Literature DB >> 23319110

Detection of breast cancer with a computer-aided detection applied to full-field digital mammography.

Ryusuke Murakami1, Shinichiro Kumita, Hitomi Tani, Tamiko Yoshida, Kenichi Sugizaki, Tomoyuki Kuwako, Tomonari Kiriyama, Kenta Hakozaki, Emi Okazaki, Keiko Yanagihara, Shinya Iida, Shunsuke Haga, Shinichi Tsuchiya.   

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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Year:  2013        PMID: 23319110      PMCID: PMC3705026          DOI: 10.1007/s10278-012-9564-5

Source DB:  PubMed          Journal:  J Digit Imaging        ISSN: 0897-1889            Impact factor:   4.056


  19 in total

1.  Computer-aided detection (CAD) in screening mammography: sensitivity of commercial CAD systems for detecting architectural distortion.

Authors:  Jay A Baker; Eric L Rosen; Joseph Y Lo; Edgardo I Gimenez; Ruth Walsh; Mary Scott Soo
Journal:  AJR Am J Roentgenol       Date:  2003-10       Impact factor: 3.959

2.  Computer-aided detection in digital mammography: comparison of craniocaudal, mediolateral oblique, and mediolateral views.

Authors:  Seung Ja Kim; Woo Kyung Moon; Nariya Cho; Joo Hee Cha; Sun Mi Kim; Jung-Gi Im
Journal:  Radiology       Date:  2006-12       Impact factor: 11.105

Review 3.  Digital mammography.

Authors:  Etta D Pisano; Martin J Yaffe
Journal:  Radiology       Date:  2005-02       Impact factor: 11.105

4.  Digital mammography and related technologies: a perspective from the National Cancer Institute.

Authors:  F Shtern
Journal:  Radiology       Date:  1992-06       Impact factor: 11.105

5.  Evaluation of breast cancer with a computer-aided detection system by mammographic appearance and histopathology.

Authors:  Rachel F Brem; Jocelyn A Rapelyea; Gilat Zisman; Jeffrey W Hoffmeister; Martin P Desimio
Journal:  Cancer       Date:  2005-09-01       Impact factor: 6.860

6.  Effect of computer-aided detection on independent double reading of paired screen-film and full-field digital screening mammograms.

Authors:  Per Skaane; Ashwini Kshirsagar; Sandra Stapleton; Kari Young; Ronald A Castellino
Journal:  AJR Am J Roentgenol       Date:  2007-02       Impact factor: 3.959

7.  Impact of breast density on computer-aided detection for breast cancer.

Authors:  Rachel F Brem; Jeffrey W Hoffmeister; Jocelyn A Rapelyea; Gilat Zisman; Kevin Mohtashemi; Guarav Jindal; Martin P Disimio; Steven K Rogers
Journal:  AJR Am J Roentgenol       Date:  2005-02       Impact factor: 3.959

8.  Influence of breast lesion size and histologic findings on tumor detection rate of a computer-aided detection system.

Authors:  Ansgar Malich; Dieter Sauner; Christiane Marx; Mirjam Facius; Thomas Boehm; Stefan O Pfleiderer; Marlies Fleck; Werner A Kaiser
Journal:  Radiology       Date:  2003-07-17       Impact factor: 11.105

9.  Computer-aided detection in full-field digital mammography: sensitivity and reproducibility in serial examinations.

Authors:  Seung Ja Kim; Woo Kyung Moon; Nariya Cho; Joo Hee Cha; Sun Mi Kim; Jung-Gi Im
Journal:  Radiology       Date:  2008-01       Impact factor: 11.105

10.  Screening mammography-detected cancers: sensitivity of a computer-aided detection system applied to full-field digital mammograms.

Authors:  Sang Kyu Yang; Woo Kyung Moon; Nariya Cho; Jeong Seon Park; Joo Hee Cha; Sun Mi Kim; Seung Ja Kim; Jung-Gi Im
Journal:  Radiology       Date:  2007-05-16       Impact factor: 11.105

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  7 in total

1.  Matching methods evaluation framework for stereoscopic breast x-ray images.

Authors:  Johanna Rousson; Mathieu Naudin; Cédric Marchessoux
Journal:  J Med Imaging (Bellingham)       Date:  2015-11-18

2.  [Future of mammography-based imaging].

Authors:  R Schulz-Wendtland; T Wittenberg; T Michel; A Hartmann; M W Beckmann; C Rauh; S M Jud; B Brehm; M Meier-Meitinger; G Anton; M Uder; P A Fasching
Journal:  Radiologe       Date:  2014-03       Impact factor: 0.635

Review 3.  Radiomics: from qualitative to quantitative imaging.

Authors:  William Rogers; Sithin Thulasi Seetha; Turkey A G Refaee; Relinde I Y Lieverse; Renée W Y Granzier; Abdalla Ibrahim; Simon A Keek; Sebastian Sanduleanu; Sergey P Primakov; Manon P L Beuque; Damiënne Marcus; Alexander M A van der Wiel; Fadila Zerka; Cary J G Oberije; Janita E van Timmeren; Henry C Woodruff; Philippe Lambin
Journal:  Br J Radiol       Date:  2020-02-26       Impact factor: 3.039

Review 4.  Is the false-positive rate in mammography in North America too high?

Authors:  Michelle T Le; Carmel E Mothersill; Colin B Seymour; Fiona E McNeill
Journal:  Br J Radiol       Date:  2016-06-08       Impact factor: 3.039

5.  Breast Cancer Detection in a Screening Population: Comparison of Digital Mammography, Computer-Aided Detection Applied to Digital Mammography and Breast Ultrasound.

Authors:  Kyu Ran Cho; Bo Kyoung Seo; Ok Hee Woo; Sung Eun Song; Jungsoon Choi; Shin Young Whang; Eun Kyung Park; Ah Young Park; Hyeseon Shin; Hwan Hoon Chung
Journal:  J Breast Cancer       Date:  2016-09-23       Impact factor: 3.588

6.  Applying Data-driven Imaging Biomarker in Mammography for Breast Cancer Screening: Preliminary Study.

Authors:  Eun-Kyung Kim; Hyo-Eun Kim; Kyunghwa Han; Bong Joo Kang; Yu-Mee Sohn; Ok Hee Woo; Chan Wha Lee
Journal:  Sci Rep       Date:  2018-02-09       Impact factor: 4.379

7.  Impact of full field digital mammography diagnosis for female patients with breast cancer.

Authors:  Tuan Wang; Jian-Jun Shuai; Xing Li; Zhi Wen
Journal:  Medicine (Baltimore)       Date:  2019-04       Impact factor: 1.817

  7 in total

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