Literature DB >> 9865433

Mammographic densities and breast cancer risk.

N F Boyd1, G A Lockwood, J W Byng, D L Tritchler, M J Yaffe.   

Abstract

The radiological appearance of the female breast varies among individuals because of differences in the relative amounts and X-ray attenuation characteristics of fat and epithelial and stromal tissues. Fat is radiolucent and appears dark on a mammogram, and epithelium and stroma are radiodense and appear light. We review here the evidence that these variations, known as mammographic parenchymal patterns, are related to risk of breast cancer. Studies that used quantitative measurement to classify mammographic patterns have consistently found that women with dense tissue in more than 60-75% of the breast are at four to six times greater risk of breast cancer than those with no densities. These risk estimates are independent of the effects of other risk factors and have been shown to persist over at least 10 years of follow up. Estimates of attributable risk suggest that this risk factor may account for as many as 30% of breast cancer cases. Mammographically dense breast tissue is associated both with epithelial proliferation and with stromal fibrosis. The relationship between these histological features and risk of breast cancer may by explained by the known actions of growth factors that are thought to play important roles in breast development and carcinogenesis. Mammographically dense tissue differs from most other breast cancer risk factors in the strength of the associated relative and attributable risks for breast cancer, and because it can be changed by hormonal and dietary interventions. This risk factor may be most useful as a means of investigating the etiology of breast cancer and of testing hypotheses about potential preventive strategies.

Entities:  

Mesh:

Year:  1998        PMID: 9865433

Source DB:  PubMed          Journal:  Cancer Epidemiol Biomarkers Prev        ISSN: 1055-9965            Impact factor:   4.254


  205 in total

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2.  Mammographic density and risk of breast cancer by adiposity: an analysis of four case-control studies.

Authors:  Shannon M Conroy; Christy G Woolcott; Karin R Koga; Celia Byrne; Chisato Nagata; Giske Ursin; Celine M Vachon; Martin J Yaffe; Ian Pagano; Gertraud Maskarinec
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Review 3.  Clinical and epidemiological issues in mammographic density.

Authors:  Valentina Assi; Jane Warwick; Jack Cuzick; Stephen W Duffy
Journal:  Nat Rev Clin Oncol       Date:  2011-12-06       Impact factor: 66.675

Review 4.  Extracellular matrix composition reveals complex and dynamic stromal-epithelial interactions in the mammary gland.

Authors:  Ori Maller; Holly Martinson; Pepper Schedin
Journal:  J Mammary Gland Biol Neoplasia       Date:  2010-09-02       Impact factor: 2.673

Review 5.  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

6.  Reduction of dietary glycaemic load modifies the expression of microRNA potentially associated with energy balance and cancer pathways in pre-menopausal women.

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

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8.  Randomized Double-Blind Placebo-Controlled Biomarker Modulation Study of Vitamin D Supplementation in Premenopausal Women at High Risk for Breast Cancer (SWOG S0812).

Authors:  Katherine D Crew; Garnet L Anderson; Dawn L Hershman; Mary Beth Terry; Parisa Tehranifar; Danika L Lew; Monica Yee; Eric A Brown; Sebastien S Kairouz; Nafisa Kuwajerwala; Therese Bevers; John E Doster; Corrine Zarwan; Laura Kruper; Lori M Minasian; Leslie Ford; Banu Arun; Marian Neuhouser; Gary E Goodman; Powel H Brown
Journal:  Cancer Prev Res (Phila)       Date:  2019-05-28

9.  Breast cancer cell-derived matrix supports vascular morphogenesis.

Authors:  Abigail C Hielscher; Connie Qiu; Sharon Gerecht
Journal:  Am J Physiol Cell Physiol       Date:  2012-01-25       Impact factor: 4.249

10.  Adaptable near-infrared spectroscopy fiber array for improved coupling to different breast sizes during clinical MRI.

Authors:  Michael A Mastanduno; Fadi El-Ghussein; Shudong Jiang; Roberta Diflorio-Alexander; Xu Junqing; Yin Hong; Brian W Pogue; Keith D Paulsen
Journal:  Acad Radiol       Date:  2014-02       Impact factor: 3.173

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