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Updated: Mar 18, 2026
Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
Published on: December 15, 2014
Automated volumetric breast density estimation out of digital breast tomosynthesis data: feasibility study of a new
Youichi Machida1, Ai Saita2, Hirofumi Namba3
1Kameda Kyobashi Clinic, Tokyo Square Garden 4F, 3-1-1 Kyobashi, Chuo City, Tokyo 104-0031 Japan ; Kameda Medical Center, Chiba, Japan.
Background:
A new software version of VolparaDensity (Volpara Algorithm version 1.5.1) is capable of calculating volumetric breast density (VBD) using either full-field digital mammography (FFDM) or digital breast tomosynthesis (DBT) images. In this preliminary study, we evaluated the feasibility and consistency of this new automated software.
Findings:
Raw data from both DBT and FFDM were acquired from women breast cancer screening at our institution between April and August 2015 using. The DBT and FFDM images obtained under a single compression were collected and VBD was measured using fully automated software. A paired t test was used to analyze differences in the VBD calculated from paired FFDM and DBT images. The correlation coefficient (R value) was calculated and p < 0.05 was considered significant. Dualmodality images were acquired in 160 women; VBD data were available for all but one. There was a significant difference in the VBD of individual breasts calculated from DBT and FFDM and when data were compared per case (<0.001 and p = 0.006, respectively). There were very good to excellent correlations between data from FFDM and from DBT (R = 0.78, p < 0.0001; per breast, R = 0.89, p < 0.0001, per case, R = 0.91, p < 0.0001).
Conclusions:
VBD from DBT was well correlated to that from FFDM, though significant differences were observed between the two.
