Bicuspid aortic valve (BAV) is the most common congenital heart disease. Calcific aortic valve disease (CAVD) accounts for the majority of aortic stenosis (AS) cases. Half of the patients diagnosed with AS have a BAV, which has an accelerated progression rate. This study aims to develop a computational modeling approach of both the calcification progression in BAV, and its biomechanical response incorporating fluid-structure interaction (FSI) simulations during the disease progression. The calcification is patient-specifically reconstructed from Micro-CT images of excised calcified BAV leaflets, and processed with a novel reverse calcification technique that predicts prior states of CAVD using a density-based criterion, resulting in a multilayered calcified structure. Four progressive multilayered calcified BAV models were generated: healthy, mild, moderate, and severe, and were modeled by FSI simulations during the full cardiac cycle. A valve apparatus model, composed of the excised calcified BAV leaflets, was tested in an in-vitro pulse duplicator, to validate the severe model. The healthy model was validated against echocardiography scans. Progressive AS was characterized by higher systolic jet flow velocities (2.08, 2.3, 3.37, and 3.85 m s), which induced intense vortices surrounding the jet, coupled with irregular recirculation backflow patterns that elevated viscous shear stresses on the leaflets. This study shed light on the fluid-structure mechanism that drives CAVD progression in BAV patients.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8862115PMC
http://dx.doi.org/10.1007/s10439-021-02877-xDOI Listing

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