Particle-based methods for multiscale modeling of blood flow in the circulation and in devices: challenges and future directions. Sixth International Bio-Fluid Mechanics Symposium and Workshop March 28-30, 2008 Pasadena, California

Preclinical modeling of mechanical thrombectomy

Mechanical thrombectomy to treat large vessel occlusions (LVO) causing a stroke is one of the most effective treatments in medicine, with a number needed to treat to improve clinical outcomes as low as 2.6. As the name implies, it is a mechanical solution to a blocked artery and modeling these mechanics preclinically for device design, regulatory clearance and high-fidelity physician training made clinical applications possible. In vitro simulation of LVO is extensively used to characterize device performance in representative vascular anatomies with physiologically accurate hemodynamics. Embolus analogues, validated against clots extracted from patients, provide a realistic simulated use experience. In vitro experimentation produces quantitative results such as particle analysis of distal emboli generated during the procedure, as well as pressure and flow throughout the experiment. Animal modeling, used mostly for regulatory review, allows estimation of device safety. Other than one recent development, nearly all animal modeling does not incorporate the desired target organ, the brain, but rather is performed in the extracranial circulation. Computational modeling of the procedure remains at the earliest stages but represents an enormous opportunity to rapidly characterize and iterate new thrombectomy concepts as well as optimize procedure workflow. No preclinical model is a perfect surrogate; however, models available can answer important questions during device development and have to date been successful in delivering efficacious and safe devices producing excellent clinical outcomes. This review reflects on the developments of preclinical modeling of mechanical thrombectomy with particular focus on clinical translation, as well as articulate existing gaps requiring additional research.

A predictive multiscale model for simulating flow-induced platelet activation: Correlating in silico results with in vitro results

Flow-induced platelet activation prompts complex filopodial formation. Continuum methods fail to capture such molecular-scale mechanisms. A multiscale numerical model was developed to simulate this activation process, where a Dissipative Particle Dynamics (DPD) model of viscous blood flow is interfaced with a Coarse Grained Molecular Dynamics (CGMD) platelet model. Embedded in DPD blood flow, the macroscopic dynamic stresses are interactively transferred to the CGMD model, inducing intra-platelet associated events. The platelets activate by a biomechanical transductive linkage chain and dynamically change their shape in response. The models are fully coupled via a hybrid-potential interface and multiple time-stepping (MTS) schemes for handling the disparity between the spatiotemporal scales. Cumulative hemodynamic stresses that may lead to platelet activation are mapped on the surface membrane and simultaneously transmitted to the cytoplasm and cytoskeleton. Upon activation, the flowing platelets lose their quiescent discoid shape and evolve by forming filopodia. The model predictions were validated by a set of in vitro experiments, Platelets were exposed to various combinations of shear stresses and durations in our programmable hemodynamic shearing device (HSD). Their shape change was measured at multiple time points using scanning electron microscopy (SEM). The CGMD model parameters were fine-tuned by interrogating a parameter space established in these experiments. Segmentation of the SEM imaging streams was conducted by a deep machine learning system. This model can be further employed to simulate shear mediated platelet activation thrombosis initiation and to study the effects of modulating platelet properties to enhance their shear resistance via mechanotransduction pathways.

Recent advances in computational modeling of fibrin clot formation: A review

The field of thrombosis and hemostasis is crucial for understanding and developing new therapies for pathologies such as deep vein thrombosis, diabetes related strokes, pulmonary embolisms, and hemorrhaging related diseases. In the last two decades, an exponential growth in studies related to fibrin clot formation using computational tools has been observed. Despite this growth, the complete mechanism behind thrombus formation and hemostasis has been long and rife with obstacles; however, significant progress has been made in the present century. The computational models and methods used in this context are diversified into different spatiotemporal scales, yet there is no single model which can predict both physiological and mechanical properties of fibrin clots. In this review, we list the major strategies employed by researchers in modeling fibrin clot formation using recent and existing computational techniques. This review organizes the computational strategies into continuum level, system level, discrete particle (DPD), and multi-scale methods. We also discuss strengths and weaknesses of various methods and future directions in which computational modeling of fibrin clots can advance.

