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Detection of Breast Cancer with a Computer-Aided Detection Applied to Full-Field Digital Mammography

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Abstract

A study was conducted to evaluate the sensitivity of computer-aided detection (CAD) with full-field digital mammography in detection of breast cancer, based on mammographic appearance and histopathology. Retrospectively, CAD sensitivity was assessed in total group of 152 cases for subgroups based on breast density, mammographic presentation, lesion size, and results of histopathological examination. The overall sensitivity of CAD was 91 % (139 of 152 cases). CAD detected 100 % (47/47) of cancers manifested as microcalcifications; 98 % (62/63) of those manifested as non-calcified masses; 100 % (15/15) of those manifested as mixed masses and microcalcifications; 75 % (12/16) of those manifested as architectural distortions, and 69 % (18/26) of those manifested as focal asymmetry. CAD sensitivity was 83 % (10/12) for cancers measuring 1–10 mm, 92 % (37/40) for those measuring 11–20 mm, and 92 % (92/100) for those measuring >20 mm. There was no significant difference in CAD detection efficiency between cancers in dense breasts (88 %; 69/78) and those in non-dense breasts (95 %; 70/74). CAD showed a high sensitivity of 91 % (139/152) for the mammographic appearance of cancer and 100 % sensitivity for identifying cancers manifested as microcalcifications. Sensitivity was not influenced by breast density or lesion size. CAD should be effective for helping radiologists detect breast cancer at an earlier stage.

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Declaration of interest

The authors report no conflicts of interest and are alone responsible for the content and writing of this paper.

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Authors and Affiliations

  1. Department of Radiology, Graduate School of Medicine, Nippon Medical School, 1-1-5 Sendagi, Bunkyo Tokyo, 1138602, Japan

    Ryusuke Murakami, Shinichiro Kumita, Hitomi Tani, Tamiko Yoshida, Kenichi Sugizaki, Tomoyuki Kuwako, Tomonari Kiriyama, Kenta Hakozaki & Emi Okazaki

  2. Department Surgery for Organ Function and Biological Regulation, Graduate School of Medicine, Nippon Medical School, 1-1-5 Sendagi, Bunkyo Tokyo, 1138602, Japan

    Keiko Yanagihara, Shinya Iida & Shunsuke Haga

  3. Division of Diagnostic Pathology, Nippon Medical School Hospital, 1-1-5 Sendagi, Bunkyo Tokyo, 1138602, Japan

    Shinichi Tsuchiya

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  1. Ryusuke Murakami
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  2. Shinichiro Kumita
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  3. Hitomi Tani
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  4. Tamiko Yoshida
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  5. Kenichi Sugizaki
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  6. Tomoyuki Kuwako
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  7. Tomonari Kiriyama
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  8. Kenta Hakozaki
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  11. Shinya Iida
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  12. Shunsuke Haga
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  13. Shinichi Tsuchiya
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Correspondence to Ryusuke Murakami.

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Murakami, R., Kumita, S., Tani, H. et al. Detection of Breast Cancer with a Computer-Aided Detection Applied to Full-Field Digital Mammography. J Digit Imaging 26, 768–773 (2013). https://doi.org/10.1007/s10278-012-9564-5

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  • DOI: https://doi.org/10.1007/s10278-012-9564-5

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