Computational Modeling on Drugs Effects for Left Ventricle in Cardiomyopathy Disease

Figures

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  Figure 1. Block diagram of the FSI algorithm coupled with multi-scale model of muscle contraction. Muscle is discretized into FEs where each FE contains muscle fiber and integration points [26].

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  Figure 2. Algorithm linking FE analysis and MP surrogate model.

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  Figure 3. Scenario 1: Drug action via modulation of calcium transient. Adopted from ref. [16].

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  Figure 4. (A) Adjusted calcium transients from the observed in human HCM trabeculae [30]. (B) Disopyramide effects on human HCM trabeculae twitch contraction, shown as comparison between the experimental twitch tension traces [30] (solid lines), and the predictions by MUSICO (dashed lines) and MP surrogate model (dotted lines) in presence of (red) and without Disopyramide (black). Figure is adopted from Prodanovic et al. [6].

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  Figure 5. Digoxin effects on human DCM trabeculae twitch contraction. (A) Calcium transient for DCM in presence of (pink) and without Digoxin (purple). Inset in (A) peak tension dependence on peak calcium concentration during twitch contractions in presence of increased doses of Digoxin. (B) MUSICO (dashed lines) and MP surrogate model predictions (dotted lines) in presence of (red) and without Digoxin (black).

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  Figure 6. Scenario 2: Changes in kinetic of contractile proteins for drug action. Adopted from ref. [16].

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  Figure 7. Risk prediction report from the Risk Stratification Tool for the selected five patients.

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  Figure 8. Left ventricle geometries for patient 3 and patient 5.

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  Figure 9. Prescribed inlet and outlet velocities for aortic output and mitral input.

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  Figure 10. Displacement, pressures, and velocity fields for patient 3.

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  Figure 11. Displacement, pressures, and velocity fields for patient 5.

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  Figure 12. P-V diagram for patient 3.