Literature DB >> 18227535

Basic physics and doubts about relationship between mammographically determined tissue density and breast cancer risk.

Daniel B Kopans1.   

Abstract

Numerous studies have suggested a link between breast tissue patterns, as defined with mammography, and risk for breast cancer. There may be a relationship, but the author believes all of these studies have methodological flaws. It is impossible, with the parameters used in these studies, to accurately measure the percentage of tissues by volume when two-dimensional x-ray mammographic images are used. Without exposure values, half-value layer information, and knowledge of the compressed thickness of the breast, an accurate volume of tissue cannot be calculated. The great variability in positioning the breast for a mammogram is also an uncontrollable factor in measuring tissue density. Computerized segmentation algorithms can accurately assess the percentage of the x-ray image that is "dense," but this does not accurately measure the true volume of tissue. Since the percentage of dense tissue is ultimately measured in relation to the complete volume of the breast, defining the true boundaries of the breast is also a problem. Studies that purport to show small percentage differences between groups are likely inaccurate. Future investigations need to use three-dimensional information. (c) RSNA, 2008.

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Year:  2008        PMID: 18227535     DOI: 10.1148/radiol.2461070309

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


  58 in total

1.  Fully Automated Quantitative Estimation of Volumetric Breast Density from Digital Breast Tomosynthesis Images: Preliminary Results and Comparison with Digital Mammography and MR Imaging.

Authors:  Said Pertuz; Elizabeth S McDonald; Susan P Weinstein; Emily F Conant; Despina Kontos
Journal:  Radiology       Date:  2015-10-21       Impact factor: 11.105

2.  Quantra™ should be considered a tool for two-grade scale mammographic breast density classification.

Authors:  Ernest U Ekpo; Mark F McEntee; Mary Rickard; Patrick C Brennan; Jyotsna Kunduri; Delgermaa Demchig; Claudia Mello-Thoms
Journal:  Br J Radiol       Date:  2016-02-16       Impact factor: 3.039

3.  Adaptive multi-cluster fuzzy C-means segmentation of breast parenchymal tissue in digital mammography.

Authors:  Brad Keller; Diane Nathan; Yan Wang; Yuanjie Zheng; James Gee; Emily Conant; Despina Kontos
Journal:  Med Image Comput Comput Assist Interv       Date:  2011

4.  Quantification of breast density with dual energy mammography: a simulation study.

Authors:  Justin L Ducote; Sabee Molloi
Journal:  Med Phys       Date:  2008-12       Impact factor: 4.071

5.  Automated fibroglandular tissue segmentation and volumetric density estimation in breast MRI using an atlas-aided fuzzy C-means method.

Authors:  Shandong Wu; Susan P Weinstein; Emily F Conant; Despina Kontos
Journal:  Med Phys       Date:  2013-12       Impact factor: 4.071

6.  Computer-aided diagnosis of breast DCE-MRI images using bilateral asymmetry of contrast enhancement between two breasts.

Authors:  Qian Yang; Lihua Li; Juan Zhang; Guoliang Shao; Chengjie Zhang; Bin Zheng
Journal:  J Digit Imaging       Date:  2014-02       Impact factor: 4.056

7.  Breast density estimation from high spectral and spatial resolution MRI.

Authors:  Hui Li; William A Weiss; Milica Medved; Hiroyuki Abe; Gillian M Newstead; Gregory S Karczmar; Maryellen L Giger
Journal:  J Med Imaging (Bellingham)       Date:  2016-12-28

8.  Development of a quantitative method for analysis of breast density based on three-dimensional breast MRI.

Authors:  Ke Nie; Jeon-Hor Chen; Siwa Chan; Man-Kwun I Chau; Hon J Yu; Shadfar Bahri; Tiffany Tseng; Orhan Nalcioglu; Min-Ying Su
Journal:  Med Phys       Date:  2008-12       Impact factor: 4.071

Review 9.  Review of quantitative multiscale imaging of breast cancer.

Authors:  Michael A Pinkert; Lonie R Salkowski; Patricia J Keely; Timothy J Hall; Walter F Block; Kevin W Eliceiri
Journal:  J Med Imaging (Bellingham)       Date:  2018-01-22

10.  Using Speed of Sound Imaging to Characterize Breast Density.

Authors:  Mark Sak; Neb Duric; Peter Littrup; Lisa Bey-Knight; Haythem Ali; Patricia Vallieres; Mark E Sherman; Gretchen L Gierach
Journal:  Ultrasound Med Biol       Date:  2016-09-29       Impact factor: 2.998

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