mean properties. Regarding wall thickness, using the literature-based value resulted in even larger discrepancies in predicted peak stress, ranging from 24.2% to 30.0% (mean 27.3%). Again, using the group-mean wall thickness offered better predictions with a difference less than 5% in three out of four cases. While peak wall stresses were most affected by the choice of mechanical properties or wall thickness, the overall distribution of wall stress hardly changed.

CONCLUSIONS

Our study demonstrated the importance of incorporating patient-specific material properties and wall thickness in FEA for risk prediction of aortic dissection or rupture. Our future efforts will focus on developing inverse methods for non-invasive determination of patient-specific wall material parameters and wall thickness.

Estimating nonlinear anisotropic properties of healthy and aneurysm ascending aortas using magnetic resonance imaging

An ascending aortic aneurysm is an often asymptomatic localized dilatation of the aorta. Aortic rupture is a life-threatening event that occurs when the stress on the aortic wall exceeds its mechanical strength. Therefore, patient-specific finite element models could play an important role in estimating the risk of rupture. This requires not only the geometry of the aorta but also the nonlinear anisotropic properties of the tissue. In this study, we presented a methodology to estimate the mechanical properties of the aorta from magnetic resonance imaging (MRI). As a theoretical framework, we used finite element models to which we added noise to simulate clinical data from real patient geometry and different properties of healthy and aneurysmal aortic tissues collected from the literature. The proposed methodology considered the nonlinear properties, the zero pressure geometry, the heart motion, and the external tissue support. In addition, we analyzed the aorta as a homogeneous material and as a heterogeneous model with different properties for the ascending and descending parts. The methodology was also applied to pre-surgical,in vivo MRI data of a patient who underwent surgery during which an aortic wall sample was obtained. The results were compared with those obtained from ex vivo biaxial test of the patient's tissue sample. The methodology showed promising results after successfully recovering the nonlinear anisotropic material properties of all analyzed cases. This study demonstrates that the variable used during the optimization process can affect the result. In particular, variables such as principal strains were found to obtain more realistic materials than the displacement field.

On the Relative Effects of Wall and Intraluminal Thrombus Constitutive Material Properties in Abdominal Aortic Aneurysm Wall Stress

INTRODUCTION

An abdominal aortic aneurysm (AAA) is a dilation localized in the infrarenal segment of the abdominal aorta that can expand continuously and rupture if left untreated. Computational methods such as finite element analysis (FEA) are widely used with in silico models to calculate biomechanical predictors of rupture risk while choosing constitutive material properties for the AAA wall and intraluminal thrombus (ILT).

METHODS

In the present work, we investigated the effect of different constitutive material properties for the wall and ILT on 21 idealized and 10 unruptured patient-specific AAA geometries. Three material properties were used to characterize the wall and two for the ILT, leading to six material model combinations for each AAA geometry subject to appropriate boundary conditions.

RESULTS

The results of the FEA simulations indicate significant differences in the average peak wall stress (PWS), 99th percentile wall stress (99th WS), and spatially averaged wall stress (SAWS) for all AAA geometries subject to the choice of a material model combination. Specifically, using a material model combination with a compliant ILT yielded statistically higher wall stresses compared to using a stiff ILT, irrespective of the constitutive equation used to model the AAA wall.

DISCUSSION

This work provides quantitative insight into the variability of the wall stress distributions ensuing from AAA FEA modeling due to its strong dependency on population-averaged soft tissue material characterizations. This dependency leads to uncertainty about the true biomechanical state of stress of an individual AAA and the subsequent assessment of its rupture risk.

Computational evaluation of interactive dynamics for a full transcatheter aortic valve device in a patient-specific aortic root

