Artificial Intelligence: The Future of Breast Cancer Detection?


BOSTON, Mass. (Ivanhoe Newswire) – Mammography is the best tool our doctors have for breast cancer detection. The screening has improved since becoming widely available in the 80’s but it still has limitations. In fact, the American Cancer Society reports that mammograms miss one in eight breast cancers. Now, one of the country’s top imaging experts and a Harvard Medical School professor are exploring the benefits of adding artificial intelligence to this potentially life-saving screening.

For women over 40, many doctors recommend a yearly mammogram – the earlier radiologists can catch breast cancer, the better a woman’s chances are of surviving. And the technology has drastically improved over the years.

“We went from old analog films of the breast tissue to fulfilled digital mammography, to now 3D mammography and even contrast enhanced mammography. The technology boom was amazing, but it was exceeding the human eye and the human brain’s ability to extract information from those beautiful images,” Mass. General Brigham’s Chief of Breast Imaging, Connie Lehman, MD, PhD explains.

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This is where artificial intelligence comes in. It’s super-fast technology that analyzes those images and searches for masses that the human eye might miss. AI could also help assess future cancer risk.

Dr. Lehman adds, “We can also guide women in understanding, ‘You may not have a cancer evident on your mammogram now, but you are at risk in the next five to 10 years. And so, we want to talk to you about a more effective screening for you.’”

Dr. Lehman and a team of researchers are currently studying the accuracy of AI in previously stored mammograms. They want to assess how accurate AI is in a population of minority women. Dr. Lehman says the technology has not yet been studied in a clinical trial, an important step to confirm that AI is an effective screening tool.

Contributors to this news report include: Cyndy McGrath, Producer; Kirk Manson, Videographer; Roque Correa, Editor.

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Connie Lehman, MD, PhD, Chief of Breast Imaging, Mass. General Brigham




REPORT:       MB #5177

BACKGROUND: Breast cancer is a disease in which cells in the breast grow out of control. There are different kinds of breast cancer. The kind of breast cancer depends on which cells in the breast turn into cancer. Breast cancer can spread outside the breast through blood vessels and lymph vessels. When breast cancer spreads to other parts of the body, it is said to have metastasized. Breast cancer is the most common cancer in women in the United States, except for skin cancers. It is about 30% (or 1 in 3) of all new female cancers each year. About 297,790 new cases of invasive breast cancer will be diagnosed in women and about 43,700 women will die from breast cancer.


DIAGNOSING: Doctors often use additional tests to find or diagnose breast cancer. They may refer women to a breast specialist or a surgeon. This does not mean that she has cancer or that she needs surgery. These doctors are experts in diagnosing breast problems. Some tests include: breast ultrasounds, diagnostic mammograms, breast MRIs, or biopsies. Different people have different symptoms of breast cancer. Some people do not have any signs or symptoms at all.


NEW TECHNOLOGY: Radiologists assisted by an AI screen for breast cancer more successfully than they do when they work alone, according to new research. That same AI also produces more accurate results in the hands of a radiologist than it does when operating solo. The large-scale study, published this month in The Lancet Digital Health, is the first to directly compare an AI’s solo performance in breast cancer screening with its performance when used to assist a human expert. The hope is that such AI systems could save lives by detecting cancers doctors miss, free up radiologists to see more patients, and ease the burden in places where there is a dire lack of specialists.



Katie Marquedant

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Doctor Q and A

Read the entire Doctor Q&A for Dr. Connie Lehman, MD, PhD, Chief of Breast Imaging

Read the entire Q&A