Physiological Boundary Conditions Research Articles

Predicting red blood cell traffcking and capillary hemodynamics in angiogenic and tumor microcirculation in silico

Objective: Angiogenic and tumor microvasculatures are known to have abnormal topology due to the presence of frequent vessel junctions, irregular and deflated blood vessels, multi-furcations, and tessellated vessel organization. Although recent advances in imaging techniques in vivo have enabled mapping such vasculatures at high spatial resolution, simultaneous measurements of hemodynamic parameters, such as the wall shear stress (WSS) with full 3D details, remain a challenge. Theoretical network flow models, often used for hemodynamic predictions in such experimentally acquired images, cannot provide the full 3D hemodynamic details either, as these models treat each blood vessel as 1D segment and do not explicitly model red blood cells (RBCs). To overcome this limitation, we have developed a high-fidelity, 3D Computational Fluid Dynamics modeling to predict the flow of a large number of deformable RBCs through physiologically realistic tumor/angiogenic microvascular networks in silico. Methods: We use in vivo images to create such vascular networks in silico and then predict RBC traffcking and capillary hemodynamics. Deformation of every flowing RBC is considered with high accuracy, and 3D geometry of each vessel is accurately modeled. Flow is driven by specifying physiological pressure boundary conditions. Model predictions have been validated against in vivo data. This in-house predictive tool is versatile, can be applied to any microvascular network image obtained in vivo in any organ, and can predict trajectories of diverse cell types including leukocytes, platelets and circulating tumor cells, drug and molecular transport in capillary blood, and cell-vessel adhesion. Results: We provide quantitative differences between healthy microvascular networks and tumor/angiogenic networks in terms of RBC distribution, perfusion, and wall shear stress. Our model shows increased heterogeneity in RBC and flow distribution in both tumor and angiogenic vasculatures than the healthy one. Also, we predict reduced flow and hematocrit in several vessels in both tumor and angiogenic vasculatures. Interestingly, several vessels in the angiogenic vasculature are predicted to have higher flow than the healthy one, while most vessels in the tumor vasculature show flow reduction. This in silico prediction is consistent with a recent in vivo study which showed higher flow in peri-tumor region and reduced flow in tumor. We further predict a significant heterogeneity in WSS and WSS gradient, blood velocity profiles, and near-wall RBC-depleted region. Conclusion: In conclusion, we have developed a versatile, in silico model that allows high-fidelity prediction of capillary hemodynamics in tumor microcirculation and provide information on hemodynamic variables that are not readily measurable in vivo but have physiological significance in tumor progression and treatment. NIH (R01EY033003) and NSF (CBET1804591). This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Prosthetic framework improvement using lattice structure: A comparative finite element study of a mandibular implant-supported prosthesis

Objectives:An alternative option was proposed regarding the prosthetic rehabilitation of a fully edentulous mandible using only four implants. The aim was to reduce the stiffness of the prosthetic framework. To that end, the alternative option consists of a prosthetic framework optimized with a porous structure. Mechanical differences were analyzed between non-prosthetic mandible and restored mandible either with a conventional bulk titanium framework or with this alternative option. The non-prosthetic mandible corresponds to the mandible in its natural state, without prosthesis. This will be considered as the reference for comparison with restored models (mandible with prosthesis). Methods:Three models are used: the first one is the non-prosthetic mandible, the second one is the restored mandible with conventional bulk titanium prosthetic framework, and the third one is the alternative option. Prosthetic framework was optimized with the use of a lattice structure. A numerical analysis was performed (with Abaqus Standard software®) to obtain the effective parameters corresponding to equivalent homogeneous behavior. In the 3 models, physiological boundary conditions were used, considering the activity of several muscles of the masticatory system during three main tasks of mastication (incisive clenching, maximum intercuspation and unilateral molar clenching). Results:Numerical simulations allowed to obtain mandibular global kinematics, local displacement at the bone–implant interface and the state of strain at the bone–implant interface, for each masticatory tasks. For this comparative study, the non-prosthetic mandible model was used as a reference to observe the benefits of using a lattice prosthetic framework compared to a conventional bulk titanium framework. Conclusion:Compared to conventional titanium framework, the lattice prosthetic one appeared to be more respectful of the natural mandible kinematics, given by the reference model. It also resulted in strain values within the physiological loading range.

