Comparing Visually Assessed BI-RADS Breast Density and Automated Volumetric Breast Density Software: A Cross-Sectional Study in a Breast Cancer Screening Setting.
BACKGROUND
The objective of this study is to compare different methods for measuring breast density, both visual assessments and automated volumetric density, in a breast cancer screening setting. These measures could potentially be implemented in future screening programmes, in the context of personalised screening or screening evaluation.


METHODS
Digital mammographic exams (N = 992) of women participating in the Dutch breast cancer screening programme (age 50-75y) in 2013 were included. Breast density was measured in three different ways: BI-RADS density (5th edition) and with two commercially available automated software programs (Quantra and Volpara volumetric density). BI-RADS density (ordinal scale) was assessed by three radiologists. Quantra (v1.3) and Volpara (v1.5.0) provide continuous estimates. Different comparison methods were used, including Bland-Altman plots and correlation coefficients (e.g., intraclass correlation coefficient [ICC]).


RESULTS
Based on the BI-RADS classification, 40.8% of the women had 'heterogeneously or extremely dense' breasts. The median volumetric percent density was 12.1% (IQR: 9.6-16.5) for Quantra, which was higher than the Volpara estimate (median 6.6%, IQR: 4.4-10.9). The mean difference between Quantra and Volpara was 5.19% (95% CI: 5.04-5.34) (ICC: 0.64). There was a clear increase in volumetric percent dense volume as BI-RADS density increased. The highest accuracy for predicting the presence of BI-RADS c+d (heterogeneously or extremely dense) was observed with a cut-off value of 8.0% for Volpara and 13.8% for Quantra.


CONCLUSIONS
Although there was no perfect agreement, there appeared to be a strong association between all three measures. Both volumetric density measures seem to be usable in breast cancer screening programmes, provided that the required data flow can be realized.
Radboud university medical center, Radboud Institute for Health Sciences, Nijmegen, The Netherlands.
Daniëlle
D
van der Waal
Dutch Reference Centre for Screening, Nijmegen, The Netherlands; Department of Radiology, Academic Medical Centre, University of Amsterdam, Amsterdam, The Netherlands.
Gerard J
GJ
den Heeten
Dutch Reference Centre for Screening, Nijmegen, The Netherlands; Department of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands.
Ruud M
RM
Pijnappel
Dutch Reference Centre for Screening, Nijmegen, The Netherlands.
Klaas H
KH
Schuur
Dutch Reference Centre for Screening, Nijmegen, The Netherlands.
Johanna M H
JM
Timmers
Radboud university medical center, Radboud Institute for Health Sciences, Nijmegen, The Netherlands.
André L M
AL
Verbeek
Radboud university medical center, Radboud Institute for Health Sciences, Nijmegen, The Netherlands; Dutch Reference Centre for Screening, Nijmegen, The Netherlands.
Mireille J M
MJ
Broeders
D000368:Aged; D001331:Automation; D001940:Breast / Q000033:anatomy & histology*; D001943:Breast Neoplasms / Q000000981:diagnostic imaging*; D003430:Cross-Sectional Studies; D005260:Female; D006801:Humans; D008875:Middle Aged; D009426:Netherlands; D011859:Radiography; D012984:Software