Image IQ: 44-year-old Woman, Screening Mammogram

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.

In this podcast, Stephen Rose, MD, president and CEO of Houston Breast Imaging and a principal investigator of the 3-D tomosynthesis clinical trials in 2010, discusses the benefits of the new technology and what his practice learned when implementing the screening program.

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.

In this podcast, Tom Gentile, president and CEO at GE Healthcare Systems, explains that “the whole focus of imaging is moving beyond the quality of the image.” Patient care, physician productivity and reimbursement take on a renewed focus in light of healthcare reform efforts internationally, he says.

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.