Design of experiment approach to identify the dominant geometrical feature of left coronary artery influencing atherosclerosis

Background and Objective. Coronary artery geometry heavily influences local hemodynamics, potentially leading to atherosclerosis. Consequently, the unique geometrical configuration of an individual by birth can be associated with future risk of atherosclerosis. Although current researches focus on exploring the relationship between local hemodynamics and coronary artery geometry, this study aims to identify the order of influence of the geometrical features through systematic experiments, which can reveal the dominant geometrical feature for future risk assessment. Methods. According to Taguchi’s method of design of experiment (DoE), the left main stem (LMS) length (l LMS), curvature (k LMS), diameter (d LMS) and the bifurcation angle between left anterior descending (LAD) and left circumflex (LCx) artery (α LAD-LCx) of two reconstructed patient-specific left coronary arteries (LCA) were varied in three levels to create L9 orthogonal array. Computational fluid dynamic (CFD) simulations with physiological boundary conditions were performed on the resulting eighteen LCA models. Average helicity intensity (h 2) and relative atheroprone area (RAA) of near-wall hemodynamic descriptors were analyzed. Results. The proximal LAD (LAD proximal) was identified to be the most atheroprone region of the left coronary artery due to higher h 2, large RAA of time averaged wall shear stress (TAWSS < 0.4 Pa), oscillatory shear index (OSI ∼ 0.5) and relative residence time (RRT > 4.17 Pa−1). In both patient-specific cases, based on h 2 and TAWSS, d lms is the dominant geometric parameter while based on OSI and RRT, α LAD-LCx is the dominant one influencing hemodynamic condition in proximal LAD (p < 0.05). Based on RRT, the rank of the geometrical factors is: α LAD-LCx > d LMS > l LMS > k LMS, indicating that α LAD-LCx is the most dominant geometrical factor affecting hemodynamics at proximal LAD which may influence atherosclerosis. Conclusion. The proposed identification of the rank of geometrical features of LCA and the dominant feature may assist clinicians in predicting the possibility of atherosclerosis, of an individual, long before it will occur. This study can further be translated to be used to rank the influence of several arterial geometrical features at different arterial locations to explore detailed relationships between the arterial geometrical features and local hemodynamics.

Accelerated simulation methodologies for computational vascular flow modelling.

Vascular flow modelling can improve our understanding of vascular pathologies and aid in developing safe and effective medical devices. Vascular flow models typically involve solving the nonlinear Navier-Stokes equations in complex anatomies and using physiological boundary conditions, often presenting a multi-physics and multi-scale computational problem to be solved. This leads to highly complex and expensive models that require excessive computational time. This review explores accelerated simulation methodologies, specifically focusing on computational vascular flow modelling. We review reduced order modelling (ROM) techniques like zero-/one-dimensional and modal decomposition-based ROMs and machine learning (ML) methods including ML-augmented ROMs, ML-based ROMs and physics-informed ML models. We discuss the applicability of each method to vascular flow acceleration and the effectiveness of the method in addressing domain-specific challenges. When available, we provide statistics on accuracy and speed-up factors for various applications related to vascular flow simulation acceleration. Our findings indicate that each type of model has strengths and limitations depending on the context. To accelerate real-world vascular flow problems, we propose future research on developing multi-scale acceleration methods capable of handling the significant geometric variability inherent to such problems.

