A left ventricle model to predict post-revascularization ejection fraction based on cine magnetic resonance images

Computational modeling of human left ventricle to assess the role of trabeculae carneae on the diastolic and systolic functions

Trabeculae carneae are irregular structures that cover the endocardial surfaces of both ventricles and account for a significant portion of human ventricular mass. The role of trabeculae carneae in diastolic and systolic functions of the left ventricle (LV) is not well understood. Thus, the objective of this study was to investigate the functional role of trabeculae carneae in the LV. Finite element analyses of ventricular functions were conducted for three different models of human LV derived from high-resolution magnetic resonance imaging (MRI). The first model comprised trabeculae carneae and papillary muscles, while the second model had papillary muscles and partial trabeculae carneae, and the third model had a smooth endocardial surface. We customized these patient-specific models with myofiber architecture generated with a rule-based algorithm, diastolic material parameters using Fung strain energy function derived from bi-axial tests and adjusted with the empirical Klotz relationship, and myocardial contractility constants optimized for average normal ejection fraction of the human LV. Results showed that the partial trabeculae cutting model had enlarged end-diastolic volume, reduced wall stiffness and even increased end-systolic function, indicating that the absence of trabeculae carneae increased the compliance of the LV during diastole, while maintaining systolic function.

The Effect of Trabeculae Carneae on Left Ventricular Diastolic Compliance: Improvement in Compliance With Trabecular Cutting

The role of trabeculae carneae in modulating left ventricular (LV) diastolic compliance remains unclear. The objective of this study was to determine the contribution of trabeculae carneae to the LV diastolic compliance. LV pressure-volume compliance curves were measured in six human heart explants from patients with LV hypertrophy at baseline and following trabecular cutting. The effect of trabecular cutting was also analyzed with finite-element model (FEM) simulations. Our results demonstrated that LV compliance improved after trabecular cutting (p < 0.001). Finite-element simulations further demonstrated that stiffer trabeculae reduce LV compliance further, and that the presence of trabeculae reduced the wall stress in the apex. In conclusion, we demonstrate that integrity of the LV and trabeculae is important to maintain LV stiffness and loss in trabeculae leads to more LV compliance.

Biomechanics of Cardiac Function

The heart pumps blood to maintain circulation and ensure the delivery of oxygenated blood to all the organs of the body. Mechanics play a critical role in governing and regulating heart function under both normal and pathological conditions. Biological processes and mechanical stress are coupled together in regulating myocyte function and extracellular matrix structure thus controlling heart function. Here, we offer a brief introduction to the biomechanics of left ventricular function and then summarize recent progress in the study of the effects of mechanical stress on ventricular wall remodeling and cardiac function as well as the effects of wall mechanical properties on cardiac function in normal and dysfunctional hearts. Various mechanical models to determine wall stress and cardiac function in normal and diseased hearts with both systolic and diastolic dysfunction are discussed. The results of these studies have enhanced our understanding of the biomechanical mechanism in the development and remodeling of normal and dysfunctional hearts. Biomechanics provide a tool to understand the mechanism of left ventricular remodeling in diastolic and systolic dysfunction and guidance in designing and developing new treatments.

A model to determine the effect of collagen fiber alignment on heart function post myocardial infarction

BACKGROUND

Adverse remodeling of the left ventricle (LV) following myocardial infarction (MI) leads to heart failure. Recent studies have shown that scar anisotropy is a determinant of cardiac function post-MI, however it remains unclear how changes in extracellular matrix (ECM) organization and structure contribute to changes in LV function. The objective of this study is to develop a model to identify potential mechanisms by which collagen structure and organization affect LV function post-MI.

METHODS

A four-region, multi-scale, cylindrical model of the post-MI LV was developed. The mechanical properties of the infarct region are governed by a constitutive equation based on the uncrimping of collagen fibers. The parameters of this constitutive equation include collagen orientation, angular dispersion, fiber stiffness, crimp angle, and density. Parametric variation of these parameters was used to elucidate the relationship between collagen properties and LV function.

