Literature DB >> 20142240

Screen-film mammographic density and breast cancer risk: a comparison of the volumetric standard mammogram form and the interactive threshold measurement methods.

Zoe Aitken1, Valerie A McCormack, Ralph P Highnam, Lisa Martin, Anoma Gunasekara, Olga Melnichouk, Gord Mawdsley, Chris Peressotti, Martin Yaffe, Norman F Boyd, Isabel dos Santos Silva.   

Abstract

BACKGROUND: Mammographic density is a strong risk factor for breast cancer, usually measured by an area-based threshold method that dichotomizes the breast area on a mammogram into dense and nondense regions. Volumetric methods of breast density measurement, such as the fully automated standard mammogram form (SMF) method that estimates the volume of dense and total breast tissue, may provide a more accurate density measurement and improve risk prediction.
METHODS: In 2000-2003, a case-control study was conducted of 367 newly confirmed breast cancer cases and 661 age-matched breast cancer-free controls who underwent screen-film mammography at several centers in Toronto, Canada. Conditional logistic regression was used to estimate odds ratios of breast cancer associated with categories of mammographic density, measured with both the threshold and the SMF (version 2.2beta) methods, adjusting for breast cancer risk factors.
RESULTS: Median percent density was higher in cases than in controls for the threshold method (31% versus 27%) but not for the SMF method. Higher correlations were observed between SMF and threshold measurements for breast volume/area (Spearman correlation coefficient = 0.95) than for percent density (0.68) or for absolute density (0.36). After adjustment for breast cancer risk factors, odds ratios of breast cancer in the highest compared with the lowest quintile of percent density were 2.19 (95% confidence interval, 1.28-3.72; P(t) <0.01) for the threshold method and 1.27 (95% confidence interval, 0.79-2.04; Pt = 0.32) for the SMF method.
CONCLUSION: Threshold percent density is a stronger predictor of breast cancer risk than the SMF version 2.2beta method in digitized images.

Entities:  

Mesh:

Year:  2010        PMID: 20142240      PMCID: PMC2875111          DOI: 10.1158/1055-9965.EPI-09-1059

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


  17 in total

1.  Novel use of single X-ray absorptiometry for measuring breast density.

Authors:  John A Shepherd; Lionel Herve; Jessie Landau; Bo Fan; Karla Kerlikowske; Steve R Cummings
Journal:  Technol Cancer Res Treat       Date:  2005-04

2.  Measurements of breast density: no ratio for a ratio.

Authors:  Gerco Haars; Paulus A H van Noord; Carla H van Gils; Diederick E Grobbee; Petra H M Peeters
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2005-11       Impact factor: 4.254

3.  The quantitative analysis of mammographic densities.

Authors:  J W Byng; N F Boyd; E Fishell; R A Jong; M J Yaffe
Journal:  Phys Med Biol       Date:  1994-10       Impact factor: 3.609

4.  Volumetric breast density estimation from full-field digital mammograms.

Authors:  Saskia van Engeland; Peter R Snoeren; Henkjan Huisman; Carla Boetes; Nico Karssemeijer
Journal:  IEEE Trans Med Imaging       Date:  2006-03       Impact factor: 10.048

5.  Mammographic parenchymal patterns and quantitative evaluation of mammographic densities: a case-control study.

Authors:  J N Wolfe; A F Saftlas; M Salane
Journal:  AJR Am J Roentgenol       Date:  1987-06       Impact factor: 3.959

6.  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

7.  Mammographic parenchymal patterns. Risk indicator for breast cancer?

Authors:  L Tabár; P B Dean
Journal:  JAMA       Date:  1982-01-08       Impact factor: 56.272

8.  Mammographic density and breast cancer risk: evaluation of a novel method of measuring breast tissue volumes.

Authors:  Norman Boyd; Lisa Martin; Anoma Gunasekara; Olga Melnichouk; Gord Maudsley; Chris Peressotti; Martin Yaffe; Salomon Minkin
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2009-06       Impact factor: 4.254

