Breast cancer: Artificial intelligence boosts accuracy of tumour diagnoses
The image recognition technique could help doctors to prescribe more effective treatments.
Each year around two million women around the world are diagnosed with breast cancer. Typically, tissue samples of the tumour are taken and analysed and then the cancer is placed into one of three categories – low risk, or grade 1; medium risk, or grade 2; and high risk, or grade 3. The specialists then design a plan of treatment based on this initial assessment.
However, due to its relative lack of detail, this method can lead to patients being treated incorrectly. Now, a team of researchers at Karolinska Institutet in Sweden have developed an AI-based imaging tool that can help specialists to diagnose breast cancer tumours more accurately.
“Roughly half of breast cancer patients have a grade 2 tumour, which unfortunately gives no clear guidance on how the patient is to be treated,” said the study’s first author Yinxi Wang, doctoral student at the Department of Medical Epidemiology and Biostatistics, Karolinska Institutet. “Consequently, some of the patients are over-treated with chemotherapy while others risk being under-treated. It’s this problem that we’ve tried to resolve.”
Read more about breast cancer:
- Breast cancer: Low-cost test could predict relapse risk
- Breast cancer: Early screening ‘could save up to 400 lives a year’
- Early-stage breast cancers ‘more than doubles’ risk of invasive breast cancer death later in life
The team trained the AI to recognise the characteristics of differing classifications of tumour using high-resolution microscopic images taken from 2,800 patients. As a result it was able to divide patients with grade 2 tumours into two sub-groups – high risk and low risk – enabling specialists to design treatment plans more suited to individual patients.
“One big advantage of the method is that it’s cost-effective and fast, since it’s based on microscope images of dyed tissue samples, which is already part of hospital procedure,” said co-author Johan Hartman, professor of pathology at the Department of Oncology-Pathology, Karolinska Institutet, and pathologist at the Karolinska University Hospital. “It enables us to offer this type of diagnosis to more people and improves our ability to give the right treatment to any one patient.”
The researchers now plan to further refine the AI and hope to have a fully functioning diagnostic product on the market by 2022.
Reader Q&A: How does radiation kill cancer if it causes cancer?
Asked by: Odysseus Ray Lopez, US
It’s rather like the way guns can be used to commit crime, or stop it. Radiation causes cancer because its high-energy photons can cause breaks in the DNA strands in your cells. Cells can repair this damage up to a point, but sometimes the repair isn’t perfect and leaves some genes defective.
If the break affects one of the many tumour-suppressing genes in your DNA, that cell can become cancerous. But cancer cells are also more vulnerable to radiation than ordinary cells. Part of what makes them cancer cells is their ability to divide rapidly and this normally means that some of the DNA ‘spellcheck’ mechanisms are turned off.
So when a cancer cell suffers a break in a DNA strand, it’s less likely to repair it correctly. Depending where the break occurs, it might either kill the cell outright, or make it reproduce more slowly.
Radiation therapy uses a focused beam that is aimed at just the part of the body with the tumour, and the dose is carefully calculated to cause the minimum collateral damage to healthy cells. Even so, radiation therapy does very slightly increase your chances of developing a second cancer.
Jason is the commissioning editor for BBC Science Focus. He holds an MSc in physics and was named Section Editor of the Year by the British Society of Magazine Editors in 2019. He has been reporting on science and technology for more than a decade. During this time, he's walked the tunnels of the Large Hadron Collider, watched Stephen Hawking deliver his Reith Lecture on Black Holes and reported on everything from simulation universes to dancing cockatoos. He looks after the magazine’s and website’s news sections and makes regular appearances on the Instant Genius Podcast.
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