Doppler-Exclusive Non-Invasive Computational Diagnostic Frameworks for Personalized Cardiology of Left-Side Heart Valves

Abstract

Aortic and mitral valve diseases are among the leading causes of mortality, particularly in the elderly population. These cardiac diseases often progress asymptomatically over an extended period, and timely and detailed diagnoses are crucial for optimizing treatment plans for heart valve diseases. Effective diagnosis and treatment planning for both aortic and mitral diseases depend on accurately estimating the dynamic behavior. In this study, we developed two computational frameworks that can quantify both the left heart’s valve dynamics and global hemodynamic metrics by solely relying on Doppler echocardiography (DE). These frameworks complement existing imaging techniques by supplying detailed patient-specific functional parameters and a comprehensive understanding of three-dimensional stress and strain distributions within the valve tissues influenced by blood pressure. Each framework has three similar key modules: a DE-based 3-D geometry reconstruction module, a rigorously validated DE-based lumped parameter algorithm, and a DE-based finite element solver. Both frameworks offer insights into the biomechanical behavior of left heart valve tissues throughout the cardiac cycle, which is not directly accessible using in vivo imaging. According to the results, patient-specific pressure loads play a primary role in dynamic behavior of leaflets of aortic leaflets. Further comparisons between pre- and post-transcatheter aortic valve replacement (TAVR) simulations showed that the dynamic behavior of the leaflets might not necessarily improve. Additionally, it is possible to provide a leaflet-specific metric to quantify the asymmetry of valve dynamics, a valuable metric for treatment planning. Regarding the dynamic behavior of mitral leaflets, we showed the 3-D transient deformation of mitral leaflets could provide a more detailed set of functional metrics, rather than relying solely on in vivo imaging’s. Furthermore, we quantified the complex interaction between the mitral leaflets and left ventricle geometry and pressure for each individual patient. The two proposed frameworks could serve as patient-specific digital twins of the left heart valves for testing different clinical scenarios.