Analytic solution for pulse wave propagation in flexible tubes with application to a patient-specific arterial tree

In this paper, we present an analytic solution for pulse wave propagation in a flexible arterial model with tapering, physiological boundary conditions and variable wall properties (wall elasticity and thickness). The change of wall properties follows a profile that is proportional to $r^\alpha$ , where $r$ represents the lumen radius and $\alpha$ is a material coefficient. The cross-sectionally averaged velocity and pressure are obtained by solving a hyperbolic system derived from the mass and momentum conservations, and they are expressed in Bessel functions of order $(4-\alpha )/(3-\alpha )$ and $1/(3-\alpha )$ , respectively. The solution is successfully validated by comparing it with numerical results from three-dimensional (3-D) fluid–structure interaction simulations. Subsequently, the solution is employed to study pulse wave propagation in an arterial model, revealing that the wall properties and the physiological outlet boundary conditions, such as the resistor–capacitor–resistor (RCR) model, play a crucial role in characterizing the input impedance and reflection coefficient. At low-frequency range, the input impedance is found to be insensitive to the wall properties and is primarily determined by the RCR parameters. At high-frequency range, the input impedance oscillates around the local characteristic impedance, and the oscillation amplitude varies non-monotonically with $\alpha$ . Expressions for the input impedance at both low-frequency and high-frequency limits are presented. This analytic solution is also successfully applied to model flow inside a patient-specific arterial tree, with the maximum relative errors in pressure and flow rate never exceeding $1.6\,\%$ and $9.0\,\%$ when compared with results from 3-D numerical simulations.

Abstract 14675: The Role of Biomechanics in Diagnosis and Evaluation of Coronary Artery Disease

While there is a strong need to assess the safety and efficacy of novel therapies prior to evaluation in human patients, the ability to accurately model the complexities of coronary disease in-vitro and/or animal models is somewhat limited. Animal models, even those with genetic predispositions toward coronary disease do not exhibit high grade stenoses, similar to those that require treatment in human patients. At the same time, most in-vitro models and simulations of fluid-structure interactions cannot simultaneously capture the complex geometries, hemodynamics, and biomechanical response of human coronary disease. Here, we introduce a robust workflow to replicate an in-vitro platform incorporating compliant, realistic diseased coronary arteries in a flow loop under physiological conditions. Through ex-vivo imaging of cadaveric specimens, coupled with co-registered measurements of coronary biomechanics, we developed protocols that allow for fabrication and testing of highly realistic 3D printed models. The anatomical and biomechanical features of the coronary arteries, including local variations associated with the observed disease burdens were extracted and 3D printed, in high spatial resolution, using commercially available printers, making this methodology conveniently reproducible. Subsequently, the models were incorporated in a testing platform made of flow loops and valve resistance to mimic circulation and microvascular resistance respectively. Under physiological boundary conditions, we successfully collected measurements along the length of the vessels that exhibit a range of biomechanical characteristics from low to high values of modulus and assessed the impact of biomechanics on gold standard diagnostic and prognostic measures such as Fractional Flow Reserve. We demonstrated that incorporating the effects of local biomechanics significantly improves the predicted hemodynamics metrics with respect to ex-vivo coronaries.

A two-scale numerical study on the mechanobiology of abdominal aortic aneurysms.

Abdominal aortic aneurysms (AAAs) are a serious condition whose pathophysiology is related to phenomena occurring at different length scales. To gain a better understanding of the disease, this work presents a multi-scale computational study that correlates AAA progression with microstructural and mechanical alterations in the tissue. Macro-scale geometries of a healthy aorta and idealized aneurysms with increasing diameter are developed on the basis of existing experimental data and subjected to physiological boundary conditions. Subsequently, microscopic representative volume elements of the abluminal side of each macro-model are employed to analyse the local kinematics at the cellular scale. The results suggest that the formation of the aneurysm disrupts the micromechanics of healthy tissue, which could trigger collagen growth and remodelling by mechanosensing cells. The resulting changes to the macro-mechanics and microstructure of the tissue seem to establish a new homeostatic state at the cellular scale, at least for the diameter range investigated.

