Developing an internationally leading radiotherapy-physics programme
The advanced radiotherapy group is one of six main areas of radiotherapy research in Manchester and is working to develop an internationally leading radiotherapy physics programme. Integrated within the Radiotherapy Related Research department at the Christie, the advanced radiotherapy group is a broad multidisciplinary team includes physicists, computer scientists, clinicians, radiographers, pathologists and statisticians. This close synergistic collaboration enables the group to exploit a wide range of clinical data.
The group’s main focus is to improve the accuracy of radiotherapy to maximise tumour control while reducing the side effects to improve patient survival and quality of life. The team are achieving this by working to optimise all aspects of radiotherapy process by refining target volume definition, optimising treatment planning, improving image guidance and correlating radiation dose with clinical outcomes.
Through The Christie, the group has access to a wide range of clinical data gathered from every patient treated at various disease sites including lung, oesophagus, prostate, breast, cervix and bladder. The group are specialists in large-scale image processing, analysis of higher-dimensional data as well as artificial intelligence (AI) methods which are then applied to oncology and radiotherapy as well as national and international clinical trials.
A Team Science Approach
The advanced radiotherapy group works together to target different aspects of the radiotherapy pathway.
The ability to image the tumour and surrounding tissues before and during radiotherapy is important to ensure that the whole tumour is targeted while reducing damage to surrounding tissues. Examples include accelerating MRI-guidance for photon treatments (e.g. using AI to enhance image contrast) and working to reduce the imaging dose received by paediatric cancer patients.
Treatment planning and adaptation
The advanced radiotherapy group is working on methods to reduce the impact of respiratory and cardiac motion on treatment accuracy. In MRI-guided radiotherapy, the group is developing AI methods to correct for the impact of gas pockets. In addition, the group are creating probabilistic models to address unavoidable sources of uncertainty during radiotherapy delivery, such as anatomical changes, and tumour delineation (inter-observer variation).
The team has pioneered a new approach of establishing dose-response relationship, named “image-based data-mining” (IBDM). This approach can identify regions of the body that when given radiation, the dose leads to severe side effects or impact survival and has led to several prize-winning posters/presentations. IBDM is one example of where world-leading research has changed clinical practice.
Researchers within the group have identified a specific region in the heart strongly linked with poorer survival in lung cancer patients and has led to changes in radiotherapy plans for patients.
Learning from Every Patient
The primary goal of the group is to learn from every patient. The group works closely with clinical colleagues at the bedside and make sure that research makes a substantial benefit to patients.
Living with and beyond cancer
Life-long side effects are common when radiotherapy is used in paediatric patients. The group are working to adapt its image-based datamining methodology to identify regions in the growing body which are especially sensitive to radiation. For this the group are establishing new collaborations with world-leaders in paediatric cancer such as St Jude Children’s Research Hospital, and national charities such as Friends of Rosie and Cancer Research UK.
Routine images contains information that can provide quantitative measures that represent the burden of the patient multi-morbidities. For example, calcifications in the vessels, liver cirrhosis, osteoporosis and sarcopenia. The aim is to build automated platforms to extract these imaging biomarkers from any available routine patient image. These will be validated and used in risk models to help better inform patient treatment decisions. Therapeutic radiographers and clinical physicists are involved in the development of functional on-treatment imaging (e.g. DWI, oxygen-enhanced MR).
Up to now, uncertainties in radiotherapy has been handled using margins, a simplified way which may result in over-treating some patients and increasing side effects. The team is modelling these uncertainties to account for them directly during treatment planning. These activities require scientists to work closely with clinical radiographers to quantify these uncertainties and introduce it into clinical practice. This will help improve life after cancer.
Changing clinical practice
Leveraging strong links with industrial partners (e.g. Elekta, Mirada Medical, RaySearch) the group strive to bring clinical results and methods to as many patients and radiotherapy professionals as possible. The group are key partners in clinical education (Royal College of Radiologists, Higher Specialist Scientist Training programme, European Society of Radiotherapy and Oncology) and several of the group’s members are involved in developing clinical guidelines at the national and international level.
Treating the complex comorbid patient is one of the challenges we face. The Advanced Radiotherapy group pioneered the use of IBDM to establish the relationship between radiation dose and site of delivery with the development of lymphopenia. This showed that severe lymphopenia during radiation therapy is a poor prognostic factor for overall survival in lung cancer patients. However severe lymphopenia could be mitigated by minimising radiation doses to the thoracic vertebrae, normal lung, and the heart, to limit irradiation of stem cells and blood pool. The group is now extending this pioneering work to other cancer sites and will perform more in depth analyses of other haematological toxicities and their link to cancer outcomes.
MR-Linac is an exciting technology that combines highly precise imaging and a radiotherapy delivery system that allows for real-time imaging with soft tissue definition superior to that of current standard…
Optimising and personalising radiotherapy using new biomarkers, techniques or imaging technology to deliver high doses of radiotherapy while minimising side effects.