iCAD’s ProFound AI Reader Study Published in Radiology: Artificial Intelligence

NASHUA, N.H., Sept. 10, 2019 (GLOBE NEWSWIRE) -- iCAD, Inc. (NASDAQ: ICAD), a global medical technology leader providing innovative cancer detection and therapy solutions, today announced the results of its reader study for ProFound AI™ for Digital Breast Tomosynthesis (DBT) were published in the peer-reviewed journal, Radiology: Artificial Intelligence. ProFound AI for DBT is the first and only FDA-cleared 3D tomosynthesis workflow solution using artificial intelligence (AI) to aid in breast cancer detection. The study showed the concurrent use of ProFound AI increased sensitivity by 8 percent, reduced false positives and unnecessary recalls by 7 percent, and slashed reading time for radiologists by 52.7 percent.¹

“The publication of our reader study results in such a renowned peer-reviewed journal is a significant milestone that further validates ProFound AI as a world-class, deep-learning workflow solution that offers real-world benefits to radiologists and patients alike,” said Michael Klein, Chairman and CEO of iCAD. “This endorsement of our research substantiates ProFound AI as the leading artificial intelligence breast cancer detection technology that empowers clinicians to read DBT images in less time and find cancers earlier, when they may be more easily treated.”

ProFound AI is a high-performing workflow solution that assists radiologists by detecting malignant soft-tissue densities and calcifications. The software rapidly and accurately analyzes each image, or slice, and provides radiologists with crucial information, such as Certainty of Finding lesion and Case Scores, which can assist in clinical decision-making and prioritizing caseloads. Featuring the latest in deep-learning intelligence, the technology allows for continuously improved performance via ongoing software updates.

“While screening with DBT has been shown to increase cancer detection while also decreasing false positive recalls, the exponentially larger number of images in a DBT study compared to 2D screening studies almost doubles the reading time for radiologists,” said principal investigator and lead author, Emily F. Conant, M.D., professor and chief of breast imaging from the Department of Radiology at the Perelman School of Medicine at the University of Pennsylvania in Philadelphia. “This reader study shows that the concurrent use of AI when reading DBT screening studies optimizes efficiency while also improving accuracy.”

The reader study examined the performance of 24 radiologists, including 13 breast subspecialists, reading an enriched set of 260 DBT cases, both with and without ProFound AI. The study found ProFound AI increased radiologist performance, measured by mean area under the receiver operating characteristic curve (AUC), from 0.795 to 0.852. ProFound AI also increased sensitivity from 77.0 percent to 85.0 percent, increased specificity from 62.7 percent to 69.6 percent, and decreased the recall rate for noncancers from 38.0 percent to 30.9 percent. Reading time for radiologists decreased from 64.1 seconds to 30.4 seconds with ProFound AI.

ProFound AI for DBT was FDA cleared, CE marked, and Health Canada licensed in 2018. For more information, visit https://www.icadmed.com/profoundai.html.

Reference:

1. 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

About this study
Case data were retrospectively collected in compliance with the Health Insurance Portability and Accountability Act, with institutional review board approval and waiver of informed consent. The study was financially supported by iCAD and performed by Intrinsic Imaging.

About iCAD, Inc.
Headquartered in Nashua, N.H., iCAD is a global medical technology leader providing innovative cancer detection and therapy solutions. For more information, visit www.icadmed.com.

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