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A machine learning technology that helps cut the time patients wait for life-saving cancer treatment has been successful in the latest round of the Artificial Intelligence (AI) in Health and Care Award.

UHB, working in partnership with Addenbrooke’s Hospital, part of Cambridge University Hospitals (CUH) are one of 38 organisations singled out for funding.

The AI Award is making £140 million available over four years to accelerate the testing and evaluation of artificial intelligence technologies which meet the aims set out in the NHS Long Term Plan.

Over the next year, UHB will work with CUH to leverage Microsoft Project InnerEye’s open-source AI toolkit to differentiate tumour and healthy tissue on cancer scans (called ‘segmenting’), prior to radiotherapy treatment. The aim of this AI Award project is to evaluate how this could save clinicians’ time, reduce the time between the scan and commencing treatment, and scale this to four NHS Trusts.

Dr Kal Natarajan, UHB consultant clinical scientist, said: “I’m really looking forward to working with colleagues in Birmingham and Cambridge on this project.

“The technology has tremendous potential to transform radiotherapy care, helping patients to be treated quicker and ensure clinicians spend their time as effectively as possible.”

Dr Raj Jena, CUH oncologist and project lead, said: “I am so pleased that our project has been awarded government funding to take it to the next level. AI has the capacity to deliver so much behind-the-scenes routine work, enabling doctors to spend more time face-to-face with patients, and shortening the time that patients have to wait for treatment.

“We believe this is first time an NHS hospital has trained its own medical imaging AI for its own patients and our aim is to assist other radiotherapy departments to use the models for their patients.”

Up to half of the UK population will be diagnosed with cancer at some point in their lives. Of those, half will be treated with radiotherapy, often in combination with other treatments such as surgery, chemotherapy, and increasingly immunotherapy.

Radiotherapy involves focusing high-intensity radiation beams to damage the DNA of hard cancerous tumours while avoiding surrounding healthy organs. This is a critical tool in the fight against cancer, with around 40% of cured patients undergoing precision radiotherapy.

Radiotherapy is most effective when treatment takes place as soon as possible. However, segmenting the tumour targets and healthy tissue on image scans is a key step that is currently performed manually by doctors, taking several hours per patient.

Microsoft's recent peer-reviewed research paper in JAMA Network Open shows that clinicians could segment prostate and head & neck cancer images up to 13 times faster when using InnerEye machine learning assistance, with an accuracy similar to that of human experts.

Javier Alvarez-Valle, from Microsoft Research Cambridge, said: “We are delighted that CUH and UHB are able to use our open-source software to build their own AI models, for the benefit of their patients. This NHSX AI Award paves the way for more NHS Trusts to reduce cancer treatment times using assistive AI, and to help alleviate the workload of clinicians.”

Already, over 17,000 stroke patients and over 25,000 patients with diabetes or high blood pressure have benefited from the first round of the AI in Health and Care Award since September, where £50 million was given to 42 AI technologies.

The AI Award is one of the programmes that make up the NHS AI Lab, led by NHSX and delivered in partnership with the Accelerated Access Collaborative (AAC) and National Institute for Health Research (NIHR).