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Primary Supervisor: Professor Katherine Vallis

Project Overview:

The adoption of highly effective anticancer radiopharmaceuticals such as 223Ra, 177Lu[Lu]-PSMA and 177Lu[Lu]-DOTATAE and, in some cases, their companion imaging tracers, into oncologic practise over the last few years has invigorated the field of radiopharmaceutical therapeutics. Current protocols rely on fixed activities over a number of repeat administrations (cycles) with no adjustments for patient- and tumour-specific characteristics such as individual pharmacokinetics or molecular target expression. The target tumour absorbed radiation dose and the dose constraints applied to normal organs at risk, are based on data derived from external beam radiotherapy, taking no account of the profoundly different biological effects of the two forms of treatment.

 The aim of this study is to develop and optimise a dosimetric framework for personalised radionuclide therapy using deep learning from patients undergoing treatment for neuroendocrine tumours and prostate cancer, to facilitate individualised treatments as a standard in practice.  

Specific goals are to:

  • Understand how changes in uptake and pharmacokinetic parameters that occur in tumour and normal organs throughout a course of therapy influence delivered absorbed dose and response to therapy.
  • Develop and apply deep learning algorithms to investigate radiomics parameters that may relate to absorbed dose and response to therapy
  • Develop and apply deep learning algorithms to accelerate image analysis and computational aspects of the dosimetry workflow. 
  • Define the minimum number of imaging time points needed for precision dosimetry to aid clinical implementation of dosimetry. 

This clinical research will be complemented by laboratory based investigations designed to understand the radiobiological effects 177Lu[Lu]-PSMA and 177Lu[Lu]-DOTATAE in cancer models, and for this new knowledge to be applied to the development of biologically-informed treatment protocols.

Training Opportunities:

The scope of this project extends across aspects of nuclear medicine, medical physics and radiation biology and will suit a student with interests in one or more of these disciplines. The student will acquire skills in image analysis and computer science methods (including deep learning) to enable personalised radiation dosimetry. Skills training will include a grounding in clinical research methods and good clinical practise including clinical data management and analysis. There will be clinical observation opportunities in nuclear medicine and radiation oncology. The project will also involve a laboratory-based component involving tissue culture, including 3D models, and molecular and cell biology methods applicable to the investigation of the biological effects of radiopharmaceutical therapeutics.

Relevant Publications:

Lee, B.Q., Abbott, E.M., Able, S., Thompson, J.M., Hill, M.A., Kartsonaki, C., Vallis, K.A. and Falzone, N., 2019. Radiosensitivity of colorectal cancer to 90Y and the radiobiological implications for radioembolisation therapy. Physics in Medicine & Biology64(13), p.135018.

Abbott, E.M., Falzone, N., Lee, B.Q., Kartsonaki, C., Winter, H., Greenhalgh, T.A., McGowan, D.R., Syed, N., Denis-Bacelar, A.M., Boardman, P. and Sharma, R.A., 2020. The impact of radiobiologically informed dose prescription on the clinical benefit of 90Y SIRT in colorectal cancer patients. Journal of Nuclear Medicine61(11), pp.1658-1664.

Abbott, E., Young, R.S., Hale, C., Mitchell, K., Falzone, N., Vallis, K.A. and Kennedy, A., 2021. Stereotactic inverse dose planning after yttrium-90 selective internal radiation therapy in hepatocellular cancer. Advances in radiation oncology6(2), p.100617.

Malcolm, J.C., Falzone, N., Gains, J.E., Aldridge, M.D., Mirando, D., Lee, B.Q., Gaze, M.N. and Vallis, K.A., 2022. Impact of cyclic changes in pharmacokinetics and absorbed dose in pediatric neuroblastoma patients receiving [177Lu] Lu-DOTATATE. EJNMMI physics9(1), pp.1-14.

McGowan, D.R. and Guy, M.J., 2015. Time to demand dosimetry for molecular radiotherapy?. The British Journal of Radiology88(1047), p.20140720.