Literature DB >> 25146640

Measurement of breast density with digital breast tomosynthesis--a systematic review.

E U Ekpo1, M F McEntee.   

Abstract

Digital breast tomosynthesis (DBT) has gained acceptance as an adjunct to digital mammography in screening. Now that breast density reporting is mandated in several states in the USA, it is increasingly important that the methods of breast density measurement be robust, reliable and consistent. Breast density assessment with DBT needs some consideration since quantitative methods are modelled for two-dimensional (2D) mammography. A review of methods used for breast density assessment with DBT was performed. Existing evidence shows Cumulus has better reproducibility than that of the breast imaging reporting and data system (BI-RADS®) but still suffers from subjective variability; MedDensity is limited by image noise, whilst Volpara and Quantra are robust and consistent. The reported BI-RADs inter-reader breast density agreement (k) ranged from 0.65 to 0.91, with inter-reader correlation (r) ranging from 0.70 to 0.93. The correlation (r) between BI-RADS and Cumulus ranged from 0.54-0.94, whilst that of BI-RADs and MedDensity ranged from 0.48-0.78. The reported agreement (k) between BI-RADs and Volpara is 0.953. Breast density correlation between DBT and 2D mammography ranged from 0.73 to 0.97, with agreement (k) ranging from 0.56 to 0.96. To avoid variability and provide more reliable breast density information for clinicians, automated volumetric methods are preferred.

Mesh:

Year:  2014        PMID: 25146640      PMCID: PMC4207156          DOI: 10.1259/bjr.20140460

Source DB:  PubMed          Journal:  Br J Radiol        ISSN: 0007-1285            Impact factor:   3.039


  53 in total

1.  Diagnostic accuracy of digital versus film mammography: exploratory analysis of selected population subgroups in DMIST.

Authors:  Etta D Pisano; R Edward Hendrick; Martin J Yaffe; Janet K Baum; Suddhasatta Acharyya; Jean B Cormack; Lucy A Hanna; Emily F Conant; Laurie L Fajardo; Lawrence W Bassett; Carl J D'Orsi; Roberta A Jong; Murray Rebner; Anna N A Tosteson; Constantine A Gatsonis
Journal:  Radiology       Date:  2008-02       Impact factor: 11.105

2.  Mammographic density estimation: comparison among BI-RADS categories, a semi-automated software and a fully automated one.

Authors:  Alberto Tagliafico; Giulio Tagliafico; Simona Tosto; Fabio Chiesa; Carlo Martinoli; Lorenzo E Derchi; Massimo Calabrese
Journal:  Breast       Date:  2008-11-17       Impact factor: 4.380

3.  Mammographic density correlation with Gail model breast cancer risk estimates and component risk factors.

Authors:  Melanie R Palomares; Joelle R B Machia; Constance D Lehman; Janet R Daling; Anne McTiernan
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2006-07       Impact factor: 4.254

4.  Parenchymal texture analysis in digital breast tomosynthesis for breast cancer risk estimation: a preliminary study.

Authors:  Despina Kontos; Predrag R Bakic; Ann-Katherine Carton; Andrea B Troxel; Emily F Conant; Andrew D A Maidment
Journal:  Acad Radiol       Date:  2009-03       Impact factor: 3.173

5.  Reproducibility of visual assessment on mammographic density.

Authors:  Jinnan Gao; Ruth Warren; Helen Warren-Forward; John F Forbes
Journal:  Breast Cancer Res Treat       Date:  2007-07-07       Impact factor: 4.872

6.  Dense breast stromal tissue shows greatly increased concentration of breast epithelium but no increase in its proliferative activity.

