The role of the pulmonary veins on left atrial flow patterns and thrombus formation.

Atrial fibrillation (AF) is the most common human arrhythmia, forming thrombi mostly in the left atrial appendage (LAA). However, the relation between LAA morphology, blood patterns and clot formation is not yet fully understood. Furthermore, the impact of anatomical structures like the pulmonary veins (PVs) have not been thoroughly studied due to data acquisition difficulties. In-silico studies with flow simulations provide a detailed analysis of blood flow patterns under different boundary conditions, but a limited number of cases have been reported in the literature. To address these gaps, we investigated the influence of PVs on LA blood flow patterns and thrombus formation risk through computational fluid dynamics simulations conducted on a sizeable cohort of 130 patients, establishing the largest cohort of patient-specific LA fluid simulations reported to date. The investigation encompassed an in-depth analysis of several parameters, including pulmonary vein orientation (e.g., angles) and configuration (e.g., number), LAA and LA volumes as well as their ratio, flow, and mass-less particles. Our findings highlight the total number of particles within the LAA as a key parameter for distinguishing between the thrombus and non-thrombus groups. Moreover, the angles between the different PVs play an important role to determine the flow going inside the LAA and consequently the risk of thrombus formation. The alignment between the LAA and the main direction of the left superior pulmonary vein, or the position of the right pulmonary vein when it exhibits greater inclination, had an impact to distinguish the control group vs. the thrombus group. These insights shed light on the intricate relationship between PV configuration, LAA morphology, and thrombus formation, underscoring the importance of comprehensive blood flow pattern analyses.

On the importance of fundamental computational fluid dynamics toward a robust and reliable model of left atrial flows.

Computational fluid dynamics (CFD) studies of left atrial flows have reached a sophisticated level, for example, revealing plausible relationships between hemodynamics and stresses with atrial fibrillation. However, little focus has been on fundamental fluid modeling of LA flows. The purpose of this study was to investigate the spatiotemporal convergence, along with the differences between high- (HR) versus normal-resolution/accuracy (NR) solution strategies, respectively. Rigid wall CFD simulations were conducted on 12 patient-specific left atrial geometries obtained from computed tomography scans, utilizing a second-order accurate and space/time-centered solver. The convergence studies showed an average variability of around 30% and 55% for time averaged wall shear stress (WSS), oscillatory shear index (OSI), relative residence time (RRT), and endothelial cell activation potential (ECAP), even between intermediate spatial and temporal resolutions, in the left atrium (LA) and left atrial appendage (LAA), respectively. The comparison between HR and NR simulations showed good correlation in the LA for WSS, RRT, and ECAP ( R 2 > .9 ), but not for OSI ( R 2 = .63 ). However, there were poor correlations in the LAA especially for OSI, RRT, and ECAP ( R 2 = .55, .63, and .61, respectively), except for WSS ( R 2 = .81 ). The errors are comparable to differences previously reported with disease correlations. To robustly predict atrial hemodynamics and stresses, numerical resolutions of 10 M elements (i.e., Δ x = ∼ .5 mm) and 10 k time-steps per cycle seem necessary (i.e., one order of magnitude higher than normally used in both space and time). In conclusion, attention to fundamental numerical aspects is essential toward establishing a plausible, robust, and reliable model of LA flows.

Domain expert evaluation of advanced visual computing solutions and 3D printing for the planning of the left atrial appendage occluder interventions.

Advanced visual computing solutions and three-dimensional (3D) printing are moving from engineering to clinical pipelines for training, planning, and guidance of complex interventions. 3D imaging and rendering, virtual reality (VR), and in-silico simulations, as well as 3D printing technologies provide complementary information to better understand the structure and function of the organs, thereby improving and personalizing clinical decisions. In this study, we evaluated several advanced visual computing solutions, such as web-based 3D imaging visualization, VR, and computational fluid simulations, together with 3D printing, for the planning of the left atrial appendage occluder (LAAO) device implantations. Six cardiologists tested different technologies in pre-operative data of five patients to identify the usability, limitations, and requirements for the clinical translation of each technology through a qualitative questionnaire. The obtained results demonstrate the potential impact of advanced visual computing solutions and 3D printing to improve the planning of LAAO interventions as well as the need for their integration into a single workflow to be used in a clinical environment.