Meshfree simulations of ultrasound vector flow imaging using smoothed particle hydrodynamics

Before embarking on a series of in vivo tests, design of ultrasound-flow-imaging modalities are generally more efficient through computational models as multiple configurations can be tested methodically. To that end, simulation models must generate realistic blood flow dynamics and Doppler signals. The current in silico ultrasound simulation techniques suffer mainly from uncertainty in providing accurate trajectories of moving ultrasound scatterers. In mesh-based Eulerian methods, numerical truncation errors from the interpolated velocities, both in the time and space dimensions, can accumulate significantly and make the pathlines unreliable. These errors can distort beam-to-beam inter-correlation present in ultrasound flow imaging. It is thus a technical issue to model a correct motion of the scatterers by considering their interaction with boundaries and neighboring scatterers. We hypothesized that in silico analysis of emerging ultrasonic imaging modalities can be implemented more accurately with meshfree approaches. We developed an original fluid-ultrasound simulation environment based on a meshfree Lagrangian CFD (computational fluid dynamics) formulation, which allows analysis of ultrasound flow imaging. This simulator combines smoothed particle hydrodynamics (SPH) and Fourier-domain linear acoustics (SIMUS  =  simulator for ultrasound imaging). With such a particle-based computation, the fluid particles also acted as individual ultrasound scatterers, resulting in a direct and physically sound fluid-ultrasonic coupling. We used the in-house algorithms for fluid and ultrasound simulations to simulate high-frame-rate vector flow imaging. The potential of the particle-based method was tested in 2D simulations of vector Doppler for the intracarotid flow. The Doppler-based velocity fields were compared with those issued from SPH. The numerical evaluations showed that the vector flow fields obtained by vector Doppler components were in good agreement with the original SPH velocities, with relative errors less than 10% and 2% in the cross-beam and axial directions, respectively. Our results showed that SPH-SIMUS coupling enables direct and realistic simulations of ultrasound flow imaging. The proposed coupled algorithm has also the advantage to be 3D compatible and parallelizable.

Fibrin polymerization simulation using a reactive dissipative particle dynamics method

The study on the polymerization of fibrinogen molecules into fibrin monomers and eventually a stable, mechanically robust fibrin clot is a persistent and enduring topic in the field of thrombosis and hemostasis. Despite many research advances in fibrin polymerization, the change in the structure of fibrin clots and its influence on the formation of a fibrous protein network are still poorly understood. In this paper, we develop a new computational method to simulate fibrin clot polymerization using dissipative particle dynamics simulations. With an effective combination of reactive molecular dynamics formularies and many body dissipative particle dynamics principles, we constructed the reactive dissipative particle dynamics (RDPD) model to predict the complex network formation of fibrin clots and branching of the fibrin network. The 340 kDa fibrinogen molecule is converted into a spring-bead coarse-grain system with 11 beads using a topology representing network algorithm, and using RDPD, we simulated polymerization and formation of the fibrin clot. The final polymerized structure of the fibrin clot qualitatively agrees with experimental results from the literature, and to the best of our knowledge this is the first molecular-based study that simulates polymerization and structure of fibrin clots.

