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Research
Insights into the pathophysiology and risk of clinical events in vascular disease using imaging, AI, mathematics and engineering.
In atherosclerosis, inflammation, neovascularisation, hypoxia and calcification are drivers of plaque destabilisation and clinical events such as myocardial infarction and stroke. Conventional x-ray angiography does not provide information about the extent of these processes in the arterial wall, and as a consequence is a poor predictor of future events.
The aim of our research is to use non-invasive imaging to answer five related questions:
First, can we quantify the pathology of interest in the artery wall?
Second, can we track the effects of therapy on this process?
Third, can we use imaging to inform us about the biology of arterial disease?
Fourth, can imaging improve our predictions about the risk of future clinical events?
Finally, can we apply techniques from mathematics, AI and engineering to improve our results?
Selected References
Le, E. P. V., Rundo, L., Tarkin, J. M., Evans, N. R., Chowdhury, M. M., Coughlin, P. A., . . . RUDD, J. H. F. (2021). Assessing robustness of carotid artery CT angiography radiomics in the identification of culprit lesions in cerebrovascular events. Nature Scientific Reports, 11(1), 3499. doi:10.1038/s41598-021-82760-w
Roberts, M., Driggs, D., Thorpe, M., Gilbey, J., Yeung, M., Ursprung, S., RUDD JHF, Sala, E, Schoenlieb, C. -B. (2021) Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans. Nature Machine Intelligence. (Joint Senior Author). doi:10.1038/s42256-021-00307-0
Alaa, A., Bolton, T., Di Angelantonio, E., RUDD, JHF., & van Der Schaar, M. (2019). Cardiovascular Disease Risk Prediction using Automated Machine Learning: A Prospective Study of 423,604 UK Biobank Participants. PLoS ONE - doi.10.1371/journal.pone.0213653
Tarkin, J. M., Joshi, F. R., Evans, N. R., Chowdhury, M. M., Figg, N. L., Shah, A. V., . . . Yu, E., RUDD, J. H. F. (2017). Detection of Atherosclerotic Inflammation by (68)Ga-DOTATATE PET Compared to [(18)F]FDG PET Imaging.. J Am Coll Cardiol, 69(14), 1774-1791. doi:10.1016/j.jacc.2017.01.060