Related Experiment Video
Updated: Aug 1, 2025
Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
Published on: December 15, 2014
Breast Density Evaluation According to BI-RADS 5th Edition on Digital Breast Tomosynthesis: AI Automated Assessment
Daniele Ugo Tari1, Rosalinda Santonastaso2, Davide Raffaele De Lucia1
1Department of Diagnostic Senology District 12, Palazzo della Salute, Caserta Local Health Authority, 81100 Caserta, Italy.
Background:
The assessment of breast density is one of the main goals of radiologists because the masking effect of dense fibroglandular tissue may affect the mammographic identification of lesions. The BI-RADS 5th Edition has revised the mammographic breast density categories, focusing on a qualitative evaluation rather than a quantitative one. Our purpose is to compare the concordance of the automatic classification of breast density with the visual assessment according to the latest available classification.
Methods:
A sample of 1075 digital breast tomosynthesis images from women aged between 40 and 86 years (58 ± 7.1) was retrospectively analyzed by three independent readers according to the BI-RADS 5th Edition. Automated breast density assessment was performed on digital breast tomosynthesis images with the Quantra software version 2.2.3. Interobserver agreement was assessed with kappa statistics. The distributions of breast density categories were compared and correlated with age.
Results:
The agreement on breast density categories was substantial to almost perfect between radiologists (κ = 0.63-0.83), moderate to substantial between radiologists and the Quantra software (κ = 0.44-0.78), and the consensus of radiologists and the Quantra software (κ = 0.60-0.77). Comparing the assessment for dense and non-dense breasts, the agreement was almost perfect in the screening age range without a statistically significant difference between concordant and discordant cases when compared by age.
Conclusions:
The categorization proposed by the Quantra software has shown a good agreement with the radiological evaluations, even though it did not completely reflect the visual assessment. Thus, clinical decisions regarding supplemental screening should be based on the radiologist's perceived masking effect rather than the data produced exclusively by the Quantra software.
