Mechano-electrical feedback explains T-wave morphology and optimizes cardiac pump function: insight from a multi-scale model

Advancing clinical translation of cardiac biomechanics models: a comprehensive review, applications and future pathways

Cardiac mechanics models are developed to represent a high level of detail, including refined anatomies, accurate cell mechanics models, and platforms to link microscale physiology to whole-organ function. However, cardiac biomechanics models still have limited clinical translation. In this review, we provide a picture of cardiac mechanics models, focusing on their clinical translation. We review the main experimental and clinical data used in cardiac models, as well as the steps followed in the literature to generate anatomical meshes ready for simulations. We describe the main models in active and passive mechanics and the different lumped parameter models to represent the circulatory system. Lastly, we provide a summary of the state-of-the-art in terms of ventricular, atrial, and four-chamber cardiac biomechanics models. We discuss the steps that may facilitate clinical translation of the biomechanics models we describe. A well-established software to simulate cardiac biomechanics is lacking, with all available platforms involving different levels of documentation, learning curves, accessibility, and cost. Furthermore, there is no regulatory framework that clearly outlines the verification and validation requirements a model has to satisfy in order to be reliably used in applications. Finally, better integration with increasingly rich clinical and/or experimental datasets as well as machine learning techniques to reduce computational costs might increase model reliability at feasible resources. Cardiac biomechanics models provide excellent opportunities to be integrated into clinical workflows, but more refinement and careful validation against clinical data are needed to improve their credibility. In addition, in each context of use, model complexity must be balanced with the associated high computational cost of running these models.

Computer Modelling for Better Diagnosis and Therapy of Patients by Cardiac Resynchronisation Therapy

Mathematical or computer models have become increasingly popular in biomedical science. Although they are a simplification of reality, computer models are able to link a multitude of processes to each other. In the fields of cardiac physiology and cardiology, models can be used to describe the combined activity of all ion channels (electrical models) or contraction-related processes (mechanical models) in potentially millions of cardiac cells. Electromechanical models go one step further by coupling electrical and mechanical processes and incorporating mechano-electrical feedback. The field of cardiac computer modelling is making rapid progress due to advances in research and the ever-increasing calculation power of computers. Computer models have helped to provide better understanding of disease mechanisms and treatment. The ultimate goal will be to create patient-specific models using diagnostic measurements from the individual patient. This paper gives a brief overview of computer models in the field of cardiology and mentions some scientific achievements and clinical applications, especially in relation to cardiac resynchronisation therapy (CRT).

Images as drivers of progress in cardiac computational modelling

Computational models have become a fundamental tool in cardiac research. Models are evolving to cover multiple scales and physical mechanisms. They are moving towards mechanistic descriptions of personalised structure and function, including effects of natural variability. These developments are underpinned to a large extent by advances in imaging technologies. This article reviews how novel imaging technologies, or the innovative use and extension of established ones, integrate with computational models and drive novel insights into cardiac biophysics. In terms of structural characterization, we discuss how imaging is allowing a wide range of scales to be considered, from cellular levels to whole organs. We analyse how the evolution from structural to functional imaging is opening new avenues for computational models, and in this respect we review methods for measurement of electrical activity, mechanics and flow. Finally, we consider ways in which combined imaging and modelling research is likely to continue advancing cardiac research, and identify some of the main challenges that remain to be solved.

Mechano-electrical coupling as framework for understanding functional remodeling during LBBB and CRT

