Cardiac remodeling in aortic and mitral valve disease: a simulation study with clinical validation.

Remodeling is an important long-term determinant of cardiac function throughout the progression of heart disease. Numerous biomolecular pathways for mechanosensing and transduction are involved. However, we hypothesize that biomechanical factors alone can explain changes in myocardial volume and chamber size in valve disease. A validated model of the human vasculature and the four cardiac chambers was used to simulate aortic stenosis, mitral regurgitation, and aortic regurgitation. Remodeling was simulated with adaptive feedback preserving myocardial fiber stress and wall shear stress in all four cardiac chambers. Briefly, the model used myocardial fiber stress to determine wall thickness and cardiac chamber wall shear stress to determine chamber volume. Aortic stenosis resulted in the development of concentric left ventricular hypertrophy. Aortic and mitral regurgitation resulted in eccentric remodeling and eccentric hypertrophy, with more pronounced hypertrophy for aortic regurgitation. Comparisons with published clinical data showed the same direction and similar magnitudes of changes in end-diastolic volume index and left ventricular diameters. Changes in myocardial wall volume and wall thickness were within a realistic range in both stenotic and regurgitant valvular disease. Simulations of remodeling in left-sided valvular disease support, in both a qualitative and quantitative manner, that left ventricular chamber size and hypertrophy are primarily determined by preservation of wall shear stress and myocardial fiber stress. NEW & NOTEWORTHY Cardiovascular simulations with adaptive feedback that normalizes wall shear stress and fiber stress in the cardiac chambers could predict, in a quantitative and qualitative manner, remodeling patterns seen in patients with left-sided valvular disease. This highlights how mechanical stress remains a fundamental aspect of cardiac remodeling. This in silico study validated with clinical data paves the way for future patient-specific predictions of remodeling in valvular disease.