PowerLook® Density Assessment
The world’s first and only multi-vendor deep learning algorithm for standardizing breast density assessments using synthesized 2D images1
Simplify and standardize breast density reporting and stratification with PowerLook® Density Assessment. The latest generation of our advanced software offers improved accuracy, providing clinicians with reliable and replicable results.2
Using mammographic images, PowerLook Density Assessment analyzes the woman’s breast anatomy and categorizes her breast density within the appropriate BI-RADS® 5th edition density category.
This innovative solution automates the process of breast density reporting and empowers clinicians to further personalize breast cancer screening recommendations for patients.
The Power of Deep Learning
PowerLook Density Assessment software is the ideal choice for those seeking to accurately automate density assessment and harmonize the patient experience.
The algorithm analyzes synthetic images generated from 3D mammography for dispersion and texture of breast tissue, delivering clinicians unique and patient-specific breast density assessments.
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 lexicon.
Benefits Include
Objective, reliable
and consistent breast
density assessmentsHighest matching accuracy for dense and non-dense assessment on the market1,2Seamless integration within multiple PACS, reading workstations and RIS/MIS
Remove the Challenges of Subjectivity
Breast 1 may have a higher percentage of densebreast tissue by volume, but Breast 2 has the greaterchance of obscuring a cancerous lesion.
Breast density assessment has traditionally been determined by the radiologist’s visual assessment, but studies show that these can vary, and clinicians may even disagree with their own assessment year to year.3 This can be confusing for patients, lead to unnecessary additional imaging, and increase patient and facility costs.
PowerLook Density Assessment software removes the challenges of subjectivity in breast density reporting. Using full field digital mammography (FFDM) or synthetic 2D images, it analyzes the dispersion and texture of breast tissue, delivering clinicians a consistent, accurate, and reliable patient-specific breast density assessment.
PowerLook Density Assessment
Addresses clinical need to standardize breast density assessment between radiologistsDelivers automatic and consistent breast density results across all patient populationsAssists in communication of breast density with referring physiciansSimulates the radiologist’s diagnostic process to quickly and accurately assess breast densityProvides a consistent protocol to manage the screening processAligns with the BI-RADS breast tissue density categories
Breast Density Matters
- Breast density is one of the strongest and most prevalent breast cancer risk factors,4 as breast density increases, the risk of developing breast cancer increases.5
- Approximately 50% of all women age 40 and older have dense breasts.6
- Studies show wide variation [6-85%] in visual assessment agreement, and radiologists may even disagree with their own assessment year to year.3
- Currently, 38 U.S. states require some form of density reporting and the FDA has proposed requiring breast density reporting to both patients and referring health providers.7
- Visit this link for the latest updates on national dense breast legislation, and visit this link to see the full list of states where dense breast legislation has been passed.
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References:
- Based on publicly available data as of September 2021. For GE and Hologic only. Uses 2D synthesized images.
- iCAD data on file.
- Sprague B, Conant E, Onega T et al. Variation 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.
- 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.
- McCormack, VA and dos Santos Silva, I. Breast density and parenchymal patterns as markers of breast cancer risk: a meta-analysis. 2006, Cancer Epidemial Biomarkers Prev, Vol. 15, pp. 1157-1169.
- National Cancer Institute. Dense Breasts: Answers to Commonly Asked Questions. Accessed via https://www.cancer.gov/types/breast/breast-changes/dense-breasts.
- Kyanko KA, Hoag J, Busch SH, Aminawung JA, Xu X, Richman IB, Gross CP. Dense Breast Notification Laws, Education, and Women's Awareness and Knowledge of Breast Density: a Nationally
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