Literature DB >> 22274840

Two-view and single-view tomosynthesis versus full-field digital mammography: high-resolution X-ray imaging observer study.

Matthew G Wallis1, Elin Moa, Federica Zanca, Karin Leifland, Mats Danielsson.   

Abstract

PURPOSE: To compare the diagnostic accuracy of two-dimensional (2D) full-field digital mammography with that of two-view (mediolateral and craniocaudal) and single-view (mediolateral oblique) tomosynthesis in an observer study involving two institutions.
MATERIALS AND METHODS: Ethical committee approval was obtained. All participating women gave informed consent. Two hundred twenty women (mean age, 56.3; range, 40-80 years) with breast density of 2-4 according to American College of Radiology criteria were recruited between November 2008 and September 2009 and underwent standard treatment plus tomosynthesis with a prototype photon-counting machine. After exclusion criteria were met, this resulted in a final test set of 130 women. Ten accredited readers classified the 130 cases (40 cancers, 24 benign lesions, and 66 normal images) using 2D mammography and two-view tomosynthesis. Another 10 readers reviewed the same cases using 2D mammography but single-view tomosynthesis. The multireader, multicase receiver operating characteristic (ROC) method was applied. The significance of the observed difference in accuracy between 2D mammography and tomosynthesis was calculated.
RESULTS: For diagnostic accuracy, 2D mammography performed significantly worse than two-view tomosynthesis (average area under ROC curve [AUC] = 0.772 for 2D, AUC = 0.851 for tomosynthesis, P = .021). Significant differences were found for both masses and microcalcification (P = .037 and .049). The difference in AUC between the two modalities of -0.110 was significant (P = .03) only for the five readers with the least experience (<10 years of reading); with AUC of -0.047 for the five readers with 10 years or more experience (P = .25). No significant difference (P = .79) in reader performance was seen when 2D mammography (average AUC = 0.774) was compared with single-view tomosynthesis (average AUC = 0.775).
CONCLUSION: Two-view tomosynthesis outperforms 2D mammography but only for readers with the least experience. The benefits were seen for both masses and microcalcification. No differences in classification accuracy was seen between and 2D mammography and single-view tomosynthesis. © RSNA, 2012.

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Year:  2012        PMID: 22274840     DOI: 10.1148/radiol.11103514

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


  55 in total

1.  Digital breast tomosynthesis: computer-aided detection of clustered microcalcifications on planar projection images.

Authors:  Ravi K Samala; Heang-Ping Chan; Yao Lu; Lubomir M Hadjiiski; Jun Wei; Mark A Helvie
Journal:  Phys Med Biol       Date:  2014-11-13       Impact factor: 3.609

2.  Digital Breast Tomosynthesis: State of the Art.

Authors:  Srinivasan Vedantham; Andrew Karellas; Gopal R Vijayaraghavan; Daniel B Kopans
Journal:  Radiology       Date:  2015-12       Impact factor: 11.105

3.  Clinical performance metrics of 3D stereoscopic digital mammography compared with 2D digital mammography: observer study.

Authors:  Akiko Daidoji; Takatoshi Aoki; Seiichi Murakami; Mari Miyata; Masami Fujii; Takefumi Katsuki; Yuzuru Inoue; Yuko Tashima; Yoshika Nagata; Keiji Hirata; Fumihiro Tanaka; Yukunori Korogi
Journal:  Br J Radiol       Date:  2018-03-02       Impact factor: 3.039

4.  Multiscale bilateral filtering for improving image quality in digital breast tomosynthesis.

Authors:  Yao Lu; Heang-Ping Chan; Jun Wei; Lubomir M Hadjiiski; Ravi K Samala
Journal:  Med Phys       Date:  2015-01       Impact factor: 4.071

5.  [Digital breast tomosynthesis].

Authors:  H Preibsch; K C Siegmann-Luz
Journal:  Radiologe       Date:  2015-01       Impact factor: 0.635

6.  Digital breast tomosynthesis within a symptomatic "one-stop breast clinic" for characterization of subtle findings.

Authors:  G J Bansal; P Young
Journal:  Br J Radiol       Date:  2015-07-02       Impact factor: 3.039

7.  Mass detection in digital breast tomosynthesis: Deep convolutional neural network with transfer learning from mammography.

Authors:  Ravi K Samala; Heang-Ping Chan; Lubomir Hadjiiski; Mark A Helvie; Jun Wei; Kenny Cha
Journal:  Med Phys       Date:  2016-12       Impact factor: 4.071

8.  Comparison of synthetic and digital mammography with digital breast tomosynthesis or alone for the detection and classification of microcalcifications.

Authors:  Ji Soo Choi; Boo-Kyung Han; Eun Young Ko; Ga Ram Kim; Eun Sook Ko; Ko Woon Park
Journal:  Eur Radiol       Date:  2018-06-21       Impact factor: 5.315

9.  Transfer Learning From Convolutional Neural Networks for Computer-Aided Diagnosis: A Comparison of Digital Breast Tomosynthesis and Full-Field Digital Mammography.

Authors:  Kayla Mendel; Hui Li; Deepa Sheth; Maryellen Giger
Journal:  Acad Radiol       Date:  2018-08-01       Impact factor: 3.173

10.  Clinical utility of dual-energy contrast-enhanced spectral mammography for breast microcalcifications without associated mass: a preliminary analysis.

Authors:  Yun-Chung Cheung; Hsiu-Pei Tsai; Yung-Feng Lo; Shir-Hwa Ueng; Pei-Chin Huang; Shin-Chih Chen
Journal:  Eur Radiol       Date:  2015-07-10       Impact factor: 5.315

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