Enabling strain imaging in realistic Eulerian ultrasound simulation methods

Cardiovascular strain imaging is continually improving due to ongoing advances in ultrasound acquisition and data processing techniques. The phantoms used for validation of new methods are often burdensome to make and lack flexibility to vary mechanical and acoustic properties. Simulations of US imaging provide an alternative with the required flexibility and ground truth strain data. However, the current Lagrangian US strain imaging models cannot simulate heterogeneous speed of sound distributions and higher-order scattering, which limits the realism of the simulations. More realistic Eulerian modelling techniques exist but have so far not been used for strain imaging. In this research, a novel sampling scheme was developed based on a band-limited interpolation of the medium, which enables accurate strain simulation in Eulerian methods. The scheme was validated in k-Wave using various numerical phantoms and by a comparison with Field II. The method allows for simulations with a large range in strain values and was accurate with errors smaller than −60 dB. Furthermore, an excellent agreement with the Fourier theory of US scattering was found. The ability to perform simulations with heterogeneous speed of sound distributions was demonstrated using a pulsating artery model. The developed sampling scheme contributes to more realistic strain imaging simulations, in which the effect of heterogenous acoustic properties can be taken into account

MarioHeart:Novel In-Vitro Flow Model for Testing Heart Valve Prostheses and Anticoagulant Therapies

Mechanical heart valve (MHV) prostheses present a risk of thromboembolic complications despite antithrombotic therapy. Further steps in the development of more hemocompatible MHVs and new anticoagulants are impeded due to the lack of adequate in-vitro models. With the development of a novel in-vitro model (MarioHeart), a pulsatile flow similar to the arterial circulation is emulated. The MarioHeart design owns unique features as 1) a single MHV within a torus with low surface/volume ratio, 2) a closed loop system, and 3) a dedicated external control system driving the oscillating rotational motion of the torus. For verification purposes, a blood analog fluid seeded with particles was used to assess fluid velocity and flow rate using a speckle tracking method on high-speed video recordings of the rotating model. The flow rate resembled the physiological flow rate in the aortic root, in both shape and amplitude. Additional in-vitro runs with porcine blood showed thrombi on the MHV associated with the suture ring, which is similar to the in-vivo situation. MarioHeart is a simple design which induces well-defined fluid dynamics resulting in physiologically nonturbulent flow without stasis of the blood. MarioHeart seems suitable for testing the thrombogenicity of MHVs and the potential of new anticoagulants.</p

A numerical simulation of heartassist5 blood pump using an advanced turbulence model

The need for mechanical assistance of the failing heart has increased with improvements in medicine and a rapidly aging population. In recent decades, significant progress has been made in the development and refinement of ventricular assist devices (VADs). Such devices operate in mixed laminar, transitional, and turbulent flow regime. One tool that assists in the development of VADs by facilitating understanding of the physical and mechanical properties of these flow regimes is computational fluid dynamics (CFD). In our investigation, we tested an advanced turbulence model that is a further development from standard Reynolds-averaged Navier-Stokes (RANS) models. From estimated pump flow rates (Q0) and constant rotation speed (n), pressure head (Δp) was calculated and validated with experimental data. An advanced turbulence model called scale adaptive simulation (SAS) was used in the solving of six different working cases comparing numerical SAS-SST and standard SST-kω models to experimental results

Uncertainty in model‐based treatment decision support: applied to aortic valve stenosis

Patient outcome in trans-aortic valve implantation (TAVI) therapy partly relies on a patient's haemodynamic properties that cannot be determined from current diagnostic methods alone. In this study, we predict changes in haemodynamic parameters (as a part of patient outcome) after valve replacement treatment in aortic stenosis patients. A framework to incorporate uncertainty in patient-specific model predictions for decision support is presented. A 0D lumped parameter model including the left ventricle, a stenotic valve and systemic circulatory system has been developed, based on models published earlier. The unscented Kalman filter (UKF) is used to optimize model input parameters to fit measured data pre-intervention. After optimization, the valve treatment is simulated by significantly reducing valve resistance. Uncertain model parameters are then propagated using a polynomial chaos expansion approach. To test the proposed framework, three in silico test cases are developed with clinically feasible measurements. Quality and availability of simulated measured patient data are decreased in each case. The UKF approach is compared to a Monte Carlo Markov Chain (MCMC) approach, a well-known approach in modelling predictions with uncertainty. Both methods show increased confidence intervals as measurement quality decreases. By considering three in silico test-cases we were able to show that the proposed framework is able to incorporate optimization uncertainty in model predictions and is faster and the MCMC approach, although it is more sensitive to noise in flow measurements. To conclude, this work shows that the proposed framework is ready to be applied to real patient data

A 1D wave propagation model of coronary flow in a beating heart

Due to recent developments in miniaturized sensors on guide-wires, assessment of coronary artery disease with intracoronary pressure and flow measurements has become available. However, direct quantification is still limited to the large epicardial vessels, which means that microvascular disease can only be determined from upstream measurements using an appropriate model of the vessels and their interaction with the cardiac muscle

Mechanical properties of the porcine coronary artery

Knowledge of the mechanical properties of arteries is important to understand vascular function during disease and the effect of interventions, such as PTCA treatment. A mechanical model of the vascular tree would facilitate the improvement of (balloon-)catheters and stents. The aim of this research is to propose general parameter values for the fiber-reinforced material model as proposed by Driessen et al. (2005) that can describe the arterial wall behavior of the porcine left anterior descending coronary artery (LAD, fig. 1a) at physiological axial stretch

Intraplaque haemorrhage detection using single-wavelength PAI and singular value decomposition in the carotid artery

The rupture of a vulnerable carotid plaque featuring a lipid-rich necrotic core and intra-plaque haemorrhages is the major cause of stroke. Photoacoustic imaging (PAI) is a promising technique for assessing plaque vulnerability in the carotid artery due to its ability to assess the chemical composition in addition to its anatomy. However, assessment of chemical composition is usually based on the absorption differences of chromophores between multiple wavelengths, which heavily increase the complexity and cost of the imaging system. In this study, a new method based on single-wavelength PAI to detect intra-plaque haemorrhages, an important indicator of plaque vulnerability, is developed. The method uses wall filtering based on singular value decomposition. To test the method, a carotid plaque phantom mimicking intra-plaque haemorrhages, lumen and vasa vasorum is designed and imaged at 808nm in vitro. The phantom experiment shows wall filtering using singular value decomposition to be a viable method capable of discriminating signals originating from the lumen, vasa vasorum and intraplaque haemorrhages, allowing for the detection of intra-plaque haemorrhages with single wavelength PAI. This enables new opportunities for PAI of vulnerable carotid plaques with more cost effective and diverse laser sources