SHOW: How artificial intelligence is being used to detect breast cancer
As the age of artificial intelligence, or AI, continues to expand, this revolutionary technology is now being used as a breast cancer detection tool.
More and more breast imaging centers across the country are now using a type of AI called computer-aided detection, or CAD, to help reduce the number of breast cancer cases that are missed by traditional mammography.
A major study estimates that mammography screenings miss about 1 in 8 cases of breast cancer.
“The main benefit of AI right now is that it makes mammogram reading faster, so a radiologist can see more mammograms accurately over a period of time,” Dr. Larry said. Norton, medical director of Evelyn H. Lauder Breast Cancer. Center at Memorial Sloan Kettering Cancer Center in New York, said “Good Morning America.”
With CAD, a patient undergoes a typical mammogram, breast X-ray, and then the scan results undergo additional computer screenings to mark areas of potential cancer.
Studies show that CAD helps review images, assess breast density, and flag high-risk mammograms that radiologists may have missed. He can also tell a technologist that a mammogram needs to be redone.
“It really changed the paradigm and it changed the value of mammography itself,” Dr. Constance Lehman, a diagnostic radiologist at Massachusetts General Hospital, told GMA. “And that’s really exciting.”
Medical guidelines suggest that most women should start having regular mammograms starting at age 50, or even earlier, depending on additional risk factors.
About 1 in 8 women in the United States will be diagnosed with breast cancer in her lifetime, according to the Centers for Disease Control and Prevention.
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For most women, mammograms are considered the best way to find breast cancer early, according to the CDC, which can lead to better outcomes and easier treatment.
Although the use of AI is exciting in the field of breast cancer, it is still a work in progress. Studies show that the use of AI in breast cancer screenings may be associated with false positive rates.
“Machine learning is very good at what you’ve taught it,” Norton explained. “Machines, when they see something they have no experience with, they’re not very good at identifying it.”
So far, studies show that AI technology is best used alongside humans. A recent study found that humans and AI working together are able to detect 2.6% more breast cancers with fewer false alarms.
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Lehman said she can see a future where AI is used not only to detect but also to prevent breast cancer and other cancers.
“AI tools will advance breast cancer detection, risk assessment, cancer prevention,” she said. “Not just detecting early, but actually preventing cancers.”