Jefferson Radiology is implementing state-of-the-art artificial intelligence software for digital breast tomosynthesis (DBT) to improve cancer detection rates and enhance overall quality of patient care. iCAD ProFound AI is an advanced deep-learning, cancer detection software solution that has been shown to detect more cancers, with fewer unnecessary callbacks, and in less than half the time[1]. Jefferson Radiology is not only the first, but currently the only practice in the state of Connecticut to offer ProFound AI.
“This new technology is revolutionizing breast cancer detection and has improved our workflow efficiency. This means more time with our patients, cancers detected earlier than ever before, and ultimately, better health outcomes for our communities,” said Diana James, MD, Section Chief of Breast Imaging at Jefferson Radiology.
Incredibly powerful, the new software is designed to run while a radiologist is actively performing a study. As the physician reads a case, Profound AI uses the latest in artificial intelligence, paired with pattern recognition technology, to assess each image and help identify potential areas of concern. It does this quickly using its algorithm that is trained with one of the largest 3D datasets available, while providing radiologists with potentially life-saving information, including Certainty of Finding lesion and Case Scores.
“Combined with our highly trained, sub-specialized breast imaging team and our new suite of GeniusTM 3D mammography units – the most advanced 3D mammogram available on the market, Profound AI is the next step towards offering our patients, referring physicians and radiologists the best in breast imaging care,” said Luce Buhl, Sr. Director of Operations at Jefferson Radiology.
The implementation was completed on June 2, 2020, and patients at each of the practice’s nine locations will benefit from this new technology.
- Conant, E. et al. (2019). Improving Accuracy and Efficiency with Concurrent Use of Artificial Intelligence for Digital Breast Tomosynthesis. Radiology: Artificial Intelligence. 1 (4).