It is not understood why, after onset of left bundle-branch block (LBBB), acute worsening of cardiac function is followed by a further gradual deterioration of function, whereas most adverse cardiac events lead to compensatory adaptations. We investigated whether mechano-electrical coupling (MEC) can explain long-term remodeling with LBBB and cardiac resynchronization therapy (CRT). To this purpose, we used an integrative modeling approach relating local ventricular electrophysiology, calcium handling, and excitation-contraction coupling to global cardiovascular mechanics and hemodynamics. Each ventricular wall was composed of multiple mechanically and electrically coupled myocardial segments. MEC was incorporated by allowing adaptation of L-type Ca2+ current aiming at minimal dispersion of local external work, an approach that we previously applied to replicate T-wave memory in a synchronous heart after a period of asynchronous activation. LBBB instantaneously decreased left-ventricular stroke work and increased end-diastolic volume. During sustained LBBB, MEC reduced intraventricular dispersion of mechanical workload and repolarization. However, MEC-induced reduction in contractility in late-activated regions was larger than the contractility increase in early-activated regions, resulting in further decrease of stroke work and increase of end-diastolic volume. Upon the start of CRT, stroke work increased despite a wider dispersion of mechanical workload. During sustained CRT, MEC-induced reduction in dispersion of workload and repolarization coincided with a further reduction in end-diastolic volume. In conclusion, MEC may represent a useful framework for better understanding the long-term changes in cardiac electrophysiology and contraction following LBBB as well as CRT.

Histo-anatomical structure of the living isolated rat heart in two contraction states assessed by diffusion tensor MRI

Deformation and wall-thickening of ventricular myocardium are essential for cardiac pump function. However, insight into the histo-anatomical basis for cardiac tissue re-arrangement during contraction is limited. In this report, we describe dynamic changes in regionally prevailing cardiomyocyte (fibre) and myolaminar (sheet) orientations, using Diffusion Tensor Imaging (DTI) of ventricles in the same living heart in two different mechanical states. Hearts, isolated from Sprague–Dawley rats, were Langendorff-perfused and imaged, initially in their slack state during cardioplegic arrest, then during lithium-induced contracture. Regional fibre- and sheet-orientations were derived from DTI-data on a voxel-wise basis. Contraction was accompanied with a decrease in left-handed helical fibres (handedness relative to the baso-apical direction) in basal, equatorial, and apical sub-epicardium (by 14.0%, 17.3%, 15.8% respectively; p < 0.001), and an increase in right-handed helical fibres of the sub-endocardium (by 11.0%, 12.1% and 16.1%, respectively; p < 0.001). Two predominant sheet-populations were observed, with sheet-angles of either positive (β+) or negative (β−) polarity relative to a ‘chamber-horizontal plane’ (defined as normal to the left ventricular long-axis). In contracture, mean ‘intersection’-angle (geometrically quantifiable intersection of sheet-angle projections) between β+ and β− sheet-populations increased from 86.2 ± 5.5° (slack) to 108.3 ± 5.4° (p < 0.001). Subsequent high-resolution DTI of fixed myocardium, and histological sectioning, reconfirmed the existence of alternating sheet-plane populations. Our results suggest that myocardial tissue layers in alternating sheet-populations align into a more chamber-horizontal orientation during contraction. This re-arrangement occurs via an accordion-like mechanism that, combined with inter-sheet slippage, can significantly contribute to ventricular deformation, including wall-thickening in a predominantly centripetal direction and baso-apical shortening.

Slow Calcium-Depolarization-Calcium waves may initiate fast local depolarization waves in ventricular tissue

Intercellular calcium waves in cardiac myocytes are a well-recognized, if incompletely understood, phenomenon. In a variety of preparations, investigators have reported multi-cellular calcium waves or triggered propagated contractions, but the mechanisms of propagation and pathological importance of these events remain unclear. Here, we review existing experimental data and present a computational approach to investigate the mechanisms of multi-cellular calcium wave propagation. Over the past 50 years, the standard modeling paradigm for excitable cardiac tissue has seen increasingly detailed models of the dynamics of individual cells coupled in tissue solely by intercellular and interstitial current flow. Although very successful, this modeling regime has been unable to capture two important phenomena: 1) the slow intercellular calcium waves observed experimentally, and 2) how intercellular calcium events resulting in delayed after depolarizations at the cellular level could overcome a source-sink mismatch to initiate depolarization waves in tissue. In this paper, we introduce a mathematical model with subcellular spatial resolution, in which we allow both inter- and intracellular current flow and calcium diffusion. In simulations of coupled cells employing this model, we observe: a) slow inter-cellular calcium waves propagating at about 0.1 mm/s, b) faster Calcium-Depolarization-Calcium (CDC) waves, traveling at about 1 mm/s, and c) CDC-waves that can set off fast depolarization-waves (50 cm/s) in tissue with varying gap-junction conductivity.