Siemens joins digital mammography field with Novation

For women with intermediate risk and a personal history of breast cancer, an emerging AI system offered an 81 percent AUC for breast cancer detection, according to new research.

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 a study of over 463,000 women who had screening mammography exams, adjunctive AI led to a 17.6 percent higher detection rate for breast cancer and a three percent increase in positive predictive value for recalls.

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 patients with PI-RADS 3 lesion assessments, the combination of AI and prostate-specific antigen density (PSAD) level achieved a 78 percent sensitivity and 93 percent negative predictive value for clinically significant prostate cancer (csPCa), according to research presented at the Radiological Society of North American (RSNA) conference.

Emerging research from the RSNA conference suggests that two-dimensional mammography would only detect 41 percent of detectable breast cancer.