A finite element model of left ventricular mechanics showed that transmural fiber angle can be predicted by minimizing sarcomere length and developed stress variance, but not ATP consumption variance.
Does fiber orientation in the left ventricular wall influence ejection fraction, efficiency, and heterogeneity of stress, strain, and ATP consumption?
Computational modeling suggests that uniform strain or stress, rather than ATP consumption distribution, regulates physiological fiber orientation in the heart.
The aim of this study was to investigate the influence of fiber orientation in the left ventricular (LV) wall on the ejection fraction, efficiency, and heterogeneity of the distributions of developed fiber stress, strain and ATP consumption. A finite element model of LV mechanics was used with active properties of the cardiac muscle described by the Huxley-type cross-bridge model. The computed variances of sarcomere length (SL var ), developed stress (DS var ), and ATP consumption (ATP var ) have several minima at different transmural courses of helix fiber angle. We identified only one region in the used design space with high ejection fraction, high efficiency of the LV and relatively small SL var , DS var , and ATP var . This region corresponds to the physiological distribution of the helix fiber angle in the LV wall. Transmural fiber angle can be predicted by minimizing SL var and DS var , but not ATP var . If ATP var was minimized, then the transverse fiber angle was considerably underestimated. The results suggest that ATP consumption distribution is not regulating the fiber orientation in the heart.
Vendelin et al. (Sun,) conducted a other in Left ventricular mechanics. Finite element model of LV mechanics was evaluated on Ejection fraction, efficiency, and heterogeneity of developed fiber stress, strain and ATP consumption. A finite element model of left ventricular mechanics showed that transmural fiber angle can be predicted by minimizing sarcomere length and developed stress variance, but not ATP consumption variance.