3D Density Assessment
Clinically Proven for Digital Mammography and Digital Breast Tomosynthesis
Experience the Benefits of VolparaDensity
- Reproducible and objective results when compared to human assessment of breast density.
- Consistent across manufacturers, models, and imaging modes. Compatible with most digital mammography and tomosynthesis units.
- Immediate identification of women who may benefit from supplemental screening.
- The only volumetric breast density (VBD%) assessment validated with the Tyrer-Cuzick 8 risk model.
Volpara®Density™ software uses the power of AI to assess breast density with clinically proven performance that offers real, actionable advantages. It provides a repeatable, consistent, and objective means of scoring breast density.
"Radiologists can guestimate the percentage of breast tissue that is dense, but they are still using 2D information to assess a 3D phenomenon, and they cannot possibly be accurate in any absolute sense."– Professor Dan Kopans, Radiology, v246, #2, Feb 2008
The Case for Automated Breast Density Assessment
- 4–6 times greater risk1 for women with dense breasts to develop breast cancer when compared to women with fatty breast.
- 30% Less sensitivity2 in mammographic cancer detection for women with dense breasts when compared to women with fatty breasts.
- Visual density assessment is not always consistent3 with 57% inter-reader agreement and 77% intra-reader agreement.
VolparaDensity is FDA-cleared to provide both volumetric breast density measurements and a breast density category, which has been shown to correlate to BI-RADS 4th and 5th Edition density categories, from most digital mammography vendors. It is easy to implement clinically, and quickly helps increase consistency and compliance with state laws while improving productivity and workflow.
VolparaDensity is used every day at clinical sites worldwide and has been validated in many peer-reviewed clinical studies at prestigious institutions. VolparaDensity has been strongly associated with risk of interval cancers4,5,6 and risk of developing breast cancer.7,8,9
1. Boyd et. al. N Engl J Med 2007; 356, 227
2. Carney et. al. Ann Intern Med 2003;138(3):168-75
3. Irshad et. al. AJR 2016;207:1366-1371
4. van Gils. European Congress of Radiology, March 2-6, 2016, Vienna, Austria. European Institute for Biomedical Imaging Research Session 1 [A-225].
6. Destounis et al. Radiological Society of North America 2015 Scientific Assembly and Annual Meeting, November 29 – December 4, 2015, Chicago IL. http://archive.rsna.org/2015/15017085.html
7. Eng et al. Breast Cancer Res 2014;21(13):4124-32 DOI 10.1186/s13058-014-0439-1
8. Brand et al. Cancer Epidemiol Biomarkers Prev 2014; 23(9):1764-72. DOI: 10.1158/1055-9965. EPI-13-1219
9. Park et al. Ann Surg Oncol 2014;21(13):4124-32. DOI 10.1245/s10434-014-3832-1