By Aine Cryts
Radiologists looking for an introduction to artificial intelligence software for automated breast ultrasound screening (ABUS) case review at the Radiological Society of North America’s (RSNA) annual meeting should consider a session with Kiyoshi Namba, MD, executive advisor of the Hokuto Breast Center in Japan. RSNA ’19 takes place in Chicago from December 1 to December 6.
Called “AI Deep Learning Radiology in Reviewing ABUS Cases: Presented by GE Healthcare,” the session takes place Sunday, Dec. 1 at 10:30 a.m. In addition to discussing the use of artificial intelligence alongside CAD technology, Namba will provide a review of published literature on CAD performance, insight into improving reading times, and a demonstration of CAD operating on ABUS cases.
Namba will also discuss the diagnostic performance of QViewCAD, the FDA-approved system developed by Los Altos, Calif.-based QView Medical; the software can be used with any currently installed GE Invenia system, according to QView Medical.
Namba tells AXIS Imaging News that his session is appropriate for breast-imaging team members who are interested in the significance and value of ultrasound imaging for women with dense breast tissue.
This technology can help radiologists improve decision-making, lessen fatigue, and enable better patient care for women with dense breasts, according to Namba. In particular, ABUS can be used to image small, node-negative cancers that are missed on mammography in women with dense breasts, he adds.
Attendees will also learn how this technology may provide detection of risky interval carcinoma. That means patients may have to undergo fewer invasive local and/or systemic therapies, and, even more significantly, this technology may save these patients’ lives, Namba tells AXIS.
A study demonstrated that the use of QViewCAD reduced radiologists’ ABUS review time with no decrease in diagnostic accuracy.
Aine Cryts is a contributing writer for AXIS Imaging News.
