Date: 15 February 2019
NIHR researchers have created new machine learning software that can forecast the response to treatments and survival rates of patients with ovarian cancer.
The artificial intelligence software, developed with support from the NIHR Imperial Biomedical Research Centre (BRC) and the Imperial College Experimental Cancer Medicine Centre, has been able to predict the prognosis of patients with ovarian cancer more accurately than current methods.
It can also predict what treatment would be most effective for patients following diagnosis.
The long-term survival rate for ovarian cancer is just 35-40%, because the disease is often diagnosed at a late stage once symptoms, such as bloating, are noticeable. Early detection of the disease could improve survival rates.
Doctors diagnose ovarian cancer using a blood test followed by a CT scan. However, the scans can’t give clinicians detailed insight into patients’ likely overall outcomes or on the likely effect of a therapeutic intervention.
The researchers used a mathematical software tool to analyse tumours in CT scans and tissue samples from 364 women with ovarian cancer between 2004 and 2015.
The software examined four biological characteristics of the tumours which significantly influence overall survival - structure, shape, size and genetic makeup - to assess the patients’ prognosis.
The researchers compared the results with blood tests and current prognostic scores used by doctors to estimate survival. They found that the software was up to four times more accurate for predicting deaths from ovarian cancer than standard methods.
The researchers hope that the technology can be used to stratify ovarian cancer patients into groups based on the subtle differences in the texture of their cancer on CT scans rather than classification based on what type of cancer they have, or how advanced it is.
Professor Eric Aboagye, lead author and Professor of Cancer Pharmacology and Molecular Imaging at Imperial College London, said: “The long-term survival rates for patients with advanced ovarian cancer are poor despite the advancements made in cancer treatments. Our technology is able to give clinicians more detailed and accurate information on the how patients are likely to respond to different treatments, which could enable them to make better and more targeted treatment decisions.”
Health Minister Nicola Blackwood said: “Artificial intelligence has huge potential to revolutionise healthcare by offering more accurate and earlier diagnoses - it could transform the lives of cancer patients in the future.
“We must embrace this type of technology to enable clinicians to provide the best possible care on the NHS which is personalised to individuals.”
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