generation of ProFound AI Risk offers greater accuracy and ethnically inclusive
precision screening


provides critical, risk-adaptive solutions for clinicians facing complex
screening challenges presented by the COVID-19 pandemic


N.H. – September 29, 2021 – iCAD, Inc. (NASDAQ: ICAD), a
global medical technology leader providing innovative cancer detection and
therapy solutions, today announced the launch of ProFound AI® Risk for digital
breast tomosynthesis (DBT), or 3D mammography, as well as an updated version of
PowerLook® Density Assessment.
Both technologies offer
improved accuracy and enhanced functionality compared to previous versions of
the software.


ProFound AI Risk is the
world’s first commercially available clinical decision support tool that
provides an accurate[1],[2]
short-term breast cancer risk estimation that is truly personalized for each
woman, based only on a 2D or 3D mammogram. The latest generation of PowerLook
Density Assessment is the world’s first and only multi-vendor deep learning
automated breast density assessment algorithm using synthetic images generated
from 3D mammography.


“ProFound AI Risk and
PowerLook Density Assessment have the potential to truly transform personalized
breast cancer screening and risk stratification as we know it,” said Stacey
Stevens, President of iCAD, inc. “We believe these technologies will lead to more
appropriate utilization of supplemental imaging and biopsies, less anxiety for
women, and decreased costs to the system overall. We believe these solutions
will be increasingly relevant in the years ahead, as mammography begins to transition
from what is primarily an age-based screening paradigm today to a more
effective and efficient risk-adjusted screening paradigm.”


ProFound AI Risk


The latest generation of ProFound AI Risk offers the ability to
calculate a short-term risk estimation for 3D mammography, with greater
accuracy compared to both the previous version of the risk software based on 2D
mammography and traditionally used risk models. The latest version of ProFound
AI Risk offers expanded features, including: 

  • The ability to calculate short-term
    (one-, two- or three-year) absolute risk based on either 2D or 3D mammography
  • The ability to factor in
    clinically relevant global screening guidelines and more than 15 country
    incidence and mortality reference tables, including ethnicities, for alignment
    with that country’s general population.

“Factoring in a woman’s racial and ethnic background adds another
dimension of personalization that allows clinicians to stratify risk in a more
inclusive way,” added Stevens. “Studies show
African American women have an approximately 40% higher risk of dying
from breast cancer, and they are disproportionately affected by more aggressive subtypes,
such as triple-negative breast cancer and inflammatory breast cancer, compared to
white women.[4],[5],[6] The latest generation of ProFound AI Risk offers the potential to include racial and ethnic backgrounds for further refinement of the image-based model, as well as the incidence and mortality rates for a specific geographic region.”


ProFound AI Risk utilizes breast complexity findings, automated breast
density and age in order to calculate a woman’s short-term, absolute risk of
breast cancer. All of this information is within a woman’s screening mammogram,
making risk assessment simple. Results include the woman’s absolute breast
cancer risk score and breast cancer risk category [low, general, moderate and


“The need for technology
like this has never been greater. The COVID pandemic truly highlighted the
absence of a practical solution to accurately determine an individual’s risk of
developing breast cancer between screenings, as several medical societies
recommended last year that women of ‘average risk’ postpone mammograms. The
issue is, most women simply don’t know their risk,” added Stevens. “As clinicians and facilities recover from the impact of the pandemic
this year, they are presented with unprecedented challenges, including a
significant reduction in patient volume, loss of income, and a growing
mammography backlog.
This technology offers a viable solution for the challenges clinicians are
facing today and offers a solution that will remain relevant for years to


Regular, age-based
mammography screening reduces breast cancer mortality by approximately 20%,[7]
but screening mammography can still miss 20 to 40% of breast cancers.[8],[9]
Many of these cancers are diagnosed as interval breast cancers, defined as
those that emerge after a normal mammogram but before the woman’s next
scheduled screening. These tumors are often diagnosed at a later stage than
cancers detected by screening, and are associated with an increased risk
of breast cancer-specific mortality, compared with cancers detected by


Clinicians have
traditionally considered risk factors such as family history as a way to assess
women’s risks of developing breast cancer, but about 85% of breast cancers
occur in women who have no family history of breast cancer.[11]


ProFound AI Risk was
created from an exclusive relationship between iCAD and leading researchers at
the Karolinska Institutet in Stockholm, Sweden, one of the world’s foremost
medical research universities and the home of the Nobel Assembly, which selects
the Nobel laureates in Physiology or Medicine. This partnership built upon a
previous research agreement whereby researchers at the Karolinska Institutet
developed a breast cancer risk prediction model using information identified in
mammography images provided by iCAD’s AI solutions.


“This leading-edge algorithm was designed to provide physicians with
crucial information about a woman’s short-term risk of being diagnosed with
breast cancer, so that they may further personalize her screening and
surveillance plan. This may include screening frequency adjustment,
supplemental imaging, genetic testing and/or risk reduction strategies,”
according to Per Hall, MD, Professor/Senior Physician, Karolinska Institutet.
“Ultimately, the goal of this technology is to enhance efficiency for
clinicians and improve outcomes for patients.”


PowerLook Density Assessment


iCAD also launched the
latest version of PowerLook® Density Assessment software on the new PowerLook
10 platform.
leading-edge software enables clinicians to automate breast density assessment
accurately and reliably,1 removing the challenges of subjectivity. It identifies the patient’s anatomy, segments
the breast, then measures adipose and fibroglandular tissue and its dispersion
to determine the density category in alignment with BI-RADS® 5th Edition
consistent scores bring confident density assessment and standardized
stratification in density-based breast cancer screening and reporting.

