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AACE-CED-113:Fluid-structure interaction assessment of patient-specific transcatheter aortic valve implantation


Project Description

This project provides an exciting opportunity to join the long term inter-disciplinary collaboration between Profs Bressloff and Curzen, seeking to develop computational engineering methods that inform and improve the devices and practices used in state of the art interventional cardiology. The focus of this project is on prosthetic aortic heart valves and the interaction between deployed devices, pulsatile blood flow and valve leaflets that open and close with every heartbeat.

As life expectancy increases, the prevalence of valvular heart disease represents a serious and growing public health problem. For people over the age of 75, approximately one in eight have some form of valvular disease including aortic stenosis (AS). The associated build-up of calcified deposits prevents the leaflets from fully opening. Once AS is severe enough to produce symptoms, short-term mortality rates are very high. Treatment for AS was revolutionised in 2002 with the first transcatheter aortic valve implantation (TAVI). Relative to open heart surgical valve replacement, TAVI is far less traumatic for the patient involving shorter hospital stays and greater cost-effectiveness. With projected double digit growth in the TAVI market over the next five to ten years, there will be a heightened need for increased device reliability and durability. However, these requirements are compromised by patient variability in valve anatomy and disease: native aortic roots vary in shape and size and are often non-circular; and AS varies extensively both within and between patients and can comprise heavily calcified resistive plaques of different sizes and distributions. Consequently, a deployed TAVI device is likely to be distorted from its intended shape leading to unknown performance of the prosthetic leaflets in vivo.

Against this background, the main aims of this project are to (i) assess the behaviour of prosthetic leaflets and the associated haemodynamics in one or more TAVI devices following sub-optimal device deployment in patient-specific aortic roots and (ii) propose alternative designs that have the potential to improve device durability. Advanced computational methods will be used including geometry construction, fluid-structure interaction and design optimisation. Using cases from the TAVI centre in the University Hospital Southampton Trust, the main objectives are (i) to setup and perform FSI simulations at various orientations in different patient-specific aortic roots; (ii) define and extract appropriate leaflet performance metrics; (iii) investigate the effects of alternative leaflet shapes and material property models and (iv) setup and conduct design studies to search for optimal device designs.

Having been the first group to report the successful simulation of the deployment of a complete balloon expandable TAVI device in a patient-specific aortic root (including both native and prosthetic leaflets) [1], the current proposal seeks to extend this research to assess and enhance prosthetic valve durability in realistic patient-specific scenarios.

The successful candidate is likely to have computational engineering experience in one or more of the following: finite element analysis, computational fluid dynamics, fluid-structure interaction, biomedical device design and/or design optimization.
1. Bailey, J., Curzen, N. and Bressloff, N. W., 2015, Assessing the impact of including leaflets in the simulation of TAVI deployment in to a patient specific aortic root. Comp. Meth. Biomech. Biomed. Eng. Article at Taylor & Francis via http://www.tandfonline.com/doi/pdf/10.1080/10255842.2015.1058928

If you wish to discuss any details of the project informally, please contact Prof Neil W. Bressloff, Computational Engineering and Design research group, Email: , Tel: +44 (0) 2380 59 5473.

How good is research at University of Southampton in General Engineering?

FTE Category A staff submitted: 192.23

Research output data provided by the Research Excellence Framework (REF)

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