First Implantation of Silicon Nanopore Membrane Hemofilters

An implantable hemofilter for the treatment of kidney failure depends critically on the transport characteristics of the membrane and the biocompatibility of the membrane, cartridge, and blood conduits. A novel membrane with slit-shaped pores optimizes the trade-off between permeability and selectivity, enabling implanted therapy. Sustained (3-8) day function of an implanted parallel-plate hemofilter with minimal anticoagulation was achieved by considering biocompatibility at the subnanometer scale of chemical interactions and the millimeter scale of blood fluid dynamics. A total of 400 nm-thick polysilicon flat sheet membranes with 5-8 nm × 2 micron slit-shaped pores were surface-modified with polyethylene glycol. Hemofilter cartridge geometries were refined based on computational fluid dynamics models of blood flow. In an uncontrolled pilot study, silicon filters were implanted in six class A dogs. Cartridges were connected to the cardiovascular system by anastamoses to the aorta and inferior vena cava and filtrate was drained to collection pouches positioned in the peritoneum. Pain medicine and acetylsalicylic acid were administered twice daily until the hemofilters were harvested on postoperative days 3 (n = 2), 4 (n = 2), 5 (n = 1), and 8 (n = 1). No hemofilters were thrombosed. Animals treated for 5 and 8 days had microscopic fractures in the silicon nanopore membranes and 20-50 ml of transudative (albumin sieving coefficient θalb ~ 0.5 - 0.7) fluid in the collection pouches at the time of explant. Shorter experimental durations (3-4 days) resulted in filtration volumes similar to predictions based on mean arterial pressures and membrane hydraulic permeability and (θalb ~ 0.2 - 0.3), similar to preimplantation measurements. In conclusion, a detailed mechanistic and materials science attention to blood-material interactions allows implanted hemofilters to resist thrombosis. Additional testing is needed to determine optimal membrane characteristics and identify limiting factors in long-term implantation.

Fully-coupled fluid-structure interaction simulation of the aortic and mitral valves in a realistic 3D left ventricle model

In this study, we present a fully-coupled fluid-structure interaction (FSI) framework that combines smoothed particle hydrodynamics (SPH) and nonlinear finite element (FE) method to investigate the coupled aortic and mitral valves structural response and the bulk intraventricular hemodynamics in a realistic left ventricle (LV) model during the entire cardiac cycle. The FSI model incorporates valve structures that consider native asymmetric leaflet geometries, anisotropic hyperelastic material models and human material properties. Comparison of FSI results with subject-specific echocardiography data demonstrates that the SPH-FE approach is able to quantitatively predict the opening and closing times of the valves, the mitral leaflet opening and closing angles, and the large-scale intraventricular flow phenomena with a reasonable agreement. Moreover, comparison of FSI results with a LV model without valves reveals substantial differences in the flow field. Peak systolic velocities obtained from the FSI model and the LV model without valves are 2.56 m/s and 1.16 m/s, respectively, compared to the Doppler echo data of 2.17 m/s. The proposed SPH-FE FSI framework represents a further step towards modeling patient-specific coupled LV-valve dynamics, and has the potential to improve our understanding of cardiovascular physiology and to support professionals in clinical decision-making.

Modeling Left Ventricular Blood Flow Using Smoothed Particle Hydrodynamics

This study aims to investigate the capability of smoothed particle hydrodynamics (SPH), a fully Lagrangian mesh-free method, to simulate the bulk blood flow dynamics in two realistic left ventricular (LV) models. Three dimensional geometries and motion of the LV, proximal left atrium and aortic root are extracted from cardiac magnetic resonance imaging and multi-slice computed tomography imaging data. SPH simulation results are analyzed and compared with those obtained using a traditional finite volume-based numerical method, and to in vivo phase contrast magnetic resonance imaging and echocardiography data, in terms of the large-scale blood flow phenomena usually clinically measured. A quantitative comparison of the velocity fields and global flow parameters between the in silico models and the in vivo data shows a reasonable agreement, given the inherent uncertainties and limitations in the modeling and imaging techniques. The results indicate the capability of SPH as a promising tool for predicting clinically relevant large-scale LV flow information.

A Review of Hemolysis Prediction Models for Computational Fluid Dynamics

Flow-induced hemolysis is a crucial issue for many biomedical applications; in particular, it is an essential issue for the development of blood-transporting devices such as left ventricular assist devices, and other types of blood pumps. In order to estimate red blood cell (RBC) damage in blood flows, many models have been proposed in the past. Most models have been validated by their respective authors. However, the accuracy and the validity range of these models remains unclear. In this work, the most established hemolysis models compatible with computational fluid dynamics of full-scale devices are described and assessed by comparing two selected reference experiments: a simple rheometric flow and a more complex hemodialytic flow through a needle. The quantitative comparisons show very large deviations concerning hemolysis predictions, depending on the model and model parameter. In light of the current results, two simple power-law models deliver the best compromise between computational efficiency and obtained accuracy. Finally, hemolysis has been computed in an axial blood pump. The reconstructed geometry of a HeartMate II shows that hemolysis occurs mainly at the tip and leading edge of the rotor blades, as well as at the leading edge of the diffusor vanes.

