LOCATION
John Radcliffe Hospital, Level 6, Headley Way, Headington, Oxford, OX3 9DU
Research groups
Colleges
Websites
Regent Lee
MBBS, MS(Vasc Surg), DPhil (Oxon), FRCS (Vasc Surg)
Associate Professor of Vascular Surgery
- UKRI Future Leaders Fellow
- Junior Research Fellow: St Catherine's College
- Chief Investigator: AICT Study
- Co-PI: OxAAA Study
- Managing Editor: Journal of the Nuffield Department of Surgical Sciences
Regent came to Oxford as an exchange surgical fellow in 2009, having completed a Master in Surgery (Vascular Surgery) at University of Sydney. He subsequently completed DPhil in Cardiovascular Medicine, under the supervision of Prof Keith Channon (RDM Cardiovascular Medicine) and Prof Benedikt Kessler (NDM, Target Discovery Institute).
Regent's research focuses on integrative assessments of biomarkers for the investigation of cardiovascular pathologies such as atherosclerosis or abdominal aortic aneurysms. He is developing new methods to characterise novel biological signals in blood tests and clinical scans (such as ultrasound scans and computerised tomography imaging).
Prior to his UKRI Future Leaders Fellowship, Regent had received research awards from the Royal Australasian College of Surgeons, including the Lumley Surgical Research Fellowship, Foundation of Surgery Research Scholarship, and the Surgeon Scientist Scholarship. His work is also supported by the Oxford University Medical Sciences Division, Oxford Biomedical Research Centre, British Heart Foundation Oxford Centre of Research Excellence, Academy of Medical Sciences, and Heart Research UK.
Regent has led several Patient and Public Involvement activities for the OxAAA study, including the OxAAA Aneurysm Awareness Day and the OxAAA International Survey. These work has been generously supported by the Oxford University Vice Chancellor's Public Engagement in Research Seed Award, and Patient Active in Research (PAIR) Thames Valley.
Regent is a clinically active academic surgeon and currently an Honorary consultant vascular surgeon at the Oxford University Hospitals NHS Foundation Trust.
Key publications
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A Deep Learning Pipeline to Automate High-Resolution Arterial Segmentation with or without Intravenous Contrast.
Journal article
Chandrashekar A. et al, (2020), Ann Surg
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Prediction of Abdominal Aortic Aneurysm Growth Using Geometric Assessment of Computerised Tomography Images Acquired During the Aneurysm Surveillance Period.
Journal article
Chandrashekar A. et al, (2020), Ann Surg
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A deep learning approach to generate contrast-enhanced computerised tomography angiograms without the use of intravenous contrast agents
Conference paper
Chandrashekar A. et al, (2020), EUROPEAN HEART JOURNAL, 41, 156 - 156
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Integrated Plasma and Tissue Proteomics Reveals Attractin Release by Intraluminal Thrombus of Abdominal Aortic Aneurysms and Improves Aneurysm Growth Prediction in Humans
Journal article
LEE R. et al, (2020), Annals of Surgery
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Integrated Physiological and Biochemical Assessments for the Prediction of Growth of Abdominal Aortic Aneurysms in Humans
Journal article
LEE R. et al, (2018), Annals of Surgery
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Applied Machine Learning for the Prediction of Growth of Abdominal Aortic Aneurysm in Humans
Journal article
Lee R. et al, (2018), European journal of vascular and Endovascular Surgery Short Reports
Recent publications
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Protective Role for Smooth Muscle Cell Hepcidin in Abdominal Aortic Aneurysm.
Journal article
Loick P. et al, (2023), Arterioscler Thromb Vasc Biol
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A Hand-Held Magnetic Acoustic Device With Integrated Real-Time Monitoring for Targeted Drug Delivery.
Journal article
Shieh B. et al, (2022), IEEE transactions on ultrasonics, ferroelectrics, and frequency control, 69, 2462 - 2473
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Applications of artificial intelligence for patients with peripheral artery disease.
Journal article
Lareyre F. et al, (2022), J Vasc Surg
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Genome-wide association analysis and replication in 810,625 individuals with varicose veins.
Journal article
Ahmed W-U-R. et al, (2022), Nat Commun, 13
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Interferon regulatory factor-5-dependent CD11c+ macrophages contribute to the formation of rupture-prone atherosclerotic plaques.
Journal article
Edsfeldt A. et al, (2022), Eur Heart J, 43, 1864 - 1877
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A deep learning pipeline to simulate fluorodeoxyglucose (FDG) uptake in head and neck cancers using non-contrast CT images without the administration of radioactive tracer.
Journal article
Chandrashekar A. et al, (2022), Insights Imaging, 13