Literature DB >> 11699849

A deformable finite element model of the breast for predicting mechanical deformations under external perturbations.

F S Azar1, D N Metaxas, M D Schnall.   

Abstract

RATIONALE AND
OBJECTIVES: Live guidance during needle breast procedures is not currently possible with high-field-strength (1.5-T), superconducting magnetic resonance (MR) imaging. The physician can calculate only the approximate location and extent of a tumor in the compressed patient breast before inserting the needle, and the tissue specimen removed at biopsy may not actually belong to the lesion of interest. The authors developed a virtual reality system for guiding breast biopsy with MR imaging, which uses a deformable finite element model of the breast.
MATERIALS AND METHODS: The geometry of the model is constructed from MR data, and its mechanical properties are modeled by using a nonlinear material model. This method allows the breast to be imaged with or without mild compression before the procedure. The breast is then compressed, and the finite element model is used to predict the position of the tumor during the procedure. Three breasts of patients with cancer were imaged with and without compression. Deformable models of these breasts were built, virtually compressed, and used to predict tumor positions in the real compressed breasts. The models were also used to register MR data sets of the same patient breast imaged with different amounts of compression.
RESULTS: The model is shown to predict reasonably well the displacement by plate compression of breast lesions 5 mm or larger.
CONCLUSION: A deformable model of the breast based on finite elements with nonlinear material properties can help in modeling and predicting breast deformation. The entire procedure lasts less than half an hour, making it clinically practical.

Entities:  

Mesh:

Year:  2001        PMID: 11699849     DOI: 10.1016/S1076-6332(03)80640-2

Source DB:  PubMed          Journal:  Acad Radiol        ISSN: 1076-6332            Impact factor:   3.173


  12 in total

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

Authors:  Christina M L Hsu; Mark L Palmeri; W Paul Segars; Alexander I Veress; James T Dobbins
Journal:  Med Phys       Date:  2011-10       Impact factor: 4.071

2.  A novel simulation algorithm for soft tissue compression.

Authors:  Christos Zyganitidis; Kristina Bliznakova; Nicolas Pallikarakis
Journal:  Med Biol Eng Comput       Date:  2007-06-06       Impact factor: 2.602

Review 3.  Deformable medical image registration: a survey.

Authors:  Aristeidis Sotiras; Christos Davatzikos; Nikos Paragios
Journal:  IEEE Trans Med Imaging       Date:  2013-05-31       Impact factor: 10.048

4.  A data-driven soft sensor for needle deflection in heterogeneous tissue using just-in-time modelling.

Authors:  Carlos Rossa; Thomas Lehmann; Ronald Sloboda; Nawaid Usmani; Mahdi Tavakoli
Journal:  Med Biol Eng Comput       Date:  2016-12-10       Impact factor: 2.602

5.  Finite element modelling and validation for breast cancer detection using digital image elasto-tomography.

Authors:  Hina M Ismail; Chris G Pretty; Matthew K Signal; Marcus Haggers; J Geoffrey Chase
Journal:  Med Biol Eng Comput       Date:  2018-03-10       Impact factor: 2.602

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.  Dynamic functional and mechanical response of breast tissue to compression.

Authors:  S A Carp; J Selb; Q Fang; R Moore; D B Kopans; E Rafferty; D A Boas
Journal:  Opt Express       Date:  2008-09-29       Impact factor: 3.894

8.  Building a virtual simulation platform for quasistatic breast ultrasound elastography using open source software: A preliminary investigation.

Authors:  Yu Wang; Emily Helminen; Jingfeng Jiang
Journal:  Med Phys       Date:  2015-09       Impact factor: 4.071

9.  Symmetric Biomechanically Guided Prone-to-Supine Breast Image Registration.

Authors:  Björn Eiben; Vasileios Vavourakis; John H Hipwell; Sven Kabus; Thomas Buelow; Cristian Lorenz; Thomy Mertzanidou; Sara Reis; Norman R Williams; Mohammed Keshtgar; David J Hawkes
Journal:  Ann Biomed Eng       Date:  2015-11-17       Impact factor: 3.934

10.  Multiscale Mechano-Biological Finite Element Modelling of Oncoplastic Breast Surgery-Numerical Study towards Surgical Planning and Cosmetic Outcome Prediction.

Authors:  Vasileios Vavourakis; Bjoern Eiben; John H Hipwell; Norman R Williams; Mo Keshtgar; David J Hawkes
Journal:  PLoS One       Date:  2016-07-28       Impact factor: 3.240

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