Femurs segmentation by machine learning from CT scans combined with autonomous finite elements in orthopedic and endocrinology applications

Efficient, accurate and reliable segmentation of femurs from CT-scans is of major importance for patient-specific autonomous finite element analysis (AFE) to determine bone's stiffness and strength. We present a fully automated segmentation algorithm for whole and partial femurs with or without tumors, and clinical applications of the AFE [1] in clinical practice.The segmentation is based on an U-Net convolutional neural network, resulting a 3D mask representing the desired femur in a CT scan. It is robust, independent of the scanning parameters such as slice spacing, pixel size, scanner manufacturer or the femoral length available in the scan. The U-Net was trained on 178 manually segmented femurs (23,721 images) and tested on 43. The performance evaluation resulted in a Dice similarity score (DSC) of 0.9924, intersection over union (IoU) of 0.9849, Hausdorff distance of 4.3315 mm and symmetric average surface distance (ASD) of 0.1326 mm. The algorithm is competitive with the best state-of-the-art femoral segmentation methodologies available.Based on the segmentation an automatic p-FE mesh is generated and physiological boundary conditions representing sidewise falls or stance are being applied automatically to improve the performance of the AFE described in [1]. New examples of the usage of the AFE in endocrinology and orthopedic oncology demonstrate this disruptive technology in actual clinical practice. We present the use of AFE for predicting hip fracture risk in the elderly population due to a sidewise fall and the identification of patients who require a prophylactic surgery due to metastatic tumors in their femurs.

Structural numerical analysis of a branched modular stent-graft for aneurysms encompassing all zones of the aortic arch

The development of stent-grafts for the total repair of aneurysms in the aortic arch is still a technical challenge due mainly to the anatomical complexity of this region. Research performed here structurally evaluated a modular branched stent-graft for aneurysms encompassing all zones of the aortic arch by means of numerical simulations using fluid–structure interaction. The geometric domain obtained by means of computed tomography was subjected to physiological boundary conditions. The blood was modelled as non-Newtonian by the Carreau model, and the arterial wall was modelled as anisotropic hyperelastic by the Holzapfel model. The material adopted for the stents was Nitinol, and expanded polytetrafluoroethylene (ePTFE) was used for the graft. A comparison of the structural behaviour of the aneurysmal aortic arch before and after stent-graft implantation was performed. The numerical flow model was experimentally verified in vitro on a representative test bench of blood flow in the aortic arch. The stent-graft was shown to minimally modify arterial wall dynamics and was not susceptible to migration and endoleak. Peak stresses and strains were found in the stents and graft, respectively, while the stresses in the aneurysm sac were significantly reduced, of the order of 97.5%, due to the isolation of the arterial wall by the stent-graft.

Advancing Risk Stratification of Coronary Artery Aneurysms Caused by Kawasaki Disease Using Hemodynamics Analysis and Computational Fluid Dynamics

This article reviews previous studies on the risk assessment of coronary artery aneurysms (CAA) caused by Kawasaki disease (KD) using the computational fluid dynamics (CFD) simulation. Patient-specific CFD is an emerging tool that provides detailed three-dimensional hemodynamic information, not available from current standard imaging techniques or invasive measures. The reviewed CFD studies on KD CAA used Computed Tomography (CT) or Magnetic Resonance Imaging (MRI) images to reconstruct the three-dimensional anatomical geometry consisting of the aorta and coronary arteries. On the inlet and outlet of the anatomical model, physiologic boundary conditions were prescribed to match the measured patient-specific blood pressure or flow data, supplemented by physiologic rules informed by population studies. Hemodynamic variables such as the blood velocity, wall shear stress, oscillatory shear index, fractional flow reserve, and particle residence time, were then quantified from the simulation results. The studies reviewed revealed strong correlations between these hemodynamic parameters and clinical outcomes, suggesting that hemodynamic metrics could be useful for treatment planning for KD patients. We discuss the limitations of the reviewed studies including small sample sizes, a narrow focus on thrombosis, and the use of different imaging modalities. The article suggests future research directions for CFD studies of KD that address these limitations.

Muscle preflex response to perturbations in locomotion: In vitro experiments and simulations with realistic boundary conditions.

