Imaging Informatics

Treadmill desks have gained popularity in recent years, but how would utilizing one impact a radiologist’s ability to interpret medical imaging results?

Centering a radiology department’s workflow around the electronic health record (EHR) can improve efficiency and make radiologists happy, according to a new study published in Academic Radiology.

Follow-up imaging adherence rates vary based on a number of factors, according to new research published in the American Journal of Roentgenology. The authors noted that closely monitoring such patterns can help providers engage patients and minimize risk.

Researchers at Harvard and several institutions in Italy have shown that clinicians managing neuromuscular conditions receive clinically relevant information more consistently from structured radiology reports than from reports rendered in free text. And the gains are greatest when the reporting radiologist is not deeply experienced.

CT scans and mammograms can reveal valuable information about a patient’s heart health, even if the exam was not specifically ordered for that purpose.

Natural language processing (NLP) could help radiology providers anticipate fluctuations in demand and provide faster patient care, according to a new study published in the Journal of the American College of Radiology.

Analytics-driven worklists can help entire groups of radiologists achieve faster MRI interpretation times, according to new research published in the American Journal of Roentgenology.

Numerous studies have shown that clinical decision support (CDS) can help reduce unnecessary imaging. According to a new study in the American Journal of Roentgenology, however, not enough research has focused on how CDS tools impact less experienced providers such as house staff physicians.

Researchers in Europe have developed an open-source, ready-to-use radiomics calculator based on a burgeoning international standard for radiologists looking to quantify tumor characteristics on CT at the level of molecular biomarkers.   

RBJ asked for—and received—in-depth answers to six high-level questions about data analytics. What all these Q&A sets have in common is the supplying of a fresh insight or two (or three) into tapping data for its power to prove value and bolster the bottom line.

Speech recognition has become a staple software category in radiology over the past three decades, and other medical specialties have adopted it as well. Yet efforts to assess the toolset’s applications and adaptations have been frustrated by the lack of a unified set of metrics.

Middle-aged smokers have smaller gray-matter volumes than their non-smoking peers, and the falloff is especially pronounced in the brains of smokers who also drink alcohol.