During pregnancy, the developing baby receives nutrients from mother via the placenta. However, in the common pregnancy complication, intrauterine growth restriction (IUGR), blood flow to the placenta and nutrient transfer are dramatically reduced. Affected babies are also at increased short term risks during labour and are at increased risk of heart disease, diabetes and raised blood pressure in adult life. Cortisol is a steroid hormone whose levels are increased by stress. Recent research has shown that high cortisol levels can alter baby‘s growth and development. If the mother is stressed during pregnancy, for example following a bereavement, her blood cortisol levels rise. Preterm labour treatments also increase cortisol in Mum‘s blood. The placenta has an inactivating enzyme to protect the baby from increased cortisol levels in Mother‘s blood. In IUGR, however, levels of this enzyme are thought to be reduced. It is not known how cortisol alters the way the placenta works. My study will investigate if cortisol alters blood flow by assessing blood vessel behaviour directly. I will also look at how cortisol alters the proteins in the placenta that move nutrients to the baby during pregnancy. Understanding how cortisol alters the function of the placenta will assist design of future treatment strategies for IUGR and ensure the safe use of steroid hormones in preterm labour.

In the past decade, the face of cardiac surgery has been changed by a number of technologic advances. One such advance is the development of minimally invasive cardiac surgery where the surgical intervention is done through small incisions ( key hole surgery ) rather than through conventional open chest surgery. With this technique, small endoscopic cameras and specialized instruments are inserted through small artificial incisions. For the patient this reduces morbidity and leads to faster, less painful recovery from surgery. However, for the surgeon this poses a number of problems such as the limited tactile feedback and restricted visual feedback.The purpose of this project is to develop a image-guided minimally invasive cardiac surgery system using a surgical robot. The key research issue which we will pursue in this project is the development of novel model-based 2D-3D registration techniques for matching 3D deformable objects such as the heart as well as vessels to 2D endoscopic video images. This registration will enable us to establish the relationship between the 2D endoscopic video images seen by the surgeon and the patient's anatomy. We propose to superimpose models derived from preoperative image data onto the live 2D endoscopic video images. This will allow the surgeon to utilise preoperative tomographic data to accurate localise and track targets during the operation.

In the past decade, the face of cardiac surgery has been changed by a number of technologic advances. One such advance is the development of minimally invasive cardiac surgery where the surgical intervention is done through small incisions ( key hole surgery ) rather than through conventional open chest surgery. With this technique, small endoscopic cameras and specialized instruments are inserted through small artificial incisions. For the patient this reduces morbidity and leads to faster, less painful recovery from surgery. However, for the surgeon this poses a number of problems such as the limited tactile feedback and restricted visual feedback.The purpose of this project is to develop a image-guided minimally invasive cardiac surgery system using a surgical robot. The key research issue which we will pursue in this project is the development of novel model-based 2D-3D registration techniques for matching 3D deformable objects such as the heart as well as vessels to 2D endoscopic video images. This registration will enable us to establish the relationship between the 2D endoscopic video images seen by the surgeon and the patient's anatomy. We propose to superimpose models derived from preoperative image data onto the live 2D endoscopic video images. This will allow the surgeon to utilise preoperative tomographic data to accurate localise and track targets during the operation.

Pre-term and stillbirths affect up to 10% of all deliveries, including in developed countries, such as the UK. Among these complications, pre-eclampsia, or the compromised supply of blood between mother and fetus via the placenta, costs over £1.2 billion each year in neonatal and infant care to the NHS and public sector services in the UK alone. The human placenta is a vital life-support system for the developing fetus. The supply of oxygen and nutrients by the mother's blood has to be well orchestrated within a complex fetal blood vessel network. There are two reasons for our limited progress in the understanding of the interaction of the structure and the function of the placenta: on the one hand, the human placenta has an extraordinarily complex structure; on the other hand, the structure and physiology of the human placenta are unique and therefore animal studies are of limited use. A direct consequence of the lack of understanding are very limited options for clinical management of pregnancy diseases such as pre-eclampsia and fetal growth restriction. Furthermore, placental insufficiency does not only result in stillbirth or premature delivery, but it has also been associated with a higher risk of heart attack, stroke, diabetes or neurological disorders later in adult life. Recognition of these challenges has resulted in a recent surge of research interest world-wide and in establishing the $41M US Human Placenta Project and the EU Placentology Network for experimental and theoretical testing of chemicals' safety in pregnancy. Moreover, a recent breakthrough in 'artificial placenta' design for life-support of extremely premature infants offers new opportunities for design optimisation by systematic 'reverse engineering' of the normal human placenta. Thus, the UK needs a critical mass of expertise in placental technologies to match the US and EU capacities and to remain an active player in international collaborations in this important area. Based on our research to date, we hypothesise that blood flow and nutrient transport in the placenta are altered in pre-eclampsia and fetal growth restriction. In this project, we propose an interdisciplinary and innovative approach harnessing our theoretical and experimental expertise to deliver precision medicine for obstetrics and neonatal critical care. We will develop and validate a framework for image-based modelling and simulation of blood flow and nutrient transport in patient-specific placentas. Thanks to existing datasets describing the structure of both healthy and diseased placentas, we will be able to explore which anatomical changes in the placenta are associated with compromised nutrient transport. This will establish a sound theoretical basis for the development of interventions and artificial solutions for the treatment of pre-eclampsia and fetal growth restriction. The long-term translational impacts include (i) model-based patient-specific treatment with drugs avoiding placental dysfunction in high-risk pregnancies and (ii) design optimisation of an 'artificial placenta' for the support of extremely premature babies.

The care of critically ill patients requiring mechanical ventilation remains beset by the combined effects of critical illness and of the mechanical ventilation of the lung. Such effects are compounded by the lack of knowledge of the rate and time at which 'weaning' from the machine should occur. This project aims at developing an adaptive decision support system to assist ICU staff in the optimisation of ventilation and weaning processes. To help achieve this, an adaptive hybrid model which describes the patient-ventilator interaction during ventilation as well as weaning phases will be elicited. In addition to knowledge gathered through data relating to blood gases and lung expansions, the project aims at exploiting a revolutionary technique developed at sheffield, called Electrical Impedance Tomography (EIT) which consists of measuring, in a non-invasive fashion, the degree of expansion or collapse of the lungs and the effect of the ventilation strategy upon these. Two important aspects of this project relate to the inclusion of the EIT measurement technique to improve the monitoring of the patient's respiratory demands and to the use of granular computing for the hybrid model represented by the neural-fuzzy layer. The elicitation of such a model will form the basis for the design and development of an adaptive decision support system for optimal therapeutic advice on ventilator settings and weaning operation. On-line and off-line validation of the system in a series of ICU trials are envisaged.