Classification. Consistency. Reporting.
cmDensity™ An investigational, artificial intelligence- based triage software that helps radiologists classify density accurately and consistently.
As reported in the Journal of the American College of Radiology (JACR)1, dense breast tissue is associated with an increased risk of breast cancer. Dense breast tissue can obscure cancers on mammograms, increasing the difficulty of detection.
The impact of breast density on cancer detection is significant enough that the FDA requires that mammography reports include an assessment of breast density and notification of the patient of her breast density.
Radiologists are required to provide a qualitative and quantitative assessment of breast density
- Classification ranges from A to D, with D being extremely dense
- Mammography centers are required to inform patients if they have heterogeneously dense or extremely dense breasts
cmDensity is an AI-based tool designed to help radiologists classify density accurately and consistently, with a high level of confidence. Based on a recent study, cmDensity:
- Helps radiologists classify density with improved consistency, reducing intra and inter-reader variability
- Helps radiologists quickly identify the correct BIRADS 5th Edition 4 density with demonstrated 4-class (A-D) accuracy
In a clinical setting, the cmDensity assessment will automatically populate the report for subsequent validation by the radiologist. This highly efficacious, automated density tool helps radiologists more quickly, accurately, and consistently meet the FDA density reporting requirements.
cmDensity Key Benefits
Automates density classification according to BIRADS 5th Edition to reduce errors and enhance radiologists’ efficiency
Increases consistency, reducing inter and intra-reader variability
Pre-populates reports, providing more consistent and accurate communication to providers and patients
Works alongside other CureMetrix mammography solutions, cmTriage and cmAssist, to provide radiologists with AI-based tools for optimal breast cancer screening and reporting