Literature DB >> 27452264

Volumetric breast density measurement: sensitivity analysis of a relative physics approach.

Susie Lau1,2, Kwan Hoong Ng1,2, Yang Faridah Abdul Aziz1,2.   

Abstract

OBJECTIVE: To investigate the sensitivity and robustness of a volumetric breast density (VBD) measurement system to errors in the imaging physics parameters including compressed breast thickness (CBT), tube voltage (kVp), filter thickness, tube current-exposure time product (mAs), detector gain, detector offset and image noise.
METHODS: 3317 raw digital mammograms were processed with Volpara(®) (Matakina Technology Ltd, Wellington, New Zealand) to obtain fibroglandular tissue volume (FGV), breast volume (BV) and VBD. Errors in parameters including CBT, kVp, filter thickness and mAs were simulated by varying them in the Digital Imaging and Communications in Medicine (DICOM) tags of the images up to ±10% of the original values. Errors in detector gain and offset were simulated by varying them in the Volpara configuration file up to ±10% from their default values. For image noise, Gaussian noise was generated and introduced into the original images.
RESULTS: Errors in filter thickness, mAs, detector gain and offset had limited effects on FGV, BV and VBD. Significant effects in VBD were observed when CBT, kVp, detector offset and image noise were varied (p < 0.0001). Maximum shifts in the mean (1.2%) and median (1.1%) VBD of the study population occurred when CBT was varied.
CONCLUSION: Volpara was robust to expected clinical variations, with errors in most investigated parameters giving limited changes in results, although extreme variations in CBT and kVp could lead to greater errors. ADVANCES IN KNOWLEDGE: Despite Volpara's robustness, rigorous quality control is essential to keep the parameter errors within reasonable bounds. Volpara appears robust within those bounds, albeit for more advanced applications such as tracking density change over time, it remains to be seen how accurate the measures need to be.

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Year:  2016        PMID: 27452264      PMCID: PMC5124801          DOI: 10.1259/bjr.20160258

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


  29 in total

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Journal:  Phys Med Biol       Date:  2012-07-06       Impact factor: 3.609

2.  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

3.  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

4.  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

5.  Assessment of a fully automated, high-throughput mammographic density measurement tool for use with processed digital mammograms.

Authors:  A M Couwenberg; H M Verkooijen; J Li; R M Pijnappel; K R Charaghvandi; M Hartman; C H van Gils
Journal:  Cancer Causes Control       Date:  2014-06-25       Impact factor: 2.506

6.  Effects of age, breast density, ethnicity, and estrogen replacement therapy on screening mammographic sensitivity and cancer stage at diagnosis: review of 183,134 screening mammograms in Albuquerque, New Mexico.

Authors:  R D Rosenberg; W C Hunt; M R Williamson; F D Gilliland; P W Wiest; C A Kelsey; C R Key; M N Linver
Journal:  Radiology       Date:  1998-11       Impact factor: 11.105

7.  Evaluating the effectiveness of using standard mammogram form to predict breast cancer risk: case-control study.

Authors:  Jane Ding; Ruth Warren; Iqbal Warsi; Nick Day; Deborah Thompson; Michael Brady; Christopher Tromans; Ralph Highnam; Douglas Easton
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2008-05       Impact factor: 4.254

8.  Endogenous hormone levels, mammographic density, and subsequent risk of breast cancer in postmenopausal women.

Authors:  Rulla M Tamimi; Celia Byrne; Graham A Colditz; Susan E Hankinson
Journal:  J Natl Cancer Inst       Date:  2007-07-24       Impact factor: 13.506

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

10.  Volumetric breast density estimation from full-field digital mammograms: a validation study.

Authors:  Albert Gubern-Mérida; Michiel Kallenberg; Bram Platel; Ritse M Mann; Robert Martí; Nico Karssemeijer
Journal:  PLoS One       Date:  2014-01-21       Impact factor: 3.240

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  1 in total

Review 1.  Qualitative Versus Quantitative Mammographic Breast Density Assessment: Applications for the US and Abroad.

Authors:  Stamatia Destounis; Andrea Arieno; Renee Morgan; Christina Roberts; Ariane Chan
Journal:  Diagnostics (Basel)       Date:  2017-05-31
  1 in total

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