Transcatheter aortic valve implantation (TAVI) has become a key treatment for severe aortic stenosis, especially for patients unsuitable for surgery. Since its introduction in 2002, TAVI has advanced significantly due to improvements in imaging, operator skills, and device engineering. Despite these innovations, challenges in device sizing and positioning remain, complicating outcome predictions. Computational modelling is a powerful tool to aid TAVI device design and to understand its interactive behaviour with the aortic root during the deployment. Previous studies often simplified tissue properties, neglected patient-specific geometries or omitted crucial elements such as leaflets and fabric. This paper presents a numerical framework capable of simulating the whole crimping and deployment process of a full TAVI device in a patient-specific aortic root including the native leaflets and calcifications. We conduct a comprehensive investigation into the mechanical behaviour of the TAVI and its interactions with patient-specific aortic root through dynamic finite element analysis during the deployment process, with validation against experimental results. Additionally, we examined the influence of applied pressure during balloon inflation on the interactive dynamics of the entire model. The study concludes that selecting optimal balloon pressures is crucial for enhancing TAVI device performance and reducing complications. Numerical simulations demonstrate that appropriate balloon pressure ensures sufficient flow area and effective contact pressure between the TAVI and the aortic root, while minimising deformation and the risk of paravalvular leak.

Evaluating the Influence of Morphological Features on the Vulnerability of Lipid-Rich Plaques During Stenting

Lipid-rich atheromas are linked to plaque rupture in stented atherosclerotic arteries. While fibrous cap thickness is acknowledged as a critical indicator of vulnerability, it is likely that other morphological features also exert influence. However, detailed quantifications of their contributions and intertwined effects in stenting are lacking. Therefore, our goal is to assess the impact of plaque characteristics on the fibrous cap stress and elucidate their underlying mechanisms. We analyzed the stent deployment in a three-dimensional patient-specific coronary artery reconstructed from intravascular optical coherence tomography (IVOCT) data using the finite element method. Additionally, we performed sensitivity analysis on 78,000 distinct plaque geometries of two-dimensional arterial cross section for verification. Results from the three-dimensional patient-specific model indicate strong correlations between maximum fibrous cap stress and lipid arc (r=0.769), area stenosis (r=0.550), and lumen curvature (r=0.642). Plaques with lipid arcs >60 deg, area stenosis >75%, and lumen curvatures >5 mm-1 are at rupture risk. While we observed a rise in stress with thicker lipid cores, it was less representative than other features. Fibrous cap thickness showed a poor correlation, with the sensitivity analysis revealing its significance only when high stretches are induced by other features, likely due to its J-shaped stress-stretch response. Contrary to physiological pressure, the stent expansion generates unique vulnerable features as the stent load-transferring characteristics modify the plaque's response. This study is expected to prompt further clinical investigations of other morphological features for predicting plaque rupture in stenting.

AI-Powered Multimodal Modeling of Personalized Hemodynamics in Aortic Stenosis

Aortic stenosis (AS) is the most common valvular heart disease in developed countries. High-fidelity preclinical models can improve AS management by enabling therapeutic innovation, early diagnosis, and tailored treatment planning. However, their use is currently limited by complex workflows necessitating lengthy expert-driven manual operations. Here, we propose an AI-powered computational framework for accelerated and democratized patient-specific modeling of AS hemodynamics from computed tomography (CT). First, we demonstrate that the automated meshing algorithms can generate task-ready geometries for both computational and benchtop simulations with higher accuracy and 100 times faster than existing approaches. Then, we show that the approach can be integrated with fluid-structure interaction and soft robotics models to accurately recapitulate a broad spectrum of clinical hemodynamic measurements of diverse AS patients. The efficiency and reliability of these algorithms make them an ideal complementary tool for personalized high-fidelity modeling of AS biomechanics, hemodynamics, and treatment planning.

An algorithmic and software framework to incorporate orientation distribution functions in finite element simulations for biomechanics and biophysics

