Uni’shi-tech way to help beat cancer
IT’S a space-age technique normally used to map the surface of Mars.
But now scientists at the University of Manchester are putting it to another, more down to earth, use - helping to fight cancer.
Specialists from the university and the Manchester Cancer Research Centre hope the precise numbercrunching method - known as a machine learning approach - will help assess the effectiveness of tumour treatments.
Initial findings suggest it could be four times as accurate as conventional techniques at measuring changes in tumours.
And it could eventually mean doctors are able to prescribe cancer patients with the right treatments and drugs earlier, with less trial and error.
Dr James O’Connor, a Cancer Research UK advanced clinician scientist, said: “Every person’s cancer is unique, which can make treating the disease challenging as a drug that works for one patient might not work for someone else.
“That’s why we’re increasingly looking at finding new ways to make treatment more personal, and this innovative work could be a step towards that goal.
“The next step will be further research to find out if that’s the case, and to help uncover this method’s potential.”
The technique was developed at Manchester to help planetary scientists map features on planets such as Mars.
It was designed to better understand the errors and uncertainties of observations, enabling researchers to present their findings with confidence.
The Manchester team, from the Division of Informatics, Imaging & Data Sciences, worked with Dr James O’Connor, head of imaging within the Manchester Cancer Research Centre on studies of lab mice.
Dr Neil Thacker, from the Division of Informatics, Imaging & Data Sciences, said: “The results of this study show that we can present findings which researchers can be much more certain of.
“This means you can get the same quality of data from one sample instead of 16.
“This has important implications for research, meaning that instead of using 16 mice, in some studies only one is needed.
“This could help reduce the use of lab mice in medical research.
“It also opens up the potential for this technique to be used in patients by quickly and confidently identifying if drugs are having a specific effect on their tumours.”
Dr Paul Tar, who co-developed the method during his PhD project, added: “This technique is all about making the most of ‘small data,’ which is common in medical studies where it is difficult to obtain large numbers of samples.
“Researchers use charitable or public money, so it is important that they use it in the most efficient way possible, something which this technique allows.”