Diagnostic Imaging's Weekly Scan: December 4-December 10
Catch up on the top radiology content of the past week.
Diagnostic Imaging's Weekly Scan is your chance to catch up on the latest radiology content, from new research and device news to the latest case quizzes and conference reports. Review the slideshow below to see this week's top content:
Click the arrows above to view top radiology content from the past week.
Can AI Improve the Consistency of Breast Density Assessment by Radiologists?
In a recent video interview, Susan Holley, MD discussed key findings from a large retrospective longitudinal study, presented at the recent Radiological Society of North America (RSNA) conference, which found that an emerging artificial intelligence (AI) model was over 24 percent more consistent than radiologist assessment of breast density. WATCH NOW
Study Assesses PET Agent for Detecting Pelvic Lymph Node Metastases in Patients with Prostate Cancer
For patients recently diagnosed with prostate cancer, the emerging positron emission tomography (PET) agent 18F-rhPSMA-7.3 reportedly has a 96 percent specificity rate for detecting pelvic lymph node metastases, according to Phase 3 study results recently presented at the 22nd Annual Scientific Meeting of the Society of Urologic Oncology (SUO). READ MORE
New AI Modality Gets FDA Nod for Detecting Aortic Atherosclerosis and Ectasia on Chest X-Rays
One study shows use of the Aorta-CAD cloud-based software led to a 62 percent reduction of missed aortic calcification that suggested aortic atherosclerosis. READ MORE
Large Multinational Study Shows Link Between CT Radiation Exposure and Brain Cancer in Children and Young Adults
In a new study based on five- to six-year follow-up data from over 650,000 children and young adults who had at least one computed tomography (CT) exam prior to the age of 22, researchers found a "strong dose-response relationship" between increased CT radiation exposure and brain cancer. READ MORE
Emerging Insights on Improving Radiology Workflows
In a recent video interview from the Radiological Society of North America (RSNA) conference, Tessa Cook, MD, PhD discussed new research on automated de-identification in radiology reports and the potential of artificial intelligence (AI) and natural language processing (NLP) to help address time-consuming challenges in the radiology workflow. READ MORE
