NCI mulls genetic risk of prostate, breast cancer

While standalone AI interpretation offered over 10 percent higher sensitivity than radiologists for patients undergoing post-mastectomy surveillance mammography, it missed over 30 percent of breast cancers.

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 recently presented at the American College of Cardiology (ACC) conference, researchers found that novice use of AI-guided cardiac ultrasound after an AI-enabled electrocardiogram increased the positive predictive value for reduced left ventricular ejection fraction (LVEF) or aortic valve stenosis by 33 percent.

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 review of over 1,630,000 office-based non-breast imaging Medicare fee-for-service (FFS) claims from 2022, researchers found that 39.5 percent of nuclear medicine imaging were interpreted by ordering clinicians.

New multicenter research suggests that radiomic features derived from breast MRI may enhance prognostic capabilities with disease upstaging for ductal carcinoma in situ (DCIS).