BI-RADS Density Classification From Areometric and Volumetric Automatic Breast Density Measurements

Digital Mammography versus Breast Tomosynthesis: Impact of Breast Density on Diagnostic Performance in Population-based Screening

BackgroundPrevious studies comparing digital breast tomosynthesis (DBT) to digital mammography (DM) have shown conflicting results regarding breast density and diagnostic performance.PurposeTo compare true-positive and false-positive interpretations in DM versus DBT according to volumetric density, age, and mammographic findings.Materials and MethodsFrom November 2010 to December 2012, 24 301 women aged 50-69 years (mean age, 59.1 years ± 5.7) were prospectively included in the Oslo Tomosynthesis Screening Trial. Participants received same-compression DM and DBT with independent double reading for both DM and DM plus DBT reading modes. Eight experienced radiologists rated the images by using a five-point scale for probability of malignancy. Participants were followed up for 2 years to assess for interval cancers. Breast density was assessed by using automatic volumetric software (scale, 1-4). Differences in true-positive rates, false-positive rates, and mammographic findings were assessed by using confidence intervals (Newcombe paired method) and P values (McNemar and χ² tests).ResultsThe true-positive rate of DBT was higher than that of DM for density groups (range, 12%-24%; P < .001 for density scores of 2 and 3, and P > .05 for density scores of 1 and 4) and age groups (range, 15%-35%; P < .05 for all age groups), mainly due to the higher number of spiculated masses and architectural distortions found at DBT (P < .001 for density scores of 2 and 3; P < .05 for women aged 55-69 years). The false-positive rate was lower for DBT than for DM in all age groups (range, -0.6% to -1.2%; P < .01) and density groups (range, -0.7 to -1.0%; P < .005) owing to fewer asymmetric densities (P ≤ .001), except for extremely dense breasts (0.1%, P = .82).ConclusionDigital breast tomosynthesis enabled the detection of more cancers in all density and age groups compared with digital mammography, especially cancers classified as spiculated masses and architectural distortions. The improvement in cancer detection rate showed a positive correlation with age. With use of digital breast tomosynthesis, false-positive findings were lower due to fewer asymmetric densities, except in extremely dense breasts.© RSNA, 2019Online supplemental material is available for this article.See also the editorial by Fuchsjäger and Adelsmayr in this issue.

Automated Breast Density Computation in Digital Mammography and Digital Breast Tomosynthesis: Influence on Mean Glandular Dose and BIRADS Density Categorization

RATIONALE AND OBJECTIVES

The study aimed to compare the breast density estimates from two algorithms on full-field digital mammography (FFDM) and digital breast tomosynthesis (DBT) and to analyze the clinical implications.

MATERIALS AND METHODS

We selected 561 FFDM and DBT examinations from patients without breast pathologies. Two versions of a commercial software (Quantra 2D and Quantra 3D) calculated the volumetric breast density automatically in FFDM and DBT, respectively. Other parameters such as area breast density and total breast volume were evaluated. We compared the results from both algorithms using the Mann-Whitney U non-parametric test and the Spearman's rank coefficient for data correlation analysis. Mean glandular dose (MGD) was calculated following the methodology proposed by Dance et al.

RESULTS

Measurements with both algorithms are well correlated (r ≥ 0.77). However, there are statistically significant differences between the medians (P < 0.05) of most parameters. The volumetric and area breast density median values from FFDM are, respectively, 8% and 77% higher than DBT estimations. Both algorithms classify 35% and 55% of breasts into BIRADS (Breast Imaging-Reporting and Data System) b and c categories, respectively. There are no significant differences between the MGD calculated using the breast density from each algorithm. DBT delivers higher MGD than FFDM, with a lower difference (5%) for breasts in the BIRADS d category. MGD is, on average, 6% higher than values obtained with the breast glandularity proposed by Dance et al.

CONCLUSIONS

Breast density measurements from both algorithms lead to equivalent BIRADS classification and MGD values, hence showing no difference in clinical outcomes. The median MGD values of FFDM and DBT examinations are similar for dense breasts (BIRADS d category).