The human cardiovascular system consists of two large arteries: the aorta (AO), which supplies oxygenated blood to the body, and the pulmonary artery (PA), which supplies deoxygenated blood to the lungs for oxygenation. In healthy individuals, the pressure in the AO is significantly higher than the pressure in the PA. Pulmonary artery hypertension (PAH) is a disease in which the PA pressure is abnormally elevated and is classified as one of the most devastating disorders by the pulmonary artery association UK. This is evidenced by a mean survival time after diagnosis of less than 30 months in adults and less than 12 months in children. A recently proposed treatment for severe PAH, i.e. the case when PA pressure is higher than the pressure in AO, is to create a connection, known as the Potts shunt, between the PA and the AO. Just as a connection between two pipes carrying fluids with high and low pressures will lead to a reduction of pressure in the high-pressure pipe and an increase of pressure in the low-pressure pipe, the idea is that a Potts shunt can lead to a reduction of PA pressure in severe PAH patients. This reduction in PA pressure is desirable but will also result in mixing of oxygenated and deoxygenated blood, an undesirable effect. Clinical experience has shown favourable results of this treatment in some patients and unfavourable in others, which is attributed largely to a reduction in cardiac output, the total volume of blood ejected by the heart in one cardiac cycle. This project aims to develop computational models to assess three measures of Potts shunt treatment: 1) reduction of pulmonary artery pressure, 2) mixing of oxygenated and deoxygenated blood, and 3) reduction in cardiac output. Through the computational models, this project will assess the mechanisms behind the success/failure of Potts shunt in relation to the above measures. The end-product will be a computer model which, given a new patient, can determine if a Potts shunt is likely to succeed in the patient. Furthermore, technology to optimise the design of Potts shunt for each patient individually, such that maximal clinical benefit is achieved, will be developed.

Our skulls consist of several bones that are joined together along their edges by soft tissues called cranial joints or sutures. During infancy, our skulls grow rapidly in size and shape to accommodate our brain growth. Once the brain has reached its maximum size, soft tissues at the sutures turn into bone to protect our brain and enable us to bite harder. Our fundamental understanding of the level of forces that our skulls and its cranial joints experience during the growth is extremely limited. This lack of knowledge has limited our ability to advance treatment of a wide range of craniofacial conditions affecting: children e.g. craniosynostosis is a medical condition caused by early fusion of cranial joints that has very nearly doubled in incidence across Europe in the last 30 years for unknown reasons adults e.g. large calvarial defects increasingly being used for the management of ischaemic stroke and traumatic brain injury Thus, this is a huge engineering challenge that requires in-depth investigations using a range of advanced techniques. CranioMech aims to address these engineering challenges and critical gaps in our knowledge while focusing on developing a revolutionary therapy for craniosynostosis (CS). CranioMech builds on my network of collaborators and strong track record in this field, significant institutional support (ca. £690k), as well as my recent work (in vivo mouse testing) that demonstrates the feasibility of a therapy that could become a reality for children of the 21st century. CranioMech aims to: (1) further expand on my therapy in mouse and unravel the fundamental underlying mechanism by which it works; (2) test its scalability in larger animal models; and (3) carry out a series of proof of concept studies in preparation for the first human trials, while unravelling the biomechanics of current treatments of CS. This is a truly high risk, high gain multidisciplinary, multi-scale project, combining fundamental principles with significant translational potential. It will use a combination of advanced approaches e.g. computer simulation, manufacturing, imaging, sensing and in vivo experiments to transform the treatment of CS by resolving its unknown mechanics. This is a neglected area, well in line with EPSRC Healthcare Technologies themes and the UK strategy for rare diseases that can offer a beacon of equality, diversity, inclusion (EDI) & responsible research and innovation (RRI).