Literature DB >> 16723760

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

R Highnam1, X Pan, R Warren, M Jeffreys, G Davey Smith, M Brady.   

Abstract

The standard mammogram form (SMF) representation of an x-ray mammogram is a standardized, quantitative representation of the breast from which the volume of non-fat tissue and breast density can be easily estimated, both of which are of significant interest in determining breast cancer risk. Previous theoretical analysis of SMF had suggested that a complete and substantial set of calibration data (such as mAs and kVp) would be needed to generate realistic breast composition measures and yet there are many interesting trials that have retrospectively collected images with no calibration data. The main contribution of this paper is to revisit our previous theoretical analysis of SMF with respect to errors in the calibration data and to show how and why that theoretical analysis did not match the results from the practical implementations of SMF. In particular, we show how by estimating breast thickness for every image we are, effectively, compensating for any errors in the calibration data. To illustrate our findings, the current implementation of SMF (version 2.2beta) was run over 4028 digitized film-screen mammograms taken from six sites over the years 1988-2002 with and without using the known calibration data. Results show that the SMF implementation running without any calibration data at all generates results which display a strong relationship with when running with a complete set of calibration data, and, most importantly, to an expert's visual assessment of breast composition using established techniques. SMF shows considerable promise in being of major use in large epidemiological studies related to breast cancer which require the automated analysis of large numbers of films from many years previously where little or no calibration data is available.

Entities:  

Mesh:

Year:  2006        PMID: 16723760     DOI: 10.1088/0031-9155/51/11/001

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  28 in total

1.  Quantification of breast density with spectral mammography based on a scanned multi-slit photon-counting detector: a feasibility study.

Authors:  Huanjun Ding; Sabee Molloi
Journal:  Phys Med Biol       Date:  2012-07-06       Impact factor: 3.609

2.  Quantification of breast density with dual energy mammography: a simulation study.

Authors:  Justin L Ducote; Sabee Molloi
Journal:  Med Phys       Date:  2008-12       Impact factor: 4.071

3.  Breast Imaging Reporting and Data System (BI-RADS) breast composition descriptors: automated measurement development for full field digital mammography.

Authors:  E E Fowler; T A Sellers; B Lu; J J Heine
Journal:  Med Phys       Date:  2013-11       Impact factor: 4.071

4.  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

5.  Single x-ray absorptiometry method for the quantitative mammographic measure of fibroglandular tissue volume.

Authors:  Serghei Malkov; Jeff Wang; Karla Kerlikowske; Steven R Cummings; John A Shepherd
Journal:  Med Phys       Date:  2009-12       Impact factor: 4.071

6.  Quantification of breast density with dual energy mammography: an experimental feasibility study.

Authors:  Justin L Ducote; Sabee Molloi
Journal:  Med Phys       Date:  2010-02       Impact factor: 4.071

7.  Calibrated breast density methods for full field digital mammography: a system for serial quality control and inter-system generalization.

Authors:  B Lu; A M Smallwood; T A Sellers; J S Drukteinis; J J Heine; E E E Fowler
Journal:  Med Phys       Date:  2015-02       Impact factor: 4.071

8.  Breast density evaluation using spectral mammography, radiologist reader assessment, and segmentation techniques: a retrospective study based on left and right breast comparison.

Authors:  Sabee Molloi; Huanjun Ding; Stephen Feig
Journal:  Acad Radiol       Date:  2015-05-29       Impact factor: 3.173

9.  Automated Volumetric Breast Density derived by Shape and Appearance Modeling.

Authors:  Serghei Malkov; Karla Kerlikowske; John Shepherd
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2014-03-22

10.  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

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.