breast cancer

Image courtesy of the UVA Center for Survey Research


Most women don't know that having dense breasts increases their risk for breast cancer and reduces a mammogram's ability to detect cancer, according to a University of Virginia School of Medicine study.

A random phone survey of 1,024 Virginia women ages 35 to 70, conducted by the UVA Center for Survey Research, found that just 1 in 8 women were aware that breast density is a risk factor for breast cancer, while just 1 in 5 women knew that dense breasts reduced the sensitivity of mammograms to find tumors.

"It is important for women to know whether or not their own breast density is classified into one of the two high-density categories since this will increase their breast cancer risk," said study co-author Wendy Cohn, Ph.D., an associate professor in UVA's Department of Public Health Sciences. "Women need to know whether their breast density will make it harder to detect breast cancer so that, along with their healthcare team, they can consider other options for screening and detection."

Virginia is among at least 27 states that require radiologists to tell women about their breast density, according to the study, and providing that information improves women's understanding of how breast density may impact their health.

The survey found that the strongest factor in knowing about breast density and its relationship with breast cancer was whether a healthcare provider had informed a woman about the density of her breasts. UVA researchers stressed the importance of a conversation between patients and healthcare providers about the impact of breast density.

"The most important thing that doctors and patients can take away from this study is that the required written notice about breast density isn't enough in itself: patients need to talk with their providers about what breast density means for each woman's individual breast cancer risk," said Thomas Guterbock, a professor of sociology and director of the UVA Center for Survey Research.

The study has been published in the Journal of the American College of Radiology. The paper was authored by Guterbock, Cohn, Deborah L. Rexrode, Casey M. Eggleston, Melissa Dean-McKinney, Wendy M. Novicoff, William A. Knaus and Jennifer A. Harvey from UVA, along with Martin J. Yaffe from Sunnybrook Research Institute in Toronto.

For more information: www.news.virginia.edu


Related Content

Feature | Women's Health | Christine Murray

In breast cancer detection, speed and accuracy are more than clinical goals – they can significantly increase chances ...

Time June 17, 2025
arrow
News | PET Imaging

May 30, 2025 — GE HealthCare recently announced that the NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines) ...

Time May 30, 2025
arrow
News | Imaging Software Development

May 27, 2025 — DeepLook Medical, a company advancing medical imaging through visual enhancement technology, recently ...

Time May 28, 2025
arrow
News | Mammography

April 29, 2025 — iCAD, a global provider of clinically proven AI-powered cancer detection solutions, has announced a ...

Time April 29, 2025
arrow
News | Mammography

April 24, 2025 — GE HealthCare will feature its latest advancements in diagnostic accuracy and patient-centered breast ...

Time April 24, 2025
arrow
News | Artificial Intelligence

March 10, 2025 — Lunit, a provider of AI-powered solutions for cancer diagnostics and therapeutics, has published a ...

Time March 10, 2025
arrow
News | Artificial Intelligence

Feb. 19, 2025 — SimonMed Imaging and HeartLung Technologies have signed a strategic partnership to offer HeartLung's AI ...

Time March 04, 2025
arrow
News | Ultrasound Imaging

Jan. 28, 2025 — GE HealthCare recently announced it has received 510(k) clearance from the United States Food and Drug ...

Time January 29, 2025
arrow
News | Breast Imaging

Jan. 8, 2025 — ScreenPoint Medical has acquiredf Biomediq A/S, a research-based company focused on the research ...

Time January 10, 2025
arrow
News | Breast Imaging

Dec.11, 2024 — iCAD, Inc., a provider of clinically proven AI-powered cancer detection solutions, recently announced ...

Time December 18, 2024
arrow
Subscribe Now