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Pairing multispectral optoacoustic tomography with ultrasound provided biomarker information that may better diagnose patient's with autoimmune diseases and thyroid nodules.

In total, the groups released seven updated practice parameters that describe recommended procedures and considerations to safely administer radiation depending on practice area.

The commercially available algorithm helped residents improve their sensitivity at spotting abnormal findings in chest x-rays.

“Leaders in radiology, like leaders everywhere, must make clear that harassing behaviors will not be tolerated and that those who have committed harassment will be held accountable,” wrote authors of a new study published in JACR.

“Given the large number of people who suffer from traumatic brain injury every day and are rushed to the emergency department, this has very big clinical importance," study authors said.

BI-RADS 4 lesions are considered among the most difficult and suspicious category of breast lesions.

“With the ability to understand each of the different domains and translate between the experts in these domains, imaging informaticists are now essential players in the development, evaluation and deployment of AI in the clinical environment.”

Manufacturers, hospitals, physicians and patient advocates have put significant marketing resources—including millions of dollars—into selling 3D mammograms to women, despite little evidence the modality is better than traditional mammography.

The number of vacant radiographer positions that are actively being recruited has risen, with many disciplines reaching their highest marks in more than a decade, according to new research from ASRT.

Using the quiet protocol reduced noise levels and improved imaging success rates compared to conventional MRI, according to authors of a new study published in Academic Radiology.

“A better understanding of how age and comorbid conditions affect mammography use may help target specific populations and improve use of preventive care," wrote Cindy Yuan, MD, PhD, with the University of Chicago’s Department of Radiology, and colleagues.

Trained on nearly 1 million screening mammography images, researchers from New York University found their algorithm could push radiologists’ ability to accurately identify breast cancer to nearly 90%.