{"id":527196,"date":"2025-10-15T09:42:27","date_gmt":"2025-10-15T13:42:27","guid":{"rendered":"https:\/\/northernvirginiamag.com\/?p=527196"},"modified":"2025-10-15T09:42:27","modified_gmt":"2025-10-15T13:42:27","slug":"artificial-intelligence-is-driving-meaningful-innovation-in-breast-cancer-care","status":"publish","type":"post","link":"https:\/\/northernvirginiamag.com\/wellness\/2025\/10\/15\/artificial-intelligence-is-driving-meaningful-innovation-in-breast-cancer-care\/","title":{"rendered":"Artificial Intelligence Is Driving Meaningful Innovation in Breast Cancer Care"},"content":{"rendered":"\n

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Rebecca Kaltman, MD<\/em><\/a>, is the Executive Director of the Inova Saville Cancer Screening and Prevention Center. A breast medical oncologist by training, Dr. Kaltman leads the Inova Saville Center, a facility dedicated to cancer prevention and early detection.<\/em><\/p>\n\n\n\n

You probably know someone whose life has been affected by breast cancer. With more than 300,000 new cases of invasive breast cancer diagnosed<\/a> each year, we all do. But you may be surprised \u2013 and encouraged \u2013 to know that if breast cancer is caught in its earliest stages, the five-year survival rate is 99 percent, according to the National Breast Cancer Foundation. Early detection is critical. And thanks to recent innovations in breast cancer detection and diagnosis, our ability to catch breast cancer early, and in some cases even predict its future development, has never been greater.<\/p>\n\n\n\n

The Promise of AI in Breast Cancer Care<\/h3>\n\n\n\n

For years, health care providers across the country have been using artificial intelligence (AI) tools.\u00a0For example, providers can use AI to automatically document a note in a patient\u2019s chart or (with the patient\u2019s permission) take detailed notes during a visit. In terms of breast cancer screening, radiologists routinely use computer-aided tools, in addition to their own reading of the images, to evaluate the mammogram and compare it to the patient\u2019s previous mammogram images.<\/p>\n\n\n\n

Now, the field of breast cancer prevention is beginning to use AI to help providers determine a patient\u2019s risk of developing breast cancer in the future. This approach, called \u201crisk stratification,\u201d aims to find out who is at higher risk of developing breast cancer. With that information, health care providers can recommend additional screening for people at higher risk \u2013 ultimately increasing the chance of catching breast cancer early if it does develop.<\/p>\n\n\n\n

The benefit of risk stratification is that it personalizes an individual\u2019s breast cancer screening schedule, rather than settling for the broad, age-based guidelines published by the American Cancer Society and the U.S. Preventive Services Task Force. Within the next five to 10 years, we hope to see AI tools for breast cancer risk stratification become mainstream.<\/p>\n\n\n\n

Spotlight on MirAI<\/h3>\n\n\n\n

One very exciting tool that we\u2019re evaluating at Inova is called MirAI. It\u2019s an MIT-developed algorithm that uses AI specifically for breast cancer risk prediction.<\/p>\n\n\n\n

Generally, for risk stratification in the clinic, we use tools that are based on patients\u2019 clinical information such as whether anyone in their family has had breast cancer, whether they have had children, whether they are pre- or postmenopausal, how dense their breasts are, and other factors. The most common risk stratification tool is called the Tyrer-Cuzick risk model, which uses this clinical information to estimate a woman\u2019s lifetime risk of developing breast cancer.<\/p>\n\n\n\n

MirAI is different. It looks at the mammogram alone, using a machine-learning algorithm, and predicts a woman\u2019s five-year risk of developing breast cancer.<\/p>\n\n\n\n

By recognizing patterns in the breast tissue that we can’t see with the naked eye, this tool identifies breast tissue patterns that are likely to develop into breast cancer. It also has the potential to identify the area in the breast where the cancer could develop. Studies have demonstrated that without any of the clinical information we normally use \u2013 without knowing the patient\u2019s age, family history or any other details \u2013 MirAI predicts breast cancer risk better than any other model currently available.<\/p>\n\n\n\n

Inova is currently engaging in a research study using MirAI. Our goal is to:<\/p>\n\n\n\n