Numerical Modelling of Human Breast Deformation

  • A. Pérez del Palomar
  • B. Calvo
  • A. Lapuebla-Ferri


Most surgical procedures in breast plastic surgery are either reconstructive procedures following oncologic interventions (tumorectomy, quadrantectomy, mastectomy…) or aesthetic ones, including both augmentation and reduction. With current techniques, the results of such procedures cannot be fully guaranteed. Usually, surgical planning is based on a photographic and anthropometric study of only the breast. Among others, one of the difficulties that plastic surgeons have is the noticeable change of the breast shape with the position of the patient. Thus, it is more and more necessary to plan a presurgical methodology to help the plastic surgeon and guarantee the patient a successful result of the intervention. Numerical methods such as finite element simulations can help in predicting the deformations of a specific tissue if a suitable definition of the tissue is introduced. These models take into account the constitutive behaviour of the involved materials, the boundary conditions and the externally applied loads. Thus, numerical modelling can be used as a powerful tool to provide accurate and useful information to the surgeon planning such surgical procedures.


Standing Position Plastic Surgeon Glandular Tissue Breast Shape Breast Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



Finite element method


Computed tomography


Magnetic resonance


  1. Azar FS, Metaxas DN, Schnall MD. A deformable finite element model of the breast for predicting mechanical deformations under external perturbations. Acad Radiol. 2001;8:965–75.PubMedCrossRefGoogle Scholar
  2. Azar FS, Metaxas DN, Schnall MD. Methods for modeling and predicting mechanical deformations of the breast under external perturbations. Med Image Anal. 2002;6:1–27.PubMedCrossRefGoogle Scholar
  3. Azar FS. A deformable finite element model of the breast for predicting mechanical deformations under external perturbations. PhD thesis, University of Pennsylvania; 2001.Google Scholar
  4. Bakic PR. Breast tissue description and modeling in mammography. PhD thesis, Lehigh University; 2000.Google Scholar
  5. Gambarotta L, Massabo R, Morbiducci R, Raposio E, Santi P. In vivo experimental testing and model identification of human scalp skin. J Biomech. 2005;38:2237–47.PubMedCrossRefGoogle Scholar
  6. Hrennikoff A. Solution of problems of elasticity by the frame-work method. ASME J. Appl. Mech. 1941;8:A619–715.Google Scholar
  7. Humphrey JD. Continuum biomechanics of soft biological tissues. Proc R Soc Lond A, R Soc Rev. 2002;175:1–44.Google Scholar
  8. Krouskop TA, Wheeler TM, Kallel F, Garra BS, Hall T. The elastic moduli of breast prostate tissues under compression. Ultrasonic Imaging. 1998;20:151–9.Google Scholar
  9. Ning X, Zhu Q, Lanir Y, Margulies SS. A transversely isotropic viscoelastic constitutive equation for brainstem undergoing finite deformation. J Biomech Eng. 2006;128:925–33.PubMedCrossRefGoogle Scholar
  10. Poplack SP, Paulsen KD, Hartov A, Meaney PM, Pogue PW, Tosteson TD, Grave MR, Soho SK, Wells WA. Electromagnetic breast imaging: average tissue property values in women with negative clinical findings. Radiology. 2004;231:571–80.PubMedCrossRefGoogle Scholar
  11. Pérez del Palomar A, Calvo B, Herrero J, López J, Doblaré M. Med Eng Phys. 2008;30:1089–97.PubMedCrossRefGoogle Scholar
  12. Reishner R, Balogh B, Menzel E. A finite element model to accurately predict real deformations of the breast. Med Eng Phys. 1995;17(4):304–13.CrossRefGoogle Scholar
  13. Roose L, Maerteleire W, Mollemans W, Suetens P. Validation of different soft tissue simulation methods for breast augmentation. Int Congress Ser. 2005;1281:485–90.CrossRefGoogle Scholar
  14. Ruiter N, Muller T, Stotzka R, Gemmeke H, Reichenbach J, Kaiser W. Automatic image matching for breast cancer diagnostics by a 3D deformation of the mamma. Biomed Tech. 2002;47:644–7.CrossRefGoogle Scholar
  15. Samani A, Bishop J, Yaffe MJ, Plewes DB. Biomechanical 3-D finite element modelling of the human breast using MRI data. IEEE Trans Med Imaging. 2001;20:271–9.PubMedCrossRefGoogle Scholar
  16. Schnabel JA, Tanner C, Castellano-Smith AD, Degenhard A, Leach MO, Hose DR, Hill DLG, Hawkes DJ. Validation of nonrigid image registration using finite-element methods: application to breast MR images. IEEE Trans Med Imaging. 2003;22:238–47.PubMedCrossRefGoogle Scholar
  17. Tanner C, Schanabel JA, Hill DLG, Hawkes DJ. Factors influencing the accuracy of biomechanical breast models, Med Phys. 2006;33(6):1758–69.PubMedCrossRefGoogle Scholar
  18. Washington CW, Miga MI. Modelity independent elastography (MIE): a new approach to elasticity imaging. IEEE Trans Med Imaging, 2004;23:1117–28.PubMedCrossRefGoogle Scholar
  19. Wellman PS. Tactile imaging PhD thesis, Harvard University; 1999.Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • A. Pérez del Palomar
    • 1
  • B. Calvo
  • A. Lapuebla-Ferri
  1. 1.Multiscale in Engineering and Biomechanics (M2BE), Aragon Institute of Engineering Research (I3A)Universidad de ZaragozaZaragozaSpain

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