iCAD Showcases Breast AI Suite at Society of Breast Imaging Symposium, World’s Largest Breast Imaging Conference

iCAD’s AI solution minimizes interval cancers and overcomes challenges associated with digital breast tomosynthesis

NASHUA, N.H., May 03, 2023 (GLOBE NEWSWIRE) -- iCAD, Inc. (NASDAQ: ICAD), a global medical technology leader providing innovative cancer detection and therapy solutions, today announced it will showcase its Breast AI Suite of cancer detection, density assessment and risk evaluation solutions at the world’s largest breast imaging conference, the Society of Breast Imaging (SBI) Symposium, taking place May 4-7 in National Harbor, MD. Attendees are invited to visit the iCAD booth #507 to see the Company’s Breast AI Suite in action and learn how leading clinicians worldwide are overcoming imaging challenges, including decreasing the incidence of interval cancers.

“While mammography screening has improved in recent decades and the introduction of digital breast tomosynthesis (DBT) offers many clinical advantages, it also creates enormous amounts of data. Processing this volume of data can weigh heavily on radiologists and imaging teams,” said Dana Brown, President and CEO of iCAD, Inc. “iCAD’s Breast AI Suite offers a 360-degree solution of cancer detection, density assessment, and risk evaluation technologies that are uniquely positioned to address the top challenges clinicians face today. Not only is our solution clinically proven to improve accuracy and efficiency for radiologists reading mammography, it offers critical information about a woman’s present and future breast health, which can help clinicians find more interval breast cancers at their earliest stage possible.”

Interval cancers, or those that are diagnosed in between screening exams after a “normal” mammogram, tend to be larger and more aggressive, diagnosed at a later stage and with worse prognoses than those found on screening mammograms.¹ In a study of 69,025 women, interval breast cancers accounted for one-fourth of breast cancers in routinely screened women. These interval cancers were six times more likely to be grade III and had 3.5 times increased hazards of breast cancer death compared with screen-detected cancers.¹

Laura Dean, MD, breast radiologist, Cleveland Clinic, recently discussed minimizing interval cancers with AI in a presentation at the Siemens Healthineers Innovations for Healthcare Professionals Education Symposium in New Orleans, LA.

“DBT has improved mammography screening considerably, particularly in the U.S., where it is available at 82% of breast imaging sites.² However, DBT has introduced new challenges for radiologists reading mammography, as it generates an exponential amount of data to review, compared to 2D mammography. AI is becoming ubiquitous in our daily lives, from smartphones to smart homes, but it is particularly well-suited for reading DBT,” said Dr. Dean. “Interval cancers tend to grow and possibly spread more quickly, making them among the most dangerous to miss. AI helps us to review every pixel of even the most complicated datasets more closely, and with greater accuracy and efficiency, which helps us detect more cancers earlier and hopefully decrease the incidence of interval cancers.”

A growing body of clinical evidence confirms the unique value iCAD’s Breast AI Suite offers to clinicians and patients alike. According to a retrospective analysis of 37,367 women published in the Journal of Medical Screening, ProFound^® AI for 2D Mammography may reduce interval breast cancer rates, as the technology found 93% of interval cancers—including eight out of nine cancers that presented with minimal signs and six out of six that were false negatives, or missed in the screening round.³ Additionally, a study published in Science Translational Medicine suggests ProFound AI Risk offered high accuracy in estimating future risk for both screen detected and interval cancers, as well as invasive and in-situ cancers, in both women with dense and non-dense breasts.²

The flagship product in iCAD’s Breast AI Suite is ProFound AI, which became the first technology of its kind to be FDA cleared in 2018. Built with the latest in deep-learning AI, ProFound AI for Digital Breast Tomosynthesis is clinically proven to improve radiologists’ sensitivity by 8%, reduce the rate of false positives and unnecessary callbacks by 7%, and slash reading time by more than half. iCAD’s Breast AI Suite also includes PowerLook Density Assessment, which automates the process of breast density reporting and empowers clinicians to further personalize breast cancer screening recommendations for patients.

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.^4,5 This first-in-kind solution uniquely combines age, breast density and subtle mammographic features, offering superior performance and accuracy in assessing both short- and long-term risk compared to traditional, commonly-used breast cancer risk models.^3,6

“Breast cancer continues to be one of the greatest threats to women’s health worldwide, but iCAD’s Breast AI Suite arms clinicians with more intelligence than ever to personalize screening based on individual risk, which can help them detect cancers at their earliest possible stages, when they may be more easily treated,” said Ms. Brown. “Using our suite of tools together provides clinicians with the latest defense in the fight against breast cancer – not only does it empower them to perform at a higher level, but it offers valuable information about patients’ individual risk of developing breast cancer that can help clinicians tailor screening regimens. This translates to finding more cancers and we look forward to sharing our powerful solutions with the clinical community at the SBI Symposium this week.”

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} Niraula S, Biswanger N, Hu P, Lambert P, Decker K. Incidence, Characteristics, and Outcomes of Interval Breast Cancers Compared With Screening-Detected Breast Cancers. JAMA Netw Open. 2020;3(9):e2018179. doi:10.1001/jamanetworkopen.2020.18179
² MQSA National Statistics. Accessed via https://www.fda.gov/radiation-emitting-products/mqsa-insights/mqsa-national-statistics.
³ Graewingholt A, Rossi PG. (2021). Retrospective analysis of the effect on interval cancer rate of adding an artificial intelligence algorithm to the reading process for two-dimensional full-field digital mammography. J Med Screen. 0(0) 1-3. Accessed via https://journals.sagepub.com/doi/10.1177/0969141320988049
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 https://www.science.org/doi/10.1126/scitranslmed.abn3971.
⁵ 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.
⁶ 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.