Towards a non-invasive computational diagnostic framework for personalized cardiology of transcatheter aortic valve replacement in interactions with complex valvular, ventricular and vascular disease

Abstract

Aortic stenosis is an acute and chronic cardiovascular disease that often coexists with other complex valvular, ventricular and vascular diseases (C3VD). Transcatheter aortic valve replacement is an emerging less invasive intervention for patients with aortic stenosis. Although hemodynamics quantification is critical for accurate and early diagnosis of aortic stenosis and C3VD, proper diagnostic methods for these diseases are still lacking because fluid-dynamics methods, that can be used as engines of new diagnostic tools, are not well developed yet. As the heart resides in a sophisticated vascular network which imposes a load on the heart, effective diagnosis requires quantifications of the global hemodynamics (metrics of circulatory function and metrics of cardiac function), and of the local hemodynamics (cardiac fluid dynamics). To enable the development of new non-invasive diagnostic methods that can quantify local and global hemodynamics, we developed an innovative computational-mechanics and imaging-based framework that only needs patient data routinely and non-invasively measured in clinics. We not only validated the framework against clinical cardiac catheterization and Doppler echocardiographic measurements but also, we demonstrated its diagnostic utility in providing novel analyses and interpretations of clinical data.