Scientists excited by potential of AI cancer tool

A new study suggests that artificial intelligence is almost twice as good at grading the aggressiveness of a rare form of cancer from scans as the current method.

The study showed that by recognising details which are invisible to the naked eye, AI was 82 per cent accurate, compared with 44 per cent for lab analysis.

Researchers from the Institute of Cancer Research and the Royal Marsden Hospital say it could improve treatment and benefit thousands of patients every year, and are also excited by its potential for detecting other cancers early.

AI is already showing significant promise for diagnosing breast cancers and reducing treatment times.  Computers can be fed huge amounts of information and trained to identify the patterns in it to make predictions, solve problems and learn from their own mistakes.

Professor Christina Messiou, of the Institute of Cancer Research in London and consultant radiologist at the Royal Marsden NHS Foundation Trust, said “We’re incredibly excited by the potential of this state-of-the-art technology.

“It could lead to patients having better outcomes, through faster diagnosis and more effectively personalised treatment.”

The researchers used a technique called radiomics to identify signs, invisible to the naked eye, of retroperitoneal sarcoma, which develops in the connective tissue at the back of the abdomen, in scans of 170 patients.  With this information, the AI algorithm was able to grade the aggressiveness of 89 other tumours, from scans, much more accurately than biopsies.

Dr Paul Huang from the Institute of Cancer Research, said “This kind of technology has the potential to transform the lives of people with sarcoma – enabling personalised treatment plans tailored to the specific biology of their cancer.

“It’s great to see such promising findings.”

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Posted by Karen Motley, Clinical Negligence Department, Chadwick Lawrence LLP (jacquelinevance@chadlaw.co.uk), medical negligence lawyers and clinical negligence solicitors in Huddersfield, Leeds, Wakefield and Halifax, West Yorkshire.

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