Emerging research suggests a robust association between pregnancy outcomes and placental measurements assessed via blood oxygen-level dependent magnetic resonance imaging (BOLD-MRI).

While a lack of detail with patient histories is a common challenge in radiology, a dash of humorous perspective can help build a sense of camaraderie among colleagues.

Catch up on the top radiology content of the past week.

Published by the American College of Cardiology, the expert recommendations offer insights on the role of intravascular ultrasound for diagnosing and treating peripheral vascular disease in the lower extremity.

The Maestro Brain Model reportedly provides automated identification, quantification and labeling of brain structures on magnetic resonance imaging (MRI).

Emerging research suggests the machine learning-based DiaBeats algorithm could facilitate early detection of prediabetes or diabetes.

In a new study, researchers examined trends with diversity in the radiology workforce, offering a closer look at the gender, race and ethnic makeup of radiology residency programs and academic faculty.

While recent recommendations from the United States Preventive Services Task Force (USPSTF) to lower lung cancer screening thresholds significantly expanded eligibility for screening tests such as low-dose computed tomography (CT), differences in education, health-care insurance and proximity to health-care facilities continue to be key drivers of racial and socioeconomic disparities limiting access to appropriate preventive care.

What is the diagnosis?

The ProstatID, an adjunctive artificial intelligence software that radiologists can utilize with traditional magnetic resonance imaging (MRI), reportedly measures prostate gland volume, and suggests PI-RADS scoring of suspicious lesions.

Consistently leveling with colleagues, patients and others can promote a relatively straightforward path to optimal goodwill.

Catch up on the top radiology content of the past week.

What is the diagnosis?

Researchers discuss key parameters for the assessment, implementation and post-implementation monitoring of emerging artificial intelligence (AI) tools in radiology practices large and small.

A recent study found the use of an alert and a request for more clinical information in a multisite health system’s electronic health record (EHR) system led to a 12 percent reduction in contrast-enhanced computed tomography (CT) exams per day and a 15.2 percent reduction in orders for CT with contrast media per day.

The Definium 656 HD fixed X-ray system reportedly features enhanced, artificial intelligence (AI)-driven image processing, facilitates radiology workflows, and reduces patient positioning time.

Preliminary research revealed an area under the curve (AUC) of 85 percent for an artificial intelligence (AI) algorithm in diagnosing COVID-19 on initial chest X-rays in comparison to a consensus 71 percent AUC for five radiologists.

Amid a sea of radiology staffing shortages, a global pandemic, and national issues, taking time out for ongoing self-care is more critical than ever to mitigate potential burnout.

Viz.ai said the Viz Subdural Hematoma (SDH) artificial intelligence (AI) algorithm provides automatic detection of acute and chronic subdural hemorrhages, facilitating timely triage and treatment of patients.

Has an overly critical approach from quality assurance committees led to an overly cautious approach in reports from teleradiologists?