Literature DB >> 1260729

Risk for breast cancer development determined by mammographic parenchymal pattern.

J N Wolfe.   

Abstract

A classification of risk for developing breast cancer has been devised based solely on the appearance of the breast parenchyma by mammography. Four groups of patients were isolated. The study encompassed a five-year period and was done by reviewing the mammograms of all women over the age of 30 who had been examined at Hutzel Hospital, Detroit. The average time of followup would be approximately 2 1/2 years. Four groups had an incidence of developing breast cancer of 0.1, 0.4, 1.7, and 2.2. These parenchymal patterns are described and criteria for their identification are given.

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Year:  1976        PMID: 1260729     DOI: 10.1002/1097-0142(197605)37:5<2486::aid-cncr2820370542>3.0.co;2-8

Source DB:  PubMed          Journal:  Cancer        ISSN: 0008-543X            Impact factor:   6.860


  137 in total

Review 1.  Mammographic densities as a marker of human breast cancer risk and their use in chemoprevention.

Authors:  N F Boyd; L J Martin; J Stone; C Greenberg; S Minkin; M J Yaffe
Journal:  Curr Oncol Rep       Date:  2001-07       Impact factor: 5.075

2.  Segmentation of the fibro-glandular disc in mammograms using Gaussian mixture modelling.

Authors:  R J Ferrari; R M Rangayyan; R A Borges; A F Frère
Journal:  Med Biol Eng Comput       Date:  2004-05       Impact factor: 2.602

3.  Interobserver agreement in breast radiological density attribution according to BI-RADS quantitative classification.

Authors:  D Bernardi; M Pellegrini; S Di Michele; P Tuttobene; C Fantò; M Valentini; M Gentilini; S Ciatto
Journal:  Radiol Med       Date:  2012-01-07       Impact factor: 3.469

4.  Biochemical and mechanical extracellular matrix properties dictate mammary epithelial cell motility and assembly.

Authors:  Olga Shebanova; Daniel A Hammer
Journal:  Biotechnol J       Date:  2011-12-16       Impact factor: 4.677

5.  Automatic breast parenchymal density classification integrated into a CADe system.

Authors:  G Bueno; N Vállez; O Déniz; P Esteve; M A Rienda; M Arias; C Pastor
Journal:  Int J Comput Assist Radiol Surg       Date:  2010-08-05       Impact factor: 2.924

6.  X-ray absorptiometry of the breast using mammographic exposure factors: application to units featuring automatic beam quality selection.

Authors:  C J Kotre
Journal:  Br J Radiol       Date:  2010-06       Impact factor: 3.039

Review 7.  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

8.  Quantification of breast density with spectral mammography based on a scanned multi-slit photon-counting detector: a feasibility study.

Authors:  Huanjun Ding; Sabee Molloi
Journal:  Phys Med Biol       Date:  2012-07-06       Impact factor: 3.609

9.  Parenchymal texture analysis in digital mammography: robust texture feature identification and equivalence across devices.

Authors:  Brad M Keller; Andrew Oustimov; Yan Wang; Jinbo Chen; Raymond J Acciavatti; Yuanjie Zheng; Shonket Ray; James C Gee; Andrew D A Maidment; Despina Kontos
Journal:  J Med Imaging (Bellingham)       Date:  2015-04-03

10.  Role of equalisation mammography of dense breasts.

Authors:  D B Plewes; J M Sabol; I Soutar; A Chevrier; R Shumak
Journal:  Med Biol Eng Comput       Date:  1995-03       Impact factor: 2.602

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