Dr. Raj Jena looks at the digital image of a scan on a computer screen

How AI is helping to shrink waiting times for NHS cancer patients

The National Health Service at Addenbrooke’s Hospital in Cambridge is now able to plan radiotherapy treatments faster than in the past, thanks to AI advances that are cutting wait times.

As the NHS approaches its 75th birthday, it continues to evolve, searching for ways to modernise healthcare delivery, and adapt to the ever-changing needs of society.

Cambridge Universities Hospitals NHS Foundation Trust (CUH) is one such example. They’ve introduced an artificial intelligence (AI) system that can cut waiting times for radiotherapy patients. Developed by and for the NHS, the new AI system, named “OSAIRIS,” has revolutionised the preparation of scans, reducing the time patients at Addenbrooke’s Hospital must wait between referral and treatment initiation.

Empowering medical specialists

Working alongside this AI technology, specialists can plan radiotherapy treatments approximately two and half times faster than if they were working alone, ensuring more patients can get treatment sooner and improving the likelihood of better outcomes.

Initially implemented at Addenbrooke’s for prostate and head and neck cancers, OSAIRIS has potential for patients across the NHS, spanning a range of cancer types.

OSAIRIS significantly reduces the labour-intensive process of manually outlining healthy organs on scans prior to radiotherapy, known as “segmentation.” Precise segmentation is critical to protect the healthy tissue around the cancer from radiation. It can take a doctor anywhere between 20 minutes and three hours to perform this task, per patient. OSAIRIS streamlines the process, freeing oncologists to focus on treatment planning while AI handles segmentation. The oncologist then meticulously reviews each scan, ensuring accuracy and retaining control throughout the process.

Dr. Raj Jena, an oncologist at CUH, spearheaded the research for the NHS and University of Cambridge.

“OSAIRIS does much of the work in the background so that when the oncologist sits down to start planning treatment, most of the heavy lifting is done,” Dr. Jena explains. “It is the first cloud-based AI technology to be developed and deployed within the NHS, which we will be able to share across the NHS for patient benefit.”


A decade in the making

Dr. Jena’s research includes collaborating with Microsoft Research on Project InnerEye, a Microsoft research effort developing machine learning and open-source software that is empowering healthcare organisations and innovators to develop their own solutions to assist clinicians in planning radiotherapy treatments.

The Project InnerEye team carried out peer-reviewed research working with eight clinical centres around the world showed that clinicians using machine learning assistance can segment images significantly faster than doing it manually, with an accuracy that is within the bounds of human expert variability. To broaden access to research in this field, Microsoft Research made available Project InnerEye toolkits as open-source software in September 2020.

Supported by a £500,000 grant from the NHS AI Lab, Dr. Jena’s team created a new AI system, OSAIRIS, using open-source software technology from Project InnerEye and Azure Machine Learning. Rigorous tests and risk assessments have been carried out to ensure OSAIRIS can be used in the day-to-day care of radiotherapy patients across the NHS. In masked tests — known as “Turing tests” — doctors were unable to tell the difference between the work of OSAIRIS and the work of a doctor colleague. Ultimately, however, the oncologist remains in control throughout.

World-class expertise

Bringing it back to where it began, all NHS patients in the Cambridge area that require radiotherapy treatment for prostate or head and neck cancer are having their treatment planning accelerated by this AI technology at Addenbrookes Hospital.

As for what’s next, Dr. Jena is keen to expand on the use cases that the AI technology can help with. “We’ve already started to work on a model that works in the chest, so that will work for lung cancer and breast cancer particularly,” he explains. “And also, from my perspective as a neurooncologist, I’m interested that we’re building the brain model as well so that we’ve got something that works for brain tumours as well.”

Aditya Nori, General Manager of Healthcare for Microsoft Research, said: “I started working in healthcare almost nine years ago and healthcare offers the possibility not only to have technical impact but also societal impact, so I am really thrilled about this. The fact that we have AI finally in the NHS also will open the doors for other kinds of AI technologies to really reduce the burden that’s placed on clinicians, and more importantly, improve patient safety, outcomes, and experiences.”

The NHS team is working with other hospitals to roll out similar efforts more broadly. “I’m tremendously excited,” says Dr. Jena. “From the clinician’s perspective, I think it’s fantastic that we can collaborate with some of the finest minds at Microsoft and then take their cloud-based open-source tools, train an AI in hospital using data from our own patients and actually deploy it across the NHS for wider patient benefit.”

You can find out more about Project InnerEye on the Microsoft Research podcast, Collaborators: Project InnerEye with Javier Alvarez and Raj Jena – Microsoft Research