Radiologist visual density assessment has suboptimal
intra- and inter- observer agreement due to its visual, subjective assessment.[12]
This inconsistent reporting causes confusion, impacts patient care and derails
referring physician and patient confidence,” said Randy Hicks, M.D., co-owner
and CEO of Regional Medical Imaging in Michigan. “With PowerLook Density
Assessment software, clinicians can feel confident in their patients’ density
assessment. This solution is easy to integrate and implement, and is the ideal
choice for those seeking to accurately automate density assessment and
harmonize the patient experience.”

Density is a measure used to personalize
screening, especially in the U.S., as the American College of Radiology
recommends that supplemental imaging should be considered for women with dense
breasts. Breast density is one of the strongest and most prevalent breast
cancer risk factors;[13]
nearly half of all women age 40 and older who get mammograms are found to have
dense breasts.[14] Currently, 38 U.S. states require
some form of density reporting[15]
and the FDA has proposed requiring breast density reporting to both patients
and referring health providers.[16]


“Early cancer detection has a tremendous impact on women, from treatment
to outcomes. These technologies empower clincians with the latest tools to
personalize screening like never before,” added Stevens. “
The commercialization of
these products is not only a significant milestone for iCAD, it’s a giant leap
forward in individualized patient care.”


AI Risk and PowerLook Density Assessment are the latest updates to iCAD’s Breast
Health Solutions suite, which also includes the Company’s leading-edge cancer
detection software, ProFound AI®. In 2018, ProFound AI for DBT became the first
artificial intelligence (AI) software application trained using deep learning
technology on DBT images to be FDA cleared. It offers clinically proven
time-savings benefits to radiologists, reducing reading time by 52.7 percent,
while also improving radiologist sensitivity by 8 percent, and reducing false
positives and unnecessary patient recall rates by 7.2 percent.[17]




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


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 expected benefits of ProFound AI® Risk
for digital breast tomosynthesis (DBT) and the updated version of PowerLook®
Density Assessment, 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 Relations:

Brian Ritchie,
LifeSci Advisors



[1] iCAD data on file.

[2] Eriksson M, Czene K, Strand F,
Zackrisson S, Lindholm P, Lång K, Förnvik D, Sartor H, Mavaddat N, Easton D,
Hall P. Identification of Women at High Risk of Breast Cancer Who Need
Supplemental Screening. Radiology. 2020 Nov;297(2):327-333. doi: 10.1148/radiol.2020201620.
Epub 2020 Sep 8. PMID: 32897160.

[3] Based on publicly available data as
of September 2021. For GE and Hologic only. Uses 2D synthetic images.

[4] Richardson LC, Henley SJ, Miller JW,
Massetti G, Thomas CC. Patterns and Trends in Age-Specific Black-White
Differences in Breast Cancer Incidence and Mortality – United States,
1999–2014. MMWR Morb Mortal Wkly Rep 2016;65:1093–1098. DOI: icon.

[5] Siddharth S, Sharma D. Racial
Disparity and Triple-Negative Breast Cancer in African-American Women: A
Multifaceted Affair between Obesity, Biology, and Socioeconomic Determinants.
Cancers (Basel). 2018;10(12):514. Published 2018 Dec 14.

[6] American Cancer Society. Inflammatory
Breast Cancer.,common%20types%20of%20breast%20cancer.

[7] Marmot M, Altman G, Cameron A, et
al.  The benefits and harms of breast
cancer screening: an independent review. 
Br J Cancer. 2013;108(11):2205-2240.

[8] NIH National Cancer Institute.
Mammograms Fact Sheet. Accessed via

[9] Lauby-Secretan B, Scoccianti C,
Loomis D et al.; Breast-cancer screening–viewpoint of the IARC Working Group;
N Engl J Med. 2015 Jun 11;372(24):2353-8. doi: 10.1056/NEJMsr1504363.

[10] Irvin
VL, Zhang Z, Simon MS, et al.
of Mortality Among Participants of Women’s Health Initiative Trials With
Screening-Detected Breast Cancers vs Interval Breast Cancers. JAMA Netw Open.
2020;3(6):e207227. Published 2020 Jun 1. doi:10.1001/jamanetworkopen.2020.7227

[11] U.S. Breast Cancer Statistics. Accessed via

[12] Sprague
B, Conant E, Onega T et al.
in Mammographic Breast Density Assessments Among Radiologists in Clinical
Practice: A Multicenter Observational Study. Ann Intern Med. 2016;
165(7):457-464. doi:10.7326/M15-2934. 

[13] Engmann NJ, Golmakani
MK, Miglioretti DL, Sprague BL, Kerlikowske K, Breast Cancer Surveillance C.
Population-Attributable Risk Proportion of Clinical Risk Factors for Breast
Cancer. JAMA Oncology 2017; 3:1228-1236.

[14] National Cancer
Institute. Dense Breasts: Answers to Commonly Asked Questions. Accessed via

[15] State Legislation Map.
Accessed via

[16] National
Reporting Standard. Accessed via

[17] Conant,
E et al.
Accuracy and Efficiency with Concurrent Use of Artificial Intelligence for
Digital Breast Tomosynthesis. Radiology: Artificial Intelligence.
2019;1(4). Accessed via