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Known to increase fatigue and impact performance, traditional call models for nighttime IR coverage contribute to burnout and gaps in patient care. 

knee x-ray

These new findings may lead to more “judicious use” of corticosteroids in pain management.  

Predictive model helps identify malignancy in thyroid nodules.

Once the model is further validated, it could help guide providers in determining how to manage thyroid nodules. 

Example of the four types of breast tissue density. The density of fibroglandular tissue inside the breast impacts the ability to easily see cancers. Cancers are very easy to spot in fatty breasts, but are almost impossible to find in extremely dense breasts. These examples show craniocaudal mammogram findings characterized as almost entirely fatty (far left), scattered areas of fibroglandular density (second from left), heterogeneously dense (second from right), and extremely dense (far right). RSNA

It is widely agreed that women with dense breast tissue should undergo supplemental imaging in addition to their routine mammogram screening, but the jury is still out on which modality is best for cancer detection in this group. 

Interventional radiologist radiology IR genicular artery embolization surgery. Images courtesy of the University of Chicago Medicine

The resolution urges the AMA to advocate for separate payment for certain services using supplies priced above $500, as well as those containing high-cost equipment. 

Enterprise-wide Advanced Visualization: Maximizing Clinical & Business Benefits

Konica Minolta and NewVue announced their collaboration on cloud-based Exa Teleradiology earlier this week.

Around the web

RadNet Chaiman and CEO Howard Berger, MD, explains why the company has invested tens of millions into DeepHealth to rapidly build up a new business model. 

 

Thanks to AI, clinicians can use mammograms to do a lot more than identify signs of breast cancer. Researchers explored data from nearly 50,000 patients, presenting their findings in Heart.

A new analysis is prompting questions regarding how rigorously many of the AI-enabled tools approved by the U.S. Food and Drug Administration are evaluated prior to their clearance.