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. [i]
“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.
[i] 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