Quantitative breast density analysis using tomosynthesis and comparison with MRI and digital mammography

Woo Kyung Moon, Jie Fan Chang, Chung Ming Lo, Jung Min Chang, Su Hyun Lee, Sung Ui Shin, Chiun Sheng Huang, Ruey Feng Chang

研究成果: 雜誌貢獻文章同行評審

6 引文 斯高帕斯(Scopus)

摘要

Background and Objective Breast density at mammography has been used as markers of breast cancer risk. However, newly introduced tomosynthesis and computer-aided quantitative method could provide more reliable breast density evaluation. Methods In the experiment, 98 tomosynthesis image volumes were obtained from 98 women. For each case, an automatic skin removal was used and followed by a fuzzy c-mean (FCM) classifier which separated the fibroglandular tissues from other tissues in breast area. Finally, percent of breast density and breast volume were calculated and the results were compared with MRI. In addition, the percent of breast density and breast area of digital mammography calculated using the software Cumulus (University of Toronto, Toronto, ON, Canada.) were also compared with 3-D modalities. Results Percent of breast density and breast volume, which were computed from tomosynthesis, MRI and digital mammography were 17.37% ± 4.39% and 607.12 cm3 ± 323.01 cm3, 20.3% ± 8.6% and 537.59 cm3 ± 287.74 cm3, and 12.03% ± 4.08%, respectively. There were significant correlations on breast density as well as volume between tomosynthesis and MRI (R = 0.482 and R = 0.805), tomosynthesis and breast density with breast area of digital mammography (R = 0.789 and R = 0.877), and MRI and breast density with breast area of digital mammography (R = 0.482 and R = 0.857) (all P values <.001). Conclusions Breast density and breast volume evaluated from tomosynthesis, MRI and breast density and breast area of digital mammographic images have significant correlations and indicate that tomosynthesis could provide useful 3-D information on breast density through proposed method.
原文英語
頁(從 - 到)99-107
頁數9
期刊Computer Methods and Programs in Biomedicine
154
DOIs
出版狀態已發佈 - 二月 1 2018

ASJC Scopus subject areas

  • Software
  • Computer Science Applications
  • Health Informatics

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