Neuromuscular control loops feature substantial communication delays, but mammals run robustly even in the most adverse conditions. In vivo experiments and computer simulation results suggest that muscles' preflex-an immediate mechanical response to a perturbation-could be the critical contributor. Muscle preflexes act within a few milliseconds, an order of magnitude faster than neural reflexes. Their short-lasting action makes mechanical preflexes hard to quantify in vivo. Muscle models, on the other hand, require further improvement of their prediction accuracy during the non-standard conditions of perturbed locomotion. Our study aims to quantify the mechanical work done by muscles during the preflex phase (preflex work) and test their mechanical force modulation. We performed in vitro experiments with biological muscle fibers under physiological boundary conditions, which we determined in computer simulations of perturbed hopping. Our findings show that muscles initially resist impacts with a stereotypical stiffness response-identified as short-range stiffness-regardless of the exact perturbation condition. We then observe a velocity adaptation to the force related to the amount of perturbation similar to a damping response. The main contributor to the preflex work modulation is not the change in force due to a change in fiber stretch velocity (fiber damping characteristics) but the change in magnitude of the stretch due to the leg dynamics in the perturbed conditions. Our results confirm previous findings that muscle stiffness is activity-dependent and show that also damping characteristics are activity-dependent. These results indicate that neural control could tune the preflex properties of muscles in expectation of ground conditions leading to previously inexplicable neuromuscular adaptation speeds.

Irregular anatomical features can alter hemodynamics in Takayasu arteritis

ObjectiveTakayasu arteritis (TA) is a difficult disease to deal with because there are neither reliable clinical signs, laboratory biomarkers, nor a single noninvasive imaging technique that can be used for early diagnosis and disease activity monitoring. Knowledge of aortic hemodynamics in TA is lacking. This study aimed to fill this gap by assessing hemodynamics in patients with TA using image-based computational fluid dynamics (CFD) simulations. MethodsEleven patients with TA were included in the present study. Patient-specific geometries were reconstructed from either clinical aortic computed tomography angiography or magnetic resonance angiography studies and coupled with physiological boundary conditions for CFD simulations. Key anatomical and hemodynamic parameters were compared with a control group consisting of 18 age- and sex-matched adults without TA who had healthy aortas. ResultsCompared with controls, patients with TA had significantly higher aortic velocities (0.9 m/s [0.7, 1.1 m/s] vs 0.6 m/s [0.5, 0.7 m/s]; P = .002), maximum time-averaged wall shear stress (14.2 Pa [9.8, 20.9 Pa] vs 8.0 Pa [6.2, 10.3 Pa]; P = .004), and maximum pressure drops between the ascending and descending aorta (36.9 mm Hg [29.0, 49.3 mm Hg] vs 28.5 mm Hg [25.8, 31.5 mm Hg]; P = .004). These significant hemodynamic alterations in patients with TA might result from abnormal anatomical features including smaller arch diameter (20.0 mm [13.8, 23.3 mm] vs 25.2 mm [23.3, 26.8 mm]; P = .003), supra-aortic branch diameters (21.9 mm [18.5, 24.6 mm] vs 25.7 mm [24.3, 28.3 mm]; P = .003) and descending aorta diameter (14.7 mm [12.2, 16.8 mm] vs 22.5 mm [19.8, 24.0 mm]; P < .001). ConclusionsCFD analysis reveals hemodynamic changes in the aorta of patients with TA. The applicability of CFD technique coupled with standard imaging assessments in predicting disease progression of such patients will be explored in future studies. Future large cohort study with outcome correlation is also warranted. Clinical RelevanceBased on patient-specific computational fluid dynamics simulations, the present retrospective study revealed significant difference in aortic hemodynamics between the patients with and without Takayasu arteritis (TA). To the best of our knowledge, this study is the first to evaluate hemodynamic conditions within TA, demonstrating the potential of computational flow modeling in capturing abnormal hemodynamic forces, such as high wall shear stress, resulted from irregular morphological changes. In the future, assessing the hemodynamic parameters within patients with TA during the prestenotic period, together with longitudinal computational fluid dynamics studies may allow better monitoring and management of TA.

Computational fluid dynamics model to predict the dynamical behavior of the cerebrospinal fluid through implementation of physiological boundary conditions.

