Quantra™ should be considered a tool for two-grade scale mammographic breast density classification

Abstract

Objective: To assess the agreement between Quantra™ (Hologic Inc., Bedford, MA) and Breast Imaging Reporting and Data Systems (BI-RADS®) and the performance of Quantra at reproducing BI-RADS mammographic breast density (MBD) assessment. Methods: MBD assessment was performed using Quantra and BI-RADS. BI-RADS assessment was performed in two phases (1314 and 292 cases, respectively). Kappa was used to assess the interreader agreement and the agreement between Quantra and BI-RADS, and receiver-operating characteristics analysis was used to assess the performance of Quantra at reproducing BI-RADS rating. In Phase 1, Quantra demonstrated 93.2% sensitivity and 86.1% specificity for BI-RADS on a two-grade scale (1-2 vs 3-4). In Phase 2, it demonstrated 91.3% sensitivity and 83.6% specificity on a two-grade scale. Conclusion: Quantra is limited in reproducing BI-RADS rating on a four-grade scale; however, it highly reproduces BI-RADS assessment on a two-grade scale. Advances in knowledge: Quantra (v. 2.0) is a poor predictor of BI-RADS assessment on a four-grade scale, but well reproduces BI-RADS rating on a two-grade scale. Therefore, it should be considered a tool for two-grade scale MBD classification. INTRODUCTIONBreast density is associated with breast cancer risk, interval breast cancer and mammographic sensitivity. 1,2 It has been shown that 30% reduction in breast cancer mortality is partly attributable to improved knowledge of its risk factors and advances in early detection and treatment strategies. 3,4 Breast density refers to the proportion of the breast that is composed of fibroglandular tissue 5 and is related to established breast cancer risk factors such as genetics, hormonal agents and lifestyle characteristics. 6,7 Most importantly, breast density reduction has been shown to be a prognostic marker of response to adjuvant tamoxifen therapy in post-menopausal females. 8,9 Therefore, adding breast density information to existing breast cancer riskprediction models may improve the stratification of breast cancer risk, 10 which may lead to earlier adoption of prevention and control measures. Breast density information can also be used for tailoring clinical decisions such as screening intervals for females who are asymptomatic and the selection of more appropriate imaging pathways such

Evaluation of automated volumetric breast density software in comparison with visual assessments in an Asian population

“…A study by Ekpo et al concluded that Quantra is a useful tool to assess mammographic breast density into dense and non-dense categories, instead of 4 distinct categories. [ 22 ] This is similar to our study findings, that shows greater agreement between Quantra with readers when the density data were dichotomized. Although breast density assessment is purely subjective with the elimination of numerical percentiles as recommended by ACR-BIRADS 5th edition, the cut-off value can be applied to stratify dense from the non-dense breast when radiologists are in doubt.…”

Evaluation of Quantra Hologic Volumetric Computerized Breast Density Software in Comparison With Manual Interpretation in a Diverse Population

“…Also in contrast were the high Quantra density cutoffs of 19.5% and 20%, respectively, reported by the studies from India and Australia. 16 , 17 It is unclear why the different studies have such disparate cutoffs. One possibility may relate to race and ethnicity.…”

“…The specificity (0.7737) corresponding to the best cutoff value represents, among patients classified as low density by the radiologist, the fraction of patients that were also classified by QUANTRA as low density. Five of the 6 other published studies, 16 – 18 , 20 , 23 plus the abstract of the unpublished study of Rafferty et al 21 reported sensitivity and specificity. Their sensitivities and specificities were uniformly higher than ours, with sensitivities ranging from 78% to 91% and specificities ranging from 77% to 92%.…”

“…However, it is reassuring that the findings were consistent with the published studies from Amsterdam and Oslo, 18 , 19 as well as with the unpublished United States–based study of Rafferty et al 21 It remains a conundrum why these 3 studies and our study are at variance with the studies from Turin, New Delhi, and Sydney. 16 , 17 , 20 , 23 …”

“…Two studies independently conducted in Turin, Italy, reported similar cutoffs of 22% and 21%. 16 , 17 A third study from New Delhi, India, 16 reported a Quantra cutoff of 19.5%, whereas a fourth study from Sydney, Australia, 17 reported Quantra cutoffs of 20.0% overall and 20.5% in a validation subset. In contrast, a fifth study from Amsterdam, the Netherlands, 18 reported a Quantra cutoff of 13.8%, whereas a sixth study from Oslo, Norway, 19 reported a Quantra cutoff of 10.0% versus the median BI-RADS classification from 5 radiologists, along with cutoffs ranging from 8% to 15% versus BI-RADS classifications from the radiologists individually.…”