Fluid-structure interaction modelling of a positive-displacement Total Artificial Heart.

For those suffering from end-stage biventricular heart failure, and where a heart transplantation is not a viable option, a Total Artificial Heart (TAH) can be used as a bridge to transplant device. The Realheart TAH is a four-chamber artificial heart that uses a positive-displacement pumping technique mimicking the native heart to produce pulsatile flow governed by a pair of bileaflet mechanical heart valves. The aim of this work was to create a method for simulating haemodynamics in positive-displacement blood pumps, using computational fluid dynamics with fluid-structure interaction to eliminate the need for pre-existing in vitro valve motion data, and then use it to investigate the performance of the Realheart TAH across a range of operating conditions. The device was simulated in Ansys Fluent for five cycles at pumping rates of 60, 80, 100 and 120 bpm and at stroke lengths of 19, 21, 23 and 25 mm. The moving components of the device were discretised using an overset meshing approach, a novel blended weak-strong coupling algorithm was used between fluid and structural solvers, and a custom variable time stepping scheme was used to maximise computational efficiency and accuracy. A two-element Windkessel model approximated a physiological pressure response at the outlet. The transient outflow volume flow rate and pressure results were compared against in vitro experiments using a hybrid cardiovascular simulator and showed good agreement, with maximum root mean square errors of 15% and 5% for the flow rates and pressures respectively. Ventricular washout was simulated and showed an increase as cardiac output increased, with a maximum value of 89% after four cycles at 120 bpm 25 mm. Shear stress distribution over time was also measured, showing that no more than [Formula: see text]% of the total volume exceeded 150 Pa at a cardiac output of 7 L/min. This study showed this model to be both accurate and robust across a wide range of operating points, and will enable fast and effective future studies to be undertaken on current and future generations of the Realheart TAH.

MRI-based strain measurements reflect morphological changes following myocardial infarction: A study on the UK Biobank cohort.

In a porcine experimental model of myocardial infarction, a localised, layer-specific, circumferential left ventricular strain metric has been shown to indicate chronic changes in ventricular function post-infarction more strongly than ejection fraction. This novel strain metric might therefore provide useful prognostic information clinically. In this study, existing clinical volume indices, global strains, and the novel, layer-specific strain were calculated for a large human cohort to assess variations in ventricular function and morphology with age, sex, and health status. Imaging and health data from the UK Biobank were obtained, including healthy volunteers and those with a history of cardiovascular illness. In total, 710 individuals were analysed and stratified by age, sex and health. Significant differences in all strain metrics were found between healthy and unhealthy populations, as well as between males and females. Significant differences in basal circumferential strain and global circumferential strain were found between healthy males and females, with males having smaller absolute values for both (all p ≤ 0.001). There were significant differences in the functional variables left ventricular ejection fraction, end-systolic volume, end-systolic volume index and mid-ventricular circumferential strain between healthy and unhealthy male cohorts aged 65-74 (all p ≤ 0.001). These results suggest that whilst regional circumferential strains may be useful clinically for assessing cardiovascular health, care must be taken to ensure critical values are indexed correctly to age and sex, due to the differences in these values observed here.

Video-based valve motion combined with computational fluid dynamics gives stable and accurate simulations of blood flow in the Realheart total artificial heart.

BACKGROUND: Patients with end-stage, biventricular heart failure, and for whom heart transplantation is not an option, may be given a Total Artificial Heart (TAH). The Realheart® is a novel TAH which pumps blood by mimicking the native heart with translation of an atrioventricular plane. The aim of this work was to create a strategy for using Computational Fluid Dynamics (CFD) to simulate haemodynamics in the Realheart®, including motion of the atrioventricular plane and valves. METHODS: The accuracies of four different computational methods for simulating fluid-structure interaction of the prosthetic valves were assessed by comparison of chamber pressures and flow rates with experimental measurements. The four strategies were: prescribed motion of valves opening and closing at the atrioventricular plane extrema; simulation of fluid-structure interaction of both valves; prescribed motion of the mitral valve with simulation of fluid-structure interaction of the aortic valve; motion of both valves prescribed from video analysis of experiments. RESULTS: The most accurate strategy (error in ventricular pressure of 6%, error in flow rate of 5%) used video-prescribed motion. With the Realheart operating at 80 bpm, the power consumption was 1.03 W, maximum shear stress was 15 Pa, and washout of the ventricle chamber after 4 cycles was 87%. CONCLUSIONS: This study, the first CFD analysis of this novel TAH, demonstrates that good agreement between computational and experimental data can be achieved. This method will therefore enable future optimisation of the geometry and motion of the Realheart®.

