Rationale and objectives: To compare the results of two software-based methods, Quantra and Volpara, for volumetric breast composition assessment.
Materials and methods: Four hundred forty-five normal, bilateral, two-view, digital mammograms were included. Breast volume (BV), fibroglandular tissue volume (FTV), and percent density (PD) were measured using both methods and compared. Deming regression was performed to obtain linear equations for mapping the results of one software on the other.
Results: The median and quartile ranges of both methods agreed well for BV but were different for FTV and PD, with Quantra showing much higher values of FTV and PD. The correlation of results obtained by both methods for BV, FTV, and PD was 0.99, 0.91, and 0.94, respectively. Intraclass correlation in the assignment of quartiles of BV, FTV, and PD was 0.96, 0.86, and 0.90, respectively. Both methods showed a similar association of FTV and PD with patient age and similar left-to-right correlation. Mapping of results onto each other using linear equations removed the systematic differences.
Conclusions: Although Quantra and Volpara use different models for analysis of volumetric breast composition and produce different nominal results of FTV and PD, both methods are highly correlated and show very good to excellent agreement in quartile assignment of all parameters measured. Both methods show a similar association with patient age and similar reproducibility. Both methods can be mapped onto each other using the equations suggested.
Keywords: Mammary glands; automatic data processing; breast density; human; mammography.
Copyright © 2015 AUR. Published by Elsevier Inc. All rights reserved.