We are looking for a bright, enthusiastic and self-motivated PhD student to join our research group in the Department of Mechanical Engineering at the University of Sheffield.
Arteriovenous malformations (AVMs) of the brain are abnormal, intricate connections of vessels thrusting blood from the arterial to the venous system (no capillary network). AVMs carry an inherent risk of bleeding, and are often treated by injecting a high-viscosity material (embolic liquid) to block blood flow through the malformation. Risks associated to treatment are influenced significantly by patient-specific anatomy. Due to their anatomical complexity and small vessel sizes, current imaging technologies do not allow an accurate visual representation of AVMs, adversely affecting treatment and introducing risks.
The project will attempt to objectively characterise AVM anatomy by analysing the pulse waves reflected by the malformation in its upstream vessels, and map this to treatment outcome. The research hypothesis is that different AVM anatomies, i.e. different distribution of large vessels and small vessels in the AVM nidus, will reflect pulse waves in different ways and leave a ‘signature’ on the waveform that can be uniquely associated to the specific anatomy. The interpretation of the reflected wave will require the use of a 1D numerical model. Similar techniques have already been used successfully to characterise the anatomy of pulmonary vascular malformations. The project will develop a disease-specific model for AVMs, and use in vitro experimental analysis of pulse waves through idealised geometries of AVMS for validation. The experimental platform will also serve as a model to study the influence of geometry and fluid flow on the behaviour of the embolic liquid.
Previous knowledge of the clinical subject area is not required, although the candidate should demonstrate an interest to learn those clinical aspects that are relevant to the development of the models.
The ideal candidate will have a 1st class or a good 2.1 degree in mechanical engineering, bioengineering, physics, applied mathematics or a related discipline. Previous knowledge of fluid mechanics, numerical modelling and good programming skills are essential.
This project will use the methodologies and tools developed within the Virtual Physiological Human initiative, and will be supported by the expertise available within the INSIGNEO Institute.
Clinical Supervisor: Dr Ana Paula Narata (Neuroradiologist at University of Tours, France)
For further information or clarifications about this project please contact Dr Alberto Marzo ([email protected]
The start date will be October 2016.