The use of AI makes it possible for women with a high risk of breast cancer to be identified in mammography screening examinations so that the cancer can be caught earlier.
Breast cancer awareness – artistic photo. Image credit: Angiola Harry via Unsplash, free license
An international research group led from Karolinska Institutet in Sweden can now show that the method is effective in different European countries. The study is published in The Lancet Regional Health – Europe.
At present, a large number of women are diagnosed at a late stage and can even develop breast cancer between screenings. The AI-based risk model can be used to determine which women need additional examination as a complement to their normal mammography, so that any tumours can be detected earlier.
The current study confirms earlier reports in which the AI-based risk model was able to identify a group of women who had almost seven times the risk of developing breast cancer as the normal population.
Individualised screening
“Although about six per cent of the women were high-risk, they are screened today in the same way as low-risk women,” says Dr Eriksson. “We think that a specially adapted screening could be more suitable for these women.”
However, the purpose of this study was not to look at clinical use per se but to examine if the method, which had already been evaluated in Sweden and the USA, also works in different mammography programmes around Europe.
“First you develop the model and test it in a slightly more limited population, and then you go on to demonstrate generalisability in other populations, after which you reach a point where you believe that the model works,” he continues.
The next phase of the research is to conduct a clinical study in Europe in which women are tested when screened and given different treatments depending on the risk value that the AI model gives them. This method was clinically evaluated in the USA several years ago.
“We’re now looking at the possibility of introducing the model in Europe,” says Dr Eriksson.
Source: Karolinska Institutet