Diagnostic Imaging's Weekly Scan: March 5-March 11

The use of a portable dual-energy X-ray detector in the ICU at one community hospital reportedly facilitated a 37.5 percent decrease in chest CT exams in comparison to the previous three months, according to research presented at the American Society of Emergency Radiology (ASER) meeting in Washington, D.C.

In the third episode of a three-part podcast, Anand Narayan, M.D., Ph.D., and Amy Patel, M.D., discuss the challenges of expanded breast cancer screening amid a backdrop of radiologist shortages and ever-increasing volume on radiology worklists.

Developed with breast ultrasound data from nearly 1,200 women, a model with mixed radiomic and autoencoder features had a 90 percent AUC for diagnosing breast cancer, according to new research.

In the second episode of a three-part podcast, Anand Narayan, M.D., Ph.D., and Amy Patel, M.D., discuss recent studies published by the Journal of the American Medical Association (JAMA) that suggested moving to more of a risk-adapted model for mammography screening.

A machine-learning-based model demonstrated an 87 percent area under the curve and a 90 percent specificity rate for predicting interstitial lung abnormality on CT scans, according to new research.

Geared toward ambulatory use, the HeartKey Rhythm suite reportedly offers enhanced signal clarity and rhythm detection algorithms.