There were ten artcles in all, including: patient control of breast compression during full-field digital mammography (FFDM), a feature of GE’s Pristina system that recently received FDA approval; the effect of paddle compression on diagnostic performance, with a target pressure of 10 kPa; the use of artificial intelligence (AI) to improve breast cancer detection; improvement of screening outcomes with automated breast ultrasound (ABUS); exploring whether digital breast tomosynthesis (DBT) reduces recall rate; evaluating automated density maps; studying the cost-effectiveness of screening in Poland; comparing contrast-enhanced spectral mammography with MRI in newly diagnosed breast cancers; and considering breast ultrasound from the patient’s perspective.
CapeRay’s CEO Kit Vaughan was invited to submit an article summarising two recent journal papers, one published in Clinical Imaging in 2016 and the other in Diagnostics earlier this year. Entitled “Detecting early breast cancer by integrating full-field digital mammography and automated breast ultrasound,” the article can be accessed by clicking here. Kit first reviewed the evidence to support FFDM followed by ABUS, but then highlighted three drawbacks: the breast is in a different orientation and degree of compression for the separate imaging modalities; the time required is 30 minutes; and considerable capital is needed for two systems.
CapeRay’s dual-modality Aceso system – named after the Greek goddess of healing – accomplishes FFDM using a slot-scanning geometry and a moving X-ray camera, while ABUS is implemented with a linear ultrasound probe. As illustrated above left, acoustic coupling is enhanced by locating both the camera and the probe in a hermetically sealed breast platform filled with mineral oil.
In the first clinical trial one of the volunteers had extremely dense breast tissue and no prior history of breast pathology, as confirmed by the FFDM image (seen at right). However, ABUS clearly identified a lesion and follow-up evaluation revealed a benign cyst. The two clinical trials were based on 83 women – 65 healthy volunteers and 18 patients – and, with a full set of images for each subject gathered in just 10 minutes, demonstrated the potential of an integrated dual-modality system to screen for breast cancer in a busy clinic.