AI Software Predicts Ovarian Cancer Survival Rates From CT Scans

Researchers from the Imperial College London (London, England) and the University of Melbourne (Melbourne, Australia) have created a new machine learning software that can forecast the survival rates and response to treatments of patients with ovarian cancer. The artificial intelligence (AI) software can predict the prognosis of patients with ovarian cancer more accurately than the current methods and can also predict the most effective treatment for patients following diagnosis.

In their study, the researchers used a mathematical software tool called TEXLab to identify the aggressiveness of tumors in CT scans and tissue samples from 364 women with ovarian cancer between 2004 and 2015. The software examined four biological characteristics of the tumors that significantly influence overall survival - structure, shape, size and genetic makeup - to assess the patients’ prognosis. The patients were then given a score known as Radiomic Prognostic Vector (RPV), which indicates how severe the disease is, ranging from mild to severe.

When the researchers compared the results with blood tests and current prognostic scores used by doctors to estimate survival, they found the software to be four times more accurate at predicting deaths from ovarian cancer than the standard methods. The researchers also found that 5% of patients with high RPV scores had a survival rate of less than two years. According to the researchers, the technology could be used to identify patients who are unlikely to respond to standard treatments and offer them alternative treatments. They now plan to carry out a larger study to see how accurately the software can predict the outcomes of surgery and/or drug therapies for individual patients.

“The long-term survival rates for patients with advanced ovarian cancer are poor despite the advancements made in cancer treatments. There is an urgent need to find new ways to treat the disease,” said Professor Eric Aboagye, lead author and Professor of Cancer Pharmacology and Molecular Imaging, at Imperial College London. “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.”

“Artificial intelligence has the potential to transform the way healthcare is delivered and improve patient outcomes,” added Professor Andrea Rockall, co-author and Honorary Consultant Radiologist, at Imperial College Healthcare NHS Trust. “Our software is an example of this and we hope that it can be used as a tool to help clinicians with how to best manage and treat patients with ovarian cancer.”

Related Links:
Imperial College London
University of Melbourne