AI-Assisted Imaging Tool for Breast Cancer Could Tailor Screening for Women According to Individual Risk

NEW YORK, Sept. 10, 2026 /PRNewswire/ -- An artificial intelligence model that analyzes women's past and recent annual 3D mammograms is more effective at predicting five-year risk of developing breast cancer than a tool that uses only the most recent, single 3D mammogram, as well as an AI model that analyzes 2D mammograms, a new study shows.

Researchers at NYU Langone Health and its Perlmutter Cancer Center developed the deep-learning tool, called NYU-DRP, using a woman's 3D mammograms taken over multiple years, also known as longitudinal digital breast tomosynthesis (longitudinal DBT).

Published in the American Journal of Roentgenology online Aug. 12, the study showed that NYU-DRP was superior to other test models at predicting a woman's risk of breast cancer after five years, correctly ranking those at higher risk 72 percent of the time. Single DBT and AI-assisted 2D testing correctly predicted higher-risk cases 70 percent and 68 percent of the time, respectively.

"Our study shows how AI models like NYU-DRP can be used to reliably determine a woman's future risk of breast cancer based on existing 3D mammograms, which hold information on how the breast tissue has changed across multiple screenings over time," said study lead investigator Yanqi Xu, PhD, a postdoctoral research fellow in the Department of Radiology at NYU Grossman School of Medicine and Perlmutter Cancer Center.

NYU-DRP was created from 313,531 yearly 3D mammograms from 161,165 women without breast cancer who had tests performed at NYU Langone hospitals between 2016 and 2020.

When researchers compared NYU-DRP with a widely used tool for measuring a woman's lifetime risk of breast cancer, called the Tyrer-Cuzick risk assessment, NYU-DRP was again more effective, correctly predicting who was at higher risk after five years 67 percent of the time, while Tyrer-Cuzick accurately predicted five-year risk 56 percent of the time.

Tyrer-Cuzick does not involve AI or mammogram scans, instead relying on personal and family medical information, such as age, genetic mutations, and breast density, backed up by biopsy results. To see whether NYU-DRP or Tyrer-Cuzick performed better, the researchers compared results for 432 women, half of whom were carefully matched to women of similar age and background who did or did not develop breast cancer after five years.

Less than 3 percent of women tested during the study, which ended in 2025, developed breast cancer, the researchers noted.

Among the study's other findings was that breast density alone did not correspond to a woman's predicted risk. Dense breast tissue is known to heighten cancer risk. In women with extremely dense breasts, the NYU-DRP model classified 37.6 percent as having average risk, while actual cases after five years were 0.7 percent. By contrast, the NYU-DRP model identified 15.5 percent of women with less dense, fatty breasts as high risk, with actual cases after five years at 2.5 percent.

"Our findings demonstrate that repeated 3D mammograms contain information about a woman's future breast cancer risk that is not fully captured by either breast density or a single mammogram on its own," said study senior investigator Yiqiu "Artie" Shen, PhD, an assistant professor in the Department of Radiology at NYU Grossman School of Medicine and Perlmutter Cancer Center.

"If future experiments in other women with breast cancer prove successful, then AI-assisted 3D mammograms like NYU-DRP could help physicians better tailor screening to a woman's actual risk, by identifying those women who may benefit from additional screening while avoiding unnecessary supplemental tests for those at lower risk," said study co-investigator Laura Heacock, MD, an associate professor in the Department of Radiology at NYU Grossman School of Medicine and Perlmutter Cancer Center.

Dr. Shen said that the team next plans to use the longitudinal DBT program to track women's breast health proactively, observing how the tool impacts their health and who develops breast cancer. They also plan to share and cross-check the tool with data from other academic health centers, as well as data from different 3-D mammogram manufacturers. All the testing performed as part of the current study used only breast imaging equipment manufactured by Hologic Inc. of Marlborough, Massachusetts.

An estimated 1 in 8 women in the United States will be diagnosed with breast cancer in their lifetime, with approximately 382,640 women diagnosed with the disease in 2026. However, the five-year relative survival rate is over 99 percent when breast cancer is caught in its earliest stages. Recent advances in early detection and treatment have increased survival rates; there are currently over 4 million breast cancer survivors in the United States.

Experts now recommend annual mammography screening for breast cancer beginning at age 40. More than 43 million mammograms were performed in 2025 alone.

Funding support for this study was provided by National Science Foundation grant 1922658, National Institutes of Health grant R01EB036530, the Milstein Pilot Project Fund, the Shifrin-Myers Breast Cancer Discovery Fund, and the Manhasset Women's Coalition Against Breast Cancer.

Besides Drs. Xu, Shen, and Heacock, other study co-investigators were Jungkyu Park, PhD; Felicia Pasadyn, MA; Qi Lei, PhD; Alana Lewin, MD; Krzysztof Geras, PhD; Linda Moy, MD; and Freya Schnabel, MD.

STUDY DOI
10.2214/AJR.26.34951

STUDY LINK
https://www.ajronline.org/doi/10.2214/AJR.26.34951

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SOURCE NYU Langone Health System