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. 2017 Nov;5(21):e13392.
doi: 10.14814/phy2.13392.

Organ-level validation of a cross-bridge cycling descriptor in a left ventricular finite element model: effects of ventricular loading on myocardial strains

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Organ-level validation of a cross-bridge cycling descriptor in a left ventricular finite element model: effects of ventricular loading on myocardial strains

Sheikh Mohammad Shavik et al. Physiol Rep. 2017 Nov.

Abstract

Although detailed cell-based descriptors of cross-bridge cycling have been applied in finite element (FE) heart models to describe ventricular mechanics, these multiscale models have never been tested rigorously to determine if these descriptors, when scaled up to the organ-level, are able to reproduce well-established organ-level physiological behaviors. To address this void, we here validate a left ventricular (LV) FE model that is driven by a cell-based cross-bridge cycling descriptor against key organ-level heart physiology. The LV FE model was coupled to a closed-loop lumped parameter circulatory model to simulate different ventricular loading conditions (preload and afterload) and contractilities. We show that our model is able to reproduce a linear end-systolic pressure volume relationship, a curvilinear end-diastolic pressure volume relationship and a linear relationship between myocardial oxygen consumption and pressure-volume area. We also show that the validated model can predict realistic LV strain-time profiles in the longitudinal, circumferential, and radial directions. The predicted strain-time profiles display key features that are consistent with those measured in humans, such as having similar peak strains, time-to-peak-strain, and a rapid change in strain during atrial contraction at late-diastole. Our model shows that the myocardial strains are sensitive to not only LV contractility, but also to the LV loading conditions, especially to a change in afterload. This result suggests that caution must be exercised when associating changes in myocardial strain with changes in LV contractility. The methodically validated multiscale model will be used in future studies to understand human heart diseases.

Keywords: Cardiac energetics; finite element modeling; left ventricle; myocardial strain.

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Figures

Figure 1
Figure 1
(A) Model schematic showing the coupling of LV FE model to a closed‐loop lumped parameter circulatory model, (B) Schematic showing the calculation of pressurevolume area (PVA), (C) Schematic showing the definition of LV torsion.
Figure 2
Figure 2
Isometric twitch profiles for different contractility cases. Force values were normalized by the maximum force of the baseline contractility case.
Figure 3
Figure 3
Effects on pressurevolume loop by due to a change in (A) preload at a constant afterload, (B) afterload at a constant preload, (C) contractility (solid) c.f. baseline (dotted), Values indicate corresponding ejection fraction.
Figure 4
Figure 4
Myocardial oxygen consumption (MVO 2) versus pressurevolume area (PVA) relationship predicted by the model. Data points are calculated at different preload, afterload and contractilites.
Figure 5
Figure 5
Longitudinal (first column), circumferential (second column), radial (third column) strain‐time profiles. (A) Comparison of the model predictions with previously published in vivo 2D STE measurements (Dandel et al. 2009; Gorcsan and Tanaka 2011; Hoit 2011). Strain‐time profiles predicted by the model with, (B) different preload (with constant afterload), (C) different afterload (with constant preload) and, (D) different contractility for a representative case (case P2 shown in Fig. 4A and C).
Figure 6
Figure 6
Regional variation in (A) longitudinal, (B) circumferential, and (C) radial strain profiles for a specific case corresponding with normal hemodynamic conditions (case P2, Fig. 4A).
Figure 7
Figure 7
(A) Longitudinal, (B) circumferential, (C) radial strain profiles calculated using different strain definitions.
Figure 8
Figure 8
Left ventricular torsion for varying (A) preload, (B) afterload, and (C) contractility (case P2 in Fig. 3A and C) compared with echocardiographic measurements by Mondillo et al. (2011).

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References

    1. Adeniran, I. , Hancox J. C., and Zhang H.. 2013a. In silico investigation of the short QT syndrome, using human ventricle models incorporating electromechanical coupling. Front. Physiol. 4:166. - PMC - PubMed
    1. Adeniran, I. , Hancox J. C., and Zhang H.. 2013b. Effect of cardiac ventricular mechanical contraction on the characteristics of the ECG: a simulation study. J Biomed Sci Eng 6:47–60.
    1. Adeniran, I. , MacIver D. H., Hancox J. C., and Zhang H.. 2015. Abnormal calcium homeostasis in heart failure with preserved ejection fraction is related to both reduced contractile function and incomplete relaxation: an electromechanically detailed biophysical modeling study. Front. Physiol. 6:78. - PMC - PubMed
    1. Burkhoff, D. 1994. Explaining load dependence of ventricular contractile properties with a model of excitation‐contraction coupling. J. Mol. Cell. Cardiol. 26:959–978. - PubMed
    1. Burkhoff, D. , de Tombe P. P., Hunter W. C., and Kass D. A.. 1991. Contractile strength a of left ventricle are enhanced anical efficiency by physiological afterload. Am J Hear Circ Physilogy 260:569–578. - PubMed

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