Patients in England having radiotherapy are likely to have part of their treatment performed with the aid of artificial intelligence after its use to help NHS clinicians was recommended for the first time.
Draft guidance from the National Institute for Health and Care Excellence (Nice) has given approval to nine AI technologies for performing external beam radiotherapy in lung, prostate and colorectal cancers, in a move it believes could save radiographers hundreds of thousands of hours and help relieve the “severe pressure” on radiotherapy departments.
NHS England data shows there were 134,419 radiotherapy episodes in England in April 2021 to March 2022 of which a significant proportion required complex planning.
At the moment, therapeutic radiographers outline healthy organs on digital images of a CT or MRI scan by hand so that the radiotherapy does not damage healthy cells by minimising the dose to normal tissue. Evidence given to Nice found that using AI to create the contours could free up between three and 80 minutes of radiographers’ time for each treatment plan, and that AI-generated contours were of a similar quality as those drawn manually.
While it recommended using AI to mark the contours, Nice said that the contours would still be reviewed by a trained healthcare professional.
Dr Sarah Byron, the programme director for health technologies at Nice, said using AI could help reduce waiting lists. She added: “NHS colleagues working on the frontline in radiotherapy departments are under severe pressure with thousands of people waiting for scans.
“The role imaging plays in radiotherapy treatment planning is quite pivotal, so recommending the use of AI technologies to help support treatment planning alongside clinical oversight by a trained healthcare professional could save both time and money.
“We will continue to focus on what matters most and the recommendations made by our independent committee can help to bring waiting lists down for those needing radiotherapy treatment.”
The health secretary, Steve Barclay, welcomed the announcement. He said: “It’s hugely encouraging to see the first positive recommendation for AI technologies from a Nice committee, as I’ve been clear the NHS must embrace innovation to keep fit for the future.
“These tools have the potential to improve efficiency and save clinicians thousands of hours of time that can be spent on patient care. Smart use of tech is a key part of our NHS long-term workforce plan, and we’re establishing an expert group to work through what skills and training NHS staff may need to make best use of AI.”
Nice said it was also examining the evidence for using AI in stroke and chest scans. It follows a study that found AI was safe to use in breast cancer screening and could almost halve the workload of radiologists, according to the world’s most comprehensive trial of its kind. Evidence is growing that AI can be more effective in detecting cancers. Researchers hope it will be able to speed up the detection of cancer by helping to fast-track patients to treatment, and by streamlining the analysis of CT scans.
The nine platforms included are AI-Rad Companion Organs RT, ART-Plan, DLCExpert, INTContour, Limbus Contour, MIM Contour ProtegeAI, MRCAT Prostate plus Auto-contouring, MVision Segmentation Service and RayStation.
Charlotte Beardmore, the executive director of professional policy at the Society of Radiographers, welcomed the draft guidance but said it was not a replacement for staff and caution was needed. “It is critical there is evidence to underpin the safe application of AI in this clinical setting,” she said. Using AI would still require input by a therapeutic radiographer or another member of the oncology multi-professional team, she added. “Investment in the growth of the radiography workforce remains critical.”
Separately, the government announced it was investing £13m in AI healthcare research before the first big international AI safety summit in autumn. The technology secretary, Michelle Donelan, said 22 university and NHS trust projects would receive funding for projects including developing a semi-autonomous surgical robotics platform for the removal of tumours and using AI to predict the likelihood of a person’s future health problems based on their existing conditions.
