ProFound AI Risk offered higher accuracy than Tyrer-Cuzick
v8 for all women, regardless of menopausal status, breast density, and family
history of breast cancer


NASHUA, N.H., April 4, 2023 – iCAD, Inc. (NASDAQ: ICAD), a global medical
technology leader providing innovative cancer detection and therapy solutions, today
announced new clinical evidence published in the Journalof Clinical Oncology found ProFound AI® Risk for 2D Mammography
is more accurate than Tyrer-Cuzick v8, a commonly used lifestyle risk model,
for both short-term and long-term risk assessments.[1]


“The clinical value of ProFound AI Risk is unparalleled,
and this exciting research adds to the growing body of evidence that confirms iCAD’s
technology is not only more personalized than traditional lifestyle risk
models, but also more accurate,” said Dana Brown, President and CEO of iCAD,
Inc. “Breast cancer is the most common cancer in women worldwide and the second
leading cause of cancer death among women in the U.S., but early detection and
diagnosis are a key part of transforming the patient journey and quality of
ProFound AI Risk provides clinicians with superior insights that can empower
them to tailor a woman’s breast screening regimen and potentially identify
cancers earlier. This is truly game changing technology with life-changing


Using the unique KARolinska MAmmography Project for Risk
Prediction of Breast Cancer (KARMA) screening cohort, researchers compared ProFound
AI Risk with Tyrer-Cuzick v8 in a case-cohort study of 8,604 women aged 40-74
years throughout a 10-year follow up. ProFound AI Risk offered higher accuracy than Tyrer-Cuzick v8
for all women – regardless of menopausal status, breast density, and family
history of breast cancer – with an area under the curve (AUC) ranging from 0.74-0.65
for ProFound AI Risk, compared to 0.62-0.60 for Tyrer-Cuzick v8.


“This research shows that an image-based risk model can
identify high-risk women who may benefit from additional screening or risk
reducing intervention. The tool is designed to help clinicians potentially
catch cancer sooner, when it is more easily treated or prevented. Both the
National Institute for Health and Care Excellence (NICE) and US Preventive
Services Task Force (USPSTF) clinical guidelines recommend risk-reducing
interventions or more intense screening for women determined to have high risk
on the basis of the 10-year or lifetime risk of breast cancer. With ProFound AI
Risk, clinicians can now do this with even greater accuracy,” said lead researcher,
Mikael Eriksson, PhD, Karolinska Institutet. “It is also worth noting that ProFound
AI Risk offered higher accuracy than Tyrer-Cuzick for women with both dense and
non-dense breasts. Given that screening sensitivity for women with extremely
dense breasts is approximately 50% compared with approximately 90% in women
with almost entirely fatty breasts,[4],[5]
ProFound AI Risk may help clinicians overcome the challenging task of detecting
a tumor masked by dense tissue by identifying women who may benefit from
supplemental screening following a negative or benign screen.”


iCAD’s Breast AI Suite offers a 360-degree solution of
clinically proven cancer detection, density assessment, and risk evaluation technologies.
The latest addition to iCAD’s Breast AI Suite, ProFound AI Risk, is the world’s
first clinical decision support tool that provides an accurate short-term
breast cancer risk estimation that is truly personalized for each woman, based
only on her mammogram.[6],[7]
Available for both 2D and 3D mammography, it uniquely combines age, breast
density and subtle mammographic features, offering superior performance and
accuracy in assessing short-term risk compared to traditional, commonly-used
breast cancer risk models. ProFound AI Risk complements traditional risk models
and is easy for clinicians and medical facilities to adopt, as it only requires
the images from a 2D or 3D mammogram, with no questionnaires, portals, or staff
required to implement.


“Physicians have traditionally estimated breast cancer
risk by examining the patient’s known risk factors, such as family history, but
about 85% of breast cancers occur in women who have no family history of breast
added Ms. Brown. “With ProFound AI Risk, patient care has never been more
personalized. By empowering radiologists with more information about a woman’s
individual risk, they can tailor breast cancer screening and maximize
mammography’s effectiveness, which ultimately leads to finding cancer sooner,
reducing costs to the overall healthcare system, and most importantly, saving


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


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 and on the SEC’s website at





Media Inquiries:

Jessica Burns, iCAD



Investor Inquiries:

iCAD Investor


[1] 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:

Arnold M, Morgan E, Rumgay H, Mafra A, Singh D, Laversanne M, et al. Current
and future burden of breast cancer: global statistics for 2020 and 2040 Breast,
Published online 2 September 2022;

American Cancer Society. Key Statistics for Breast Cancer. Accessed via,decline%20of%2043%25%20through%202020.

[4] Boyd
NF, Martin LJ, Yaffe MJ, et al: Mammographic density and breast cancer risk:
Current understanding and future prospects. Breast Cancer Res 13:223-312, 2011.

[5] Huo
CW, Chew GL, Britt KL, et al: Mammographic density—A review on the current
understanding of its association with breast cancer. Breast Cancer Res Treat
144:479-502, 2014.

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

[7] Eriksson
M, Czene K, Strand F et al. Identification of Women at High Risk of Breast
Cancer Who Need Supplemental Screening. Radiology. 2020 Sept 8,

[8] Breast
Cancer Facts and Statistics. Accessed 3/29/23 via