Device thrombosis and pre-clinical blood flow models for assessing antithrombogenic efficacy of drug-device combinations

Thrombosis associated with blood-contacting devices is a complex process involving several component interactions that have eluded precise definition. Extensive investigations of individual biological modules such as protein adsorption, coagulation cascade activation and platelet activation/adhesion/aggregation have provided an initial foundation for developing biomaterials for blood-contacting devices, but a material that is intrinsically non-thrombogenic is yet to be developed. The well-recognized association between fluid dynamics parameters such as shear stress, vortices, stagnation and thrombotic processes such as platelet aggregation and coagulation aggravate thrombosis on most device geometries that elicit these flow disturbances. Thus, antithrombotic drugs that were developed to treat thrombosis associated with vascular diseases such as atherosclerosis have also been adapted to mitigate the risk of device thrombosis. However, balancing the risk of bleeding with the antithrombotic efficacy of these drugs continues to be a challenge, and surface modification of devices with these drug molecules to mitigate device thrombosis locally has been explored. Pre-clinical blood flow models to test the effectiveness of these drug-device combinations have also evolved and several in-vitro, ex-vivo, and in-vivo test configurations are available with their attendant merits and limitations. Despite considerable efforts toward iterative design and testing of blood contacting devices and antithrombogenic surface modifications, device thrombosis remains an unsolved problem.

A multiscale biomechanical model of platelets: Correlating with in-vitro results

Using dissipative particle dynamics (DPD) combined with coarse grained molecular dynamics (CGMD) approaches, we developed a multiscale deformable platelet model to accurately describe the molecular-scale intra-platelet constituents and biomechanical properties of platelets in blood flow. Our model includes the platelet bilayer membrane, cytoplasm and an elaborate elastic cytoskeleton. Correlating numerical simulations with published in-vitro experiments, we validated the biorheology of the cytoplasm, the elastic response of membrane to external stresses, and the stiffness of the cytoskeleton actin filaments, resulting in an accurate representation of the molecular-level biomechanical microstructures of platelets. This enabled us to study the mechanotransduction process of the hemodynamic stresses acting onto the platelet membrane and transmitted to these intracellular constituents. The platelets constituents continuously deform in response to the flow induced stresses. To the best of our knowledge, this is the first molecular-scale platelet model that can be used to accurately predict platelets activation mechanism leading to thrombus formation in prosthetic cardiovascular devices and in vascular disease processes. This model can be further employed to study the effects of novel therapeutic approaches of modulating platelet properties to enhance their shear resistance via mechanotransduction pathways.

Scalability Test of Multiscale Fluid-Platelet Model for Three Top Supercomputers

We have tested the scalability of three supercomputers: the Tianhe-2, Stampede and CS-Storm with multiscale fluid-platelet simulations, in which a highly-resolved and efficient numerical model for nanoscale biophysics of platelets in microscale viscous biofluids is considered. Three experiments involving varying problem sizes were performed: Exp-S: 680,718-particle single-platelet; Exp-M: 2,722,872-particle 4-platelet; and Exp-L: 10,891,488-particle 16-platelet. Our implementations of multiple time-stepping (MTS) algorithm improved the performance of single time-stepping (STS) in all experiments. Using MTS, our model achieved the following simulation rates: 12.5, 25.0, 35.5 μs/day for Exp-S and 9.09, 6.25, 14.29 μs/day for Exp-M on Tianhe-2, CS-Storm 16-K80 and Stampede K20. The best rate for Exp-L was 6.25 μs/day for Stampede. Utilizing current advanced HPC resources, the simulation rates achieved by our algorithms bring within reach performing complex multiscale simulations for solving vexing problems at the interface of biology and engineering, such as thrombosis in blood flow which combines millisecond-scale hematology with microscale blood flow at resolutions of micro-to-nanoscale cellular components of platelets. This study of testing the performance characteristics of supercomputers with advanced computational algorithms that offer optimal trade-off to achieve enhanced computational performance serves to demonstrate that such simulations are feasible with currently available HPC resources.

