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Automated volumetric breast density estimation out of digital breast tomosynthesis data: feasibility study of a new software version

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 an...

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Detalles Bibliográficos
Autores principales: Machida, Youichi, Saita, Ai, Namba, Hirofumi, Fukuma, Eisuke
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4912534/
https://www.ncbi.nlm.nih.gov/pubmed/27386266
http://dx.doi.org/10.1186/s40064-016-2519-4
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author Machida, Youichi
Saita, Ai
Namba, Hirofumi
Fukuma, Eisuke
author_facet Machida, Youichi
Saita, Ai
Namba, Hirofumi
Fukuma, Eisuke
author_sort Machida, Youichi
collection PubMed
description 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.
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spelling pubmed-49125342016-07-06 Automated volumetric breast density estimation out of digital breast tomosynthesis data: feasibility study of a new software version Machida, Youichi Saita, Ai Namba, Hirofumi Fukuma, Eisuke Springerplus Technical Note 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. Springer International Publishing 2016-06-18 /pmc/articles/PMC4912534/ /pubmed/27386266 http://dx.doi.org/10.1186/s40064-016-2519-4 Text en © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Technical Note
Machida, Youichi
Saita, Ai
Namba, Hirofumi
Fukuma, Eisuke
Automated volumetric breast density estimation out of digital breast tomosynthesis data: feasibility study of a new software version
title Automated volumetric breast density estimation out of digital breast tomosynthesis data: feasibility study of a new software version
title_full Automated volumetric breast density estimation out of digital breast tomosynthesis data: feasibility study of a new software version
title_fullStr Automated volumetric breast density estimation out of digital breast tomosynthesis data: feasibility study of a new software version
title_full_unstemmed Automated volumetric breast density estimation out of digital breast tomosynthesis data: feasibility study of a new software version
title_short Automated volumetric breast density estimation out of digital breast tomosynthesis data: feasibility study of a new software version
title_sort automated volumetric breast density estimation out of digital breast tomosynthesis data: feasibility study of a new software version
topic Technical Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4912534/
https://www.ncbi.nlm.nih.gov/pubmed/27386266
http://dx.doi.org/10.1186/s40064-016-2519-4
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