Literature DB >> 26520725

Breast dose in mammography is about 30% lower when realistic heterogeneous glandular distributions are considered.

Andrew M Hernandez1, J Anthony Seibert2, John M Boone2.   

Abstract

PURPOSE: Current dosimetry methods in mammography assume that the breast is comprised of a homogeneous mixture of glandular and adipose tissues. Three-dimensional (3D) dedicated breast CT (bCT) data sets were used previously to assess the complex anatomical structure within the breast, characterizing the statistical distribution of glandular tissue in the breast. The purpose of this work was to investigate the effect of bCT-derived heterogeneous glandular distributions on dosimetry in mammography.
METHODS: bCT-derived breast diameters, volumes, and 3D fibroglandular distributions were used to design realistic compressed breast models comprised of heterogeneous distributions of glandular tissue. The bCT-derived glandular distributions were fit to biGaussian functions and used as probability density maps to assign the density distributions within compressed breast models. The MCNPX 2.6.0 Monte Carlo code was used to estimate monoenergetic normalized mean glandular dose "DgN(E)" values in mammography geometry. The DgN(E) values were then weighted by typical mammography x-ray spectra to determine polyenergetic DgN (pDgN) coefficients for heterogeneous (pDgNhetero) and homogeneous (pDgNhomo) cases. The dependence of estimated pDgN values on phantom size, volumetric glandular fraction (VGF), x-ray technique factors, and location of the heterogeneous glandular distributions was investigated.
RESULTS: The pDgNhetero coefficients were on average 35.3% (SD, 4.1) and 24.2% (SD, 3.0) lower than the pDgNhomo coefficients for the Mo-Mo and W-Rh x-ray spectra, respectively, across all phantom sizes and VGFs when the glandular distributions were centered within the breast phantom in the coronal plane. At constant breast size, increasing VGF from 7.3% to 19.1% lead to a reduction in pDgNhetero relative to pDgNhomo of 23.6%-27.4% for a W-Rh spectrum. Displacement of the glandular distribution, at a distance equal to 10% of the compressed breast width in the superior and inferior directions, resulted in a 37.3% and a -26.6% change in the pDgNhetero coefficient, respectively, relative to the centered distribution for the Mo-Mo spectrum. Lateral displacement of the glandular distribution, at a distance equal to 10% of the compressed breast width, resulted in a 1.5% change in the pDgNhetero coefficient relative to the centered distribution for the W-Rh spectrum.
CONCLUSIONS: Introducing bCT-derived heterogeneous glandular distributions into mammography phantom design resulted in decreased glandular dose relative to the widely used homogeneous assumption. A homogeneous distribution overestimates the amount of glandular tissue near the entrant surface of the breast, where dose deposition is exponentially higher. While these findings are based on clinically measured distributions of glandular tissue using a large cohort of women, future work is required to improve the classification of glandular distributions based on breast size and overall glandular fraction.

Entities:  

Mesh:

Year:  2015        PMID: 26520725      PMCID: PMC4600085          DOI: 10.1118/1.4931966

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  15 in total

1.  Monte Carlo calculation of conversion factors for the estimation of mean glandular breast dose.

Authors:  D R Dance
Journal:  Phys Med Biol       Date:  1990-09       Impact factor: 3.609

2.  Spectral dependence of glandular tissue dose in screen-film mammography.

Authors:  X Wu; G T Barnes; D M Tucker
Journal:  Radiology       Date:  1991-04       Impact factor: 11.105

3.  Monte Carlo reference data sets for imaging research: Executive summary of the report of AAPM Research Committee Task Group 195.

Authors:  Ioannis Sechopoulos; Elsayed S M Ali; Andreu Badal; Aldo Badano; John M Boone; Iacovos S Kyprianou; Ernesto Mainegra-Hing; Kyle L McMillan; Michael F McNitt-Gray; D W O Rogers; Ehsan Samei; Adam C Turner
Journal:  Med Phys       Date:  2015-10       Impact factor: 4.071

4.  Breast dosimetry using high-resolution voxel phantoms.

Authors:  D R Dance; R A Hunt; P R Bakic; A D A Maidment; M Sandborg; G Ullman; G Alm Carlsson
Journal:  Radiat Prot Dosimetry       Date:  2005       Impact factor: 0.972

5.  Characterization of the homogeneous tissue mixture approximation in breast imaging dosimetry.

Authors:  Ioannis Sechopoulos; Kristina Bliznakova; Xulei Qin; Baowei Fei; Steve Si Jia Feng
Journal:  Med Phys       Date:  2012-08       Impact factor: 4.071

