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"Two U.S. Food and Drug Administration (FDA)-cleared AI algorithms show promise for prioritizing high-risk screening mammograms for same-day diagnostic evaluation, researchers have reported.

A team led by Diana L. Miglioretti, PhD, of the University of California, Davis, found that the tools identified half of all screen-detected cancers while flagging just 2% of exams. The study results were published May 2 in the Journal of the American College of Radiology."

Read here: https://radiologybusiness.com/topics/medical-imaging/womens-imaging/risk-based-screening-strategy-averts-more-breast-cancer-deaths-reduces-false-positives 

October is Breast Cancer Awareness Month. Women over 40 are encouraged to get annual mammograms because early detection is key to beating breast cancer. Artificial Intelligence (AI) is used in many health settings to help determine the results of breast cancer screenings, but is it effective?

Diana Miglioretti, professor and division chief of biostatistics at UC Davis Health, is co-leading a $16 million national study on the role of artificial intelligence in breast cancer screening. Miglioretti will direct the study’s data coordinating center from Sacramento.

See full story here: https://www.medpagetoday.com/radiology/diagnosticradiology/117515 

See the full story here:

https://www.cancer.gov/news-events/cancer-currents-blog/2024/mammogram-false-positives-affect-future-screening?cid=eb_govdel

"Some women who receive a false-positive result on a mammogram may not come back for routine mammograms in the future, according to results from a large study.

Early detection of breast cancer through mammography screening continues to save lives.

In a new Breast Cancer Surveillance Consortium (BCSC) study published in JAMA Oncology, researchers calculated the population attributable risk proportions (PARPs) for advanced breast cancer by race/ethnicity. Using the large BCSC cohort, the study evaluated 904,615 women aged 40 to 74 (with a median age of 57 years) undergoing 3,331,740 annual or biennial screening mammograms. The study found that regular screening is not always sufficient to prevent an advanced breast cancer diagnosis.

The Breast Cancer Surveillance Consortium (BCSC) has extended its version 2 invasive breast cancer risk model to include body mass index (BMI), second-degree family history of breast cancer, and age at first live birth. The new version 3 model estimates a woman’s five- and ten-year risk of developing invasive breast cancer based on her age, race and ethnicity, first- and second-degree family history, breast density, history of benign breast biopsy, BMI, and age at first live birth.

In a new Breast Cancer Surveillance Consortium (BCSC) study published in the Journal National Cancer Institute, researchers evaluated whether screening breast MRI plus mammography improves screening outcomes compared to MRI or mammography alone for women with dense versus nondense breasts. Using the large BCSC cohort, the study evaluated 52 237 women aged 40-79 years who underwent 2611 screening MRIs alone and 6518 supplemental MRI plus mammography.