A comprehensive study on different modelling approaches to predict platelet deposition rates in a perfusion chamber

Thrombus formation is a multiscale phenomenon triggered by platelet deposition over a protrombotic surface (eg. a ruptured atherosclerotic plaque). Despite the medical urgency for computational tools that aid in the early diagnosis of thrombotic events, the integration of computational models of thrombus formation at different scales requires a comprehensive understanding of the role and limitation of each modelling approach. We propose three different modelling approaches to predict platelet deposition. Specifically, we consider measurements of platelet deposition under blood flow conditions in a perfusion chamber for different time periods (3, 5, 10, 20 and 30 minutes) at shear rates of 212 s⁻¹, 1390 s⁻¹ and 1690 s⁻¹. Our modelling approaches are: i) a model based on the mass-transfer boundary layer theory; ii) a machine-learning approach; and iii) a phenomenological model. The results indicate that the three approaches on average have median errors of 21%, 20.7% and 14.2%, respectively. Our study demonstrates the feasibility of using an empirical data set as a proxy for a real-patient scenario in which practitioners have accumulated data on a given number of patients and want to obtain a diagnosis for a new patient about whom they only have the current observation of a certain number of variables.

Self-consistent description of electrokinetic phenomena in particle-based simulations

A new computational method is presented for study suspensions of charged particles undergoing fluctuating hydrodynamic and electrostatic interactions. The proposed model is appropriate for polymers, proteins, and porous particles embedded in a continuum electrolyte. A self-consistent Langevin description of the particles is adopted in which hydrodynamic and electrostatic interactions are included through a Green's function formalism. An Ewald-like split is adopted in order to satisfy arbitrary boundary conditions for the Stokeslet and Poisson Green functions, thereby providing a formalism that is applicable to any geometry and that can be extended to deformable objects. The convection-diffusion equation for the continuum ions is solved simultaneously considering Nernst-Planck diffusion. The method can be applied to systems at equilibrium and far from equilibrium. Its applicability is demonstrated in the context of electrokinetic motion, where it is shown that the ionic clouds associated with individual particles can be severely altered by the flow and concentration, leading to intriguing cooperative effects.

A Multiple Time Stepping Algorithm for Efficient Multiscale Modeling of Platelets Flowing in Blood Plasma

We developed a multiple time-stepping (MTS) algorithm for multiscale modeling of the dynamics of platelets flowing in viscous blood plasma. This MTS algorithm improves considerably the computational efficiency without significant loss of accuracy. This study of the dynamic properties of flowing platelets employs a combination of the dissipative particle dynamics (DPD) and the coarse-grained molecular dynamics (CGMD) methods to describe the dynamic microstructures of deformable platelets in response to extracellular flow-induced stresses. The disparate spatial scales between the two methods are handled by a hybrid force field interface. However, the disparity in temporal scales between the DPD and CGMD that requires time stepping at microseconds and nanoseconds respectively, represents a computational challenge that may become prohibitive. Classical MTS algorithms manage to improve computing efficiency by multi-stepping within DPD or CGMD for up to one order of magnitude of scale differential. In order to handle 3-4 orders of magnitude disparity in the temporal scales between DPD and CGMD, we introduce a new MTS scheme hybridizing DPD and CGMD by utilizing four different time stepping sizes. We advance the fluid system at the largest time step, the fluid-platelet interface at a middle timestep size, and the nonbonded and bonded potentials of the platelet structural system at two smallest timestep sizes. Additionally, we introduce parameters to study the relationship of accuracy versus computational complexities. The numerical experiments demonstrated 3000x reduction in computing time over standard MTS methods for solving the multiscale model. This MTS algorithm establishes a computationally feasible approach for solving a particle-based system at multiple scales for performing efficient multiscale simulations.

