ProFound AI® Risk

Revolutionizing Personalized Screening

Now available for 2D and 3D mammography

Risk Assessment Reimagined

ProFound AI® Risk is the world’s first clinical decision support tool that provides an accurate1 short-term breast cancer risk estimation that is truly personalized for each woman, based only on her mammogram.

The easy-to-implement solution provides superior insights that empower clinicians to tailor a woman’s breast screening regimen and potentially identify cancers earlier.

ProFound AI Risk uniquely combines a range of risk factors, offering superior performance and accuracy in assessing short-term risk compared to traditional, commonly-used breast cancer risk models.1

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Superior AccuracySuperior Accuracy An AUC of 0.73 offers superior accuracy compared to traditional risk assessment models.1An AUC3 of 0.83 offers greater accuracy compared to traditional risk assessment models.1,2Simplified WorkflowSimplified Workflow Efficient and easy to implement solution provides a rapid short-term risk estimate based on the mammographic exam.Efficient and easy to implement solution provides a rapid short-term risk estimate based on the mammographic exam.Personalized CarePersonalized Care Improved model delivers operational efficiency and enhances patient care.Improved model delivers operational efficiency and enhances patient care.

Next Level Insights

The latest generation of ProFound AI Risk offers unprecedented insights for clinicians and patients

  • Flexibility to calculate a one, two, or three-year absolute risk and risk category for the woman and compares her risk relative to the average risk for women in her age group (country specific).
  • Designed to offer greater accuracy and ethnically inclusive precision screening.
  • More than 15 country-specific incidence and mortality rates for alignment with the country’s general population.

Risk Stratification Simplified

ProFound AI Risk software offers a practical approach to risk stratification that seamlessly integrates into the breast cancer screening process. All that is needed is a standard full field digital mammogram (FFDM) or combined digital breast tomosynthesis exam (DBT + 2D synthetic or 2D FFDM).

The easy to integrate ProFound AI Risk model offers superior accuracy2 and enables clinicians to truly personalize screening in order to find breast cancer early.

Results include the short-term breast cancer risk category [low, general, moderate and high].

ProFound AI Risk Score CardProFound AI Index Card

Personalized Screening Made Easy

Some women have a higher risk of developing breast cancer based on their geographical location and ancestry. With ProFound AI Risk, patient care has never been more personalized.

Specifically designed to factor in racial and ethnic backgrounds, ProFound AI Risk offers an equitable and inclusive approach to precision screening.1,4  The algorithm also factors in clinically relevant global screening guidelines and more than 15 country incidence and mortality reference tables, for alignment with that country’s general population.

ProFound AI Risk also includes multiple risk factors found in a screening mammogram:

AgeProFound AI Risk incorporates multiple risk factors found in a screening mammogram: ProFound AI Risk provides physicians with a broad view oBreast DensityProFound AI Risk incorporates multiple risk factors found in a screening mammogram: ProFound AI Risk provides physicians with a broad view oSubtle Mammographic FeaturesProFound AI Risk incorporates multiple risk factors found in a screening mammogram: ProFound AI Risk provides physicians with a broad view o

Unrivaled Accuracy and Clinical Performance

ProFound AI Risk offers the highest AUC available (AUC = 0.832) for providing a one-year future risk estimation based on a screening mammogram. This advanced solution provides superior insights that empower clinicians to tailor a woman’s breast screening regimen and potentially identify cancers earlier, when they may be more easily treated.

Risk Model Performance2

Relative AUC performance for traditional risk models compared to ProFound AI Risk for 2D Mammography and ProFound AI Risk for DBT. Uncertainties are given as the upper and lower 95% confidence intervals

Ethnically-Inclusive Risk Assessment Matters

  • Breast cancer recently surpassed lung cancer as the number 1 diagnosed cancer in the U.S., excluding non-melanoma skin cancers.5
  • African American women have an approximately 40% higher risk of dying from breast cancer compared to white women.6
  • African American women are disproportionately affected by more aggressive subtypes, such as triple-negative breast cancer7 and inflammatory breast cancer.8

Quadrupe Aim IllustrationOne Comprehensive Breast Cancer Care Partner

iCAD’s product portfolio offers innovative solutions to support breast cancer detection, measure breast density, assess personalized risk, and provide targeted radiation therapy. Our technologies offer clinically proven benefits to clinicians and patients, and are designed to optimize efficiency, enhance the patient experience, and improve outcomes.

  • Aligns with the Institute for Health Care Improvement’s Quadruple Aim optimization of health system performance: Better Outcomes, Lower Costs, Enhanced Patient Experience, Improved Clinical Experience.

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References:

  1. iCAD data on file.
  2. 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.
  3. Area under the receiver operating characteristic curve.
  4. ProFound AI Risk for DBT offers an AUC of 0.83 (1-year risk estimation); ProFound AI Risk for 2D Mammography offers an AUC of 0.73 (2-year risk estimation).
  5. Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, Bray F. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin. 2021 May;71(3):209-249. doi: 10.3322/caac.21660. Epub 2021 Feb 4. PMID: 33538338.
  6. 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: http://dx.doi.org/10.15585/mmwr.mm6540a1external icon.
  7. 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. doi:10.3390/cancers10120514
  8. American Cancer Society. Inflammatory Breast Cancer. https://www.cancer.org/cancer/breast-cancer/about/types-of-breast-cancer/inflammatory-breast-cancer.html#:~:text=IBC%20tends%20to%20occur%20in,common%20types%20of%20breast%20cancer.

 

 

 

© iCAD Inc.  All rights reserved.  iCAD, the iCAD logo, PowerLook, ProFound AI, ProFound, Xoft, the Xoft logo, Axxent, Electronic Brachytherapy System and eBx are trademarks of iCAD, Inc. Reproduction of any of the material contained herein in any format or media without the express written permission of iCAD, Inc. is prohibited.

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Quadrupe Aim Illustration

Quadrupe Aim Illustration

Quadrupe Aim Illustration

Quadrupe Aim Illustration

ProFound AI Risk Score CardProFound AI Index Card

Quadrupe Aim Illustration