Recent advancements in understanding valve diseases have led to more effective techniques for aortic valve repair, notably the annuloplasty procedure. Annuloplasty aims to address aortic valve conditions like regurgitation by minimizing the need for complex interventions, reducing associated risks and patient management challenges.The aim is to provide surgeons with insights into optimal annuloplasty techniques, enhancing patient outcomes by determining appropriate device placement and mechanical specifications.
This project focuses on validating an aortic annuloplasty test-bench flow-loop through computational fluid-structure interaction (FSI) analysis, combining experimental work at CAVE Lab and validation with 4D flow magnetic resonance clinical measurements at the Department of Cardiological Medicine (Aarhus University). An active exchange and collaboration with Politecnico di Milano leverage the computational effort.
Calcific aortic valve disease often necessitates percutaneous heart valve replacement, particularly for high-risk patients. To prevent complications like leaflet thrombosis post-implantation, understanding flow disturbances in aortic root is vital.
This project focuses on creating and validating a reliable computational fluid dynamics (CFD) model of transcatheter aortic valve implantation (TAVI), expanding 2D models to fluid-structure interaction (FSI) models validated with in-vitro data acquired at CAVE Lab. Parametric modeling and magnetic resonance scans (acquired at the Department of Cardiological Medicine of Aarhus University) capture leaflet changes during the cardiac cycle. The subsequent 2D FSI model enables fully transient computational analysis, assessing effects like leaflet calcification and stent presence, enhancing insights into valve dynamics and optimizing percutaneous valve replacement procedures.
Blood microvasculature represents the smallest yet the most extensive portion of our circulatory systems. When compromised due to inflammatory or hypoxic conditions, huge sections of the major organs are highly affected and leading to deadly consequences. In the very last decades, hydrogels have emerged as ultimate resources for the treatment of local injuries given their high biocompatibility, biodegradability, and application flexibility.
This wide project includes creating an integrative platform to engineer the hydrogel-blood cell interaction by coupling biomolecular mechanics and computational fluid dynamics (CFD). By conjugating these two computational and dimensional levels, we aim at defining the most important parameters to describe the hydrogel-based process. The key coefficients of the multiscale model are estimated by performing preliminary experiments with controlled 3D-printed vasculature structures where known commercial hydrogels are introduced and perfused.
