Ron Blankstein, MD, professor of radiology, Harvard Medical School, explains the use of artificial intelligence to detect heart disease in non-cardiac CT exams.
Compared to standard hip-to-waist ratio measurements and BMI, the algorithm identifies significantly more instances of metabolic syndrome and its severity in individual patients.
A large academic medical center launched a virtual radiology reading room in 2020 to comply with COVID-related social distancing guidelines. Today the room is still something of a hit.
Capping the RSNA 2022 conference in Chicago, an RSNA editorial board has selected a 3D cinematic rendering as the single best radiological image of the year.
Stanford researchers have created synthetic yet highly realistic chest X-rays by customizing an open-source AI model called Stable Diffusion for rendering text as images.
“This type of screening could be used to identify individuals who would benefit from statin medication but are currently untreated," one specialist said. The full analysis will be presented at RSNA 2022 in Chicago.
PET/CT with the common radiotracer 18F-FDG has been found useful for workups and monitoring of infections in real-world hospitalized patients, according to a study conducted by researchers at Yale and Stanford published Nov. 14.
Prior to the final proposal’s release, the American College of Radiology reached out to CMS to offer its recommendations on payment rates for five out of the six the new codes.
