Imaging Prompt Gamma Emissions in Radiotherapy Environments

1) Brief description of the context of the research including potential impact

Radiotherapy is a widely used and successful treatment for cancer globally, being used either alone or in combination with surgery and/or chemotherapy for approximately one third of patients undergoing treatment. Together with the therapeutic effect of the depositing radiation, a small proportion of interactions give rise to the emission of so-called prompt gamma photons. By measuring the spatial distribution of these prompt gammas, it is possible to infer the proton range and dose deposition profile. This is important to ensure the prescribed treatment is being delivered according to plan. Furthermore, the ability to track the proton dose could allow the treatment to be optimized and designed to avoid organs at risk. This is particularly important with certain types of radiotherapy, such as proton therapy, where a great percentage of the patients are children or young adults, the expectation is that they will go on to live a long life, so avoiding long term complications following treatment is essential to the quality of life of the patients.

2) Aims and Objectives

This project aims to develop a novel detector to image the prompt gamma distribution in radiotherapy environments and to combine this distribution with knowledge of the imaging geometry to reconstruct the spatial distribution of the delivered radiation dose during the treatment.

The specific objectives are:

- To develop an understanding of the radiation environment present in different treatments as well as their similarities and differences.
- To design and implement a Monte Carlo model of the treatment.
- To optimize the detector design and implementation to different requirements and conditions.
- To utilize this model, together with notions of inverse problems and potentially with other methods such as Machine Learning for different approaches to event sorting (separating signal from background).
- To put these together in manufacturing said detector and evaluating it in an environment where its feasibility for treatment can be studied.

3) Novelty of Research Methodology

There are multiple detectors available for prompt gamma imaging. In this project, we aim to focus on RadiCAL. This technology (originally developed for nuclear security applications) can detect, localize, and identify sources of radiation. It works by rotating a specially shaped scintillator detector and encoding the magnitude of the received signal. By fitting the measured data with an appropriate detector response function and analysing the received spectrum, it is possible to recover the spatial location of a radiation source and its characteristics. We aim to utilize this to improve localization to a few mm and resolve a spatially distributed source (i.e., the prompt gamma emitter), thus finding the dose distribution of the treatment. This method introduces potential advantages, such as its fast response time, which could lead to in vivo verification during treatment, or its relatively low cost. However, despite RadiCAL being the main detector in which we will focus, other potential detector concepts will be studied and potentially used if found better suited for the task.

4) Alignment to EPSRC's strategies and research areas

This project aligns closely with the strategic priority of transforming health and healthcare. The specific area of this research is medical imaging. It will potentially utilize artificial intelligence techniques in the context of event discrimination.

5) Any companies or collaborators involved

In collaboration with UCLH (University College London Hospitals NHS Foundation Trust). Studying other potential partnerships.