期刊
EUROPEAN JOURNAL OF RADIOLOGY
卷 93, 期 -, 页码 121-127出版社
ELSEVIER IRELAND LTD
DOI: 10.1016/j.ejrad.2017.05.033
关键词
Breast cancer; Breast density; Image analysis; Volpara (TM); Mammography
资金
- Ministry of Economy and Competitiveness of Spain [DPI201568442-R]
- Universitat de Girona by UdG [MPCUdG2016/022]
- Eloy Garcia holds a FPI [BES-2013-065314]
- SCARtool (H2020-MSCA-IF-2014) [657875]
- European Union within the Marie Sklodowska-Curie Innovative Training Networks
Purpose: The aim of this paper is to evaluate the spatial glandular volumetric tissue distribution as well as the density measures provided by Volpara (TM) using a dataset composed of repeated pairs of mammograms, where each pair was acquired in a short time frame and in a slightly changed position of the breast. Materials and methods: We conducted a retrospective analysis of 99 pairs of repeatedly acquired full-field digital mammograms from 99 different patients. The commercial software Volpara (TM) Density Maps (Volpara Solutions, Wellington, New Zealand) is used to estimate both the global and the local glandular tissue distribution in each image. The global measures provided by Volpara (TM), such as breast volume, volume of glandular tissue, and volumetric breast density are compared between the two acquisitions. The evaluation of the local glandular information is performed using histogram similarity metrics, such as intersection and correlation, and local measures, such as statistics from the difference image and local gradient correlation measures. Results: Global measures showed a high correlation (breast volume R = 0.99, volume of glandular tissue R = 0.94, and volumetric breast density R = 0.96) regardless the anode/filter material. Similarly, histogram intersection and correlation metric showed that, for each pair, the images share a high degree of information. Regarding the local distribution of glandular tissue, small changes in the angle of view do not yield significant differences in the glandular pattern, whilst changes in the breast thickness between both acquisition affect the spatial parenchymal distribution. Conclusions: This study indicates that Volpara (TM) Density Maps is reliable in estimating the local glandular tissue distribution and can be used for its assessment and follow-up. Volpara (TM) Density Maps is robust to small variations of the acquisition angle and to the beam energy, although divergences arise due to different breast compression conditions.
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