Radiology

Researchers have developed a natural language processing based model, which utilises information from radiology reports to accurately identify patients with suspected pulmonary embolism in the emergency department.

Researchers at Johns Hopkins University, Baltimore, Maryland, USA, have investigated muscle loss as a risk factor of heart failure, emphasising the underexplored association between thigh muscle measurements and heart failure.

Deep learning methods have the potential to improve clinical strategies for addressing ultrasound Breast imaging-reporting and data system 4A lesions, according to recent research.

New research has shown that CT may be the preferred method for treating obstructive coronary artery disease in younger patients, being less invasive than ICA.

Artificial intelligence was an integral part of this year’s European Congress of Radiology, in Vienna, Austria, and this was showcased in a captivating plenary lecture, on the second day of Congress.

New research suggests that annual breast cancer screening starting at age 40 years, and continuing to age 79 or older, results in the highest reduction in mortality with minimal risks.

Recent studies have suggested that augmented reality may help radiologists perform safer and more efficient CT-guided ablations. AR has the ability to merge virtual 3D objects seamlessly with the real-world environment.

Research suggests that, in comparison with EID-CT myelograms, photon-counting detector CT myelography could facilitate earlier diagnosis of spontaneous intracranial hypotension, showing higher image quality.