Breast cancer high-risk diagnosis by robots? FUTURE of medicine could save THOUSANDS

Breast cancer high-risk diagnosis by robots? FUTURE of medicine could save THOUSANDS

HIGH risk breast cancer lesions could be spotted by using robots, potentially saving the NHS thousands on unnecessary surgeries.

Using machines to find lumps that could become cancerous would save some patients from having unnecessary surgery, scientists said.

High risk breast lesions are diagnosed after a biopsy.

Surgery is often the preferred treatment to remove the lesion.

But, a lot of the lesions don’t pose an immediate danger to patients, scientists have said.

Using the accurate, new machine to test for high risk lesions could also save patients and the NHS money.

Lesions that aren’t high risk could be safely monitored with follow-up imaging, the scientists said.

“Most institutions recommend surgical excision for high-risk lesions such as atypical ductal hyperplasia, for which the risk of upgrade to cancer is about 20 per cent,” said research author Manisha Bahl.

“For other types of high-risk lesions, the risk of upgrade varies quite a bit, and patient management, including the decision about whether to remove or survey the lesion, varies across practices.”

Researchers used robots to find high risk lesions in 335 patients. 

The machine was ‘taught’ by the scientists to include risk factors, including patient age and medical history.

The robot correctly found 37 of the 38 high risk lesions, out of all 335.

About 33% of surgeries would have been prevented by using the machine, the scientists claimed.

Senior author of the researcher, Constance Lehman, said: “Our study provides proof of concept, that machine learning can not only decrease unnecessary surgery by nearly one-third in this specific patient population, but also can support more targeted, personalised approaches to patient care.”

Bahl added: “Our goal is to apply the tool in clinical settings to help make more informed decisions as to which patients will be surveilled and which will go on to surgery.

“I believe we can capitalise on machine learning to inform clinical decision making and ultimately improve patient care.”

A breast lesion doesn’t always end in cancer. Lesions could also be caused by a hepatoma - a collection of blood in the breast tissue - or a thickening of the tissue.