Imaging Informatics

Radiology reports derived from structured brain tumor MRI reporting and data systems (BT-RADS) showed measurable improvements compared to free text reports, according to a new study published in Academic Radiology.

A machine learning algorithm can determine appropriate follow-up imaging based off of radiology reports, according to a new study published in the Journal of Digital Imaging. The technology may eventually be developed to automatically tell if a patient completed their follow-up exam.

Patients would like to maintain some control over what data they share and who they share it with, however, according to results of a new study published in JAMA Network Open.

An audio/visual reporting tool integrated into an emergency department’s musculoskeletal workflow can improve communication between radiologists and referring providers while making imaging findings easier to comprehend.

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.