Imperial College London


Faculty of MedicineDepartment of Surgery & Cancer




+44 (0)20 3313 3759eric.aboagye




Mrs Maureen Francis +44 (0)20 7594 2793




GN1Commonwealth BuildingHammersmith Campus





Eric Aboagye is Professor of Cancer Pharmacology & Molecular Imaging and Director of the CRUK-EPSRC-MRC-NIHR Comprehensive Cancer Imaging Centre. He joined the college after a PhD at the CRUK Beatson Laboratories in Glasgow, UK and post-doc fellowship at The Johns Hopkins University & Hospital in Baltimore, USA. His group is interested in the discovery and development of new methods for experimental and clinical cancer molecular imaging. In the past 5 years, the team has invented and translated three novel cancer diagnostics into human application. He has acted as an advisor to GE-Healthcare, GSK, Roche and Novartis.

Professor Aboagye was recipient of the 2009 Sir Mackenzie Davidson Medal and was  elected as a Fellow of the Academy of Medical Sciences in 2010. Academy Fellows are elected for outstanding contributions to the advancement of medical science, for innovative application of scientific knowledge or for conspicuous service to healthcare.



Talbot T, Lu H, Aboagye EO, 2023, Amplified therapeutic targets in high-grade serous ovarian carcinoma - a review of the literature with quantitative appraisal., Cancer Gene Ther, Pages:1-9

Chen M, Lu H, Copley SJ, et al., 2023, A novel radiogenomics biomarker for predicting treatment response and pneumotoxicity from programmed cell death protein or ligand-1 inhibition immunotherapy in NSCLC, Journal of Thoracic Oncology, ISSN:1556-0864, Pages:1-13

Ćorović A, Wall C, Nus M, et al., 2023, Somatostatin receptor PET/MR imaging of inflammation in patients with large vessel vasculitis and atherosclerosis., Journal of the American College of Cardiology, Vol:81, ISSN:0735-1097, Pages:336-354

Aboagye EO, Barwick TD, Haberkorn U, 2023, Radiotheranostics in oncology: Making precision medicine possible, Ca-a Cancer Journal for Clinicians, ISSN:0007-9235

Li X, Marcus D, Russell J, et al., 2022, An integrated clinical-MR radiomics model to estimate survival time in patients with endometrial cancer, Journal of Magnetic Resonance Imaging, ISSN:1053-1807

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