Frank Van Den Heuvel
The main concept we take is a physics approach. The model is used to provide predictions outside of the current measurement set and thereby test the model, which has the minimum number of parameters needed to describe the experimental data. While this is the standard practice of scientific methodology, we keep the ultimate clinical applicability of the concept in mind.
Fundamental concepts: One area of research is a first principle approach to quantifying DNA-damage induction by irradiation with different types of ionising radiation (photon, protons, alpha-particles), in such a way that it can be used in clinically relevant environments. In addition, confounding factors like the level of oxygen (as low oxygen levels confirm radio-resistance) and repair altering chemicals. The models can take these confounding factors into account. Another area of research is the use of the notion of alpha-stable distributions which are used to parametrise treatments and provide mathematical models for the robustness of external beam treatments.
Applied Work: The fundamental work is developed in a number of applied projects using dose calculations (Monte Carlo simulation and biological effects through DNA-damage estimates), imaging using new equipment to allow visualisation of tumour and tumour changes during treatment, and proton therapy. Our group is strongly involved in the building of the proton therapy arm of the Precision Cancer Medicine Institute (PCMI), mainly concentrating on the possibility of low-impact treatments of breast and haematological cancers (Hodgkin's Lymphoma + Non-Hodgkin’s Lymphoma).
Clinical Implementation: Implementing concepts directly in the clinic where we introduce imaging during treatment to allow physicians to use models based on the change in texture to adapt the treatment using biological quantities (treatment response) rather than only physical ones (patient position, geometry changes). Also the robustness of models allows the planning process to be adapted to provide patient-individualised treatment margins.
22 July 2020
Understanding the molecular subtype of a cancer is becoming an importance part of the diagnostic process as it helps a doctor better understand a patient’s prognosis, determine the best course of action for treatment and helps researchers devise new, more-efficient, precision therapies.
3 July 2020
UK Research and Innovation, Cancer Research UK and industry are investing more than £11 million in an Oxford-led artificial intelligence (AI) research programme to improve the diagnosis of lung cancer and other thoracic diseases.
6 November 2018
Greg Clark, UK Secretary of State for Business, Energy and Industrial Strategy (BEIS), will confirm today (Tuesday 6 November) that UK Research and Innovation will invest £10million in the National Consortium of Intelligent Medical Imaging (NCIMI), to be led from Oxford University as part of the Industrial Strategy Challenge Fund.