Comparison of the within-reader and inter-vendor agreement of left ventricular circumferential strains and volume indices derived from cardiovascular magnetic resonance imaging.

PURPOSE: Volume indices and left ventricular ejection fraction (LVEF) are routinely used to assess cardiac function. Ventricular strain values may provide additional diagnostic information, but their reproducibility is unclear. This study therefore compares the repeatability and reproducibility of volumes, volume fraction, and regional ventricular strains, derived from cardiovascular magnetic resonance (CMR) imaging, across three software packages and between readers. METHODS: Seven readers analysed 16 short-axis CMR stacks of a porcine heart. Endocardial contours were manually drawn using OsiriX and Simpleware ScanIP and repeated in both softwares. The images were also contoured automatically in Circle CVI42. Endocardial global, apical, mid-ventricular, and basal circumferential strains, as well as end-diastolic and end-systolic volume and LVEF were compared. RESULTS: Bland-Altman analysis found systematic biases in contour length between software packages. Compared to OsiriX, contour lengths were shorter in both ScanIP (-1.9 cm) and CVI42 (-0.6 cm), causing statistically significant differences in end-diastolic and end-systolic volumes, and apical circumferential strain (all p<0.006). No differences were found for mid-ventricular, basal or global strains, or left ventricular ejection fraction (all p<0.007). All CVI42 results lay within the ranges of the OsiriX results. Intra-software differences were found to be lower than inter-software differences. CONCLUSION: OsiriX and CVI42 gave consistent results for all strain and volume metrics, with no statistical differences found between OsiriX and ScanIP for mid-ventricular, global or basal strains, or left ventricular ejection fraction. However, volumes were influenced by the choice of contouring software, suggesting care should be taken when comparing volumes across different software.

Normal fluid stresses are prevalent in rotary ventricular assist devices: A computational fluid dynamics analysis.

Despite the evolution of ventricular assist devices, ventricular assist device patients still suffer from complications due to the damage to blood by fluid dynamic stress. Since rotary ventricular assist devices are assumed to exert mainly shear stress, studies of blood damage are based on shear flow experiments. However, measurements and simulations of cell and protein deformation show normal and shear stresses deform, and potentially damage, cells and proteins differently. The aim was to use computational fluid dynamics to assess the prevalence of normal stress, in comparison with shear stress, in rotary ventricular assist devices. Our calculations showed normal stresses do occur in rotary ventricular assist devices: the fluid volumes experiencing normal stress above 10 Pa were 0.011 mL (0.092%) and 0.027 mL (0.39%) for the HeartWare HVAD and HeartMate II (HMII), and normal stresses over 100 Pa were present. However, the shear stress volumes were up to two orders of magnitude larger than the normal stress volumes. Considering thresholds for red blood cell and von Willebrand factor deformation by normal and shear stresses, the fluid volumes causing deformation by normal stress were between 2.5 and 5 times the size of those causing deformation by shear stress. The exposure times to the individual normal stress deformation regions were around 1 ms. The results clearly show, for the first time, that while blood within rotary ventricular assist devices experiences more shear stress at much higher magnitudes as compared with normal stress, there is sufficient normal stress exposure present to cause deformation of, and potentially damage to, the blood components. This study is the first to quantify the fluid stress components in real blood contacting devices.

In silico coronary wave intensity analysis: application of an integrated one-dimensional and poromechanical model of cardiac perfusion.

Coronary wave intensity analysis (cWIA) is a diagnostic technique based on invasive measurement of coronary pressure and velocity waveforms. The theory of WIA allows the forward- and backward-propagating coronary waves to be separated and attributed to their origin and timing, thus serving as a sensitive and specific cardiac functional indicator. In recent years, an increasing number of clinical studies have begun to establish associations between changes in specific waves and various diseases of myocardium and perfusion. These studies are, however, currently confined to a trial-and-error approach and are subject to technological limitations which may confound accurate interpretations. In this work, we have developed a biophysically based cardiac perfusion model which incorporates full ventricular-aortic-coronary coupling. This was achieved by integrating our previous work on one-dimensional modelling of vascular flow and poroelastic perfusion within an active myocardial mechanics framework. Extensive parameterisation was performed, yielding a close agreement with physiological levels of global coronary and myocardial function as well as experimentally observed cumulative wave intensity magnitudes. Results indicate a strong dependence of the backward suction wave on QRS duration and vascular resistance, the forward pushing wave on the rate of myocyte tension development, and the late forward pushing wave on the aortic valve dynamics. These findings are not only consistent with experimental observations, but offer a greater specificity to the wave-originating mechanisms, thus demonstrating the value of the integrated model as a tool for clinical investigation.