Cerebrospinal fluid (CSF) dynamics play an important role in maintaining a stable central nervous system environment and are influenced by different physiological processes. Multiple studies have investigated these processes but the impact of each of them on CSF flow is not well understood. A deeper insight into the CSF dynamics and the processes impacting them is crucial to better understand neurological disorders such as hydrocephalus, Chiari malformation, and intracranial hypertension. This study presents a 3D computational fluid dynamics (CFD) model which incorporates physiological processes as boundary conditions. CSF production and pulsatile arterial and venous volume changes are implemented as inlet boundary conditions. At the outlets, 2-element windkessel models are imposed to simulate CSF compliance and absorption. The total compliance is first tuned using a 0D model to obtain physiological pressure pulsations. Then, simulation results are compared with in vivo flow measurements in the spinal subarachnoid space (SAS) and cerebral aqueduct, and intracranial pressure values reported in the literature. Finally, the impact of the distribution of and total compliance on CSF pressures and velocities is evaluated. Without respiration effects, compliance of 0.17ml/mmHg yielded pressure pulsations with an amplitude of 5mmHg and an average value within the physiological range of 7-15mmHg. Also, model flow rates were found to be in good agreement with reported values. However, when adding respiration effects, similar pressure amplitudes required an increase of compliance value to 0.51ml/mmHg, which is within the range of 0.4-1.2ml/mmHg measured in vivo. Moreover, altering the distribution of compliance over the four different outlets impacted the local flow, including the flow through the foramen magnum. The contribution of compliance to each outlet was directly proportional to the outflow at that outlet. Meanwhile, the value of total compliance impacted intracranial pressure. In conclusion, a computational model of the CSF has been developed that can simulate CSF pressures and velocities by incorporating boundary conditions based on physiological processes. By tuning these boundary conditions, we were able to obtain CSF pressures and flows within the physiological range.

Boundary Conditions and Long-Term Implantation Effects with Cardiovascular Nitinol Implants

Nitinol-based cardiovascular implants are used frequently to treat a wide range of cardiovascular diseases. Accordingly, understanding the durability of these devices once deployed into the geometrically dynamic cardiovascular system is of critical importance. While the fundamental material properties of Nitinol are relatively well understood, the boundary conditions imposed on Nitinol-based devices by the cardiovascular system and the corresponding effects on durability are not as well understood. Moreover, longitudinal studies report mixed long-term outcomes which raises question about long-term durability of cardiovascular implants. Understanding of the physiologic boundary conditions with focus on the regions with high mobility can warrant not only the short-term benefit, but also the long-term success with minimized incidence of implant-driven complications. In this article, Nitinol-based implants for the aortic valve, cerebral arteries, thoracic aorta, renovisceral arteries, and peripheral arteries are considered, research studies characterizing related variations in cardiovascular geometry are detailed, and summaries of available clinical studies reporting on outcomes are provided.

A Pilot Study Characterizing Flow Patterns in the Thoracic Aorta of Patients With Connective Tissue Disease: Comparison to Age- and Gender-Matched Controls via Fluid Structure Interaction

Prior computational and imaging studies described changes in flow patterns for patients with Marfan syndrome, but studies are lacking for related populations. This pilot study addresses this void by characterizing wall shear stress (WSS) indices for patients with Loeys-Dietz and undifferentiated connective tissue diseases. Using aortic valve-based velocity profiles from magnetic resonance imaging as input to patient-specific fluid structure interaction (FSI) models, we determined local flow patterns throughout the aorta for four patients with various connective tissue diseases (Loeys-Dietz with the native aorta, connective tissue disease of unclear etiology with native aorta in female and male patients, and an untreated patient with Marfan syndrome, as well as twin patients with Marfan syndrome who underwent valve-sparing root replacement). FSI simulations used physiological boundary conditions and material properties to replicate available measurements. Time-averaged WSS (TAWSS) and oscillatory shear index (OSI) results are presented with localized comparison to age- and gender-matched control participants. Ascending aortic dimensions were greater in almost all patients with connective tissue diseases relative to their respective control. Differences in TAWSS and OSI were driven by local morphological differences and cardiac output. For example, the model for one twin had a more pronounced proximal descending aorta in the vicinity of the ductus ligamentum that impacted WSS indices relative to the other. We are optimistic that the results of this study can serve as a foundation for larger future studies on the connective tissue disorders presented in this article.

