Search

Development of cardiac multiphysics models has progressed significantly over the decades and simulations combining multiple physics interactions have become increasingly common. In this review, we summarise the progress in this field focusing on various approaches of integrating ventricular structures. electrophysiological properties, myocardial mechanics, as well as incorporating blood hemodynamics and the circulatory system. Common coupling approaches are discussed and compared, including the advantages and shortcomings of each. Currently used strategies for patient-specific implementations are highlighted and potential future improvements considered.

Background: The appropriate placement and size selection of mitral prostheses in transcatheter mitral valve implantation (TMVI) is critical, as encroachment on the left ventricular outflow tract (LVOT) may lead to flow obstruction. Recent advances in computed tomography (CT) can be employed for pre-procedural planning of mitral prosthetic valve placement. This study aims to develop patient-specific computational fluid dynamics models of the left ventricle (LV) in the presence of a mitral valve prosthesis to investigate blood flow and LVOT pressure gradient during systole., Methods: Patient-specific computational fluid dynamics simulations of TMVI with varied cardiac anatomy and insertion angles were performed (n = 30). Wide-volume full cycle cardiovascular CT images prior to TMVI were used as source anatomical data (n = 6 patients). Blood movement was governed by Navier-Stokes equations and the LV endocardial wall deformation was derived from each patient's CT images., Results: The computed pressure gradients in the presence of the mitral prosthesis compared well with clinically measured gradients. Analysis of the effects of prosthetic valve angulation, aorto-mitral annular angle, ejection fraction, LV size and new LVOT area (neo-LVOT) after TMVI in silico revealed that the neo-LVOT area (p < 0.001) was the most significant factor affecting LVOT pressure gradient. Angulation of the mitral valve can substantially mitigate LVOT gradient., Conclusions: Computational fluid dynamics simulation is a promising method to aid in pre-TMVI planning and understanding the factors underlying LVOT obstruction., (Copyright © 2020 Society of Cardiovascular Computed Tomography. Published by Elsevier Inc. All rights reserved.)

A generic cardiomyocyte ionic model, whose complexity lies between a simple phenomenological formulation and a biophysically detailed ionic membrane current description, is presented. The model provides a user-defined number of ionic currents, employing two-gate Hodgkin-Huxley type kinetics. Its generic nature allows accurate reconstruction of action potential waveforms recorded experimentally from a range of cardiac myocytes. Using a multiobjective optimisation approach, the generic ionic model was optimised to accurately reproduce multiple action potential waveforms recorded from central and peripheral sinoatrial nodes and right atrial and left atrial myocytes from rabbit cardiac tissue preparations, under different electrical stimulus protocols and pharmacological conditions. When fitted simultaneously to multiple datasets, the time course of several physiologically realistic ionic currents could be reconstructed. Model behaviours tend to be well identified when extra experimental information is incorporated into the optimisation.

A 3D model of atrial electrical activity has been developed with spatially heterogeneous electrophysiological properties. The atrial geometry, reconstructed from the male Visible Human dataset, included gross anatomical features such as the central and peripheral sinoatrial node (SAN), intra-atrial connections, pulmonary veins, inferior and superior vena cava, and the coronary sinus. Membrane potentials of myocytes from spontaneously active or electrically paced in vitro rabbit cardiac tissue preparations were recorded using intracellular glass microelectrodes. Action potentials of central and peripheral SAN, right and left atrial, and pulmonary vein myocytes were each fitted using a generic ionic model having three phenomenological ionic current components: one time-dependent inward, one time-dependent outward, and one leakage current. To bridge the gap between the single-cell ionic models and the gross electrical behaviour of the 3D whole-atrial model, a simplified 2D tissue disc with heterogeneous regions was optimised to arrive at parameters for each cell type under electrotonic load. Parameters were then incorporated into the 3D atrial model, which as a result exhibited a spontaneously active SAN able to rhythmically excite the atria. The tissue-based optimisation of ionic models and the modelling process outlined are generic and applicable to image-based computer reconstruction and simulation of excitable tissue.

Generic ionic models optimized to replicate experimentally recorded cardiac action potentials (APs) from the central and peripheral sinoatrial node (SAN), the natural pacemaker of the heart, as well as atrial intact-myocytes are implemented in a realistic 2D model of rabbit SAN geometry. The model was used to investigate two frequently-proposed modes of SAN architecture: the gradient and mosaic hypotheses. In a simplified gradient arrangement, the peripheral SAN region acts as a transition zone between the central SAN and atrium and is required for spontaneous rhythmic initiation of APs from central SAN into the atria. Furthermore, the application of optimized single cell parameters to the realistic 2D rabbit geometry did not accurately replicate experimentally recorded APs. On the other hand, in an adapted mosaic geometry, peripheral SAN cells were not required to produce spontaneous regular excitation.

A cardiac sino-atrial tissue model based on a simplified 2D disc geometry and a generic ionic model is described and optimized to fit intact-tissue microelectrode experimental recordings. Concentric regions were defined representing the central and peripheral sino-atrial node and the atrium, each with a unique set of ionic model parameters. Intracellular action potentials were recorded from the respective myocytes in an intact rabbit in vitro sino-atrial tissue preparation. The 2D disc geometry was described numerically using a modified version of the cable equation of electrical propagation. The cell-specific model parameters at three nodes representing each region of the disc geometry were optimized, using a curvilinear gradient optimization algorithm, to generate action potentials waveforms that fitted the experimentally recorded waveforms. The optimized model was able to reproduce spontaneous sino-atrial node activation and atrial excitation and propagation. It offers an improved representation of the electrotonic interactions between heterogenous cell types and is able to reproduce the transition in action potential morphology between different regions. This tissue based optimization approach is a contribution to the development of realistic electro-anatomical cardiac models based on experimental data.

A multiple dataset model fitting approach for improving parameter reliability in action potential modeling is presented. A robust generic cardiac ionic model employing membrane currents based on two-gate Hodgkin-Huxley kinetics is described. Its generic nature allows it to accurately reproduce action potential waveforms in heterogeneous cardiac tissue by optimizing parameters governing ion channel kinetics and magnitudes. The model allows a user-defined number of voltage and time-dependent ion currents to be incorporated, in order to reproduce and predict multiple action potential waveforms recorded in intact cardiac myocyte. In total 12 N(c)+2 parameters were optimized using a curvilinear gradient method, where N(c) is the user-specified number of time-dependent currents. Given appropriate experimental datasets, many of the known physiological membrane currents could be effectively reconstructed. Also, the optimized models were able to predict additional experimental action potential recordings that were not used in the optimization process.