The development and clinical use of patient-specific models of the heart is now a feasible goal. Models have the potential to aid in diagnosis and support decision-making in clinical cardiology. Several groups are now working on developing multi-scale models of the heart for understanding therapeutic mechanisms and better predicting clinical outcomes of interventions such as cardiac resynchronization therapy. Here we describe the methodology for generating a patient-specific model of the failing heart with a myocardial infarct and left ventricular bundle branch block. We discuss some of the remaining challenges in developing reliable patient-specific models of cardiac electromechanical activity, and identify some of the main areas for focusing future research efforts. Key challenges include: efficiently generating accurate patient-specific geometric meshes and mapping regional myofiber architecture to them; modeling electrical activation patterns based on cellular alterations in human heart failure, and estimating regional tissue conductivities based on clinically available electrocardiographic recordings; estimating unloaded ventricular reference geometry and material properties for biomechanical simulations; and parameterizing systemic models of circulatory dynamics from available hemodynamic measurements.

The excitation-contraction coupling properties of cardiac myocytes isolated from different regions of the mammalian left ventricular wall have been shown to vary considerably, with uncertain effects on ventricular function. We embedded a cell-level excitation-contraction coupling model with region-dependent parameters within a simple finite element model of left ventricular geometry to study effects of electromechanical heterogeneity on local myocardial mechanics and global haemodynamics. This model was compared with one in which heterogeneous myocyte parameters were assigned randomly throughout the mesh while preserving the total amount of each cell subtype. The two models displayed nearly identical transmural patterns of fibre and cross-fibre strains at end-systole, but showed clear differences in fibre strains at earlier points during systole. Haemodynamic function, including peak left ventricular pressure, maximal rate of left ventricular pressure development and stroke volume, were essentially identical in the two models. These results suggest that in the intact ventricle heterogeneously distributed myocyte subtypes primarily impact local deformation of the myocardium, and that these effects are greatest during early systole.

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Recently, attention has been focused on comparing left ventricular (LV) endocardial (ENDO) with epicardial (EPI) pacing for cardiac resynchronization therapy. However, the effects of ENDO and EPI lead placement at multiple sites have not been studied in failing hearts. We hypothesized that differences in the improvement of ventricular function due to ENDO vs. EPI pacing in dyssynchronous (DYSS) heart failure may depend on the position of the LV lead in relation to the original activation pattern. In six nonfailing and six failing dogs, electrical DYSS was created by atrioventricular sequential pacing of the right ventricular apex. ENDO was compared with EPI biventricular pacing at five LV sites. In failing hearts, increases in the maximum rate of LV pressure change (dP/dt; r = 0.64), ejection fraction (r = 0.49), and minimum dP/dt (r = 0.51), relative to DYSS, were positively correlated (P < 0.01) with activation time at the LV pacing site during ENDO but not EPI pacing. ENDO pacing at sites with longer activation delays led to greater improvements in hemodynamic parameters and was associated with an overall reduction in electrical DYSS compared with EPI pacing (P < 0.05). These findings were qualitatively similar for nonfailing hearts. Improvement in hemodynamic function increased with activation time at the LV pacing site during ENDO but not EPI pacing. At the anterolateral wall, end-systolic transmural function was greater with local ENDO compared with EPI pacing. ENDO pacing and intrinsic activation delay may have important implications for management of DYSS heart failure.

Here we describe new computational models of cardiac electromechanics starting from the cellular scale and building to the tissue, organ and system scales. We summarize application to human genetic diseases (LQT1 and LQT3) and to modeling of congestive heart failure.