News | Artificial Intelligence | March 26, 2019

iCAD Reports Strong Momentum of ProFound AI for Digital Breast Tomosynthesis

Radiology centers across the U.S. report decreased reading time for breast tomosynthesis exams

iCAD Reports Strong Momentum of ProFound AI for Digital Breast Tomosynthesis

March 26, 2019 — iCAD Inc. reported strong adoption of its latest deep-learning, cancer detection software solution for digital breast tomosynthesis (DBT), ProFound AI. The artificial intelligence (AI)-powered solution delivers critical benefits to radiologists, their facilities and patients in identifying cancer earlier.

“ProFound AI for DBT is like having another radiologist right there in the reading room with you,” said Randy Hicks, M.D., MBA, radiologist, co-owner and CEO at Regional Medical Imaging, Flint, Mich. “It’s software you can trust to help diagnose cancers and improve workflow, keeping physicians on track and enabling them to read cases more quickly.”

Since the product was launched in the United States in December 2018, ProFound AI has been adopted by a significant number of high-profile hospitals and imaging centers in all major geographic areas of the country, according to iCAD.

ProFound AI is a high-performance, deep-learning, breast cancer detection and workflow solution for DBT delivering critical benefits to radiologists, their facilities and their patients through the improvement of cancer detection rates by an average of 8 percent and decreasing unnecessary patient recall rates by an average of 7 percent. The new technology has been trained to detect malignant soft-tissue densities and calcifications. It also provides radiologists with scoring information representing the likelihood that a detection or case is malignant based on the large dataset of clinical images used to train the algorithm.

“Following our recent implementation of ProFound AI from iCAD, we have already recognized the value and benefits it is providing to us in reading our DBT studies. Our radiologists appreciate this compelling technology and the high sensitivity and specificity it delivers in identifying lesion markings. It is imperative for us to continue providing the community with the best technology available to detect breast cancer, and our use of ProFound AI is indicative of this,” said Harold Tanenbaum, M.D., radiologist, medical director Marine Park Radiology, Brooklyn, N.Y.

In addition to improving clinical performance related to breast cancer detection and false positive rates, study results showed that ProFound AI can reduce radiologists’ reading time by more than 50 percent on average. An increase in reading time has been a significant challenge for radiologists when moving from 2-D to 3-D mammography.

“We are proud to be using ProFound AI for DBT to assist our radiology team in providing improved quality patient care. Timing is critical for patients with hidden breast cancers, and the combination of 3-D mammography and iCAD’s ProFound AI software could be life saving,” said John Ervin, imaging director for Hunt Regional Healthcare.

For more information: www.icadmed.com

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Single-slice of the chest CT showing the abnormalities. Arrows indicate the location of the breast mass (red arrow), lymphadenopathy (blue arrow), and a lung nodule (yellow arrow). Arrows not present in experimental display. Image courtesy of Psychonomic Bulletin & Review

Single-slice of the chest CT showing the abnormalities. Arrows indicate the location of the breast mass (red arrow), lymphadenopathy (blue arrow), and a lung nodule (yellow arrow). Arrows not present in experimental display. Image courtesy of Psychonomic Bulletin & Review

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