Literature DB >> 21992390

An analysis of the mechanical parameters used for finite element compression of a high-resolution 3D breast phantom.

Christina M L Hsu1, Mark L Palmeri, W Paul Segars, Alexander I Veress, James T Dobbins.   

Abstract

PURPOSE: The authors previously introduced a methodology to generate a realistic three-dimensional (3D), high-resolution, computer-simulated breast phantom based on empirical data. One of the key components of such a phantom is that it provides a means to produce a realistic simulation of clinical breast compression. In the current study, they have evaluated a finite element (FE) model of compression and have demonstrated the effect of a variety of mechanical properties on the model using a dense mesh generated from empirical breast data. While several groups have demonstrated an effective compression simulation with lower density finite element meshes, the presented study offers a mesh density that is able to model the morphology of the inner breast structures more realistically than lower density meshes. This approach may prove beneficial for multimodality breast imaging research, since it provides a high level of anatomical detail throughout the simulation study.
METHODS: In this paper, the authors describe methods to improve the high-resolution performance of a FE compression model. In order to create the compressible breast phantom, dedicated breast CT data was segmented and a mesh was generated with 4-noded tetrahedral elements. Using an explicit FE solver to simulate breast compression, several properties were analyzed to evaluate their effect on the compression model including: mesh density, element type, density, and stiffness of various tissue types, friction between the skin and the compression plates, and breast density. Following compression, a simulated projection was generated to demonstrate the ability of the compressible breast phantom to produce realistic simulated mammographic images.
RESULTS: Small alterations in the properties of the breast model can change the final distribution of the tissue under compression by more than 1 cm; which ultimately results in different representations of the breast model in the simulated images. The model properties that impact displacement the most are mesh density, friction between the skin and the plates, and the relative stiffness of the different tissue types.
CONCLUSIONS: The authors have developed a 3D, FE breast model that can yield high spatial resolution breast deformations under uniaxial compression for imaging research purposes and demonstrated that small changes in the mechanical properties can affect images generated using the phantom.

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Year:  2011        PMID: 21992390      PMCID: PMC3203130          DOI: 10.1118/1.3637500

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


  30 in total

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Authors:  Julia A Schnabel; Christine Tanner; Andy D Castellano-Smith; Andreas Degenhard; Martin O Leach; D Rodney Hose; Derek L G Hill; David J Hawkes
Journal:  IEEE Trans Med Imaging       Date:  2003-02       Impact factor: 10.048

2.  Factors influencing the accuracy of biomechanical breast models.

Authors:  Christine Tanner; Julia A Schnabel; Derek L G Hill; David J Hawkes; Martin O Leach; D Rodney Hose
Journal:  Med Phys       Date:  2006-06       Impact factor: 4.071

3.  A biomechanical model of mammographic compressions.

Authors:  J H Chung; V Rajagopal; P M F Nielsen; M P Nash
Journal:  Biomech Model Mechanobiol       Date:  2007-01-09

4.  Point/counterpoint. Molecular breast imaging will soon replace x-ray mammography as the imaging modality of choice for women at high risk with dense breasts.

Authors:  Michael K O'Connor; Georgia Tourassi; Colin G Orton
Journal:  Med Phys       Date:  2009-05       Impact factor: 4.071

5.  Methodology for generating a 3D computerized breast phantom from empirical data.

Authors:  Christina M Li; W Paul Segars; Georgia D Tourassi; John M Boone; James T Dobbins
Journal:  Med Phys       Date:  2009-07       Impact factor: 4.071

6.  Biomechanical 3-D finite element modeling of the human breast using MRI data.

Authors:  A Samani; J Bishop; M J Yaffe; D B Plewes
Journal:  IEEE Trans Med Imaging       Date:  2001-04       Impact factor: 10.048

Review 7.  Modeling breast biomechanics for multi-modal image analysis--successes and challenges.

Authors:  Vijay Rajagopal; Poul M F Nielsen; Martyn P Nash
Journal:  Wiley Interdiscip Rev Syst Biol Med       Date:  2010 May-Jun

Review 8.  Cancer screening in the United States, 2010: a review of current American Cancer Society guidelines and issues in cancer screening.

Authors:  Robert A Smith; Vilma Cokkinides; Durado Brooks; Debbie Saslow; Otis W Brawley
Journal:  CA Cancer J Clin       Date:  2010 Mar-Apr       Impact factor: 508.702

9.  Validation of a method for measuring the volumetric breast density from digital mammograms.

Authors:  O Alonzo-Proulx; N Packard; J M Boone; A Al-Mayah; K K Brock; S Z Shen; M J Yaffe
Journal:  Phys Med Biol       Date:  2010-05-12       Impact factor: 3.609

10.  Realistic CT simulation using the 4D XCAT phantom.

Authors:  W P Segars; M Mahesh; T J Beck; E C Frey; B M W Tsui
Journal:  Med Phys       Date:  2008-08       Impact factor: 4.071

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  8 in total

1.  Methodology based on genetic heuristics for in-vivo characterizing the patient-specific biomechanical behavior of the breast tissues.

Authors:  M A Lago; M J Rúperez; F Martínez-Martínez; S Martínez-Sanchis; P R Bakic; C Monserrat
Journal:  Expert Syst Appl       Date:  2015-11-30       Impact factor: 6.954

2.  Generation of a suite of 3D computer-generated breast phantoms from a limited set of human subject data.

Authors:  Christina M L Hsu; Mark L Palmeri; W Paul Segars; Alexander I Veress; James T Dobbins
Journal:  Med Phys       Date:  2013-04       Impact factor: 4.071

3.  Finite-element modeling of compression and gravity on a population of breast phantoms for multimodality imaging simulation.

Authors:  Gregory M Sturgeon; Nooshin Kiarashi; Joseph Y Lo; E Samei; W P Segars
Journal:  Med Phys       Date:  2016-05       Impact factor: 4.071

4.  Impact of breast structure on lesion detection in breast tomosynthesis, a simulation study.

Authors:  Nooshin Kiarashi; Loren W Nolte; Joseph Y Lo; W Paul Segars; Sujata V Ghate; Justin B Solomon; Ehsan Samei
Journal:  J Med Imaging (Bellingham)       Date:  2016-09-13

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

6.  Finite element model of mechanical imaging of the breast.

Authors:  Rebecca Axelsson; Hanna Tomic; Sophia Zackrisson; Anders Tingberg; Hanna Isaksson; Predrag R Bakic; Magnus Dustler
Journal:  J Med Imaging (Bellingham)       Date:  2022-05-23

7.  Development and application of a suite of 4-D virtual breast phantoms for optimization and evaluation of breast imaging systems.

Authors:  Nooshin Kiarashi; Joseph Y Lo; Yuan Lin; Lynda C Ikejimba; Sujata V Ghate; Loren W Nolte; James T Dobbins; William P Segars; Ehsan Samei
Journal:  IEEE Trans Med Imaging       Date:  2014-03-20       Impact factor: 10.048

8.  An Anthropometric-Based Subject-Specific Finite Element Model of the Human Breast for Predicting Large Deformations.

Authors:  Silvia Pianigiani; Leonardo Ruggiero; Bernardo Innocenti
Journal:  Front Bioeng Biotechnol       Date:  2015-12-24
  8 in total

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