Diagnostic Imaging

The new agent is manganese-based (Mn-PyC3A) and produces tumor contrast enhancement similarly to that seen when using “state of the art” gadolinium-based contrast agents (GBCAs).

“We hope these results will help test the effectiveness of new therapies for this form of MS and reduce the suffering patients experience,” said lead author of the study published in JAMA Neurology.

There’s a strong case to be made for mammography to become a “dual test” for both breast cancer screening and cardiovascular disease (CVD) prevention, according to a new review published in the European Journal of Radiology.

A neural network model can scour electronic medical record (EMR) data and determine if a patient has imaging-specific pulmonary embolism (PE)—a potential remedy for unnecessary CT imaging, reported authors of a multicenter study published in JAMA Network Open.

The U.S. Preventative Services Task Force (USPSTF) has released a statement recommending against screening for pancreatic cancer in asymptomatic adults.

A new study found that chronic kidney disease (CKD) patients who received IV contrast-enhanced imaging faced no more risk of developing contrast-induced nephropathy than those who did not receive contrast material.

MRI and CT scans of infants exposed to the Zika virus in the womb revealed a range of brain abnormalities, reported authors of a recent study published in JAMA Network Open. The findings place neuroimaging as an important step in evaluating such patients.

"Smoking cessation is very important if these patients want to help themselves and avoid further procedures," authors of the study published in Radiology wrote. "We should urge current smokers to stop smoking before treatment."

The method—dual-energy CT virtual non-calcium (VNCa) imaging—can remove calcium from CT data and produce a quantitative assessment of injuries in the largest and most complex joint in the human body.

"It's important to quantify exposure to ionizing radiation because it can cause cancer and birth defects and should be kept to a minimum, especially during pregnancy," said co-lead author Marilyn L. Kwan, PhD.

A deep learning model that simulates a clinician’s diagnostic process can accurately diagnose Alzheimer’s disease from cognitively normal patients, according to a study published July 16 in Neurocomputing.

“The CXR-risk score took as input the radiograph only. This was intended to prove a point—that a CNN can extract prognostic information embedded in the image, without any other demographic or clinical information,” wrote authors of a new study published in JAMA Network Open.