Literature DB >> 19523854

Clinical MR-mammography: are computer-assisted methods superior to visual or manual measurements for curve type analysis? A systematic approach.

Pascal Andreas Thomas Baltzer1, Christian Freiberg, Sebastian Beger, Tibor Vag, Matthias Dietzel, Aimee B Herzog, Mieczyslaw Gajda, Oumar Camara, Werner A Kaiser.   

Abstract

RATIONALE AND
OBJECTIVES: Enhancement characteristics after administration of a contrast agent are regarded as a major criterion for differential diagnosis in magnetic resonance mammography (MRM). However, no consensus exists about the best measurement method to assess contrast enhancement kinetics. This systematic investigation was performed to compare visual estimation with manual region of interest (ROI) and computer-aided diagnosis (CAD) analysis for time curve measurements in MRM.
MATERIALS AND METHODS: A total of 329 patients undergoing surgery after MRM (1.5 T) were analyzed prospectively. Dynamic data were measured using visual estimation, including ROI as well as CAD methods, and classified depending on initial signal increase and delayed enhancement.
RESULTS: Pathology revealed 469 lesions (279 malignant, 190 benign). Kappa agreement between the methods ranged from 0.78 to 0.81. Diagnostic accuracies of 74.4% (visual), 75.7% (ROI), and 76.6% (CAD) were found without statistical significant differences.
CONCLUSIONS: According to our results, curve type measurements are useful as a diagnostic criterion in breast lesions irrespective of the method used.

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Year:  2009        PMID: 19523854     DOI: 10.1016/j.acra.2009.03.017

Source DB:  PubMed          Journal:  Acad Radiol        ISSN: 1076-6332            Impact factor:   3.173


  15 in total

1.  Diffusion tensor magnetic resonance imaging of the breast: a pilot study.

Authors:  Pascal A T Baltzer; Anja Schäfer; Matthias Dietzel; David Grässel; Mieczyslaw Gajda; Oumar Camara; Werner A Kaiser
Journal:  Eur Radiol       Date:  2010-07-29       Impact factor: 5.315

2.  Kinetic analysis of lesions without mass effect on breast MRI using manual and computer-assisted methods.

Authors:  Tibor Vag; Pascal A T Baltzer; Matthias Dietzel; Ramy Zoubi; Mieczyslaw Gajda; Oumar Camara; Werner A Kaiser
Journal:  Eur Radiol       Date:  2010-11-10       Impact factor: 5.315

3.  Current Status and New Developments in Breast MRI.

Authors:  Katja C Siegmann; Bernhard Krämer; Claus Claussen
Journal:  Breast Care (Basel)       Date:  2011-04-29       Impact factor: 2.860

4.  Size assessment of breast lesions by means of a computer-aided detection (CAD) system for magnetic resonance mammography.

Authors:  G Levrini; R Sghedoni; C Mori; A Botti; R Vacondio; A Nitrosi; M Iori; F Nicoli
Journal:  Radiol Med       Date:  2011-03-19       Impact factor: 3.469

5.  Automated Semi-Quantitative Analysis of Breast MRI: Potential Imaging Biomarker for the Prediction of Tissue Response to Neoadjuvant Chemotherapy.

Authors:  Matthias Dietzel; Clemens Kaiser; Katja Pinker; Evelyn Wenkel; Matthias Hammon; Michael Uder; Barbara Bennani Baiti; Paola Clauser; Rüdiger Schulz-Wendtland; Pascal Baltzer
Journal:  Breast Care (Basel)       Date:  2017-08-29       Impact factor: 2.860

6.  2D/3D image fusion of X-ray mammograms with breast MRI: visualizing dynamic contrast enhancement in mammograms.

Authors:  Torsten Hopp; Pascal Baltzer; Matthias Dietzel; Werner A Kaiser; Nicole V Ruiter
Journal:  Int J Comput Assist Radiol Surg       Date:  2011-06-05       Impact factor: 2.924

7.  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

8.  Potential of Noncontrast Magnetic Resonance Imaging With Diffusion-Weighted Imaging in Characterization of Breast Lesions: Intraindividual Comparison With Dynamic Contrast-Enhanced Magnetic Resonance Imaging.

Authors:  Pascal A T Baltzer; Hubert Bickel; Claudio Spick; Georg Wengert; Ramona Woitek; Panagiotis Kapetas; Paola Clauser; Thomas H Helbich; Katja Pinker
Journal:  Invest Radiol       Date:  2018-04       Impact factor: 6.016

Review 9.  Computer-aided detection in breast MRI: a systematic review and meta-analysis.

Authors:  Monique D Dorrius; Marijke C Jansen-van der Weide; Peter M A van Ooijen; Ruud M Pijnappel; Matthijs Oudkerk
Journal:  Eur Radiol       Date:  2011-03-15       Impact factor: 5.315

10.  3 Tesla breast MR imaging as a problem-solving tool: Diagnostic performance and incidental lesions.

Authors:  Claudio Spick; Dieter H M Szolar; Klaus W Preidler; Pia Reittner; Katharina Rauch; Peter Brader; Manfred Tillich; Pascal A Baltzer
Journal:  PLoS One       Date:  2018-01-02       Impact factor: 3.240

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