Rina Ariga

I use computational approaches to ECG and cardiac imaging data to improve mechanistic understanding of cardiovascular disease and to help find new treatment targets.

I currently work on Hypertrophic Cardiomyopathy (HCM), a common inherited heart muscle disease which can cause sudden cardiac death and heart failure. The disease is highly heterogeneous and the gene-negative majority have dissimilar features to gene-positive patients. Yet clinical management strategies are equivalent. My work aims to individualise patient care by using pathophysiological insights gained from deep learning of ECG and Cardiac Magnetic Resonance (CMR) data from UK Biobank and the international HCMRegistry study.

My doctoral research pioneered Diffusion Tensor CMR in HCM. This novel imaging method measures heart muscle disarray, which underlies sudden cardiac death – previously only possible to see at post-mortem. In collaboration with colleagues from Computer Science, we applied machine learning and computational simulation to integrate ECG and imaging to detect subtle electrical changes indicative of such underlying defects. I have received several prizes and awards for my DPhil work, and my publication findings were reported in the media. 

I am training in clinical trials through an MSc at Nuffield Department of Population Health. I hope this grounding in the design and delivery of randomised trials will help me translate key research innovations into evidence-based treatments.