Density is in the eye of the beholder: visual versus semi-automated assessment of breast density on standard mammograms

Abstract

Objectives: Visual inspection is generally used to assess breast density. Our study aim was to compare visual assessment of breast density of experienced and inexperienced readers with semi-automated analysis of breast density.

Methods: Breast density was assessed by an experienced and an inexperienced reader in 200 mammograms and scored according to the quantitative BI-RADS classification. Breast density was also assessed by dedicated software using a semi-automated thresholding technique. Agreement between breast density classification of both readers as well as agreement between their assessment versus the semi-automated analysis as reference standard was expressed as the weighted kappa value.

Results: Using the semi-automated analysis, agreement between breast density measurements of both breasts in both projections was excellent (ICC >0.9, P < 0.0001). Reproducibility of the semi-automated analysis was excellent (ICC >0.8, P < 0.0001). The experienced reader correctly classified the BI-RADS breast density classification in 58.5% of the cases. Classification was overestimated in 35.5% of the cases and underestimated in 6.0% of the cases. Results of the inexperienced reader were less accurate. Agreement between the classification of both readers versus the semi-automated analysis was considered only moderate with weighted kappa values of 0.367 (experienced reader) and 0.232 (inexperienced reader).

Conclusion: Visual assessment of breast density on mammograms is inaccurate and observer-dependent.

Fig. 1

Semi-automated detection of mammographic breast density. a Standard craniocaudal mammogram of the left breast. b Detection of fibroglandular tissue. c Detection of total breast tissue. d Graphic overlay of (b) and (c). In this particular example, the mammographic breast density was 22% (BI-RADS density category 1)

Fig. 2

Bland-Altman plots for the semi-automated analyses of breast densities of both breasts in two projections. The plots show very good agreement for all analyses performed. Intra-class correlation coefficients (ICC) of the measurements were highly significant (all P < 0.0001). Solid lines represent the mean of the differences between the two analyses, dotted lines represent the boundaries of two times the standard deviation of the difference

Fig. 3

Intra-observer agreement of the semi-automated analyses. Bland-Altman plots show good agreement for all analyses performed. Intra-class correlation coefficients (ICC) were highly significant (all P < 0.0001). Solid lines represent the mean of the differences between the two analyses, dotted lines represent the boundaries of two times the standard deviation of the differences

Fig. 4

Inter-observer agreement of the semi-automated analyses. Bland-Altman plots show good agreement for all analyses performed. Intra-class correlation coefficients (ICC) of the measurements were highly significant (all P < 0.0001). Solid lines represent the mean of the differences between the two analyses, dotted lines represent the boundaries of two times the standard deviation of the differences