In Silico Biomechanical Evaluation of WE43 Magnesium Plates for Mandibular Fracture Fixation.

Titanium fixation devices are the gold standard for the treatment of mandibular fractures; however, they present serious limitations, such as non-degradability and generation of imaging artifacts. As an alternative, biodegradable magnesium alloys have lately drawn attention due to their biodegradability and biocompatibility. In addition, magnesium alloys offer a relatively high modulus of elasticity in comparison to biodegradable polymers, being a potential option to substitute titanium in highly loaded anatomical areas, such as the mandible. This study aimed to evaluate the biomechanical competence of magnesium alloy WE43 plates for mandibular fracture fixation in comparison to the clinical standard or even softer polymer solutions. A 3D finite element model of the human mandible was developed, and four different fracture scenarios were simulated, together with physiological post-operative loading and boundary conditions. In a systematic comparison, the material properties of titanium alloy Ti-6Al-4V, magnesium alloy WE43, and polylactic acid (PLA) were assigned to the fixation devices, and two different plate thicknesses were tested. No failure was predicted in the fixation devices for any of the tested materials. Moreover, the magnesium and titanium fixation devices induced a similar amount of strain within the healing regions. On the other hand, the PLA devices led to higher mechanical strains within the healing region. Plate thickness only slightly influenced the primary fixation stability. Therefore, magnesium alloy WE43 fixation devices seem to provide a suitable biomechanical environment to support mandibular fracture healing in the early stages of bone healing. Magnesium WE43 showed a biomechanical performance similar to clinically used titanium devices with the added advantages of biodegradability and radiopacity, and at the same time it showed a remarkably higher primary stability compared to PLA fixation devices, which appear to be too unstable, especially in the posterior and more loaded mandibular fracture cases.

A quasi-static poromechanical model of the lungs.

The lung vital function of providing oxygen to the body heavily relies on its mechanical behavior and the interaction with its complex environment. In particular, the large compliance and the porosity of the pulmonary tissue are critical for lung inflation and air inhalation, and the diaphragm, the pleura, the rib cage and intercostal muscles all play a role in delivering and controlling the breathing driving forces. In this paper, we introduce a novel poromechanical model of the lungs. The constitutive law is derived within a general poromechanics theory via the formulation of lung-specific assumptions, leading to a hyperelastic potential reproducing the volume response of the pulmonary mixture to a change of pressure. Moreover, physiological boundary conditions are formulated to account for the interaction of the lungs with their surroundings, including a following pressure and bilateral frictionless contact. A strategy is established to estimate the unloaded configuration from a given loaded state, with a particular focus on ensuring a positive porosity. Finally, we illustrate through several realistic examples the relevance of our model and its potential clinical applications.

Haemodynamic Analysis of Branched Endografts for Complex Aortic Arch Repair.

This study aims to investigate the haemodynamic response induced by implantation of a double-branched endograft used in thoracic endovascular aortic repair (TEVAR) of the aortic arch. Anatomically realistic models were reconstructed from CT images obtained from patients who underwent TEVAR using the RelayPlus double-branched endograft implanted in the aortic arch. Two cases (Patient 1, Patient 2) were included here, both patients presented with type A aortic dissection before TEVAR. To examine the influence of inner tunnel branch diameters on localised flow patterns, three tunnel branch diameters were tested using the geometric model reconstructed for Patient 1. Pulsatile blood flow through the models was simulated by numerically solving the Navier–Stokes equations along with a transitional flow model. The physiological boundary conditions were imposed at the model inlet and outlets, while the wall was assumed to be rigid. Our simulation results showed that the double-branched endograft allowed for the sufficient perfusion of blood to the supra-aortic branches and restored flow patterns expected in normal aortas. The diameter of tunnel branches in the device plays a crucial role in the development of flow downstream of the branches and thus must be selected carefully based on the overall geometry of the vessel. Given the importance of wall shear stress in vascular remodelling and thrombus formation, longitudinal studies should be performed in the future in order to elucidate the role of tunnel branch diameters in long-term patency of the supra-aortic branches following TEVAR with the double-branched endograft.

