Agfa flirts with digital mammography

Patients with Medicaid or means-tested insurance were over 27 percent more likely to miss mammography appointments, and only 65 percent of women with three of more adverse social determinants of health had a mammography exam in a two-year period covering 2020 and 2021, according to new research and a report from the CDC.

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.

In addition to full-field digital mammography and titanium contrast-enhanced mammography capabilities, the Mammomat B.brilliant system also offers ergonomic, workflow and patient comfort benefits.

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.

A proposed alternative to a previously validated deep learning neural network for assessing short-term breast cancer risk, the emerging AsymMirai deep learning mammography-based model showed comparable breast cancer risk prediction with an emphasis on bilateral dissimilarity, according to new research.

For women who have had radial scars detected on digital breast tomosynthesis (DBT) exams, researchers noted a 5 percent upstaging rate to cancer, according to a recent study.