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Predicting Breast Cancer Using Digital Breast Tomosynthesis Screening: A Risk Model

By: Joseph Fanelli
Posted: Monday, July 18, 2022

According to findings presented in Science Translational Medicine, using mammographic features generated from digital breast tomosynthesis screenings combined with an image-based risk prediction model may lead to earlier detection and improved prognosis of breast cancer. Mikael Eriksson, PhD, of the Karolinska Institutet, Stockholm, and colleagues analyzed mammographic features—a patient’s left-right breast difference and age—to determine whether a woman will be diagnosed with an interval cancer or a cancer at the next screening following a negative or benign digital breast tomosynthesis.

“Given the accuracy of the digital breast tomosynthesis risk tool, it has the potential to support radiologists in better identifying women who may benefit from additional or enhanced screening and could facilitate the development of a refined protocol for risk-based breast cancer screening,” the authors said.

In this study, the authors evaluated 805 incidents of breast cancer and a random sample of 5,173 healthy women from a nested case-control study including 154,200 multiethnic women between the ages of 35 and 74. All participants underwent digital breast tomosynthesis screening in the United States between 2014 and 2019.

The median risk follow-up time from digital breast tomosynthesis screening to breast cancer diagnosis was 371 days, and 84% of the cancers were detected by screening. Using the U.S. Preventive Service Task Force guidelines, the authors determined that 14% of the women were at high risk for cancer, which is 19.6 times higher than women at general risk. In the high-risk group of patients, 76% of stage II and III cancer cases and 59% of stage 0 cancer cases were observed.

Disclosure: For a full disclosure of the study authors, visit

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