Multiscale Particle-Based Modeling of Flowing Platelets in Blood Plasma Using Dissipative Particle Dynamics and Coarse Grained Molecular Dynamics

We developed a multiscale particle-based model of platelets, to study the transport dynamics of shear stresses between the surrounding fluid and the platelet membrane. This model facilitates a more accurate prediction of the activation potential of platelets by viscous shear stresses - one of the major mechanisms leading to thrombus formation in cardiovascular diseases and in prosthetic cardiovascular devices. The interface of the model couples coarse-grained molecular dynamics (CGMD) with dissipative particle dynamics (DPD). The CGMD handles individual platelets while the DPD models the macroscopic transport of blood plasma in vessels. A hybrid force field is formulated for establishing a functional interface between the platelet membrane and the surrounding fluid, in which the microstructural changes of platelets may respond to the extracellular viscous shear stresses transferred to them. The interaction between the two systems preserves dynamic properties of the flowing platelets, such as the flipping motion. Using this multiscale particle-based approach, we have further studied the effects of the platelet elastic modulus by comparing the action of the flow-induced shear stresses on rigid and deformable platelet models. The results indicate that neglecting the platelet deformability may overestimate the stress on the platelet membrane, which in turn may lead to erroneous predictions of the platelet activation under viscous shear flow conditions. This particle-based fluid-structure interaction multiscale model offers for the first time a computationally feasible approach for simulating deformable platelets interacting with viscous blood flow, aimed at predicting flow induced platelet activation by using a highly resolved mapping of the stress distribution on the platelet membrane under dynamic flow conditions.

Parameterizing the Morse Potential for Coarse-Grained Modeling of Blood Plasma

Multiscale simulations of fluids such as blood represent a major computational challenge of coupling the disparate spatiotemporal scales between molecular and macroscopic transport phenomena characterizing such complex fluids. In this paper, a coarse-grained (CG) particle model is developed for simulating blood flow by modifying the Morse potential, traditionally used in Molecular Dynamics for modeling vibrating structures. The modified Morse potential is parameterized with effective mass scales for reproducing blood viscous flow properties, including density, pressure, viscosity, compressibility and characteristic flow dynamics of human blood plasma fluid. The parameterization follows a standard inverse-problem approach in which the optimal micro parameters are systematically searched, by gradually decoupling loosely correlated parameter spaces, to match the macro physical quantities of viscous blood flow. The predictions of this particle based multiscale model compare favorably to classic viscous flow solutions such as Counter-Poiseuille and Couette flows. It demonstrates that such coarse grained particle model can be applied to replicate the dynamics of viscous blood flow, with the advantage of bridging the gap between macroscopic flow scales and the cellular scales characterizing blood flow that continuum based models fail to handle adequately.

Platelet size and density affect shear-induced thrombus formation in tortuous arterioles

Thrombosis accounts for 80% of deaths in patients with diabetes mellitus. Diabetic patients demonstrate tortuous microvessels and larger than normal platelets. Large platelets are associated with increased platelet activation and thrombosis, but the physical effects of large platelets in the microscale processes of thrombus formation are not clear. Therefore, the objective of this study was to determine the physical effects of mean platelet volume (MPV), mean platelet density (MPD) and vessel tortuosity on platelet activation and thrombus formation in tortuous arterioles. A computational model of the transport, shear-induced activation, collision, adhesion and aggregation of individual platelets was used to simulate platelet interactions and thrombus formation in tortuous arterioles. Our results showed that an increase in MPV resulted in a larger number of activated platelets, though MPD and level of tortuosity made little difference on platelet activation. Platelets with normal MPD yielded the lowest amount of mural thrombus. With platelets of normal MPD, the amount of mural thrombus decreased with increasing level of tortuosity but did not have a simple monotonic relationship with MPV. The physical mechanisms associated with MPV, MPD and arteriole tortuosity play important roles in platelet activation and thrombus formation.

