Giotto to Demo Newly Cleared Mammo Systems

In a large retrospective study involving over 523,000 digital breast tomosynthesis (DBT) exams and over one million digital mammography (DM) exams, researchers found that DBT was associated with significantly lower recall rates but showed no advantage over DM in the diagnosis of interval or advanced breast cancer.

Nina Kottler, M.D., chief medical officer of AI at Radiology Partners, discusses, during RSNA 2020, what new developments the annual meeting provided about these technologies, sessions to access, and what to expect in the coming year.

Six reader studies on digital mammography revealed a pooled sensitivity rate of 80.8 percent for stand-alone artificial intelligence (AI) in comparison to 72.4 percent for radiologist assessment while seven historic cohort studies showed a 75.8 percent pooled sensitivity rate for stand-alone AI versus 72.6 percent for radiologist interpretation of digital mammography.

Rich Heller, M.D., with Radiology Partners, and Lucy Spalluto, M.D., with Vanderbilt University School of Medicine, discuss the highlights of their RSNA 2020 session on health disparities, focusing on the underlying factors and challenges radiologists face to providing greater access to care.

While calling for a universal breast cancer risk assessment by the age of 25, the American College of Radiology (ACR) emphasized that ascertaining screening needs prior to the age of 40 is particularly important in high-risk populations such as Black women, who are 42 percent more likely to die from breast cancer in comparison to non-Hispanic White women.

Regardless of experience level, radiologists are likely to be affected by automation bias when utilizing adjunctive artificial intelligence (AI) for mammography interpretation, according to newly published research.