Medical Imaging

EPSRC Centre for Doctoral Training

Research

Projects

  • 309: Advanced image-based computational modelling for patient-specific optimisation of anti-arrhythmia electrotherapy

    Application of strong electrical shocks to the heart is the only currently reliable means of terminating otherwise lethal cardiac arrhythmias (defibrillation). However, the use of such high shock energies is highly detrimental to the patient’s long-term health and psychological well-being. Currently, there is therefore a strong urge to develop novel, lower energy defibrillation devices and shock protocols. This project aims to develop a detailed biophysical understanding of the interaction of electric fields with diseased hearts in order to optimise anti-arrhythmia shock therapy in a personalised manner, reducing required shock strengths. To do this, we will develop a novel computational modelling pipeline to generate high-resolution image-based models of patients with ischemic heart disease (scar). Simulations will be conducted to better predict which individuals may benefit from electrotherapy and optimise the configurations of the electrotherapy devices, depending on the specific nature of their scar in a personalized manner. More...

  • 315: Computational Modelling Cellular Variability

    Robust cardiac function depends on the billions of individual cells that make up the heart working together to contract synchronously and pump blood. While all cardiac cells are similar, experimental measurements show that each cell is also distinct. Conventionally experimental and clinical recordings are averaged to remove variability from measurements, however, this approach removes the measurement of potentially important physiological or pathological co-variation and variation. Combining advanced multi-scale biophysical computer simulations of cardiac function (Figure 1) with Bayesian statistical approaches, this PhD will develop a statistical-systems approach to quantify the degree and impact of variability and covariance in clinical and experimental measurements. More...