iCAD’s ProFound AI Breast Suite Wins U.S. General Services Administration’s AI Healthcare Challenge Award

NASHUA, N.H., May 18, 2023 (GLOBE NEWSWIRE) -- iCAD, Inc. (NASDAQ: ICAD), a global medical technology leader providing innovative cancer detection and therapy solutions, today announced its ProFound AI^® Breast Suite is a winner of the U.S. General Services Administration’s (GSA) “AI Healthcare Challenge” award. iCAD presented its portfolio of breast cancer detection, density assessment and risk evaluation solutions at the competition, focused on improving health outcomes in a range of areas, including using AI to detect cancers earlier and improve outcomes.

“It is an honor for iCAD’s technology to be recognized as a winner of this challenge, as it is further testament to the unique value our ProFound AI Breast Suite offers to both clinicians and patients. Our detection solution is already trusted by our government and military, as last year the U.S. Department of Defense (DoD) determined it met the DoD’s stringent cybersecurity prevention thresholds and granted the technology an Authorization to Operate (ATO), allowing its use in DoD healthcare facilities, which care for military servicemembers, retirees and family members,” said Dana Brown, President and CEO of iCAD, Inc. “With unrivaled accuracy, performance and speed, ProFound AI is revolutionizing breast cancer screening and detection, leading to a better experience for both patients and their radiologists. Our density and risk evaluation solutions further personalize screening by providing clinicians and their patients with a more holistic view of their breast health and individual risk of developing breast cancer. With breast cancer affecting one in eight women during their lifetime,¹ it is essential for women to have access to this technology, as it is clinically proven to improve cancer detection and reduce false positives and unnecessary callbacks, which can be stressful for women.”

Built with the latest in deep-learning AI, ProFound AI rapidly analyzes each 3D mammography image, detecting both malignant soft tissue densities and calcifications with unrivaled accuracy. With up to 2x the clinical performance improvement for radiologists compared to leading competitors, ProFound AI was clinically proven in a large reader study to increase radiologist sensitivity by an average of 8%, increase specificity by 7%, reduce recall rate in non-cancers by 7.2%, and slash reading time by 52.7%.^2,3

In a clinical study, ProFound AI Risk for 3D Mammography was up to 2.4 times more accurate for short-term risk assessments than traditionally used risk models, such as Gail and Tyrer-Cuzick.⁴ ProFound AI Risk for 2D Mammography is more accurate than Tyrer-Cuzick v8 for both short-term and long-term risk assessments.⁵ In a clinical study, ProFound AI Risk for 2D Mammography accurately identified 20% of breast cancers as high-risk, compared to 7.1% for Tyrer-Cuzick.⁵ iCAD’s Density Assessment solution aids in accurate and consistent density-based stratification and reporting and offers the highest matching accuracy for dense and non-dense assessment on the market.⁶

The GSA launched the Applied AI Healthcare Challenge earlier this year as a prize competition seeking diverse and practical solutions to help federal agencies provide the highest level of medical care. The challenge awarded four grand prizes of $25,000 each for winning prototypes, for a combined sum of $100,000. iCAD was also featured as part of the Cancer Focus Area at the Applied AI Healthcare Challenge Industry Day on May 2, where 10 industry vendors were selected out of 53 entrants to discuss their technologies at the event.

“For more than two decades, our innovative artificial intelligence solutions have empowered providers and professionals to accurately, reliably, and quickly detect cancer and improve outcomes – optimizing every patient’s opportunity to live longer, better lives. Some of the most prestigious academic hospitals and imaging centers around the world trust our technology to detect cancer sooner, and with greater accuracy,” said Ms. Brown. “We remain steadfast in our mission to create a world where cancer can’t hide by offering the most pervasive and personalized breast AI technologies, and we look forward to continuing to expand access to this technology and enhancing care for more women worldwide.”

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

Forward-Looking Statements                                    
Certain statements contained in this News Release constitute “forward-looking statements” within the meaning of the Private Securities Litigation Reform Act of 1995, including statements about the expansion of access to the Company’s products, improvement of performance, acceleration of adoption, expected benefits of ProFound AI^®, the benefits of the Company’s products, and future prospects for the Company’s technology platforms and products. Such forward-looking statements involve a number of known and unknown risks, uncertainties and other factors which may cause the actual results, performance, or achievements of the Company to be materially different from any future results, performance, or achievements expressed or implied by such forward-looking statements. Such factors include, but are not limited, to the Company’s ability to achieve business and strategic objectives, the willingness of patients to undergo mammography screening in light of risks of potential exposure to Covid-19, whether mammography screening will be treated as an essential procedure, whether ProFound AI will improve reading efficiency, improve specificity and sensitivity, reduce false positives and otherwise prove to be more beneficial for patients and clinicians, the impact of supply and manufacturing constraints or difficulties on our ability to fulfill our orders, uncertainty of future sales levels, to defend itself in litigation matters, protection of patents and other proprietary rights, product market acceptance, possible technological obsolescence of products, increased competition, government regulation, changes in Medicare or other reimbursement policies, risks relating to our existing and future debt obligations, competitive factors, the effects of a decline in the economy or markets served by the Company; and other risks detailed in the Company’s filings with the Securities and Exchange Commission. The words “believe,” “demonstrate,” “intend,” “expect,” “estimate,” “will,” “continue,” “anticipate,” “likely,” “seek,” and similar expressions identify forward-looking statements. Readers are cautioned not to place undue reliance on those forward-looking statements, which speak only as of the date the statement was made. The Company is under no obligation to provide any updates to any information contained in this release. For additional disclosure regarding these and other risks faced by iCAD, please see the disclosure contained in our public filings with the Securities and Exchange Commission, available on the Investors section of our website at http://www.icadmed.com and on the SEC’s website at http://www.sec.gov.

Contact:

Media Inquiries:
Jessica Burns, iCAD
+1-201-423-4492
jburns@icadmed.com

Investor Inquiries:
iCAD Investor Relations
ir@icadmed.com

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¹ American Cancer Society. Key Statistics for Breast Cancer. Accessed via https://www.cancer.org/cancer/breast-cancer/about/how-common-is-breast-cancer.html
² FDA 510K submissions K182373, K201019, K193229 https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm. Accessed 1-19-22.
³ 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
⁴ Eriksson, M et al. A risk model for digital breast tomosynthesis to predict breast cancer and guide clinical care. Science Translational Medicine. 14 (644). 2022 May 11. Accessed via DOI: 10.1126/scitranslmed.abn3971.
⁵ Eriksson M, CzeneK , Vachon C, Conant E, Hall P. Long-Term Performance of an Image-Based Short-Term Risk Model for Breast Cancer. Journal of Clinical Oncology. DOI: 10.1200/JCO.22.01564.
⁶ iCAD data on file.