iCAD’s Breast AI Suite Wins U.S. General Services Administration’s AI Healthcare Challenge Award
Company presented portfolio of breast cancer
detection, density assessment and risk evaluation solutions at the competition,
focused on improving health outcomes
NASHUA, N.H., May 18, 2023 – iCAD, Inc. (NASDAQ: ICAD), a global medical
technology leader providing innovative cancer detection and therapy solutions, today
announced its Breast AI 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 winnerof this challenge, as it is further testament to the unique value our
Breast AI Suite offers to both clinicians and patients. Our detection solution,
ProFound AI®, 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 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
Investor Inquiries:
iCAD Investor
Relations
[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.