Quantra™ 2.2 Technology
Standardise Breast Density Analysis
Higher breast density is known to increase a woman’s risk for breast cancer.1 The need for accurate, unbiased analysis is therefore critical. Powered by machine learning, Quantra software analyses both 2D™ and tomosynthesis images for distribution and texture of parenchymal tissue. It categorises breasts in four breast composition categories consistent with guidance from the American College of Radiation (ACR) BI-RADS Atlas 5th Edition.2
Better Risk Prediction
In addition to volume, pattern and texture of fibroglandular tissue may play just as an important role in mammographic cancer risk prediction.3-5 By analysing and categorising breast texture and pattern, our technology can deliver the accurate information you need to achieve more consistent and reliable scoring and confidently design patient-specific screening.
Design Intent & Clinical Performance
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Hologic AI-powered Integrated Software Solutions
Highest risk category: left breast D, right breast D
Varying risk category: left breast C, right breast B
Varying risk category: left breast A, right breast B
Varying risk category: left breast C, right breast D
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