Novel imaging modalities, like whole breast ultrasound, contrast-enhanced mammography, and molecular breast imaging technology, can supplement the mammogram and enhance our ability to find breast cancer early, but selecting appropriate patients for these advanced tests remains a challenge. Here to share key highlights from her session at the 2024 San Antonio Breast Cancer Symposium that focused on how AI can be used to identify which patients should be screened for breast cancer using novel imaging modalities is Dr. Connie Lehman, Professor of Radiology at Harvard Medical School the Co-Director of the Breast Imaging Research Center at Massachusetts General Hospital.
Selecting Patients for Novel Breast Cancer Imaging Modalities: The Role of AI

Announcer:
You’re listening to Project Oncology on ReachMD. On this episode, we’ll hear from Dr. Connie Lehman, who’s a Professor of Radiology at Harvard Medical School, the Co-Director of the Breast Imaging Research Center at Massachusetts General Hospital, and a cofounder of Clairity. She’ll be discussing novel imaging modalities, which she spoke about at the 2024 San Antonio Breast Cancer Symposium. Let’s hear from Dr. Lehman now.
Dr. Lehman:
Screening mammography has proven to be a very strong test for detecting breast cancer early when it can be cured; however, it certainly has limitations, and some of those limitations are specific to patient subgroups, such as women at increased risk or women with dense breast tissue. Many organizations agree that we need to think beyond screening mammography by looking at new technology that can supplement the mammogram, whether that is whole breast ultrasound or contrast-enhanced MRI, contrast-enhanced mammography, or our molecular breast imaging technology. These tests can enhance our ability to find cancers early, but they cannot be used in large populations of average-risk women because they have false-positives, cost challenges, and access issues that just don’t make them into tests that are good for large populations of average-risk women.
So what we’re seeing on the horizon, and we’re right there ready for this transition, is we’re going to move from one size fits all where almost everyone is told “get a mammogram” and then that’s it. We’re going to move from that space into a much more elegant domain and paradigm where we’re going to use AI risk assessment to be much more precise in the screening strategies for each individual woman.
We’re getting close to it. You know, we’ve been using breast density and traditional risk models to assess a woman’s risk and to tailor her screening paradigm, but it’s not enough. So we’re very excited about the almost immediate future where we can start using and leveraging AI risk models to be better at determining which women are really going to benefit from these advanced imaging technologies that have been around for quite some time but actually haven’t been in use because we don’t know the best women to receive those. So it’s a pretty exciting time.
Announcer:
That was Dr. Connie Lehman discussing novel imaging modalities for the early detection of breast cancer. To access this and other episodes in our series, visit Project Oncology on ReachMD.com, where you can Be Part of the Knowledge. Thanks for listening!
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Overview
Novel imaging modalities, like whole breast ultrasound, contrast-enhanced mammography, and molecular breast imaging technology, can supplement the mammogram and enhance our ability to find breast cancer early, but selecting appropriate patients for these advanced tests remains a challenge. Here to share key highlights from her session at the 2024 San Antonio Breast Cancer Symposium that focused on how AI can be used to identify which patients should be screened for breast cancer using novel imaging modalities is Dr. Connie Lehman, Professor of Radiology at Harvard Medical School the Co-Director of the Breast Imaging Research Center at Massachusetts General Hospital.
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