Rationale and Objectives
To investigate agreement on mammographic breast density (MD) assessment between automated volumetric software and Breast Imaging Reporting and Data System (BIRADS) categorization by expert radiologists.
Materials and Methods
Forty cases of left craniocaudal and mediolateral oblique mammograms from 20 women were used. All images had their volumetric density classified using Volpara density grade (VDG) and average volumetric breast density percentage. The same images were then classified into BIRADS categories (I–IV) by 20 American Board of Radiology examiners.
Results
The results demonstrated a moderate agreement (κ = 0.537; 95% CI = 0.234–0.699) between VDG classification and radiologists’ BIRADS density assessment. Interreader agreement using BIRADS also demonstrated moderate agreement (κ = 0.565; 95% CI = 0.519–0.610) ranging from 0.328 to 0.669. Radiologists’ average BIRADS was lower than average VDG scores by 0.33, with their mean being 2.13, whereas the mean VDG was 2.48 (U = −3.742; P < 0.001). VDG and BIRADS showed a very strong positive correlation (ρ = 0.91; P < 0.001) as did BIRADS and average volumetric breast density percentage (ρ = 0.94; P < 0.001).
Conclusions
Automated volumetric breast density assessment shows moderate agreement and very strong correlation with BIRADS; interreader variations still exist within BIRADS. Because of the increasing importance of MD measurement in clinical management of patients, widely accepted, reproducible, and accurate measures of MD are required.
Introduction
Women with dense breasts have a two- to sixfold increased risk of breast cancer compared to fatty breasts . Mammographic density (MD), the most common measure of breast density, is defined by the relative amount of fat and fibroglandular tissue in the breast as seen on a mammogram. This is usually expressed as a percentage, where MD is the proportion of the breast area on a mammogram that is radiodense or opaque . However, area-based, two-dimensional measures of MD such as semiautomated Cumulus do not take the volume of density into account. It has been proposed that MD might be used to stratify women into different screening regimes, such as increasing the frequency of screening or using adjunctive imaging modalities for women with dense breasts . However, this would rely on reproducible and accurate measurement of MD, which to date has proven to be troublesome . Measurement reproducibility is important if MD is to be incorporated into breast screening imaging pathways and cancer risk predictive models .
There is no gold standard method for measuring actual breast density, although attempts to quantify this feature using mammography are well reported. The most common (conventional) method in practice involves visual (qualitative) assessment by the radiologist, for example, the fourth edition of the Breast Imaging Reporting and Data System (BIRADS) , which defines MD from I (describing an entirely fatty breast) to IV (representing an extremely dense breast) . The recent update in the BIRADS standard changed numbered categories to letters and removed percentage descriptors from the four categories .
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Materials and Methods
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Selection of Images
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Image Display and MD Quantification using BIRADS
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Breast Density Quantification Using Volpara Automated Software
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Agreement Between BIRADS and Volpara (VDG and AvBD%)
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Statistics
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Results
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Correlation Between BIRADS and Volpara (VDG and AvBD%)
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Agreement Between BIRADS and Volpara (VDG and AvBD%)
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Table 1
Mean Difference in Time Spent on Each BIRADS Category Assessment by Radiologists
BIRADS BIRADS Mean Difference Std. Error_P_ Value 95% Confidence Interval Lower Bound Upper Bound I II −0.55317 .51747 1.000 −1.9218 .8155 III −2.54092 \* .49325 .000 −3.8455 −1.2363 IV −3.96609 \* .74457 .000 −5.9354 −1.9968 II III −1.98775 \* .52820 .001 −3.3848 −.5907 IV −3.41293 \* .76817 .000 −5.4446 −1.3812 III IV −1.42518 .75207 .351 −3.4143 .5640
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Interreader Agreement on BIRADS Categorization
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Table 2
The Number of Images Allocated to BIRADS Categories I, II, II, and IV in Our Research Setting and VDG Categories 1, 2, 3, and 4 as well as the Number of Images on which BIRADS and VGD Agreed for Each Category (Shown in Squares)
VDG Total 1 2 3 4 BIRADS I 9 5 0 0 14 II 0 8 2 0 10 III 0 0 6 7 13 IV 0 0 0 3 3 Total 9 13 8 10 40
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Discussion
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Comparison Between BIRADS and Volpara MD Assessments
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Conclusions
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Acknowledgments
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