Artificial intelligence can help doctors do a better job of finding breast cancer on mammograms, researchers from Google and medical centers in the United States and Britain are reporting in the journal Nature.
The new system for reading mammograms, which are X-rays of the breast, is still being studied and is not yet available for widespread use. It is just one of Google’s latest ventures into medicine. Computers can be trained to recognize patterns and interpret images, and the company has already created algorithms to help detect lung cancers on CT scans, diagnose eye disease in people with diabetes and find cancer on microscope slides.
“This paper will help move things along quite a bit,” said Dr. Constance Lehman, director of breast imaging at the Massachusetts General Hospital in Boston, who was not involved in the study. “there are challenges to their methods. But having Google at this level is a very good thing.”
Tested on images where the diagnosis was already known, the new system performed better than radiologists. On scans from the United States, the system produced a 9.4 percent reduction in false negatives, in which a mammogram is mistakenly read as normal and cancer is missed. It also provided a lowering of 5.7 percent in false positives, where the scan is incorrectly judged abnormal but there is no cancer.
On mammograms performed in Britain, the system also beat the radiologists, reducing false negative by 2.7 percent and false positives by 1.2 percent.
Google paid for the study and worked with researchers from Northwestern University in Chicago and two British medical centers, Cancer Research Imperial Centre and Royal Surrey County Hospital.
Last year, 268,600 new cases of invasive breast cancer and 41,760 deaths were expected among women in the United States, according to the American Cancer Society. Globally, there are about 2 million new cases a year, and more than half a million deaths.
About 33 million screening mammograms are performed each year in the United States. The test misses about 20 percent of breast cancers, according to the American Cancer Society, and false positives are common, resulting in women being called back for more tests, sometimes even biopsies.
Doctors have long wanted to make mammography more accurate.
“There are many radiologists who are reading mammograms who make mistakes, some well outside the acceptable margins of normal human error,” Dr. Lehman said.
To apply artificial intelligence to the task, the authors of the Nature report used mammograms from about 76,000 women in Britain and 15,000 in the United States, whose diagnoses were already known, to train computers to recognize cancer.
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