Deep learning techniques have shown potential to change cardiac MRI forever, according to a new analysis published in the American Journal of Roentgenology. However, the authors wrote, it is also important to remember deep learning’s current limitations.

RadNet has announced a new partnership with Santa Clara, California-based Whiterabbit.ai to improve mammography screening rates and breast cancer care through the use of AI and other advanced technologies.

If such technology is made available commercially, it could revolutionize magnetic resonance imaging, noted Stephan Anderson, a Boston Medical Center radiologist and BU School of Medicine professor of radiology. 

The updated guidelines suggest clinicians screen adults ages 50-75 who are at average risk for the disease, and discuss the benefits, harms and costs of the three screening methods prior to undertaking any one procedure.

The algorithm can also reduce imaging time and improve the patient experience.

Clariscan is a gadolinium-based agent indicated for IV use in brain, spine and associated tissues to help detect areas with disruption of the blood brain barrier, or abnormal vascularity.

Healthcare technology is constantly changing, something radiologists know all too well. And while some within the specialty have expressed fear or concern over the continued rise of AI, a new commentary in Clinical Radiology noted that it’s all par for the course—and radiologists must rise to the occasion yet again.

A new AI algorithm developed by researchers at Case Western Reserve University can predict which malignant breast cancers will progress and benefit from additional treatment.