PMC7219000_01
Aorta CT scan image from (a) sagittal (b) coronal (c) and axial planes. (d) 3D aorta model.
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A 3D aorta model is developed based on pre-CT scan image data of the patient as shown in Figures 1(a)-1(d). The complete 3D model of the aorta that consists of the ascending aorta, aortic arch, brachiocephalic artery, common carotid artery, left subclavian artery, and descending aorta is developed as shown in Figure 1(d).
Process in developing the(a) 3D aorta model using CATIA and (b) 3D aorta model with valve location.
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Then, the final 3D model of aorta geometry is converted into Stereo-Lithography format (*.stl) before being exported to CATIA V5 software for the generation of a solid model (Figure 2(a)). Meanwhile, Figure 2(b) shows the 3D aorta model with valve location at the ascending aorta region.
26 mm diameter of Sapien XT (Edward SAPIEN Aortic Valve; Edwards Lifesciences, Irvine, California).
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Irvine, California), as depicted in Figure 3. The undersized of 26 mm TAVI valve is selected for this study which represent the presence of PVL occured at the aortic annulus. In this study, the TAVI leaflet is drawn in four different valve openings representing the GOA in terms of percentage, which are 100%, 80%, 60%, and 40% as in Figure 3.
3D geometrical drawing of TAVI 26 Sapien XT with different GOA openings: (a) 100% GOA, (b) 80% GOA, (c) 60% GOA, and (d) 40% GOA.
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From Figure 4, it is observed that the lowest GOA percentage (40%) showed the mild valve stenosis, where higher net blood pressure loss through the valve occurs under this condition.
Relationship between GOA and EOA.
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AVA is estimated based on the valve inflow shape and cross-sectional area of the ascending aorta, which is represented as effective orifice area (EOA), as shown in Figure 5. According to Garcia et al., the American College of Cardiology/American Heart Association (ACC/AHA) recommended the EOA/AVA value based on the classification of severity as follows: mild (>1.5 cm2); moderate (1.0 cm2-1.5 cm2); and severe (<1.0 cm2).
Result of meshes: (a) fluid domains and (b) solid domains. (c) Maximum velocity for fluid mesh dependence; (d) maximum total deformation for solid mesh dependence.
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The best selection of mesh for the fluid domain can be concluded to be approximately 2 million tetrahedral elements after being tested from 500,000 to 2.5 million number of mesh elements (Figures 6(a) and 6(c)). However, a mesh of approximately 75,000 quadrilateral elements is considered sufficient for the case of solid domain (Figures 6(b) and 6(d)). The dependency graph and mesh images are depicted in Figure 6.
Boundary condition of fluid and solid domains.
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In this simulation, the mass flow rate and pressure are indicated as the respective inlet and outlet with the condition of pulsatile blood flow, according to Basri et al. and Lantz et al. (as in Figures 7-9). The geometry is constrained in an axial direction at the inlet, branch outlet, and main outlet, as shown in Figure 7.
Mass flow rate inlet consists of early systole (ES), peak systole (PS), early diastole (ED), and late diastole (LD).
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In this simulation, the mass flow rate and pressure are indicated as the respective inlet and outlet with the condition of pulsatile blood flow, according to Basri et al. and Lantz et al. (as in Figures 7-9). Those points are early systole (ES), peak systole (PS), early diastole (ED), and late diastole (LD), as depicted in Figure 8.
Blood pressure pulse that is used as output condition.
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In this simulation, the mass flow rate and pressure are indicated as the respective inlet and outlet with the condition of pulsatile blood flow, according to Basri et al. and Lantz et al. (as in Figures 7-9).