AI shows major promise in breast cancer detection, new studies suggest
CBC
Researchers experimenting with artificial intelligence have found that these tools seem to reliably detect breast cancer, while also reducing a demanding workload for radiologists.
Breast cancer is the most common cancer among adults, with more than 2.3 million cases diagnosed each year, according to the World Health Organization. In most countries, the illness is one of the top two leading causes of cancer deaths in women.
But research shows that early detection and treatment can save lives.
To increase screening capacity and better identify high and low risk breast cancer, two recent studies show that specific applications of artificial intelligence (AI) performed similarly to highly trained radiologists.
"I think that breast imaging, especially mammography, [is] one of the front runners when it comes to the maturity of these AI tools," said Kristina Lång, lead author on one of the studies.
Lång's research, which was published in the Lancet Oncology journal last month, is the first of its kind to use AI to detect breast cancer from mammograms in a randomized control trial.
Preliminary results of the Swedish trial show that AI detected more cancer, while keeping false positives to a minimum.
"The results were actually [above] our expectations," said Lång, a breast radiologist and associate professor at Lund University in Sweden.
Another smaller study, published earlier this week in the journal Radiology, found that radiologists and AI came to similar conclusions after reviewing the same mammograms.
These recent studies are practical examples of the way AI could be used in healthcare to relieve a strained workforce, while ensuring more accurate diagnoses, say experts like Lång.
But other experts warn that the technology is still being refined to ensure it doesn't over diagnose or miss the cancer.
Radiologists are placing extra significance on Lång's research as it randomly assigned mammograms from more than 80,000 women to two groups.
One group involved AI-supported screening and the other followed double reading — a standard practice in Europe where two radiologists independently review each mammogram.
In the AI-supported group, the software triaged the scans by determining which ones were of low risk and needed only one radiologist to look at them, or high risk, requiring two radiologists.
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