Dissecting contributions of pulmonary arterial remodeling to right ventricular afterload in pulmonary hypertension

Figures

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  FIGURE 1. Combined in‐vivo, ex‐vivo, and in‐silico approaches were used to separate the contribution of individual remodeling events toward increased MPA pressure. Data from in‐vivo and ex‐vivo measurements were combined to create an in‐silico model of the pulmonary vasculature. Circ, circumferential; CTL, control; FSI, fluid structure interaction; Long, longitudinal; MPA, main pulmonary artery; PA, pulmonary artery; PH, pulmonary hypertension; μCT, x‐ray microtomography.

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  FIGURE 2. Resin‐filled lungs from (a) control (CTL) rat and (d) pulmonary hypertension (PH) rat; scale bar: 1 cm. Representative x‐ray microtomography image slices of fixed lungs, with polymer resin infused pulmonary vasculature of (b) CTL and (e) PH rat; scale bar: 5 mm. Reconstructed pulmonary vasculature of (c) CTL and (f) PH rats; scale bar: 5 mm.

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  FIGURE 3. (a) Pressure in the main pulmonary artery (MPA) at diastole (PADP). (b) Difference in MPA pressure between systole and diastole (∆MPA pressure). (c) Pulmonary vascular resistance (PVR). (d) Stroke volume. (e) MPA thickness. Statistics were performed using student t‐tests. Male and female animals are denoted by filled and hollow markers, respectively. CTL: n = 8, PH: n = 8.

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  FIGURE 4. (a) Stress in the main pulmonary artery (MPA) during mechanical testing at 50% strain and (b) stiffness of the MPA at 60% strain. Fit of the non‐linear constitutive model to the PA mechanical behavior in the (c) circumferential and (d) longitudinal (axial) directions. Stress and strain denote the 2nd‐PK stress Green‐Lagrange strain, respectively. The constitutive model was fit to the mean stress–strain curve measured through uniaxial testing of PA specimens. Mean curves with error bars are presented in the Supplementary Materials. Statistics in (a), (b) were performed using two‐way ANOVA with Tukey's correction for multiple comparisons. Male and female animals are denoted by filled and hollow markers, respectively. CTL: n = 8, PH: n = 8. Circ, circumferential; Long, longitudinal.

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  FIGURE 5. (a) Measured main pulmonary artery (MPA) flow profile in the control (CTL) and pulmonary hypertension (PH) rats used in the in‐silico model. (b) The simulated pressure waveform obtained from the in‐silico model for the MPA after altering flow and remodeling parameters. (c) Simulated changes in ∆MPA pressure as a result of individual remodeling parameters. (d) The ∆MPA pressure obtained through in‐vivo measurements and in‐silico simulations. Male and female animals are denoted by filled and hollow markers, respectively. For in‐vivo measurements: CTL, n = 8; PH, n = 8. For in‐silico simulations, n = 3 control vascular geometries were used. ∆MPA Pressure is the difference in the MPA pressure between systole and diastole.

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  FIGURE 6. Variation of pressure in the pulmonary vasculature in (a) control (CTL) and (b) pulmonary hypertension (PH) rats with the corresponding time point marked on the pressure–time plot. Variation of flow rate in the pulmonary vasculature in (c) CTL and (d) PH rats. Results from the 1D FSI simulation were mapped onto the 3D geometry obtained from segmentation with the corresponding time point marked on the flow–time plot. Representative branching generations of the vessel have been labeled in (a) and (b). ∆MPA Pressure: difference in the MPA pressure between systole and diastole. Both scale bars represent 5 mm.

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  FIGURE 7. (a) Variation of 0 Hz PA impedance (Z 0) due to PA remodeling events. (b)Variation of characteristic PA impedance (Z c) due to PA remodeling events. Male and female animals are denoted by filled and hollow markers, respectively. CTL, n = 8; PH, n = 8. For in‐silico simulations, n = 3 control vascular geometries were used. Statistical significance was estimated through Student's t‐test to compare the in‐vivo impedance values.