Diagnostic Imaging's Weekly Scan: September 3-September 9

Photon-counting CT fat fraction evaluation offered a maximum sensitivity of 81 percent for detecting steatosis and had a 91 percent ICC agreement with MRI proton density fat fraction assessment, according to new prospective 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.

The Kaiser score offers 24 percent higher pooled specificity than the Breast Imaging Reporting and Data System (BI-RADS) for detecting malignancies on breast MRI, according to a 29-study meta-analysis.

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.

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.

While DCE MRI was deemed helpful in over 67 percent of cases in which it was used, researchers found that monitored prostate MRI exams, which facilitated a 75 percent reduction of DCE MRI sequences, had comparable sensitivity for prostate cancer as non-monitored exams.