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.
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.
Professor of Experimental Radiotherapeutics
- Group Leader, Oxford Institute for Radiation Oncology
- Honorary Consultant in Clinical Oncology, Oxford University Hospitals NHS Trust
Our research focus is on understanding and exploiting the biological effects of external beam ionizing radiation and therapeutic radionuclides in solid tumours (breast, lung, pancreas, oesophageal and colorectal cancers among others).
Katherine undertook specialist training in Clinical Oncology at the Hammersmith Hospital and doctoral research at Edinburgh University. In 1995 she was appointed as Staff Radiation Oncologist at the Princess Margaret Hospital and Scientist at the Ontario Cancer Institute, Toronto. She returned to the UK in 2006 to join the Oxford Institute for Radiation Oncology and established the Experimental Radiotherapeutics Group.
Sarah Able, Laboratory Manager
Ole Tietz, Postdoctoral Researcher
Fernando Cortezon-Tamarit, Postdoctoral Researcher
Joao Lourenco, DPhil Student
Anis Theljani, Postdoctoral Researcher
Rachel Anderson, DPhil Student
Abirami Lakshminarayanan, Postdoctoral Researcher
Sreejesh Sreedharan, Postdoctoral Researcher
Reinforcement Learning for Bandits with Continuous Actions and Large Context Spaces
Duckworth P. et al, (2023), Frontiers in Artificial Intelligence and Applications, 372, 590 - 597
Cancer Informatics for Cancer Centers: Sharing Ideas on How to Build an Artificial Intelligence-Ready Informatics Ecosystem for Radiation Oncology.
Bitterman DS. et al, (2023), JCO Clin Cancer Inform, 7
Ultrasensitive Reagent for Ratiometric Detection and Detoxification of iAsIII in Water and Mitochondria.
Pasha SS. et al, (2022), Inorg Chem
9th International Symposium on Physical, Molecular, Cellular, and Medical Aspects of Auger Processes: Preface.
Vallis KA. et al, (2022), Int J Radiat Biol, 1 - 2
Impact of Cyclic Changes in Pharmacokinetics and Absorbed Dose in Pediatric Neuroblastoma Patients Receiving [177Lu]Lu-DOTATATE
VALLIS K. et al, (2022), EJNMMI Physics