NASHUA, N.H. and Chicago – December 2, 2019 - iCAD, Inc. (NASDAQ: ICAD), a global medical technology leader providing innovative cancer detection and therapy solutions, today announced it will showcase its Breast Health Solutions suite including the expanded ProFound AI™ platform in the iCAD exhibition booths (#3929 in the south hall and #10716 in the north hall) at the Radiological Society of North America (RSNA) Annual Meeting in Chicago, December 1-6, 2019.

iCAD’s Breast Health Solutions suite includes ProFound AI for Digital Breast Tomosynthesis (DBT), the first artificial intelligence (AI) software for DBT to be FDA-cleared, as well as software solutions for 2D mammography and breast density. During the meeting, the Company will also unveil its vision for future technologies, including solutions that will enable clinicians to more easily consider patients’ prior images* and prospective breast cancer risk assessment over time.*

“ProFound AI has extensive potential in the realm of clinical AI – and in the future it will offer a more holistic clinical approach that can provide clinicians with a broader view of each individual patient’s case, history, and short-term risk,” said Michael Klein, Chairman and CEO of iCAD. “Today, ProFound AI offers clinically-proven improvements in sensitivity, specificity, time-savings and recall rates, but our panoramic vision for the future will include innovative tools that allow physicians to correlate findings across time and provide more tailored and personalized patient care.”


Trained with one of the largest available DBT datasets, ProFound AI rapidly and accurately analyzes each DBT image, or slice, and provides radiologists with key information, such as Certainty of Finding lesion and Case Scores, which assists in clinical decision-making and improving reading efficiency. Featuring the latest in deep-learning artificial intelligence, the algorithm allows for continuously improved performance via ongoing updates.

Clinical data from a large reader study involving ProFound AI for DBT were recently published in Radiology: Artificial Intelligence. According to study findings, ProFound AI for DBT improved radiologist sensitivity by 8 percent, reduced unnecessary patient recall rates by 7.2 percent, and slashed reading time for radiologists by 52.7 percent.1 Additionally, ProFound AI cut reading time by up to 57.4 percent for radiologists reading cases of women with dense breasts.2

Results from a subgroup analysis of this reader study examining improvement in accuracy and reading times for traditional 2D mammography will be presented during the meeting on Sunday, December 1 by 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. According to study findings, ProFound AI improved sensitivity and specificity and reduced reading time for radiologists reading DBT with digital or with synthetic 2D.

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