Eric Aboagye

Aboagye was born in Ghana.^[1] He studied pharmacy at the Kwame Nkrumah University of Science and Technology in 1989.^[1] He moved to the United Kingdom shortly after, and completed a master's degree in pharmaceutical analysis at the University of Strathclyde.^[1] He earned his doctoral degree at the Cancer Research UK Beatson Laboratories in Glasgow. He was a postdoctoral researcher at Johns Hopkins University.^[2]

Aboagye joined Imperial College London as a research associate in 1998.^[1] He was promoted to Professor in 2006. He is interested in molecular imaging and the development of novel imaging for cancer diagnosis.^[1] He is Director of the Comprehensive Cancer Imaging Centre, which combines synthetic chemistry, software development and biomedical science in an effort to diagnose and treat cancer patients.^[3]

He has demonstrated that artificial intelligence is significantly more accurate than blood tests in predicting the survival rates of ovarian cancer.^[4] For the study, Aboagye used TexLab to analyse CT scans and establish the health risks associated with different tumours.^[4] The software was trained to analyse the shape, size, genetic composition and structure of tumours.^[4] Aboagye have developed imaging tools capable of characterising choline, glycogen and fatty acid metabolism.^[5]

His awards and honours include:

• 2009 British Institute of Radiology Sir Mackenzie Davidson Medal^[6]
• 2010 Elected Fellow of the Academy of Medical Sciences^[3]

His publications include:

• Aboagye, Eric O. (1999). "Malignant transformation alters membrane choline phospholipid metabolism of human mammary epithelial cells". Cancer Research. 59 (1): 80–4. PMID 9892190.
• Aboagye, Eric O. (2013). "Magnetic nanoparticles as contrast agents in the diagnosis and treatment of cancer". Chemical Society Reviews. 42 (19): 7816–33. doi:10.1039/C3CS60149H. PMID 23788179.
• Aboagye, Eric O. (2003). "3′-Deoxy-3′-[¹⁸F]Fluorothymidine as a New Marker for Monitoring Tumor Response to Antiproliferative Therapy in Vivo with Positron Emission Tomography". Cancer Research. 63.