The computer-aided detection system is designed to use VuComp’s proprietary computer vision algorithms (M-Vu Algorithm Engine) to identify areas of mammograms consistent with breast cancer.
The submission includes both clinical validation and internal software testing that compares computer-aided detection performance of DBT and digital radiography (DR) images to DR images alone.
"This important PMA submission demonstrates our continued focus on developing the most advanced technologies for the early detection of breast cancer, as well as providing radiologists with tools that will impact their diagnostic confidence," said Jim Pike, the company’s chief technology officer. “By being the first company to submit a PMA for computer-aided detection for breast tomosynthesis, VuComp once again stakes its claim as the market leader.”
According to data cited by the company, use of computer-aided detection with breast tomosynthesis is expected to re-ignite computer-aided detection for the mammography market. Installations of tomosynthesis systems are expected to increase four fold in the United States by 2016. With tomosynthesis adoption continuing to grow, demand for a tool to help the radiologist assess the vast amount of data is expected. Tomosynthesis provides 50 to 100 times as much data as 2-D mammography studies.
Debra Somers Copit, M.D., director of breast Imaging at Einstein Healthcare Network and associate professor of radiology at Jefferson Medical College, in Philadelphia, Pa., commented: “DBT clearly decreases the recall rates for screening mammography and increases invasive cancer detection. Yet, there is a critical role for computer-aided detection not only for the radiologist new to tomosynthesis, but also those who have had more experience, given the vastly increased amount of information presented to the reader.”
Officials with the Plano, Texas-based firm anticipate the launch of their computer-aided detection for tomosynthesis solution no later than the fourth quarter of 2015.