Rabin Medical Center (RMC), one of the most prominent and largest medical facilities in Israel, recently initiated a clinical evaluation involving ProFound AI® for Digital Breast Tomosynthesis (DBT) at the
Radiology Department at the Clalit Rabin Medical Center. Owned and operated by Clalit Health Services, RMC is Israel’s largest health maintenance organization, with a capacity of 1,300 beds.
“The workload for radiologists had increased significantly at our facility. With an influx of tomosynthesis images to read through each day, it was clear we needed to implement technology to help with this
extensive amount of data,” according to Prof. Eli Atar, MD, SFIR, Associate Professor of Clinical Radiology, Head of Department of Imaging at Rabin Medical Center. “ProFound AI is now an integral decision support tool that has proven to be a reliable workflow solution to help with physician burnout, accuracy and
efficiency. ProFound AI is a significant breakthrough in breast imaging.”
ProFound AI for DBT is a high-performance, deep-learning workflow solution trained to detect malignant soft-tissue densities and calcifications. ProFound AI became the first 3D tomosynthesis software using artificial intelligence (AI) to be FDA cleared in December 2018; it is also CE marked and has been registered with the Israeli MOH AMAR system.
Built with the latest in deep-learning technology, ProFound AI for DBT rapidly analyzes each tomosynthesis image, detecting malignant soft tissue densities with unrivaled accuracy. Certainty of Finding and Case Scores are relative scores that represent the algorithm’s confidence regarding whether a lesion or case is malignant. These scores provide crucial information for radiologists that aids in clinical decision
making and helps them gain a sense of case complexity, which may be useful for prioritizing the reading worklist.
“We can see the percentage rating of each tumor on the screen, which aids in determining if a suspicious finding needs further workup,” according to Ahuva Grubstain, MD, Head of Breast Imaging Unit, Department of Imaging, Rabin Medical Center, Hasharon, Israel, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel. The software shortens radiologists’ reading times and enables quick and safe decision-making that helps us avoid unnecessary recalls and tests for patients. iCAD has developed an excellent high-level technology. As a radiologist, I can say that this is the first AI product I
have used that enhances my workflow and I trust the results.”
ProFound AI for DBT was clinically proven in a large reader study to reduce reading time for
radiologists by 52.7 percent, improve radiologists’ sensitivity by 8 percent, and reduce the rate of false positives and unnecessary patient recalls by 7.2 percent.1
“The software is reliable. It really knows how to identify benign and malignant tumors, and ranks them correctly, with high accuracy,” added Dr. Grubstain.
iCAD’s Breast Health Solutions suite also includes software to evaluate breast density, ProFound AI for 2D Mammography, and ProFound AI Risk, the world’s first and only clinical decision support tool that provides an accurate two-year breast cancer risk estimation that is truly personalized for each woman, based only on a screening mammogram.
Conant, E. et al. (2019). Improving Accuracy and Efficiency with Concurrent Use of Artificial Intelligence for Digital Breast Tomosynthesis. Radiology: Artificial Intelligence. 1 (4). Accessed via https://pubs.rsna.org/doi/10.1148/ryai.2019180096