Authors:  Debra Hawes; Susan Downey; Celeste Leigh Pearce; Sue Bartow; Peggy Wan; Malcolm C Pike; Anna H Wu
Journal:  Breast Cancer Res       Date:  2006-04-28       Impact factor: 6.466

7.  Collagen reorganization at the tumor-stromal interface facilitates local invasion.

Authors:  Paolo P Provenzano; Kevin W Eliceiri; Jay M Campbell; David R Inman; John G White; Patricia J Keely
Journal:  BMC Med       Date:  2006-12-26       Impact factor: 8.775

8.  Comparing measurements of breast density.

Authors:  R Highnam; M Jeffreys; V McCormack; R Warren; G Davey Smith; M Brady
Journal:  Phys Med Biol       Date:  2007-09-14       Impact factor: 3.609

9.  Visually assessed breast density, breast cancer risk and the importance of the craniocaudal view.

Authors:  Stephen W Duffy; Iris D Nagtegaal; Susan M Astley; Maureen G C Gillan; Magnus A McGee; Caroline R M Boggis; Mary Wilson; Ursula M Beetles; Miriam A Griffiths; Anil K Jain; Jill Johnson; Rita Roberts; Heather Deans; Karen A Duncan; Geeta Iyengar; Pam M Griffiths; Jane Warwick; Jack Cuzick; Fiona J Gilbert
Journal:  Breast Cancer Res       Date:  2008-07-23       Impact factor: 6.466

10.  Comparison of a new and existing method of mammographic density measurement: intramethod reliability and associations with known risk factors.

Authors:  Valerie A McCormack; Ralph Highnam; Nicholas Perry; Isabel dos Santos Silva
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2007-06       Impact factor: 4.254

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  16 in total

1.  An Evaluation of Performance Characteristics of Primary Display Devices.

Authors:  Ernest U Ekpo; Mark F McEntee
Journal:  J Digit Imaging       Date:  2016-04       Impact factor: 4.056

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.  Intercountry analysis of breast density classification using visual grading.

Authors:  Christine N Damases; Peter Hogg; Mark F McEntee
Journal:  Br J Radiol       Date:  2017-06-14       Impact factor: 3.039

4.  Integrating mammographic breast density in glandular dose calculation.

Authors:  Moayyad E Suleiman; Patrick C Brennan; Ernest Ekpo; Peter Kench; Mark F McEntee
Journal:  Br J Radiol       Date:  2018-02-13       Impact factor: 3.039

5.  Automated mammographic density measurement using Quantra™: comparison with the Royal Australian and New Zealand College of Radiology synoptic scale.

Authors:  Inez Yeo; Judith Akwo; Ernest Ekpo
Journal:  J Med Imaging (Bellingham)       Date:  2020-05-29

Review 6.  Chemical Effects on Breast Development, Function, and Cancer Risk: Existing Knowledge and New Opportunities.

Authors:  Jennifer E Kay; Bethsaida Cardona; Ruthann A Rudel; Laura N Vandenberg; Ana M Soto; Sofie Christiansen; Linda S Birnbaum; Suzanne E Fenton
Journal:  Curr Environ Health Rep       Date:  2022-08-19

7.  Association between mammographic breast composition and breast cancer risk among Japanese women: a retrospective cohort study.

Authors:  Toshifumi Namba; Naoko Matsuda; Mahbubur Rahman; Naoki Kanomata; Hideko Yamauchi; Hiroko Tsunoda
Journal:  Breast Cancer       Date:  2022-07-13       Impact factor: 3.307

8.  Relationship Between Breast Density and Selective Estrogen-Receptor Modulators, Aromatase Inhibitors, Physical Activity, and Diet: A Systematic Review.

Authors:  Ernest U Ekpo; Patrick C Brennan; Claudia Mello-Thoms; Mark F McEntee
Journal:  Integr Cancer Ther       Date:  2016-04-29       Impact factor: 3.279

Review 9.  Breast density implications and supplemental screening.

Authors:  Athina Vourtsis; Wendie A Berg
Journal:  Eur Radiol       Date:  2018-09-25       Impact factor: 5.315

Review 10.  Raised mammographic density: causative mechanisms and biological consequences.

Authors:  Michael J Sherratt; James C McConnell; Charles H Streuli
Journal:  Breast Cancer Res       Date:  2016-05-03       Impact factor: 6.466

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