AI in breast cancer advance

Scientists have developed an artificial intelligence (AI) model which may be able to predict whether an aggressive type of breast cancer will spread.

The AI model is able to detect changes in the lymph nodes – small, beanshaped structures that help filter cancer cells and fight infection – of women with triple negative breast cancer.

One of the first places breast cancer can spread to is the lymph nodes under the arm on the same side as the cancer. In these cases, patients are likely to need more intensive treatment.

The researchers said the ability to detect changes in the lymph nodes could help doctors plan treatment, as well as give patients peace of mind about the likelihood of triple negative breast cancer spreading.

Dr Anita Grigoriadis, who led the research at the Breast Cancer Now Unit at King’s College London, said: “We’ve taken these findings from under the microscope and translated them into a deep-learning framework to create an AI model to potentially help doctors treat and care for patients.”

Around one in seven, or 15%, of all breast cancers in the UK are triple negative, with more than 8,000 cases a year. This type of cancer does not have any of the receptors (proteins) commonly found in breast cancer and accounts for around 25% of breast cancer deaths.

Women who have inherited an altered BRCA gene, black women, and women who have not yet reached menopause are at higher risk of triple negative breast cancer.

For the study, published in The Journal of Pathology, the researchers tested their AI model on more than 5,000 lymph nodes donated by 345 patients to biobanks such as the Breast Cancer Now Tissue Bank.

The model was able to establish the likelihood of breast cancer spreading to other organs.

The team also found the AI model was able to make this prediction by simply analysing the immune responses in the lymph nodes, even when the breast cancer cells had not spread to the organs.

As part of the next steps, the researchers are hoping their AI model will be tested in clinical trials.

Dr Grigoriadis added: “We’re planning to test the model further at centres across Europe to make it even more robust and precise.”