This study aims to compare Quantra, as an automated volumetric breast density (Vbd) tool, with visual assessment according to ACR BI-RADS density categories and to determine its potential usage in clinical practice.Five hundred randomly selected screening and diagnostic mammograms were included in this retrospective study. Three radiologists independently assigned qualitative ACR BI-RADS density categories to the mammograms. Quantra automatically calculates the volumetric density data into the system. The readers were blinded to the Quantra and other readers assessment. Inter-reader agreement and agreement between Quantra and each reader were tested. Region under the curve (ROC) analysis was performed to obtain the cut-off value to separate dense from a non-dense breast. Results with P value <.05 was taken as significant.There were 40.4% Chinese, 27% Malays, 19% Indian and 3.6% represent other ethnicities. The mean age of the patients was 57. 15%, 45.6%, 30.4%, and 9% of patients fall under BI-RADS A, B, C and D density category respectively. Fair agreement with Kappa (κ) value: 0.49, 0.38, and 0.30 were seen for Reader 1, 2 and 3 versus Quantra. Moderate agreement with κ value: 0.63, 0.64, 0.51 was seen when the data were dichotomized (density A and B to "non-dense", C and D to "dense"). The cut-off Vbd value was 13.5% to stratify dense from non-dense breasts with a sensitivity of 86.2% and specificity of 83.1% (AUC 91.4%; confidence interval: 88.8, 94.1).Quantra showed moderate agreement with radiologists visual assessment. Hence, this study adds to the available evidence to support the potential use of Quantra as an adjunct tool for breast density assessment in routine clinical practice in the Asian population. We found 13.5% is the best cut-off value to stratify dense to non-dense breasts in our study population. Its application will provide an objective, consistent and reproducible results as well as aiding clinical decision-making on the need for supplementary breast ultrasound in our screening population.