National Mammography Day: A Closer Look at Recent Studies and Breast Cancer Screening

While recalls initiated by one of two reviewing radiologists after screening mammography were nearly 10 percent higher than recalls initiated by an AI software, the AI-initiated recalls had an 85 percent higher positive predictive value for breast cancer, according to a new study.

In the third episode of a three-part podcast, Anand Narayan, M.D., Ph.D., and Amy Patel, M.D., discuss the challenges of expanded breast cancer screening amid a backdrop of radiologist shortages and ever-increasing volume on radiology worklists.

Researchers found that a higher waist-to-hip ratio in midlife was associated with higher mean diffusivity in 26 percent of total white matter tracts in the cingulum as well as the superior and inferior longitudinal fasciculus.

In the second episode of a three-part podcast, Anand Narayan, M.D., Ph.D., and Amy Patel, M.D., discuss recent studies published by the Journal of the American Medical Association (JAMA) that suggested moving to more of a risk-adapted model for mammography screening.

In a study involving over 24,000 women, two-thirds of whom had dense breasts, adjunctive AI led to a significantly higher rate of cancer detection for breast radiologists with no difference in recall rates.

The use of ivonescimab was correlated with a median 5.3-month improvement in progression-free survival (PFS) over pembrolizumab in patients with PD-L1 positive non-small cell lung cancer, according to CT and MRI findings from a phase 3 randomized multicenter trial.