Joint Analysis of Morphological Parameters and In Silico Haemodynamics of the Left Atrial Appendage for Thrombogenic Risk Assessment.

Background: Atrial fibrillation (AF) is considered the most common human arrhythmia. In nonvalvular AF, around 99% of thrombi are formed in the left atrial appendage (LAA). Nevertheless, there is not a consensus in the community about the relevant factors to stratify the AF population according to thrombogenic risk. Objective: To demonstrate the need for combining left atrial morphological and haemodynamics indices to improve the thrombogenic risk assessment in nonvalvular AF patients. Methods: A cohort of 71 nonvalvular AF patients was analysed. Statistical analysis, regression models, and random forests were used to analyse the differences between morphological and haemodynamics parameters, extracted from computational simulations built on 3D rotational angiography images, between patients with and without transient ischemic attack (TIA) or cerebrovascular accident (CVA). Results: The analysis showed that models composed of both morphological and haemodynamic factors were better predictors of TIA/CVA compared with models based on either morphological or haemodynamic factors separately. Maximum ostium diameter, length of the centreline, blood flow velocity within the LAA, oscillatory shear index, and time average wall shear stress parameters were found to be key risk factors for TIA/CVA prediction. In addition, TIA/CVA patients presented more flow stagnation within the LAA. Conclusion: Thrombus formation in the LAA is the result of multiple factors. Analyses based only on morphological or haemodynamic parameters are not precise enough to predict such a phenomenon, as demonstrated in our results; a better patient stratification can be obtained by jointly analysing morphological and haemodynamic features.

In silico Optimization of Left Atrial Appendage Occluder Implantation Using Interactive and Modeling Tools.

According to clinical studies, around one third of patients with atrial fibrillation (AF) will suffer a stroke during their lifetime. Between 70 and 90% of these strokes are caused by thrombus formed in the left atrial appendage. In patients with contraindications to oral anticoagulants, a left atrial appendage occluder (LAAO) is often implanted to prevent blood flow entering in the LAA. A limited range of LAAO devices is available, with different designs and sizes. Together with the heterogeneity of LAA morphology, these factors make LAAO success dependent on clinician's experience. A sub-optimal LAAO implantation can generate thrombi outside the device, eventually leading to stroke if not treated. The aim of this study was to develop clinician-friendly tools based on biophysical models to optimize LAAO device therapies. A web-based 3D interactive virtual implantation platform, so-called VIDAA, was created to select the most appropriate LAAO configurations (type of device, size, landing zone) for a given patient-specific LAA morphology. An initial LAAO configuration is proposed in VIDAA, automatically computed from LAA shape features (centreline, diameters). The most promising LAAO settings and LAA geometries were exported from VIDAA to build volumetric meshes and run Computational Fluid Dynamics (CFD) simulations to assess blood flow patterns after implantation. Risk of thrombus formation was estimated from the simulated hemodynamics with an index combining information from blood flow velocity and complexity. The combination of the VIDAA platform with in silico indices allowed to identify the LAAO configurations associated to a lower risk of thrombus formation; device positioning was key to the creation of regions with turbulent flows after implantation. Our results demonstrate the potential for optimizing LAAO therapy settings during pre-implant planning based on modeling tools and contribute to reduce the risk of thrombus formation after treatment.

Coupled Immunological and Biomechanical Model of Emphysema Progression.