6.  The myth of the 50-50 breast.

Authors:  M J Yaffe; J M Boone; N Packard; O Alonzo-Proulx; S Y Huang; C L Peressotti; A Al-Mayah; K Brock
Journal:  Med Phys       Date:  2009-12       Impact factor: 4.071

7.  The effect of skin thickness determined using breast CT on mammographic dosimetry.

Authors:  Shih-Ying Huang; John M Boone; Kai Yang; Alexander L C Kwan; Nathan J Packard
Journal:  Med Phys       Date:  2008-04       Impact factor: 4.071

8.  Simulation of mechanical compression of breast tissue.

Authors:  Albert L Kellner; Thomas R Nelson; Laura I Cerviño; John M Boone
Journal:  IEEE Trans Biomed Eng       Date:  2007-10       Impact factor: 4.538

9.  Normalized average glandular dose in molybdenum target-rhodium filter and rhodium target-rhodium filter mammography.

Authors:  X Wu; E L Gingold; G T Barnes; D M Tucker
Journal:  Radiology       Date:  1994-10       Impact factor: 11.105

10.  The characterization of breast anatomical metrics using dedicated breast CT.

Authors:  Shih-Ying Huang; John M Boone; Kai Yang; Nathan J Packard; Sarah E McKenney; Nicolas D Prionas; Karen K Lindfors; Martin J Yaffe
Journal:  Med Phys       Date:  2011-04       Impact factor: 4.071

View more
  13 in total

1.  Radiation doses received in the United Kingdom breast screening programme in 2010 to 2012.

Authors:  Kenneth C Young; Jennifer M Oduko
Journal:  Br J Radiol       Date:  2015-12-14       Impact factor: 3.039

2.  Average glandular dose coefficients for pendant-geometry breast CT using realistic breast phantoms.

Authors:  Andrew M Hernandez; John M Boone
Journal:  Med Phys       Date:  2017-08-20       Impact factor: 4.071

3.  Monte Carlo Basics for Radiation Dose Assessment in Diagnostic Radiology.

Authors:  John M Boone; Michael F McNitt-Gray; Andrew M Hernandez
Journal:  J Am Coll Radiol       Date:  2017-04-29       Impact factor: 5.532

4.  A Monte Carlo model for mean glandular dose evaluation in spot compression mammography.

Authors:  Antonio Sarno; David R Dance; Ruben E van Engen; Kenneth C Young; Paolo Russo; Francesca Di Lillo; Giovanni Mettivier; Kristina Bliznakova; Baowei Fei; Ioannis Sechopoulos
Journal:  Med Phys       Date:  2017-06-13       Impact factor: 4.071

5.  Monte Carlo study on optimal breast voxel resolution for dosimetry estimates in digital breast tomosynthesis.

Authors:  Christian Fedon; Carolina Rabin; Marco Caballo; Oliver Diaz; Eloy García; Alejandro Rodríguez-Ruiz; Gabriel A González-Sprinberg; Ioannis Sechopoulos
Journal:  Phys Med Biol       Date:  2018-12-19       Impact factor: 3.609

Review 6.  Two-dimensional breast dosimetry improved using three-dimensional breast image data.

Authors:  John M Boone; Andrew M Hernandez; J Anthony Seibert
Journal:  Radiol Phys Technol       Date:  2017-06-01

7.  Generation and analysis of clinically relevant breast imaging x-ray spectra.

Authors:  Andrew M Hernandez; J Anthony Seibert; Anita Nosratieh; John M Boone
Journal:  Med Phys       Date:  2017-05-04       Impact factor: 4.071

8.  Dosimetry in x-ray-based breast imaging.

Authors:  David R Dance; Ioannis Sechopoulos
Journal:  Phys Med Biol       Date:  2016-09-12       Impact factor: 3.609

9.  Internal breast dosimetry in mammography: Monte Carlo validation in homogeneous and anthropomorphic breast phantoms with a clinical mammography system.

Authors:  Christian Fedon; Marco Caballo; Ioannis Sechopoulos
Journal:  Med Phys       Date:  2018-06-29       Impact factor: 4.071

10.  Shading artifact correction in breast CT using an interleaved deep learning segmentation and maximum-likelihood polynomial fitting approach.

Authors:  Peymon Ghazi; Andrew M Hernandez; Craig Abbey; Kai Yang; John M Boone
Journal:  Med Phys       Date:  2019-06-23       Impact factor: 4.071

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.