No abstract

No abstract

Infarcted segments of myocardium demonstrate functional impairment ranging in severity from hypokinesis to dyskinesis. We sought to better define the contributions of passive material properties (stiffness) and active properties (contracting myocytes) to infarct thickening. Using a finite-element (FE) model, we tested the hypothesis that infarcted myocardium must contain contracting myocytes to be akinetic and not dyskinetic. A three-dimensional FE mesh of the left ventricle was developed with echocardiographs from a reperfused ovine anteroapical infarct. The nonlinear stress-strain relationship for the diastolic myocardium was anisotropic with respect to the local muscle fiber direction, and an elastance model for active fiber stress was incorporated. The diastolic stiffness (C) and systolic material property (isometric tension at longest sarcomere length and peak intracellular calcium concentration, T(max)) of the uninfarcted remote myocardium were assumed to be normal (C = 0.876 kPa, T(max) = 135.7 kPa). Diastolic and systolic properties of the infarct necessary to produce akinesis, defined as an average radial strain between -0.01 and 0.01, were determined by assigning a range of diastolic stiffnesses and scaling infarct T(max) to represent the percentage of contracting myocytes between 0% and 100%. As C was increased to 11 times normal (C = 10 kPa) the percentage of T(max) necessary for akinesis increased from 20% to 50%. Without contracting myocytes, C = 250 kPa was necessary to achieve akinesis. If infarct stiffness is <285 times normal, contracting myocytes are required to prevent dyskinetic infarct wall motion.

Although computational modeling is common in many areas of science and engineering, only recently have advances in experimental techniques and medical imaging allowed this tool to be applied in cardiac surgery. Despite its infancy in cardiac surgery, computational modeling has been useful in calculating the effects of clinical devices and surgical procedures. In this review, we present several examples that demonstrate the capabilities of computational cardiac modeling in cardiac surgery. Specifically, we demonstrate its ability to simulate surgery, predict myofiber stress and pump function, and quantify changes to regional myocardial material properties. In addition, issues that would need to be resolved in order for computational modeling to play a greater role in cardiac surgery are discussed.