Biological tissues and biomaterials routinely feature a fibrous microstructure that contributes to physical and mechanical properties while influencing cellular guidance, organization and extracellular matrix (ECM) production. Specialized three-dimensional (3D) imaging techniques can visualize fibrillar structure and orientation, and previously we developed a nonparametric approach to extract orientation distribution functions (ODFs) directly from 3D image data [1]. In this work, we expanded our previous approach to provide a complete algorithmic and software framework to characterize inhomogeneous ODFs in image data and use ODFs to model the physics of materials with the finite element method. We characterized inhomogeneity using image subdomains and specialized interpolation methods, and we developed methods to incorporate ODFs directly into constitutive models. To facilitate its adoption by the biomechanics and biophysics communities, we developed a unified software framework in FEBio Studio (www.febio.org). This included new interpolation methods to spatially map the ODFs onto finite element meshes and an approach to downsample ODFs for efficient numerical calculations. The software provides the option to fit ODFs to parametric distributions, and scalar metrics provide means to assess goodness of fit. We evaluated the utility and accuracy of the algorithms and implementation using representative 3D image datasets. Our results demonstrated that utilizing the true measured ODFs provide a more accurate and spatially resolved representation of fiber ODFs and the resulting predicted mechanical response when compared with parametric approaches to approximating the true ODFs. This research provides a powerful, interactive software framework to extract and represent the inhomogeneous anisotropic characteristics of fibrous tissues directly from image data, and to incorporate them into biomechanics and biophysics simulations using the finite element method. STATEMENT OF SIGNIFICANCE: Biological tissues and biomaterials routinely feature a fibrous microstructure that contributes to physical and mechanical properties while influencing cellular guidance, organization and extracellular matrix (ECM) production. In this study, we developed a complete algorithmic and software framework to characterize inhomogeneous orientation distribution functions (ODFs) directly from biomedical image data and apply the ODFs to model the physics of biological materials. We characterized inhomogeneity using image subdomains and specialized interpolation methods, and we developed methods to incorporate ODFs directly into constitutive models. We developed a unified software framework in FEBio Studio (www.febio.org) to accommodate its adoption by the biomechanics and biophysics communities. The result is a powerful, interactive software framework to extract and represent inhomogeneous, anisotropic characteristics directly from image data, and incorporate them into biomechanics and biophysics simulations.

Sacrificial Templating for Accelerating Clinical Translation of Engineered Organs

Transplantable engineered organs could one day be used to treat patients suffering from end-stage organ failure. Yet, producing hierarchical vascular networks that sustain the viability and function of cells within human-scale organs remains a major challenge. Sacrificial templating has emerged as a promising biofabrication method that could overcome this challenge. Here, we explore and evaluate various strategies and materials that have been used for sacrificial templating. First, we emphasize fabrication approaches that use highly biocompatible sacrificial reagents and minimize the duration that cells spend in fabrication conditions without oxygen and nutrients. We then discuss strategies to create continuous, hierarchical vascular networks, both using biofabrication alone and using hybrid methods that integrate biologically driven vascular self-assembly into sacrificial templating workflows. Finally, we address the importance of structurally reinforcing engineered vessel walls to achieve stable blood flow in vivo, so that engineered organs remain perfused and functional long after implantation. Together, these sacrificial templating strategies have the potential to overcome many current limitations in biofabrication and accelerate clinical translation of transplantable, fully functional engineered organs to rescue patients from organ failure.

Fracture properties of porcine versus human thoracic aortas from tricuspid/bicuspid aortic valve patients via symmetry-constraint Compact Tension testing

Aneurysm rupture is a life-threatening event, yet its underlying mechanisms remain largely unclear. This study investigated the fracture properties of the thoracic aneurysmatic aorta (TAA) using the symmetry-constraint Compact Tension (symconCT) test and compared results to native and enzymatic-treated porcine aortas' tests. With age, the aortic stiffness increased, and tissues ruptured at lower fracture energy [Formula: see text]. Patients with bicuspid aortic valves were more sensitive to age, had stronger aortas and required more [Formula: see text] than tricuspid valves individuals (peak load: axial loading 4.42 ± 1.56 N vs 2.51 ± 1.60 N; circumferential loading 5.76 ± 2.43 N vs 4.82 ± 1.49 N. Fracture energy: axial loading 1.92 ± 0.60 kJ m-2 vs 0.74 ± 0.50 kJ m-2; circumferential loading 2.12 ± 2.39 kJ m-2 vs 1.47 ± 0.91 kJ m-2). Collagen content partly explained the variability in [Formula: see text], especially in bicuspid cases. Besides the primary crack, TAAs and enzymatic-treated porcine aortas displayed diffuse and shear-dominated dissection and tearing. As human tissue tests resembled enzymatic-treated porcine aortas, microstructural degeneration, including elastin loss and collagen degeneration, seems to be the main cause of TAA wall weakening. Additionally, a tortuous crack developing during the symconCT test reflected intact fracture toughening mechanisms and might characterize a healthier aorta.