RESULTS

The mathematical model of the LV revealed several factors that influenced cardiac function post-MI. LV function was maximized when collagen fibers were aligned longitudinally. Increased collagen density was also found to improve stroke volume for longitudinal alignments while increased fiber stiffness decreased stroke volume for circumferential alignments.

CONCLUSIONS

The results suggest that cardiac function post-MI is best preserved through increased circumferential compliance. Further, this study identifies several collagen fiber-level mechanisms that could potentially regulate both infarct level and organ level mechanics. Improved understanding of the multi-scale relationships between the ECM and LV function will be beneficial in the design of new diagnostic and therapeutic technologies.

Mathematical modeling of left ventricular dimensional changes in mice during aging

Cardiac aging is characterized by diastolic dysfunction of the left ventricle (LV), which is due in part to increased LV wall stiffness. In the diastolic phase, myocytes are relaxed and extracellular matrix (ECM) is a critical determinant to the changes of LV wall stiffness. To evaluate the effects of ECM composition on cardiac aging, we developed a mathematical model to predict LV dimension and wall stiffness changes in aging mice by integrating mechanical laws and our experimental results. We measured LV dimension, wall thickness, LV mass, and collagen content for wild type (WT) C57/BL6J mice of ages ranging from 7.3 months to those of 34.0 months. The model was established using the thick wall theory and stretch-induced tissue growth to an isotropic and homogeneous elastic composite with mixed constituents. The initial conditions of the simulation were set based on the data from the young mice. Matlab simulations of this mathematical model demonstrated that the model captured the major features of LV remodeling with age and closely approximated experimental results. Specifically, the temporal progression of the LV interior and exterior dimensions demonstrated the same trend and order-of-magnitude change as our experimental results. In conclusion, we present here a validated mathematical model of cardiac aging that applies the thick-wall theory and stretch-induced tissue growth to LV remodeling with age.

The relation between viable segments and left ventricular ejection fraction improvement

For patients with coronary artery disease and left ventricular dysfunction who undergo revascularization, it is important to estimate the left ventricular ejection fraction (LVEF) improvement after revascularization, as this is a strong indicator of the long-term outcome. Identification of viable segments from echocardiography has been considered a predictive sign of LVEF improvement. However, a quantitative relation between segmental function recovery and global ejection fraction improvement has not been established. There is a clinical need to determine parameters that are predictive to LVEF improvement. A cylindrical left ventricular model is proposed to establish the relation between segmental myocardial function and LVEF based on a 12-segment echocardiograph model. Model results show that LVEF improvement is directly related to the contraction ratio in normal segments and a weighted sum of the number of viable segments that recover to normal or hypokinetic, which is equal to a weighted sum of the change in wall motion scores. This new combined parameter is a better predictor of the amount of LVEF improvement than the total number of viable segments or preoperative ejection fraction. The predictive value of the model was illustrated in a group of four patients with coronary artery disease who underwent revascularization.

An echocardiogram-based 16-segment model for predicting left ventricular ejection fraction improvement

An important goal of cardiac revascularization is to improve the left ventricular ejection fraction, which is an important clinical determinant of the long-term outcome for patients with coronary artery disease. Regional myocardium function improvement may be expected from revascularization when viable myocardium is detected using non-invasive cardiac imaging. However, the quantitative relation between regional myocardial function recovery and global heart function improvement has not been determined and there is no tool to predict the amount of ejection fraction improvement prior to revascularization. A 16 segment biomechanical model of the left ventricle is proposed to establish the relationship between the ejection fraction improvement and the viable segments detected by echocardiography. With the assumption that the viable segments would potentially improve contractility after revascularization, the ejection fraction improvement is estimated for all possible wall motion score improvement in viable segments. The model shows that the ejection fraction improvement is linearly related to the contractility in the normal segments and a weighted sum of the numbers of viable segments that recover to normal or hypokinetic contractility. The predictive value of the model is illustrated for a group of patients reported in the literature. The model predictions of the post-revascularization ejection fraction are very close to the follow-up data with a very strong correlation (R2 = 0.92). By predicting the ejection fraction improvement, the model may provide a tool for evaluating the efficacy of revascularization and for selecting patients who would benefit from revascularization.