Chronic Obstructive Pulmonary Disease (COPD) is a disabling respiratory pathology, with a high prevalence and a significant economic and social cost. It is characterized by different clinical phenotypes with different risk profiles. Detecting the correct phenotype, especially for the emphysema subtype, and predicting the risk of major exacerbations are key elements in order to deliver more effective treatments. However, emphysema onset and progression are influenced by a complex interaction between the immune system and the mechanical properties of biological tissue. The former causes chronic inflammation and tissue remodeling. The latter influences the effective resistance or appropriate mechanical response of the lung tissue to repeated breathing cycles. In this work we present a multi-scale model of both aspects, coupling Finite Element (FE) and Agent Based (AB) techniques that we would like to use to predict the onset and progression of emphysema in patients. The AB part is based on existing biological models of inflammation and immunological response as a set of coupled non-linear differential equations. The FE part simulates the biomechanical effects of repeated strain on the biological tissue. We devise a strategy to couple the discrete biological model at the molecular /cellular level and the biomechanical finite element simulations at the tissue level. We tested our implementation on a public emphysema image database and found that it can indeed simulate the evolution of clinical image biomarkers during disease progression.

Multi-scale immunological and biomechanical model of emphysema progression.

This work presents a multi-scale agent-based model of emphysema progression that includes both the slow action of the immune system and the fast action of force redistribution and fracture propagation of the biological tissue. The two scales are coupled because the immune response causes inflammation and adaptation, which affects the biomechanical parameters of the tissue such as his elasticity. During repeated inflammation and breathing cycles, the tissue weakens and breaks down. We found that macrophages lifespan and cytokynes diffusion ratio are the parameters that influence the outcome of the model the most.

Virtual exploration of early stage atherosclerosis.

MOTIVATION: Biological mechanisms contributing to atherogenesis are multiple and complex. The early stage of atherosclerosis (AS) is characterized by the accumulation of low-density lipoprotein (LDL) droplets, leading to the creation of foam cells (FC). To address the difficulty to explore the dynamics of interactions that controls this process, this study aimed to develop a model of agents and infer on the most influential cell- and molecule-related parameters. RESULTS: FC started to accumulate after six to eight months of simulated hypercholesterolemia. A sensitivity analysis revealed the strong influence of LDL oxidation rate on the risk of FC creation, which was exploited to model the antioxidant effect of statins. Combined with an empirical simulation of the drug ability to decrease the level of LDL, the virtual statins treatment led to reductions of oxidized LDL levels similar to reductions measured in vivo. AVAILABILITY AND IMPLEMENTATION: An Open source software was used to develop the agent-based model of early AS. Two different concentrations of LDL agents were imposed in the intima layer to simulate healthy and hypercholesterolemia groups of 'virtual patients'. The interactions programmed between molecules and cells were based on experiments and models reported in the literature. A factorial sensitivity analysis explored the respective effects of the less documented model parameters as (i) agent migration speed, (ii) LDL oxidation rate and (iii) concentration of autoantibody agents. Finally, the response of the model to known perturbations was assessed by introducing statins agents, able to reduce the oxidation rate of LDL agents and the LDL boundary concentrations. CONTACT: jerome.noailly@upf.eduSupplementary information: Supplementary data are available at Bioinformatics online.

Simulation of cell seeding within a three-dimensional porous scaffold: a fluid-particle analysis.

Cell seeding is a critical step in tissue engineering. A high number of cells evenly distributed in scaffolds after seeding are associated with a more functional tissue culture. Furthermore, high cell densities have shown the possibility to reduce culture time or increase the formation of tissue. Experimentally, it is difficult to predict the cell-seeding process. In this study, a new methodology to simulate the cell-seeding process under perfusion conditions is proposed. The cells are treated as spherical particles dragged by the fluid media, where the physical parameters are computed through a Lagrangian formulation. The methodology proposed enables to define the kinetics of cell seeding continuously over time. An exponential relationship was found to optimize the seeding time and the number of cells seeded in the scaffold. The cell distribution and cell efficiency predicted using this methodology were similar to the experimental results of Melchels et al. One of the main advantages of this method is to be able to determine the three-dimensional position of all the seeded cells and to, therefore, better know the initial conditions for further cell proliferation and differentiation studies. This study opens up the field of numerical predictions related to the interactions between biomaterials, cells, and dynamics media.