Determinants of Human Corneal Mechanical Wave Dispersion for In Vivo Optical Coherence Elastography

Purpose

To characterize frequency-dependent wave speed dispersion in the human cornea using microliter air-pulse optical coherence elastography (OCE), and to evaluate the applicability of Lamb wave theory for determining corneal elastic modulus using high-frequency symmetric (S0) and anti-symmetric (A0) guided waves in cornea.

Methods

Wave speed dispersion analysis for transient (0.5 ms) microliter air-pulse stimulation was performed in four rabbit eyes ex vivo and compared to air-coupled ultrasound excitation. The effects of stimulation angle and sample geometry on the dispersion were evaluated in corneal phantoms. Corneal wave speed dispersion was measured in 36 healthy human eyes in vivo.

Results

Air-pulse-induced dispersion was comparable to ultrasound-induced dispersion between 0.7 and 5 kHz (mean-difference ± 1.96 × SD: 0.006 ± 0.5 m/s) in ex vivo rabbit corneas. Stimulation 0° relative to the surface normal generated A0 Lamb waves in corneal tissue phantoms, while oblique stimulation (35° and 65°) generated S0 waves. Stimulating normal to the human corneal apex in vivo (0°) induced A0 waves, plateauing at 10.87 to 13.63 m/s at 4 kHz, and when obliquely stimulated at the periphery (65°), produced S0 waves, plateauing at 13.10 to 15.98 m/s at 4 kHz.

Conclusions

Air-pulse OCE can be used to measure human corneal Lamb wave dispersion of A0 and S0 propagation modes in vivo. These modes are selectively excited by changing the stimulation angle. Accounting for wave speed dispersion enables reliable estimation of corneal elastic modulus in vivo.

Translational Relevance

This work demonstrates the feasibility of air-pulse stimulation for robust OCE measurements of corneal stiffness in vivo for disease detection and therapy evaluation.

Biomechanics of soft biological tissues and organs, mechanobiology, homeostasis and modelling

The human body consists of many different soft biological tissues that exhibit diverse microstructures and functions and experience diverse loading conditions. Yet, under many conditions, the mechanical behaviour of these tissues can be described well with similar nonlinearly elastic or inelastic constitutive relations, both in health and some diseases. Such constitutive relations are essential for performing nonlinear stress analyses, which in turn are critical for understanding physiology, pathophysiology and even clinical interventions, including surgery. Indeed, most cells within load-bearing soft tissues are highly sensitive to their local mechanical environment, which can typically be quantified using methods of continuum mechanics only after the constitutive relations are determined from appropriate data, often multi-axial. In this review, we discuss some of the many experimental findings of the structure and the mechanical response, as well as constitutive formulations for 10 representative soft tissues or organs, and present basic concepts of mechanobiology to support continuum biomechanical studies. We conclude by encouraging similar research along these lines, but also the need for models that can describe and predict evolving tissue properties under many conditions, ranging from normal development to disease progression and wound healing. An important foundation for biomechanics and mechanobiology now exists and methods for collecting detailed multi-scale data continue to progress. There is, thus, considerable opportunity for continued advancement of mechanobiology and biomechanics.

Modeling Fibrous Tissue in Vascular Fluid-Structure Interaction: A Morphology-Based Pipeline and Biomechanical Significance

Modeling fibrous tissue for vascular fluid-structure interaction analysis poses significant challenges due to the lack of effective tools for preparing simulation data from medical images. This limitation hinders the physiologically realistic modeling of vasculature and its use in clinical settings. Leveraging an established lumen modeling strategy, we propose a comprehensive pipeline for generating thick-walled artery models. A specialized mesh generation procedure is developed to ensure mesh continuity across the lumen and wall interface. Exploiting the centerline information, a series of procedures are introduced for generating local basis vectors within the arterial wall. The procedures are tailored to handle thick-walled tissues where basis vectors may exhibit transmural variations. Additionally, we propose methods for accurately identifying the centerline in multi-branched vessels and bifurcating regions. These modeling approaches are algorithmically implementable, rendering them readily integrable into mainstream cardiovascular modeling software. The developed fiber generation method is evaluated against the strategy using linear elastostatics analysis, demonstrating that the proposed approach yields satisfactory fiber definitions in the considered benchmark. Finally, we examine the impact of anisotropic arterial wall models on the vascular fluid-structure interaction analysis through numerical examples, employing the neo-Hookean model for comparative purposes. The first case involves an idealized curved geometry, while the second studies an image-based abdominal aorta model. Our numerical results reveal that the deformation and stress distribution are critically related to the constitutive model of the wall, whereas hemodynamic factors are less sensitive to the wall model. This work paves the way for more accurate image-based vascular modeling and enhances the prediction of arterial behavior under physiologically realistic conditions.

