Reliability of automated breast density measurements.
OBJECTIVE
To estimate the reliability of a reference standard two-dimensional area-based method and three automated volumetric breast density measurements by using repeated measures.


METHODS
Thirty women undergoing screening mammography consented to undergo a repeated left craniocaudal examination performed by a second technologist in this prospective institutional review board-approved HIPAA-compliant study. Breast density was measured by using an area-based method (Cumulus ABD) and three automated volumetric methods (CumulusV [University of Toronto], Volpara [version 1.4.5; Volpara Solutions, Wellington, New Zealand), and Quantra [version 2.0; Hologic, Danbury, Conn]). Discrepancy between the first and second breast density measurements (Δ1-2) was obtained for each algorithm by subtracting the second measurement from the first. The Δ1-2 values of each algorithm were then analyzed with a random-effects model to derive Bland-Altman-type limits of measurement agreement.


RESULTS
Variability was higher for Cumulus ABD and CumulusV than for Volpara or Quantra. The within-breast density measurement standard deviations were 3.32% (95% confidence interval [CI]: 2.65, 4.44), 3.59% (95% CI: 2.86, 4.48), 0.99% (95% CI: 0.79, 1.33), and 1.64% (95% CI: 1.31, 1.39) for Cumulus ABD, CumulusV, Volpara, and Quantra, respectively. Although the mean discrepancy between repeat breast density measurements was not significantly different from zero for any of the algorithms, larger absolute breast density discrepancy (Δ1-2) values were associated with larger breast density values for Cumulus ABD and CumulusV but not for Volpara and Quantra.


CONCLUSIONS
Variability in a repeated measurement of breast density is lowest for Volpara and Quantra; these algorithms may be more suited to incorporation into a risk model.
From the Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada (O.A., G.E.M., M.J.Y.); and Department of Public Health Sciences (J.T.P.) and Department of Radiology and Medical Imaging (J.A.H.), University of Virginia, Box 800170, Charlottesville, VA 22908.
Olivier
O
Alonzo-Proulx
Gordon E
GE
Mawdsley
James T
JT
Patrie
Martin J
MJ
Yaffe
Jennifer A
JA
Harvey
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D001940:Breast / Q000473:pathology*; D001330:Electronic Data Processing; D005260:Female; D006801:Humans; D008327:Mammography / Q000706:statistics & numerical data*; D008875:Middle Aged; D011446:Prospective Studies; D012016:Reference Values; D015203:Reproducibility of Results; D012984:Software