Simon Doran
Senior Researcher
Magnetic Resonance
The Institute Of Cancer Research
United Kingdom
Biography
Dr Simon Doran is a senior staff scientist in the Cancer Research UK Cancer Imaging Centre at The Institute of Cancer Research, London, where he leads the effort in advanced imaging informatics. Dr Doran gained his first degree in physics and theoretical physics at the University of Cambridge and obtained a PhD in quantitative magnetic resonance imaging at the laboratory of Professor Laurie Hall. After a hugely enjoyable period of postdoctoral research in ultra-rapid MR imaging with the team of Prof Michel Décorps (INSERM U438) in Grenoble, he lectured for 11 years in the Department of Physics at the University of Surrey before moving to the ICR in 2006.
Research Interest
Dr Doran works on the development of the ICR’s Research PACS platform for archiving and visualising image data. The philosophy behind these developments is described in Doran et al. Radiographics 32, 2135–2150 (2012). Ongoing work in the group is customising the XNAT platform to meet the needs of the cancer imaging community, with a particular focus on the areas of radiotherapy physics, clinical trials, multimodality imaging and preclinical imaging. Dr Doran also works on comparison of 3D optical computed tomography (CT) microscopy and high-resolution MRI in the imaging of cancer tissues. His research explores use of 3D radiation dosimetry using optical CT in combination with radiochromic dosimeters, particularly PRESAGE®. This work concentrates on high-resolution microimaging of doses delivered in synchrotron microbeam radiotherapy. Dr Doran is a member of the EU’s SYRA3 COST Action TD1205 – a multidisciplinary network to develop synchrotron radiotherapy and radiosurgery techniques to treat brain tumours and other diseases of the central nervous system.
Publications
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McErlean, C.M., Bräuer-Krisch, E., Adamovics, J. & Doran, S.J. (2016). Assessment of optical CT as a future QA tool for synchrotron x-ray microbeam therapy. Physics in medicine and biology, Vol.61(1), pp. 320-337.
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Panek, R., Welsh, L., Dunlop, A., Wong, K.H., Riddell, A.M., Koh, D.-., Schmidt, M.A., Doran, S., Mcquaid, D., Hopkinson, G., et al. (2016). Repeatability and sensitivity of T2* measurements in patients with head and neck squamous cell carcinoma at 3T. Journal of magnetic resonance imaging, Vol.44(1), pp. 72-80.
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Winfield, J.M., Tunariu, N., Rata, M., Miyazaki, K., Jerome, N.P., Germuska, M., Blackledge, M.D., Collins, D.J., de Bono, J.S., Yap, T.A., et al. (2017). Extracranial Soft-Tissue Tumors: Repeatability of Apparent Diffusion Coefficient Estimates from Diffusion-weighted MR Imaging. Radiology, Vol.284(1), pp. 88-99.
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Doran, S.J., Hipwell, J.H., Denholm, R., Eiben, B., Busana, M., Hawkes, D.J., Leach, M.O. & dos Santos Silva, I. (2017). Breast MRI segmentation for density estimation: Do different methods give the same results and how much do differences matter?. Medical physics,
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Ertas, G., Doran, S.J. & Leach, M.O. (2017). A computerized volumetric segmentation method applicable to multi-centre MRI data to support computer-aided breast tissue analysis, density assessment and lesion localization. Medical & biological engineering & computing, Vol.55(1), pp. 57-68.