Biomechanical stress analysis of Type-A aortic dissection at pre-dissection, post-dissection, and post-repair states

Acute type A aortic dissection remains a deadly and elusive condition, with risk factors such as hypertension, bicuspid aortic valves, and genetic predispositions. As existing guidelines for surgical intervention based solely on aneurysm diameter face scrutiny, there is a growing need to consider other predictors and parameters, including wall stress, in assessing dissection risk. Through our research, we aim to elucidate the biomechanical underpinnings of aortic dissection and provide valuable insights into its prediction and prevention. We applied finite element analysis (FEA) to assess stress distribution on a rare dataset comprising computed tomography (CT) images obtained from eight patients at three stages of aortic dissection: pre-dissection (preD), post-dissection (postD), and post-repair (postR). Our findings reveal significant increases in both mean and peak aortic wall stresses during the transition from the preD state to the postD state, reflecting the mechanical impact of dissection. Surgical repair effectively restores aortic wall diameter to pre-dissection levels, documenting its effectiveness in mitigating further complications. Furthermore, we identified stress concentration regions within the aortic wall that closely correlated with observed dissection borders, offering insights into high-risk areas. This study demonstrates the importance of considering biomechanical factors when assessing aortic dissection risk. Despite some limitations, such as uniform wall thickness assumptions and the absence of dynamic blood flow considerations, our patient-specific FEA approach provides valuable mechanistic insights into aortic dissection. These findings hold promise for improving predictive models and informing clinical decisions to enhance patient care.

Integration of cross-links, discrete fiber distributions and of a non-local theory in the Homogenized Constrained Mixture Model to Simulate Patient-Specific Thoracic Aortic Aneurysm Progression

Thoracic aortic aneurysms (TAA) represent a critical health issue for which computational models can significantly contribute to better understand the physiopathology. Among different computational frameworks, the Homogenized Constrained Mixture Theory has shown to be a computationally efficient option, allowing the inclusion of several mechanically significant constituents into a layer-specific mixture. Different patient-specific Growth and Remodeling (G&R) models correctly predicted TAA progression, although simplifications such as the inclusion of a limited number of collagen fibers and imposed boundary conditions might limit extensive analyses. The current study aims to enhance existing models by incorporating several discrete collagen fibers and to remove restrictive boundary conditions of the previous models. The implementation of discretized fiber dispersion presents a more realistic description of the vessel, while the removal of boundary conditions was addressed by including cross-links in the model to provide a supplemental stiffness against through-thickness shearing, a feature that was previously absent, and by the development of a non-local framework that ensures the stable deposition and degradation of collagen fibers. With these improvements, the current model represents a step forward towards more robust and comprehensive simulations of TAA growth.

Image-based simulation of mitral valve dynamic closure including anisotropy

Simulation of the dynamic behavior of mitral valve closure could improve clinical treatment by predicting surgical procedures outcome. We propose here a method to achieve this goal by using the immersed boundary method. In order to go towards patient-based simulation, we tailor our method to be adapted to a valve extracted from medical image data. It includes investigating segmentation process, smoothness of geometry, case setup and the shape of the left ventricle. We also study the influence of leaflet tissue anisotropy on the quality of the valve closure by comparing with an isotropic model. As part of the anisotropy analysis, we study the influence of the principal material direction by comparing methods to obtain them without dissection. Results show that our method can be scaled to various image-based data. We evaluate the mitral valve closure quality based on measuring bulging area, contact map, and flow rate. The results show also that the anisotropic material model more precisely represents the physiological characteristics of the valve tissue. Furthermore, results indicate that the orientation of the principal material direction plays a role in the effectiveness of the valve seal.