Document Detail

Detection of breast cancer with a computer-aided detection applied to full-field digital mammography.
MedLine Citation:
PMID:  23319110     Owner:  NLM     Status:  MEDLINE    
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.
Ryusuke Murakami; Shinichiro Kumita; Hitomi Tani; Tamiko Yoshida; Kenichi Sugizaki; Tomoyuki Kuwako; Tomonari Kiriyama; Kenta Hakozaki; Emi Okazaki; Keiko Yanagihara; Shinya Iida; Shunsuke Haga; Shinichi Tsuchiya
Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Journal of digital imaging     Volume:  26     ISSN:  1618-727X     ISO Abbreviation:  J Digit Imaging     Publication Date:  2013 Aug 
Date Detail:
Created Date:  2013-07-09     Completed Date:  2014-03-07     Revised Date:  2014-08-05    
Medline Journal Info:
Nlm Unique ID:  9100529     Medline TA:  J Digit Imaging     Country:  United States    
Other Details:
Languages:  eng     Pagination:  768-73     Citation Subset:  IM    
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MeSH Terms
Aged, 80 and over
Breast Neoplasms / radiography*
Calcinosis / radiography
Mammography / methods*
Middle Aged
Radiographic Image Enhancement / methods
Radiographic Image Interpretation, Computer-Assisted / methods*
Reproducibility of Results
Retrospective Studies
Sensitivity and Specificity

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

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