Abstract
This paper presents a novel general approach to simulation of soft tissue compression. A theoretical framework of the compression algorithm has been developed and implemented, based on the concept of a simple spring. The volume subjected to compression is divided into a number of “model elements”, each one consisting of 27 nodes. The nodes are connected with springs. The mechanical properties of the tissues are assumed to be linear and isotropic. The compressed volume remains constant due to the introduced concept of spring variable equilibrium lengths. Initial settings for compression simulation are introduced in order that the algorithm converges faster. The developed compression algorithm was used to model breast compression during a standard mammography examination. Specifically, the method was applied to a high-resolution three-dimensional software breast phantom, composed to have a medium glandularity and calcification abnormalities. The compression was set to 50%. Results showed that the abnormalities maintain their shape and dimensions during the compression, while the surrounding breast tissues undergo considerable deformation and displacement. A “decompression” algorithm was also applied to test the reversibility of the model.
Similar content being viewed by others
References
Azar F, Metaxas D, Schnall M (2000) A finite element model of the breast for predicting mechanical deformations during biopsy procedures. In: Proceedings of the IEEE workshop on math methods in biomedical image analysis, pp 38–45
Azar F, Metaxas D, Schnall M (2001) A deformable finite element model of the breast for predicting mechanical deformations under external perturbations. Acad Radiol 8:965–975
Azar F, Metaxas D, Schnall M (2002) Methods for modeling and predicting mechanical deformations of the breast under external perturbations. Med Image Anal 6:1–27
Baumann R, Glauser D, Tappy D et al (1996) Force feedback for virtual reality based minimally invasive surgery simulator. Stud Health Technol Inform 29:564–579
Bliznakova K, Bliznakov Z, Bravou V et al (2003) A three-dimensional breast software phantom for mammography simulation. Phys Med Biol 48:3699–3719
Bliznakova K, Kolitsi Z, Pallikarakis N (2006) Dual-energy mammography: simulation studies. Phys Med Biol 51:4497–4515
Desbrun, Gascuel M (1995) Animating soft substances with implicit surfaces. In: Proceedings ACM SIGGRAPH
Luciani A, Jimenez S, Florens J et al (1991) Computational physics: a modeler simulator for animated physical objects. In: Proceedings of Eurographics conference, pp 425–437
Meseure P, Chailou C (1997) Deformable body simulation with adaptive subdivision and cuttings. In: Proceedings of the WSCG’97 conference, pp 361–370
Poulos A, McLean D (2004) The application of breast compression in mammography: a new perspective. Radiography 10:131–137
Wellman P, Howe R, Dalton E et al (1999) Breast tissue stiffness in compression is correlated to histological diagnosis. Technical report, Harvard Biorobotics Laboratory
Zienkiewich O (1977) The finite element method, 3rd edn. McGraw-Hill, New York
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Zyganitidis, C., Bliznakova, K. & Pallikarakis, N. A novel simulation algorithm for soft tissue compression. Med Bio Eng Comput 45, 661–669 (2007). https://doi.org/10.1007/s11517-007-0205-y
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11517-007-0205-y