Canon Medical Research Europe has been awarded £140,000 to develop a prototype that combines Artificial Intelligence (AI) and medical imaging technology to improve assessment for one of the most difficult cancers to manage, Malignant Pleural Mesothelioma (MPM).

The Cancer Innovation Challenge aims to inspire novel data and technology innovations to help Scotland become a world leader in cancer care. Funded by Scottish Government through the Scottish Funding Council and delivered by three Scottish innovation centres led by The Data Lab, this Phase II funding focuses on identifying innovative ways to improve cancer treatment and outcomes using data science.

Working with renowned mesothelioma physician and researcher Dr Kevin Blyth, of NHS Greater Glasgow and Clyde, Canon Medical is seeking to show that AI can be an effective tool in the fight against this particularly challenging cancer.

If successful, the company hopes to start development on an AI tool that will recognise, assess and measure cancer tumours, while contributing to the growing body of evidence for how AI can help medical advancement across the world.

Scotland has one of the highest incidence rates of mesothelioma, sometimes known as ‘asbestos cancer’, in the world. Unlike most types of tumour, which are roughly spherical in shape, mesothelioma grows in a skin-like manner around the lung.

This makes measuring its size much more time-consuming and error-prone than for other cancers. Without a reliable measurement it is very difficult to gauge how well a treatment is working, or to choose the most effective treatment for each patient.

This project will develop AI technology that rapidly and accurately measures the size of the mesothelioma tumour, which could form an important component of a precision medicine system for treating patients with the disease.

The project team also hopes that an AI-based assessment tool could have a positive impact on the cost of cancer drugs. This is because clinical trials may become more efficient using AI tools to determine whether new drugs are having a useful effect. AI systems have the potential to make these assessments more accurate and less expensive than current human reporting systems.

Minister for Trade, Investment and Innovation, Ivan McKee MSP, commented: “Most of us will have been affected by cancer at some stage either personally or through family members. This research, if successful, will bring us closer to vital advances in cancer treatment through data science.

“I am really pleased to hear of Canon Medical’s success in Phase II of the Cancer Innovation Challenge. This is a great example of how our investment in innovation is supporting advancements in Artificial Intelligence to deliver better outcomes for the people of Scotland.”

Dr Ken Sutherland, president of Canon Medical Research Europe, said: “Canon Medical is fully focused on improving the lives of patients and providing the latest and most advanced clinical decision support tools to clinicians.

“We are actively tackling those areas where our technology and know-how can make a significant impact on people’s lives. MPM is a terrible condition for those that are unfortunate enough to suffer from it, and we believe that an automated assessment method using AI would be a major advance in fighting this disease and, potentially, other forms of lung cancer. The funding from CIC is critical to developing this ground-breaking tool.”

Dr Kevin Blyth, of NHS Greater Glasgow and Clyde added: “MPM is an exceptionally challenging cancer to start with, but the possibilities are enormous using Canon Medical’s technology and our clinical and research input.

“While it is an ambitious project we are positive that whatever we learn will be valuable for advancing medical knowledge and taking us towards a world in which treatments are increasingly tailored, affordable, and successful.”

Gillian Docherty, chief executive of The Data Lab, which is leading the innovation centres’ support on the project, said: “We were extremely impressed with Canon Medical’s innovative concept and obvious commitment to best practice in data science, clinical input, and AI development for improving patient care and outcomes. We believe this research will go a long way to advancing medical technology and precision in Scotland, and across the world.”