Comparison of breast density assessments according to BI-RADS 4th and 5th editions and experience level

Abstract

Background Breast density is an important variable that can change the sensitivity of mammography. It can be analyzed with using the 4th and 5th editions of the Breast Imaging and Reporting Data System (BI-RADS) recommendations from the American College of Radiology (ACR). Purpose To define the intra- and inter-reader agreement levels of breast density assignments performed by readers with different experience levels using two versions of BI-RADS. Material and Methods The breast density assessments of 330 women were conducted by two readers with different levels of experience (one breast radiologist and one resident). Each reader independently defined the breast density four times—twice using the 4th edition and twice using the 5th edition. Assessments were analyzed on four- and two-category scales. Results The intra-reader agreement of the breast radiologist for the 4th and 5th editions of BI-RADS was almost perfect (k = 0.90 and k = 0.87, respectively.) The resident had similar results (k = 0.88 and k = 0.87, respectively). The agreement between the breast radiologist and resident for the 4th and 5th edition of BI-RADS was substantial (k = 0.70 and k = 0.63, respectively). There was a statistically significant difference with the two-category scale analysis between the dense and non-dense for both readers and versions of BI-RADS (McNemar’s test, P < 0.001). Conclusion Although there were high intra- and inter-reader agreement levels when using both versions, the percentage of women having dense breasts increased when using the 5th edition, and the difference was statistically significant. There were no differences found with regard to the readers’ level of experience in all analyses.

Mammographic breast density and the risk of breast cancer: A systematic review and meta-analysis

“…In the fifth edition, percentage quartiles are removed with the goal to better identify women whose cancers may be masked by dense breast tissue [ 23 ]. Multiple studies have shown that BI-RADS lexicon 5th edition is associated with significant higher numbers of dense assessments compared to the fourth edition [ 53 , 54 ]. This might also explain the lower risk estimate than previously reported.…”

Association between changes in mammographic density category and the risk of breast cancer: A nationwide cohort study in East‐Asian women

“…Second, the BI‐RADS was updated in 2013, and the breast density composition scale was modified 43 . Studies have shown that the percentage of women with dense breasts when classified using the fifth edition was slightly higher than when using the fourth edition 37,44,45 . However, women who underwent mammographic screening in both 2019 to 2010 and 2011 to 2012 were included in our study.…”

“…43 Studies have shown that the percentage of women with dense breasts when classified using the fifth edition was slightly higher than when using the fourth edition. 37,44,45 However, women who underwent mammographic screening in both 2019 to 2010 and 2011 to 2012 were included in our study. Thus, we used the BI-RADS fourth edition in our study for breast classification.…”

Breast Density Evaluation According to BI-RADS 5th Edition on Digital Breast Tomosynthesis: AI Automated Assessment Versus Human Visual Assessment

“…Specifically, by shifting the target from tissue percentage to parenchymal density, the new classification became more subjective, and the visual assessments of the BI-RADS categories showed a heterogeneous level of agreement between readers that varied from "slight" to "almost perfect", as reported in previously published papers [18,19]. This discrepancy persisted due to many reasons, which included differences in the study populations, the reader's level of experience, and the methods used in the study [20]. To support the analysis and to reduce the inter-reader variability, existing or new software has been upgraded to carry out an automatic assessment of breast density by analyzing mammographic images with machine-learning procedures, focusing on the distribution pattern of breast tissue rather than breast volumetric density alone.…”