Clinical Diagnostic Biomarkers from the Personalization of Computational Models of Cardiac Physiology.

Computational modelling of the heart is rapidly advancing to the point of clinical utility. However, the difficulty of parameterizing and validating models from clinical data indicates that the routine application of truly predictive models remains a significant challenge. We argue there is significant value in an intermediate step towards prediction. This step is the use of biophysically based models to extract clinically useful information from existing patient data. Specifically in this paper we review methodologies for applying modelling frameworks for this goal in the areas of quantifying cardiac anatomy, estimating myocardial stiffness and optimizing measurements of coronary perfusion. Using these indicative examples of the general overarching approach, we finally discuss the value, ongoing challenges and future potential for applying biophysically based modelling in the clinical context.

Measurement and modeling of coronary blood flow.

Ischemic heart disease that comprises both coronary artery disease and microvascular disease is the single greatest cause of death globally. In this context, enhancing our understanding of the interaction of coronary structure and function is not only fundamental for advancing basic physiology but also crucial for identifying new targets for treating these diseases. A central challenge for understanding coronary blood flow is that coronary structure and function exhibit different behaviors across a range of spatial and temporal scales. While experimental studies have sought to understand this feature by isolating specific mechanisms, in tandem, computational modeling is increasingly also providing a unique framework to integrate mechanistic behaviors across different scales. In addition, clinical methods for assessing coronary disease severity are continuously being informed and updated by findings in basic physiology. Coupling these technologies, computational modeling of the coronary circulation is emerging as a bridge between the experimental and clinical domains, providing a framework to integrate imaging and measurements from multiple sources with mathematical descriptions of governing physical laws. State-of-the-art computational modeling is being used to combine mechanistic models with data to provide new insight into coronary physiology, optimization of medical technologies, and new applications to guide clinical practice.

Comparison of vortical structures induced by arteriovenous grafts using vector Doppler ultrasound.

Arteriovenous prosthetic grafts are used in hemodialysis. Stenosis in the venous anastomosis is the main cause of occlusion and the role of local hemodynamics in this is considered significant. A new spiral graft design has been proposed to stabilize the flow phenomena in the host vein. Cross-flow vortical structures in the outflow of this graft were compared with those from a control device. Both grafts were integrated in identical in-house ultrasound-compatible flow phantoms with realistic surgical configurations. Constant flow rates were applied. In-plane 2-D velocity and vorticity mapping was developed using a vector Doppler technique. One or two vortices were detected for the spiral graft and two to four for the control, along with reduced stagnation points for the former. The in-plane peak velocity and circulation were calculated and found to be greater for the spiral device, implying increased in-plane mixing, which is believed to inhibit thrombosis and neo-intimal hyperplasia.

Toward GPGPU accelerated human electromechanical cardiac simulations.

In this paper, we look at the acceleration of weakly coupled electromechanics using the graphics processing unit (GPU). Specifically, we port to the GPU a number of components of CHeart--a CPU-based finite element code developed for simulating multi-physics problems. On the basis of a criterion of computational cost, we implemented on the GPU the ODE and PDE solution steps for the electrophysiology problem and the Jacobian and residual evaluation for the mechanics problem. Performance of the GPU implementation is then compared with single core CPU (SC) execution as well as multi-core CPU (MC) computations with equivalent theoretical performance. Results show that for a human scale left ventricle mesh, GPU acceleration of the electrophysiology problem provided speedups of 164 × compared with SC and 5.5 times compared with MC for the solution of the ODE model. Speedup of up to 72 × compared with SC and 2.6 × compared with MC was also observed for the PDE solve. Using the same human geometry, the GPU implementation of mechanics residual/Jacobian computation provided speedups of up to 44 × compared with SC and 2.0 × compared with MC.

Multi-scale parameterisation of a myocardial perfusion model using whole-organ arterial networks.

A method to extract myocardial coronary permeabilities appropriate to parameterise a continuum porous perfusion model using the underlying anatomical vascular network is developed. Canine and porcine whole-heart discrete arterial models were extracted from high-resolution cryomicrotome vessel image stacks. Five parameterisation methods were considered that are primarily distinguished by the level of anatomical data used in the definition of the permeability and pressure-coupling fields. Continuum multi-compartment porous perfusion model pressure results derived using these parameterisation methods were compared quantitatively via a root-mean-square metric to the Poiseuille pressure solved on the discrete arterial vasculature. The use of anatomical detail to parameterise the porous medium significantly improved the continuum pressure results. The majority of this improvement was attributed to the use of anatomically-derived pressure-coupling fields. It was found that the best results were most reliably obtained by using porosity-scaled isotropic permeabilities and anatomically-derived pressure-coupling fields. This paper presents the first continuum perfusion model where all parameters were derived from the underlying anatomical vascular network.

