Literature DB >> 28943704

Using ultrasound tomography to identify the distributions of density throughout the breast.

Mark Sak1, Neb Duric1, Peter Littrup1,2, Mark E Sherman3, Gretchen L Gierach4.   

Abstract

Women with high breast density are at increased risk of developing breast cancer. Breast density has usually been defined using mammography as the ratio of fibroglandular tissue to total breast area. Ultrasound tomography (UST) is an emerging modality that can also be used to measure breast density. UST creates tomographic sound speed images of the patient's breast which is useful as sound speed is directly proportional to tissue density. Furthermore, the volumetric and quantitative information contained in the sound speed images can be used to describe the distribution of breast density. The work presented here measures the UST sound speed density distributions of 165 women with negative screening mammography. Frequency distributions of the sound speed voxel information were examined for each patient. In a preliminary analysis, the UST sound speed distributions were averaged across patients and grouped by various patient and density-related factors (e.g., age, body mass index, menopausal status, average mammographic breast density). It was found that differences in the distribution of density could be easily visualized for different patient groupings. Furthermore, findings suggest that the shape of the distributions may be used to identify participants with varying amounts of dense and non-dense tissue.

Entities:  

Keywords:  Breast density; Density distribution; Sound speed; Ultrasound tomography

Year:  2016        PMID: 28943704      PMCID: PMC5609507          DOI: 10.1117/12.2217611

Source DB:  PubMed          Journal:  Proc SPIE Int Soc Opt Eng        ISSN: 0277-786X


  16 in total

1.  A first evaluation of breast radiological density assessment by QUANTRA software as compared to visual classification.

Authors:  Stefano Ciatto; Daniela Bernardi; Massimo Calabrese; Manuela Durando; Maria Adalgisa Gentilini; Giovanna Mariscotti; Francesco Monetti; Enrica Moriconi; Barbara Pesce; Antonella Roselli; Carmen Stevanin; Margherita Tapparelli; Nehmat Houssami
Journal:  Breast       Date:  2012-01-27       Impact factor: 4.380

2.  Development of ultrasound tomography for breast imaging: technical assessment.

Authors:  Nebojsa Duric; Peter Littrup; Alex Babkin; David Chambers; Stephen Azevedo; Roman Pevzner; Mikhail Tokarev; Earle Holsapple; Olsi Rama; Robert Duncan
Journal:  Med Phys       Date:  2005-05       Impact factor: 4.071

3.  Differential impact of body mass index on absolute and percent breast density: implications regarding their use as breast cancer risk biomarkers.

Authors:  Susann E Schetter; Terryl J Hartman; Jason Liao; John P Richie; Bogdan Prokopczyk; Cindy DuBrock; Carina Signori; Christopher Hamilton; Laurence M Demers; Karam El-Bayoumy; Andrea Manni
Journal:  Breast Cancer Res Treat       Date:  2014-06-21       Impact factor: 4.872

4.  Direct measurement of sound velocity in various specimens of breast tissue.

Authors:  W Weiwad; A Heinig; L Goetz; H Hartmann; D Lampe; J Buchmann; R Millner; R P Spielmann; S H Heywang-Koebrunner
Journal:  Invest Radiol       Date:  2000-12       Impact factor: 6.016

Review 5.  Mammographic density-a review on the current understanding of its association with breast cancer.

Authors:  C W Huo; G L Chew; K L Britt; W V Ingman; M A Henderson; J L Hopper; E W Thompson
Journal:  Breast Cancer Res Treat       Date:  2014-03-11       Impact factor: 4.872

6.  Breast density measurements with ultrasound tomography: a comparison with film and digital mammography.

Authors:  Neb Duric; Norman Boyd; Peter Littrup; Mark Sak; Lukasz Myc; Cuiping Li; Erik West; Sal Minkin; Lisa Martin; Martin Yaffe; Steven Schmidt; Muhammad Faiz; Jason Shen; Olga Melnichouk; Qing Li; Teri Albrecht
Journal:  Med Phys       Date:  2013-01       Impact factor: 4.071

7.  Breast density measurements using ultrasound tomography for patients undergoing tamoxifen treatment.

Authors:  Mark Sak; Neb Duric; Peter Littrup; Cuiping Li; Lisa Bey-Knight; Mark Sherman; Norman Boyd; Gretchen Gierach
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2013-03-29

8.  Dense and nondense mammographic area and risk of breast cancer by age and tumor characteristics.

Authors:  Kimberly A Bertrand; Christopher G Scott; Rulla M Tamimi; Matthew R Jensen; V Shane Pankratz; Aaron D Norman; Daniel W Visscher; Fergus J Couch; John Shepherd; Yunn-Yi Chen; Bo Fan; Fang-Fang Wu; Lin Ma; Andrew H Beck; Steven R Cummings; Karla Kerlikowske; Celine M Vachon
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2015-02-25       Impact factor: 4.254

9.  Digital mammographic density and breast cancer risk: a case-control study of six alternative density assessment methods.

Authors:  Amanda Eng; Zoe Gallant; John Shepherd; Valerie McCormack; Jingmei Li; Mitch Dowsett; Sarah Vinnicombe; Steve Allen; Isabel dos-Santos-Silva
Journal:  Breast Cancer Res       Date:  2014-09-20       Impact factor: 6.466

Review 10.  Mammographic density phenotypes and risk of breast cancer: a meta-analysis.

Authors:  Andreas Pettersson; Rebecca E Graff; Giske Ursin; Isabel Dos Santos Silva; Valerie McCormack; Laura Baglietto; Celine Vachon; Marije F Bakker; Graham G Giles; Kee Seng Chia; Kamila Czene; Louise Eriksson; Per Hall; Mikael Hartman; Ruth M L Warren; Greg Hislop; Anna M Chiarelli; John L Hopper; Kavitha Krishnan; Jingmei Li; Qing Li; Ian Pagano; Bernard A Rosner; Chia Siong Wong; Christopher Scott; Jennifer Stone; Gertraud Maskarinec; Norman F Boyd; Carla H van Gils; Rulla M Tamimi
Journal:  J Natl Cancer Inst       Date:  2014-05-10       Impact factor: 13.506

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