Literature DB >> 12869683

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

Ansgar Malich1, Dieter Sauner, Christiane Marx, Mirjam Facius, Thomas Boehm, Stefan O Pfleiderer, Marlies Fleck, Werner A Kaiser.   

Abstract

PURPOSE: To evaluate associations between histopathologic findings, tumor size, and detection rate of malignant mammographic findings by using a computer-aided detection (CAD) system.
MATERIALS AND METHODS: The study included 208 mammographically detected histologically proven malignant breast lesions in 208 women. Findings were 150 masses and 114 microcalcifications; 56 lesions showed both findings; 94 lesions, mass only; and 58 lesions, microcalcification only. CAD was used to evaluate mammograms in two views retrospectively. Also, corresponding histopathologic findings and lesion size were evaluated. CAD marks were considered positive if, on at least one view, they correctly identified the corresponding mammographic lesion location.
RESULTS: Ninety percent (135 of 150) of masses and 93.0% (106 of 114) of microcalcifications were marked correctly by the CAD system. Overall tumor detection rate was 93.8% (195 of 208). Size-related detection rate for masses was 83.3% (25 of 30) for lesions up to 10 mm, 100% (45 of 45) for lesions 11-20 mm, 100% (46 of 46) for lesions 21-30 mm, 83.3% (10 of 12) for lesions 31-40 mm, and 52.9% (nine of 17) for lesions larger than 40 mm. Size-related tumor detection rate for microcalcifications was 92.5% (37 of 40) for microcalcifications up to 10 mm, 93.1% (27 of 29) for lesions 11-20 mm, 100% (20 of 20) for lesions 21-30 mm, 87.5% (seven of eight) for lesions 31-40 mm, and 88.2% (15 of 17) for larger microcalcifications. Detection rates for mammographically visible masses (invasive ductal carcinoma, invasive lobular carcinoma, invasive tubular carcinoma, noninvasive cancers, mucinoid cancers, and others) were 92.3% (84 of 91), 89.3% (25 of 28), 75.0% (six of eight), 100% (15 of 15), 33.3% (one of three), and 80.0% (four of five), respectively. Detectability rates for mammographically visible areas suspicious for microcalcifications (invasive ductal carcinoma, invasive lobular carcinoma, invasive tubular carcinoma, and noninvasive cancers) were 92.3% (60 of 65), 100% (eight of eight), 100% (five of five), and 91.9% (31 of 34), respectively. Highest overall detection rates were observed for invasive ductal carcinomas (96.6% [112 of 116]) and noninvasive cancers (92.9% [39 of 42]).
CONCLUSION: Highest detection rates were observed for 10-30-mm tumor masses and for invasive ductal carcinomas and noninvasive cancers.

Entities:  

Mesh:

Year:  2003        PMID: 12869683     DOI: 10.1148/radiol.2283011906

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  10 in total

Review 1.  CAD for mammography: the technique, results, current role and further developments.

Authors:  Ansgar Malich; Dorothee R Fischer; Joachim Böttcher
Journal:  Eur Radiol       Date:  2006-01-17       Impact factor: 5.315

2.  False positive marks on unsuspicious screening mammography with computer-aided detection.

Authors:  Mary C Mahoney; Karthikeyan Meganathan
Journal:  J Digit Imaging       Date:  2011-10       Impact factor: 4.056

3.  Virtual assessment of stereoscopic viewing of digital breast tomosynthesis projection images.

Authors:  Gezheng Wen; Ho-Chang Chang; Jacob Reinhold; Joseph Y Lo; Mia K Markey
Journal:  J Med Imaging (Bellingham)       Date:  2018-01-17

4.  Influence of computer-aided detection on performance of screening mammography.

Authors:  Joshua J Fenton; Stephen H Taplin; Patricia A Carney; Linn Abraham; Edward A Sickles; Carl D'Orsi; Eric A Berns; Gary Cutter; R Edward Hendrick; William E Barlow; Joann G Elmore
Journal:  N Engl J Med       Date:  2007-04-05       Impact factor: 91.245

5.  Computer-aided diagnostic models in breast cancer screening.

Authors:  Turgay Ayer; Mehmet Us Ayvaci; Ze Xiu Liu; Oguzhan Alagoz; Elizabeth S Burnside
Journal:  Imaging Med       Date:  2010-06-01

6.  Effect of breast density on computer aided detection.

Authors:  Ansgar Malich; Dorothee R Fischer; Mirjam Facius; Alexander Petrovitch; Joachim Boettcher; Christiane Marx; Andreas Hansch; Werner A Kaiser
Journal:  J Digit Imaging       Date:  2005-09       Impact factor: 4.056

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

Authors:  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
Journal:  J Digit Imaging       Date:  2013-08       Impact factor: 4.056

8.  Detection of breast cancer in asymptomatic and symptomatic groups using computer-aided detection with full-field digital mammography.

Authors:  Chang Suk Park; Na Young Jung; Kijun Kim; Hyun Seouk Jung; Kyung-Myung Sohn; Se Jeong Oh
Journal:  J Breast Cancer       Date:  2013-09-30       Impact factor: 3.588

9.  Volumetric breast ultrasound as a screening modality in mammographically dense breasts.

Authors:  Vincenzo Giuliano; Concetta Giuliano
Journal:  ISRN Radiol       Date:  2012-10-23

Review 10.  Errors in Mammography Cannot be Solved Through Technology Alone

Authors:  Ernest Usang Ekpo; Maram Alakhras; Patrick Brennan
Journal:  Asian Pac J Cancer Prev       Date:  2018-02-26
  10 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.