The American College of Radiology (ACR) submitted comments Aug. 12 to CMS indicating its support for reducing administrative burden through the Patients over Paperwork initiative.

New research suggests screening kids for cervical spine injury (CSI) risk factors could reduce unnecessary CT scans by 50%, significantly limiting radiation exposure.

“Substantial differences in report structure, content, length, and degree of detail provided by different radiologists can be a source of confusion and frustration for referrers and patients," wrote authors of a new study published in the American Journal of Roentgenology.

Parents of pediatric radiology patients value speed over all other aspects of radiology results reporting, according to findings from a new survey published Aug. 14 in Academic Radiology.

When radiologists have complete imaging histories of their patients they are more likely to provide better interpretations, but such information is often incomplete and inconsistent.

A fully automated algorithm can accurately detect microcalcification clusters in mammogram scans and may help reduce radiology workloads.

Deep learning can be used to triage cancer-free mammograms and improve the efficiency of radiologists, according to an Aug. 6 feasibility study published in Radiology.

“For radiologists, who generally perform routine activities, involvement in clinical trials increases their workload and raises human resources issues at hospitals which are already running chronic medical deficits,” wrote authors of a new study published in the European Journal of Radiology.

A deep learning platform created by researchers at the Dana-Farber Cancer Institute can identify cancer in radiology reports as well as clinicians, but in a fraction of the time, according to new research published July 25 in JAMA Oncology.

Clinical decision support (CDS) tools can improve the appropriateness scores of advanced imaging orders when used in clinical practice, according to a single-center analysis published in the American Journal of Roentgenology.

A newly created three-dimensional (3D) neural network can improve the detection of pulmonary nodules on CT scans, according to a study published July 12 in PLOS ONE. 

The updated LR-5 criteria for Liver Imaging Reporting and Data System (LI-RADS) version 2018 can improve sensitivity for diagnosing small hepatocellular carcinomas (HCC) compared to LI-RADS 2017.