How Artificial Intelligence Is Transforming Breast Cancer Detection and Treatment

During Breast Cancer Awareness Month, Dr. Amar Rewari, Chief of Radiation Oncology at Luminis Health and Adjunct Assistant Professor at Johns Hopkins School of Medicine, joined hosts Morgan Radford and Vicky Nguyen on NBC News Daily to discuss how artificial intelligence is changing the way doctors detect and treat breast cancer.

AI in breast cancer detection

Dr. Rewari explained that mammograms remain the most important tool for detecting breast cancer, and AI now acts as a second set of eyes for radiologists, helping ensure nothing is missed. Beyond detection, AI can analyze normal breast tissue and calcifications to generate a personalized risk score, helping determine whether a woman should be screened more or less frequently. He noted that one such tool was recently FDA approved, with more expected to follow. These tools can also help women with dense breast tissue, who often need additional screening such as ultrasound.

AI in radiation treatment

As a radiation oncologist, Dr. Rewari described how AI helps his team build treatment plans by mapping the healthy structures around a tumor, a task that has traditionally been time-consuming. This allows patients to begin treatment sooner while radiation is targeted more precisely at the tumor and away from healthy tissue.

Rising rates among younger women

The conversation also addressed recent data showing breast cancer is increasing among younger women at about 1.4% per year. Dr. Rewari explained that the causes are likely multifactorial, including diet, obesity, alcohol use, and sedentary lifestyle, and noted that about 44% of cancers today are linked to modifiable risk factors.

The most important takeaway: get screened

Dr. Rewari emphasized that screening is the single most important step women can take. Women at average risk should begin screening at age 45, while those at higher risk may need to start earlier. He encouraged women to talk with their doctors about their individual risk and the right screening schedule for them.