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Simvascular

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SimVascular is a computational fluid dynamics software package designed for the simulation of blood flow in the cardiovascular system. It provides tools for medical image segmentation, solid modeling, mesh generation, and flow simulation. SimVascular is primarily used for research and educational purposes in the field of biomedical engineering.

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Lab products found in correlation

Meshmixer, by Autodesk (3 mentions)

3 protocols using simvascular

1

Aortic Wall 3D Modeling from MRI

Cited 1 time
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FSI models were constructed for each mouse using two- and six-month MRI scans. Two domains are required for the FSI simulations: the fluid domain, given by the vessel lumen, and the solid domain, representing the aortic wall. A 3D model of the fluid domain was generated from MRI scans. Scans were segmented using image segmentation and model generation in SimVascular[26 (link)], with supplemental editing in Meshmixer (Autodesk, Inc.). The 3D model included the brachiocephalic trunk, the left common carotid, and the left subclavian artery.
Because the aortic wall is too thin to measure directly from the MR images, the aortic wall was generated by extruding the lumen wall outward. The mouse-specific unloaded wall thickness was based on experimental measurement for the ascending aortic region shown in Table 1 and was treated as constant over the length of the aorta.
A tetrahedral mesh was created using the TetGen mesh generator that is embedded in SimVascular [27 ]. The mesh included both the solid and the fluid domains, with matching nodes at the interface between the domains to satisfy the kinematic and dynamic boundary conditions at the interfaces.
Bazzi M.S., Balouchzadeh R., Pavey S.N., Quirk J.D., Yanagisawa H., Vedula V., Wagenseil J.E, & Barocas V.H. (2022). Experimental and mouse-specific computational models of the Fbln4SMKO mouse to identify potential biomarkers for ascending thoracic aortic aneurysm. Cardiovascular engineering and technology, 13(4), 558-572.
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2

Aortic Wall 3D Modeling from MRI

Cited 1 time
Check if the same lab product or an alternative is used in the 5 most similar protocols
FSI models were constructed for each mouse using two- and six-month MRI scans. Two domains are required for the FSI simulations: the fluid domain, given by the vessel lumen, and the solid domain, representing the aortic wall. A 3D model of the fluid domain was generated from MRI scans. Scans were segmented using image segmentation and model generation in SimVascular[26 (link)], with supplemental editing in Meshmixer (Autodesk, Inc.). The 3D model included the brachiocephalic trunk, the left common carotid, and the left subclavian artery.
Because the aortic wall is too thin to measure directly from the MR images, the aortic wall was generated by extruding the lumen wall outward. The mouse-specific unloaded wall thickness was based on experimental measurement for the ascending aortic region shown in Table 1 and was treated as constant over the length of the aorta.
A tetrahedral mesh was created using the TetGen mesh generator that is embedded in SimVascular [27 ]. The mesh included both the solid and the fluid domains, with matching nodes at the interface between the domains to satisfy the kinematic and dynamic boundary conditions at the interfaces.
Bazzi M.S., Balouchzadeh R., Pavey S.N., Quirk J.D., Yanagisawa H., Vedula V., Wagenseil J.E, & Barocas V.H. (2022). Experimental and mouse-specific computational models of the Fbln4SMKO mouse to identify potential biomarkers for ascending thoracic aortic aneurysm. Cardiovascular engineering and technology, 13(4), 558-572.
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3

Computational Analysis of Aortic Valve Dynamics

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Computer simulations were performed to examine the effects of individual leaflet excursions on AVA using a customized workflow (Figure 1, blue path). A more detailed description of the simulation method can be found in Supplemental Methods. Briefly, for each control patient, we used the SimVascular10 (link) and MeshMixer (Autodesk, San Rafael, CA) software to create a three-dimensional valve model in two cardiac phases from the mid-systolic and diastolic CTA images. We used Coherent Point Drift (CPD) algorithm11 (link) to map the corresponding valve surfaces in the two phases to obtain a displacement field, from which the maximal systolic displacement within each leaflet was derived. We then assessed the contribution of each leaflet to AVA by initializing the valve model in mid-systole and computing the AVA as we incrementally closed one leaflet at a time.
Chen I.Y., Vedula V., Malik S.B., Liang T., Chang A.Y., Chung K.S., Sayed N., Tsao P.S., Giacomini J.C., Marsden A.L, & Wu J.C. (2021). Preoperative Computed Tomography Angiography Reveals Leaflet-Specific Calcification and Excursion Patterns in Aortic Stenosis. Circulation. Cardiovascular imaging, 14(12), 1122-1132.
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