Breast cancer is the second-leading cause of cancer deaths in women. About one in eight women will be diagnosed with the disease in their lifetimes. To combat that, some doctors are using AI as a tool to help them not only detect breast cancer, but also predict a woman's risk factors.

Doctors are increasingly using artificial intelligence to improve the detection and risk prediction of breast cancer through mammogram analysis. The Clarity platform, developed by Dr. Connie Lehman and authorized by the FDA, allows clinicians to estimate a woman's five-year risk of developing breast cancer by analyzing mammogram images for predictive features beyond breast density.

This approach aims to provide more precise risk assessments, potentially identifying women at higher risk earlier and reducing unnecessary invasive procedures. The technology may also influence future screening guidelines, with research indicating that some women in their 30s have higher risks than those currently targeted for routine screening.

Doctors using AI mammogram readings to predict breast cancer risk

October is Breast Cancer Awareness Month. It is the second leading cause of cancer deaths in women. About one in eight will be diagnosed with the disease in their lifetime. And we're also seeing a rise in women under the age of 50 being diagnosed. That's why early screening and knowing if you're considered at risk can be life-saving. Mammograms have saved countless lives, but they aren't perfect. Now some doctors are actually using AI technology as a tool to help them not only detect breast cancer, but also predict a woman's risk factors. I wanna welcome in Dr. Connie Lehman. She's a breast imaging specialist at Mass General Bingham and the founder of Clarity, the first FDA authorized AI platform used to help predict a woman's five-year future risk of developing breast cancer. Dr. Lehman, thank you so much for being with us. So how does this technology work in detecting cancer before it's even formed? Well, we're so excited about this. You know, there was a radiologist way back in the 1970s that thought he noticed mammograms in women who end up being diagnosed with breast cancer actually look different than mammograms in women who don't develop breast cancer. He wondered if we had powerful enough computers, could we pull that information out? I just wish you were alive today because with AI, we can now do that. We can go far beyond breast density. Breast density is important. It can hide cancers. We need to be careful in how we talk to women about their breast density, but it's actually a very weak predictor of future breast cancer. And that's where AI comes in. AI and the power of computer vision can extract many more predictive elements than just the density and predict a woman's future risk of breast cancer. 40% of women are told that they have dense breasts. Can you tell us a little bit what that means to have a dense breast and how soon we could see this technology in all medical facilities? So all women's breast tissue has two basic components. One is normal, healthy breast fat and the other are these fibrous and glandular elements. And those show up as white on the mammogram as we can see here, whereas the fat is more dark. It's like a gray color and cancers tend to be white. So people refer to it as you're trying to find a white snowball in a white snowstorm when you have a cancer and a very dense breast. So the masking, the hiding of a cancer can be really important, but also there's a little bit of a bump up in risk if you have dense breast tissue. Turns out that bump up is very, very small. But when we use AI, we can really focus in and target those women with dense breast tissue who really are at increased risk and reassure those that we find are actually not at increased risk. Now, there is some concern that AI may frankly be too good at its job and may detect tumors that are not life-threatening. And then a patient may go through the painful process of treating something that frankly didn't need to be treated at all. What do you say to that concern? Yeah, we've been struggling and working on and focused on this idea of over-diagnosis, finding cancers that don't matter. So that's across the whole board. Obviously our focus is to find cancers as early as possible when they can be cured. But we do think when we have a risk model like Clarity Breast, we can actually reduce the quote over-diagnosis because we're going to find the right kinds of patients to have the right kinds of tests. What I worry about is when we take expensive new invasive technologies and we suggest that all women need them or all women with dense breast tissue need them. When in fact, we can be much more precise in how we direct women in that decision-making so that those that are having more invasive, more aggressive screening and cancer prevention interventions are the right women. Right now the guidelines say that you need to start getting a mammogram or getting screened at the age of 40 with this new technology and its ability to detect cancer before it even starts. Do you think that the guidelines may change and that women may start getting screened even earlier? Absolutely. Until now, we really were very limited in how we recommended women start screening mammography. We've been arguing for a long time, is it 50 or 40? Most parts of the world, women don't start screening until 50. In the US, we now have pretty good agreement that we should start at 40. But what we know is the fastest rising group of breast cancer diagnoses are in women under 40. It's also the fastest rising group of metastatic breast cancer that can't be cured. We know that shock when we hear someone was diagnosed with breast cancer, but they were only 33. How is that possible? They were only 36. So we've done a lot as a healthcare community to identify women at high risk that should start screening in the 30s. Do they have a first degree relative with breast cancer diagnosed before the age of 50? Do they have a genetic mutation? But we're missing the majority of women in their 30s being diagnosed with breast cancer. We just completed a study showing that we can identify 10% of women, one in 10 in their 30s, that have a much higher risk of future breast cancer than women were screening in their 50s and 60s. So that's groundbreaking. And that's where we really see a future where we have a baseline at 30. We assess the woman's risk on that baseline mammogram at 30. We talk to her about her family history and her other health history. And then we put her on a plan to move safely through her 30s until she reaches 40 and starts average annual, age 40, average risk-based screening. Dr. Connie Lehman, thank you so much. Thank you.

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