9.  Initial experiences of using an automated volumetric measure of breast density: the standard mammogram form.

Authors:  M Jeffreys; R Warren; R Highnam; G Davey Smith
Journal:  Br J Radiol       Date:  2006-05       Impact factor: 3.039

10.  Breast composition measurements using retrospective standard mammogram form (SMF).

Authors:  R Highnam; X Pan; R Warren; M Jeffreys; G Davey Smith; M Brady
Journal:  Phys Med Biol       Date:  2006-05-09       Impact factor: 3.609

View more
  41 in total

Review 1.  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

2.  The effect of change in body mass index on volumetric measures of mammographic density.

Authors:  Vicki Hart; Katherine W Reeves; Susan R Sturgeon; Nicholas G Reich; Lynnette Leidy Sievert; Karla Kerlikowske; Lin Ma; John Shepherd; Jeffrey A Tice; Amir Pasha Mahmoudzadeh; Serghei Malkov; Brian L Sprague
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2015-08-27       Impact factor: 4.254

3.  Methods for assessing and representing mammographic density: an analysis of 4 case-control studies.

Authors:  Christy G Woolcott; Shannon M Conroy; Chisato Nagata; Giske Ursin; Celine M Vachon; Martin J Yaffe; Ian S Pagano; Celia Byrne; Gertraud Maskarinec
Journal:  Am J Epidemiol       Date:  2013-10-11       Impact factor: 4.897

4.  Reproductive factors related to childbearing and mammographic breast density.

Authors:  Lusine Yaghjyan; Graham A Colditz; Bernard Rosner; Kimberly A Bertrand; Rulla M Tamimi
Journal:  Breast Cancer Res Treat       Date:  2016-06-28       Impact factor: 4.872

5.  Associations of aspirin and other anti-inflammatory medications with mammographic breast density and breast cancer risk.

Authors:  Lusine Yaghjyan; Akemi Wijayabahu; A Heather Eliassen; Graham Colditz; Bernard Rosner; Rulla M Tamimi
Journal:  Cancer Causes Control       Date:  2020-05-31       Impact factor: 2.506

6.  Association of multiple genetic variants with breast cancer susceptibility in the Han Chinese population.

Authors:  Xu Li; Wenjing Zou; Ming Liu; Wei Cao; Yonghong Jiang; Gaili An; Yuzheng Wang; Shangke Huang; Xinhan Zhao
Journal:  Oncotarget       Date:  2016-12-20

7.  Volume of mammographic density and risk of breast cancer.

Authors:  John A Shepherd; Karla Kerlikowske; Lin Ma; Frederick Duewer; Bo Fan; Jeff Wang; Serghei Malkov; Eric Vittinghoff; Steven R Cummings
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2011-05-24       Impact factor: 4.254

8.  Computer-aided assessment of breast density: comparison of supervised deep learning and feature-based statistical learning.

Authors:  Songfeng Li; Jun Wei; Heang-Ping Chan; Mark A Helvie; Marilyn A Roubidoux; Yao Lu; Chuan Zhou; Lubomir M Hadjiiski; Ravi K Samala
Journal:  Phys Med Biol       Date:  2018-01-09       Impact factor: 3.609

9.  Reported mammographic density: film-screen versus digital acquisition.

Authors:  Jennifer A Harvey; Charlotte C Gard; Diana L Miglioretti; Bonnie C Yankaskas; Karla Kerlikowske; Diana S M Buist; Berta A Geller; Tracy L Onega
Journal:  Radiology       Date:  2012-12-18       Impact factor: 11.105

10.  Racial Differences in Quantitative Measures of Area and Volumetric Breast Density.

Authors:  Anne Marie McCarthy; Brad M Keller; Lauren M Pantalone; Meng-Kang Hsieh; Marie Synnestvedt; Emily F Conant; Katrina Armstrong; Despina Kontos
Journal:  J Natl Cancer Inst       Date:  2016-04-29       Impact factor: 13.506

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.