Literature DB >> 20095256

The myth of the 50-50 breast.

M J Yaffe1, J M Boone, N Packard, O Alonzo-Proulx, S Y Huang, C L Peressotti, A Al-Mayah, K Brock.   

Abstract

PURPOSE: For dosimetry and for work in optimization of x-ray imaging of the breast, it is commonly assumed that the breast is composed of 50% fibroglandular tissue and 50% fat. The purpose of this study was to assess whether this assumption was realistic.
METHODS: First, data obtained from an experimental breast CT scanner were used to validate an algorithm that measures breast density from digitized film mammograms. Density results obtained from a total of 2831 women, including 191 women receiving CT and from mammograms of 2640 women from three other groups, were then used to estimate breast compositions.
RESULTS: Mean compositions, expressed as percent fibroglandular tissue (including the skin), varied from 13.7% to 25.6% among the groups with an overall mean of 19.3%. The mean compressed breast thickness for the mammograms was 5.9 cm (sigma = 1.6 cm). 80% of the women in our study had volumetric breast density less than 27% and 95% were below 45%.
CONCLUSIONS: Based on the results obtained from the four groups of women in our study, the "50-50" breast is not a representative model of the breast composition.

Entities:  

Mesh:

Year:  2009        PMID: 20095256      PMCID: PMC2787062          DOI: 10.1118/1.3250863

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  28 in total

1.  Measurement of breast density with dual X-ray absorptiometry: feasibility.

Authors:  John A Shepherd; Karla M Kerlikowske; Rebecca Smith-Bindman; Harry K Genant; Steve R Cummings
Journal:  Radiology       Date:  2002-05       Impact factor: 11.105

2.  A volumetric method for estimation of breast density on digitized screen-film mammograms.

Authors:  Olga Pawluczyk; Bindu J Augustine; Martin J Yaffe; Dan Rico; Jiwei Yang; Gordon E Mawdsley; Norman F Boyd
Journal:  Med Phys       Date:  2003-03       Impact factor: 4.071

3.  Additional factors for the estimation of mean glandular breast dose using the UK mammography dosimetry protocol.

Authors:  D R Dance; C L Skinner; K C Young; J R Beckett; C J Kotre
Journal:  Phys Med Biol       Date:  2000-11       Impact factor: 3.609

4.  Accurate estimation of compressed breast thickness in mammography.

Authors:  Gordon E Mawdsley; Albert H Tyson; Chris L Peressotti; Roberta A Jong; Martin J Yaffe
Journal:  Med Phys       Date:  2009-02       Impact factor: 4.071

5.  Absorbed radiation dose in mammography.

Authors:  G R Hammerstein; D W Miller; D R White; M E Masterson; H Q Woodard; J S Laughlin
Journal:  Radiology       Date:  1979-02       Impact factor: 11.105

6.  Dosage evaluation in mammography.

Authors:  L Stanton; T Villafana; J L Day; D A Lightfoot
Journal:  Radiology       Date:  1984-02       Impact factor: 11.105

7.  A calibration approach to glandular tissue composition estimation in digital mammography.

Authors:  J Kaufhold; J A Thomas; J W Eberhard; C E Galbo; D E González Trotter
Journal:  Med Phys       Date:  2002-08       Impact factor: 4.071

8.  Individual and combined effects of age, breast density, and hormone replacement therapy use on the accuracy of screening mammography.

Authors:  Patricia A Carney; Diana L Miglioretti; Bonnie C Yankaskas; Karla Kerlikowske; Robert Rosenberg; Carolyn M Rutter; Berta M Geller; Linn A Abraham; Steven H Taplin; Mark Dignan; Gary Cutter; Rachel Ballard-Barbash
Journal:  Ann Intern Med       Date:  2003-02-04       Impact factor: 25.391

9.  Factors contributing to mammography failure in women aged 40-49 years.

Authors:  Diana S M Buist; Peggy L Porter; Constance Lehman; Stephen H Taplin; Emily White
Journal:  J Natl Cancer Inst       Date:  2004-10-06       Impact factor: 13.506

10.  Mammographic signs as risk factors for breast cancer.

Authors:  N F Boyd; B O'Sullivan; J E Campbell; E Fishell; I Simor; G Cooke; T Germanson
Journal:  Br J Cancer       Date:  1982-02       Impact factor: 7.640

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  80 in total

1.  Dedicated breast CT: radiation dose for circle-plus-line trajectory.

Authors:  Srinivasan Vedantham; Linxi Shi; Andrew Karellas; Frederic Noo
Journal:  Med Phys       Date:  2012-03       Impact factor: 4.071

2.  Automated detection of mass lesions in dedicated breast CT: a preliminary study.

Authors:  I Reiser; R M Nishikawa; M L Giger; J M Boone; K K Lindfors; K Yang
Journal:  Med Phys       Date:  2012-02       Impact factor: 4.071

3.  A statistically defined anthropomorphic software breast phantom.

Authors:  Beverly A Lau; Ingrid Reiser; Robert M Nishikawa; Predrag R Bakic
Journal:  Med Phys       Date:  2012-06       Impact factor: 4.071

Review 4.  Breast tissue composition and susceptibility to breast cancer.

Authors:  Norman F Boyd; Lisa J Martin; Michael Bronskill; Martin J Yaffe; Neb Duric; Salomon Minkin
Journal:  J Natl Cancer Inst       Date:  2010-07-08       Impact factor: 13.506

5.  Dosimetric characterization of a dedicated breast computed tomography clinical prototype.

Authors:  Ioannis Sechopoulos; Steve Si Jia Feng; Carl J D'Orsi
Journal:  Med Phys       Date:  2010-08       Impact factor: 4.071

6.  Breast dose in mammography is about 30% lower when realistic heterogeneous glandular distributions are considered.

Authors:  Andrew M Hernandez; J Anthony Seibert; John M Boone
Journal:  Med Phys       Date:  2015-11       Impact factor: 4.071

7.  Population of 224 realistic human subject-based computational breast phantoms.

Authors:  David W Erickson; Jered R Wells; Gregory M Sturgeon; Ehsan Samei; James T Dobbins; W Paul Segars; Joseph Y Lo
Journal:  Med Phys       Date:  2016-01       Impact factor: 4.071

8.  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

9.  Breast tissue characterization with photon-counting spectral CT imaging: a postmortem breast study.

Authors:  Huanjun Ding; Michael J Klopfer; Justin L Ducote; Fumitaro Masaki; Sabee Molloi
Journal:  Radiology       Date:  2014-05-07       Impact factor: 11.105

10.  Association between power law coefficients of the anatomical noise power spectrum and lesion detectability in breast imaging modalities.

Authors:  Lin Chen; Craig K Abbey; John M Boone
Journal:  Phys Med Biol       Date:  2013-02-19       Impact factor: 3.609

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