Impact of juxta-anastomotic stent implantation on the haemodynamics within a single representative patient AVF

An arteriovenous fistula (AVF), a vascular structure surgically created to enable haemodialysis, is commonly affected by stenosis in the juxta-anastomotic region. A new treatment involving the implantation of a flexible stent has shown good potential for retaining healthy AVFs. Since vascular disease in the AVF is known to be related to the haemodynamic environment within the vasculature, this study aims to understand the impact of the stent implantation on the flow dynamics within a single patient-specific AVF. A virtual stented geometry of the AVF was obtained with micro-CT images of a benchtop AVF model implanted with a Supera stent. Reynolds averaged Navier–Stokes simulations were conducted with physiological boundary conditions (Reynolds numbers varying from 345 to 730) applied on the AVF model with and without the presence of the stent. Velocity contour slices within the vein showed the concentration of high velocity in the stent encapsulated region. Moreover, the ratios of flow rate across the stent-lumen cross-sections over the flow rate across the vessel-lumen cross-sections suggested that the flow was being funnelled through the stent encapsulated regions of a malapposed section, despite the porous structure of the stent. A larger low velocity recirculation region translated to a larger vessel wall area of high Oscillatory Shear Index (OSI) and low Time-Averaged Wall Shear Stress (TAWSS) in the AVF model with the stent absent, compared to the stented model. This suggested that the adverse haemodynamic behaviour was being funnelled away from the vessel wall, possibly leading to a protective environment in the malapposed region of the vein.

Abstract 9587: Combined Aortic Regurgitation and Stenosis of the Bicuspid Aortic Valve Increases Ascending Aortic Wall Shear Stress and Left Ventricle Energy Burden

Introduction: The bicuspid aortic valve (BAV) opening pattern and the degree of aortic stenosis (AS) are reportedly associated with the aneurysmal formation in the ascending aorta. Although AS is often accompanied by aortic regurgitation (AR), the combined effect of AR and AS on the wall of the ascending aorta and energy loss of the blood flow are not well understood. Hypothesis: We hypothesize that AR along with AS can increase the wall shear stress (WSS) to develop the aneurysm in the ascending aorta and increase the load on the left ventricle (LV). Methods: The effects of AR along with AS BAV on the hemodynamic features were assessed using an image-based subject-specific LV-aorta integrated computational model. The computational model was constructed based on an MRI dataset of a 72-year-old healthy volunteer. Four different types of stenosed (52% stenosis) BAV models were created: Type 0, RL fused, RN fused, and LN fused. Then, physiological boundary conditions were given based on a parameter-adjusted 0-1D cardiovascular model of the AS BAV with no AR, mild AR (17% regurgitant fraction (RF)), and severe AR (48% RF) to assess hemodynamic indices such as time-average of WSS in the ascending aorta and pulsatile energy loss index (PELI), an index to estimate energy loss in the aorta. Results: Averaged WSS was highest in the severe AR with AS BAV in 4.1±0.2 Pa, followed by the mild AR with AS BAV in 3.1±0.21 Pa, and no AR with AS BAV in 2.7±0.3 Pa. The intra-ventricular flow (LV) showed more disturbed flow in mid-diastole in severe AR with AS BAV. PELI was augmented in mild AR with AS BAV in 0.34±0.05 and severe AR with AS BAV in 0.25±0.06, compared to no AR with AS BAV in 0.19±0.16. Conclusions: AR along with AS in BAV has a great impact on increasing the WSS in the ascending aorta and increasing the energy loss of the flow in the aorta. These features imply that advanced AR along with AS in BAV may raise the risk of the development of aortic aneurysm as well as heart failure due to the increased workload on the LV.