Continuum- and particle-based modeling of shapes and dynamics of red blood cells in health and disease

We review recent advances in multiscale modeling of the mechanics of healthy and diseased red blood cells (RBCs), and blood flow in the microcirculation. We cover the traditional continuum-based methods but also particle-based methods used to model both the RBCs and the blood plasma. We highlight examples of successful simulations of blood flow including malaria and sickle cell anemia.

A review of macroscopic thrombus modeling methods

Hemodynamics applied to mechanobiology offers powerful means to predict thrombosis, and to understand the kinetics of thrombus formation on areas of vascular damage in blood flowing through the human circulatory system. Specifically, the advances in computational processing and the progress in modeling complex biological processes with spatio-temporal multi-scale methods have the potential to shift the way in which cardiovascular diseases are diagnosed and treated. This article systematically surveys the state of the art of macroscopic computational fluid dynamics (CFD) Computational fluid dynamics techniques for modeling thrombus formation, highlighting their strengths and weaknesses. In particular, a comprehensive and systematic revision of the hemodynamics models and methods is given, and the strengths and weaknesses of those employed for studying thrombus formation are highlighted.

Computational evaluation of the thrombogenic potential of a hollow-fiber oxygenator with integrated heat exchanger during extracorporeal circulation

The onset of thromboembolic phenomena in blood oxygenators, even in the presence of adequate anticoagulant strategies, is a relevant concern during extracorporeal circulation (ECC). For this reason, the evaluation of the thrombogenic potential associated with extracorporeal membrane oxygenators should play a critical role into the preclinical design process of these devices. This study extends the use of computational fluid dynamics simulations to guide the hemodynamic design optimization of oxygenators and evaluate their thrombogenic potential during ECC. The computational analysis accounted for both macro- (i.e., vortex formation) and micro-scale (i.e., flow-induced platelet activation) phenomena affecting the performances of a hollow-fiber membrane oxygenator with integrated heat exchanger. A multiscale Lagrangian approach was adopted to infer the trajectory and loading history experienced by platelet-like particles in the entire device and in a repetitive subunit of the fiber bundles. The loading history was incorporated into a damage accumulation model in order to estimate the platelet activation state (PAS) associated with repeated passes of the blood within the device. Our results highlighted the presence of blood stagnation areas in the inlet section that significantly increased the platelet activation levels in particles remaining trapped in this region. The order of magnitude of PAS in the device was the same as the one calculated for the components of the ECC tubing system, chosen as a term of comparison for their extensive diffusion. Interpolating the mean PAS values with respect to the number of passes, we obtained a straightforward prediction of the thrombogenic potential as a function of the duration of ECC.

The use of computational fluid dynamics in the development of ventricular assist devices

Progress in the field of prosthetic cardiovascular devices has significantly contributed to the rapid advancements in cardiac therapy during the last four decades. The concept of mechanical circulatory assistance was established with the first successful clinical use of heart-lung machines for cardiopulmonary bypass. Since then a variety of devices have been developed to replace or assist diseased components of the cardiovascular system. Ventricular assist devices (VADs) are basically mechanical pumps designed to augment or replace the function of one or more chambers of the failing heart. Computational Fluid Dynamics (CFD) is an attractive tool in the development process of VADs, allowing numerous different designs to be characterized for their functional performance virtually, for a wide range of operating conditions, without the physical device being fabricated. However, VADs operate in a flow regime which is traditionally difficult to simulate; the transitional region at the boundary of laminar and turbulent flow. Hence different methods have been used and the best approach is debatable. In addition to these fundamental fluid dynamic issues, blood consists of biological cells. Device-induced biological complications are a serious consequence of VAD use. The complications include blood damage (haemolysis, blood cell activation), thrombosis and emboli. Patients are required to take anticoagulation medication constantly which may cause bleeding. Despite many efforts blood damage models have still not been implemented satisfactorily into numerical analysis of VADs, which severely undermines the full potential of CFD. This paper reviews the current state of the art CFD for analysis of blood pumps, including a practical critical review of the studies to date, which should help device designers choose the most appropriate methods; a summary of blood damage models and the difficulties in implementing them into CFD; and current gaps in knowledge and areas for future work.