The influence of the scaffold design on the distribution of adhering cells after perfusion cell seeding.

In natural tissues, the extracellular matrix composition, cell density and physiological properties are often non-homogeneous. Here we describe a model system, in which the distribution of cells throughout tissue engineering scaffolds after perfusion seeding can be influenced by the pore architecture of the scaffold. Two scaffold types, both with gyroid pore architectures, were designed and built by stereolithography: one with isotropic pore size (412 ± 13 µm) and porosity (62 ± 1%), and another with a gradient in pore size (250-500 µm) and porosity (35%-85%). Computational fluid flow modelling showed a uniform distribution of flow velocities and wall shear rates (15-24 s(-1)) for the isotropic architecture, and a gradient in the distribution of flow velocities and wall shear rates (12-38 s(-1)) for the other architecture. The distribution of cells throughout perfusion-seeded scaffolds was visualised by confocal microscopy. The highest densities of cells correlated with regions of the scaffolds where the pores were larger, and the fluid velocities and wall shear rates were the highest. Under the applied perfusion conditions, cell deposition is mainly determined by local wall shear stress, which, in turn, is strongly influenced by the architecture of the pore network of the scaffold.

Bioreactor based engineering of large-scale human cartilage grafts for joint resurfacing.

Apart from partial or total joint replacement, no surgical procedure is currently available to treat large and deep cartilage defects associated with advanced diseases such as osteoarthritis. In this work, we developed a perfusion bioreactor system to engineer human cartilage grafts in a size with clinical relevance for unicompartmental resurfacing of human knee joints (50 mm diameter × 3 mm thick). Computational fluid dynamics models were developed to optimize the flow profile when designing the perfusion chamber. Using the developed system, human chondrocytes could be seeded throughout large 50 mm diameter scaffolds with a uniform distribution. Following two weeks culture, tissues grown in the bioreactor were viable and homogeneously cartilaginous, with biomechanical properties approaching those of native cartilage. In contrast, tissues generated by conventional manual production procedures were highly inhomogeneous and contained large necrotic regions. The unprecedented engineering of human cartilage tissues in this large-scale opens the practical perspective of grafting functional biological substitutes for the clinical treatment for extensive cartilage defects, possibly in combination with surgical or pharmacological therapies to support durability of the implant. Ongoing efforts are aimed at integrating the up-scaled bioreactor based processes within a fully automated and closed manufacturing system for safe, standardized, and GMP compliant production of large-scale cartilage grafts.

Finite element study of scaffold architecture design and culture conditions for tissue engineering.

Tissue engineering scaffolds provide temporary mechanical support for tissue regeneration and transfer global mechanical load to mechanical stimuli to cells through its architecture. In this study the interactions between scaffold pore morphology, mechanical stimuli developed at the cell microscopic level, and culture conditions applied at the macroscopic scale are studied on two regular scaffold structures. Gyroid and hexagonal scaffolds of 55% and 70% porosity were modeled in a finite element analysis and were submitted to an inlet fluid flow or compressive strain. A mechanoregulation theory based on scaffold shear strain and fluid shear stress was applied for determining the influence of each structures on the mechanical stimuli on initial conditions. Results indicate that the distribution of shear stress induced by fluid perfusion is very dependent on pore distribution within the scaffold. Gyroid architectures provide a better accessibility of the fluid than hexagonal structures. Based on the mechanoregulation theory, the differentiation process in these structures was more sensitive to inlet fluid flow than axial strain of the scaffold. This study provides a computational approach to determine the mechanical stimuli at the cellular level when cells are cultured in a bioreactor and to relate mechanical stimuli with cell differentiation.