Myocardial perfusion distribution and coronary arterial pressure and flow signals: clinical relevance in relation to multiscale modeling, a review.

Coronary artery disease, CAD, is associated with both narrowing of the epicardial coronary arteries and microvascular disease, thereby limiting coronary flow and myocardial perfusion. CAD accounts for almost 2 million deaths within the European Union on an annual basis. In this paper, we review the physiological and pathophysiological processes underlying clinical decision making in coronary disease as well as the models for interpretation of the underlying physiological mechanisms. Presently, clinical decision making is based on non-invasive magnetic resonance imaging, MRI, of myocardial perfusion and invasive coronary hemodynamic measurements of coronary pressure and Doppler flow velocity signals obtained during catheterization. Within the euHeart project, several innovations have been developed and applied to improve diagnosis-based understanding of the underlying biophysical processes. Specifically, MRI perfusion data interpretation has been advanced by the gradientogram, a novel graphical representation of the spatiotemporal myocardial perfusion gradient. For hemodynamic data, functional indices of coronary stenosis severity that do not depend on maximal vasodilation are proposed and the Valsalva maneuver for indicating the extravascular resistance component of the coronary circulation has been introduced. Complementary to these advances, model innovation has been directed to the porous elastic model coupled to a one-dimensional model of the epicardial arteries. The importance of model development is related to the integration of information from different modalities, which in isolation often result in conflicting treatment recommendations.

Parameterisation of multi-scale continuum perfusion models from discrete vascular networks.

Experimental data and advanced imaging techniques are increasingly enabling the extraction of detailed vascular anatomy from biological tissues. Incorporation of anatomical data within perfusion models is non-trivial, due to heterogeneous vessel density and disparate radii scales. Furthermore, previous idealised networks have assumed a spatially repeating motif or periodic canonical cell, thereby allowing for a flow solution via homogenisation. However, such periodicity is not observed throughout anatomical networks. In this study, we apply various spatial averaging methods to discrete vascular geometries in order to parameterise a continuum model of perfusion. Specifically, a multi-compartment Darcy model was used to provide vascular scale separation for the fluid flow. Permeability tensor fields were derived from both synthetic and anatomically realistic networks using (1) porosity-scaled isotropic, (2) Huyghe and Van Campen, and (3) projected-PCA methods. The Darcy pressure fields were compared via a root-mean-square error metric to an averaged Poiseuille pressure solution over the same domain. The method of Huyghe and Van Campen performed better than the other two methods in all simulations, even for relatively coarse networks. Furthermore, inter-compartment volumetric flux fields, determined using the spatially averaged discrete flux per unit pressure difference, were shown to be accurate across a range of pressure boundary conditions. This work justifies the application of continuum flow models to characterise perfusion resulting from flow in an underlying vascular network.

OpenCMISS: a multi-physics & multi-scale computational infrastructure for the VPH/Physiome project.

The VPH/Physiome Project is developing the model encoding standards CellML (cellml.org) and FieldML (fieldml.org) as well as web-accessible model repositories based on these standards (models.physiome.org). Freely available open source computational modelling software is also being developed to solve the partial differential equations described by the models and to visualise results. The OpenCMISS code (opencmiss.org), described here, has been developed by the authors over the last six years to replace the CMISS code that has supported a number of organ system Physiome projects. OpenCMISS is designed to encompass multiple sets of physical equations and to link subcellular and tissue-level biophysical processes into organ-level processes. In the Heart Physiome project, for example, the large deformation mechanics of the myocardial wall need to be coupled to both ventricular flow and embedded coronary flow, and the reaction-diffusion equations that govern the propagation of electrical waves through myocardial tissue need to be coupled with equations that describe the ion channel currents that flow through the cardiac cell membranes. In this paper we discuss the design principles and distributed memory architecture behind the OpenCMISS code. We also discuss the design of the interfaces that link the sets of physical equations across common boundaries (such as fluid-structure coupling), or between spatial fields over the same domain (such as coupled electromechanics), and the concepts behind CellML and FieldML that are embodied in the OpenCMISS data structures. We show how all of these provide a flexible infrastructure for combining models developed across the VPH/Physiome community.