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Trends in Biomechanical Finite Element Breast Deformation Modelling

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Innovations in Biomedical Engineering

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 526))

Abstract

Breast tissue deformation has recently gained interest in various medical application. The recovery of large deformation caused by gravity or compression loads and image registration is non-trivial task. The need arise to estimate large breast deformation, which can mimic natural body movement caused by examinations or surgery. Finite element methods (FEM) have been widely applied in this field. In this work we present the current breast deformation modelling trend. The meaningful applications and essentials examinations are described. The modelling software and basic techniques are presented.

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References

  1. De Abreu, F.B., Wells, W.A., Tsongalis, G.J.: The emerging role of the molecular diagnostics laboratory in breast cancer personalized medicine. Am. J. Pathol. 183(4), 1075–1083 (2013)

    Article  Google Scholar 

  2. Azar, F.S., Metaxas, D.N., Schnall, M.D.: A finite element model of the breast for predicting mechanical deformations during biopsy procedures. In: Proceedings of the IEEE Workshop on Mathematical Methods in Biomedical Image Analysis, pp. 38–45 (2000)

    Google Scholar 

  3. Azar, F.S., Metaxas, D.N., Schnall, M.D.: Methods for modelling predicting mechanical deformations of the breast under external perturbations. Med. Image Anal. 6, 1–27 (2002)

    Article  MATH  Google Scholar 

  4. Bleyer, A., Welch, G.: Effect of Three decades of screening mammography on breast-cancer incidence. N. Engl. J. Med. 367, 1998–2005 (2012)

    Article  Google Scholar 

  5. Danch-Wierzchowska, M., Borys, D., Swierniak, A.: Breast deformation modeling based on MRI images, preliminary results. Inf. Technol. Med. 472, 227–234 (2016)

    Article  Google Scholar 

  6. Danch-Wierzchowska, M., Borys, D., Bobek-Billewicz, B., Jarzab, M., Swierniak, A.: Simplification of breast deformation modelling to support breast cancer treatment planning. Preliminary Results Biomed. Eng. 36(4), 531–536 (2016)

    Google Scholar 

  7. Dehghani, H., Doyley, M.M., Pogue, B.W., Jiang, S., Geng, J., Paulsen, K.D.: Breast deformation modelling for image reconstruction in near infrared optical tomography. Phys. Med. Biol. 49(7), 1131–1145 (2004)

    Article  Google Scholar 

  8. Eiben, B., Vavourakis, V., Hipwell, J.H., Kabus, S., Buelow, T., Lorenz, C., Mertzanidou, T., Reis, S., Williams, N.R., Keshtgar, M., Hawkes, D.J.: Symmetric biomechanically guided prone-to-supine breast image registration. Ann. Biomed. Eng. 44(1), 154–173 (2016)

    Article  Google Scholar 

  9. Gamage, T.P.B., Boyes, R., Rajagopal, V., Nielsen, P.M.F., Nash, M.P.: Modelling prone to supine breast deformation under gravity loading using heterogeneous finite element models. In: Computational Biomechanics for Medicine, pp. 29–38 (2012)

    Google Scholar 

  10. Georgii, J., Eder, M., BÃijrger, K., Klotz, S., Ferstl, F., Kovacs, L., Westermann, R.: A computational tool for preoperative breast augmentation planning in aesthetic plastic surgery. IEEE J. Biomed. Health Inform. 18(3), 907-19 (2014)

    Article  Google Scholar 

  11. Haddad, S.M., Omidi, E., Flynn, L.E., Samani, A.: Comparative biomechanical study of using decellularized human adipose tissues for post-mastectomy and post-lumpectomy breast reconstruction. J. Mech. Behav. Biomed. Mater. 57, 235–245 (2016)

    Article  Google Scholar 

  12. Han, L., Hipwell, J., Taylor, Z., Tanner, C., Ourselin, S., Hawkes, D.J.: Fast deformation simulation of breasts using GPU-based dynamic explicit finite element method. Digit. Mammo. 6136, 728–735 (2010)

    Article  Google Scholar 

  13. Han, L., Hipwell, J., Mertzanidou, T., Carter, T., Modat, M., Ourselin, S., Hawkes, D.: A hybrid FEM-based method for aligning prone and supine images for image guided breast surgery. In: 2011 IEEE International Symposium on Biomedical Imaging, From Nano to Macro, pp. 1239–1242 (2011)

    Google Scholar 

  14. Han, L., Hipwell, J., Tanner, C., Taylor, Z., Mertzanidou, T., Cardoso, J., Ourselin, S., Hawkes, D.: Development of patient specific biomechanical models for predicting large breast deformation. Phys. Med. Biol. 57, 455–472 (2012)

    Article  Google Scholar 

  15. Han, L., Hipwell, J.H., Eiben, B., Barratt, D., Modat, M., Ourselin, S., Hawkes, D.J.: A nonlinear biomechanical model based registration method for aligning prone and supine MR breast images. IEEE Trans. Med. Imaging 33(3), 682–694 (2014)

    Article  Google Scholar 

  16. Harz, M., Georgii, J., Schilling, K., Hahn, H.K.: Towards navigated breast surgery using efficient breast deformation simulation. In: Proceedings of Workshop on Breast Image Analysis, pp. 137–144 (2011)

    Google Scholar 

  17. Harz, M.T., Georgii, J., Schilling, K., Hahn, H.K.: Real-time breast defomation using non-linear tissue properties. In: Lecture Notes in Informatics, vol. 192 (2011)

    Google Scholar 

  18. Hopp, T., Baltzer, P., Dietzel, M., Kaiser, W.A., Ruiter, N.V.: 2D/3D image fusion of X-ray mammograms with breast MRI: visualizing dynamic contrast enhancement in mammograms. Int. J. Comput. Assist. Radiol. Surg. 7(3), 339–348 (2012)

    Article  Google Scholar 

  19. Hopp, T., Dietzel, M., Baltzer, P.A., Kreisel, P., Kaiser, W.A., Gemmeke, H., Ruiter, N.V.: Automatic multimodal 2D/3D breast image registration using biomechanical FEM models and intensity-based optimization. Med. Image Anal. 17(2), 209–218 (2013)

    Article  Google Scholar 

  20. Insana, M.F., Liu, J., Sridhar, M., Pellot-Barakat, C.: Ultrasonic Mechanical Relaxation Imaging and the Material Science of Breast Cancer IEEE Ultrasonics Symposium (2005)

    Google Scholar 

  21. Lee, A.W.C., Schnabel, J.A., Rajagopal, V., Nielsen, P.M.F., Nash, M.P.: Breast image registration by combining finite elements and free-form deformations. In: Martí, J., Oliver, A., Freixenet, J., Martí, R. (eds.) IWDM 2010. LNCS, vol. 6136, pp. 736–743. Springer, Heidelberg (2010). doi:10.1007/978-3-642-13666-5_99

    Chapter  Google Scholar 

  22. Lee, A.W., Rajagopal, V., Babarenda Gamage, T.P., Doyle, A.J., Nielsen, P.B., Nash, M.P.: Breast lesion co-localisation between X-ray and MR images using finite element modelling. Med. Image Anal. 17(8), 1256–1264 (2013)

    Article  Google Scholar 

  23. Lorenzen, J., Sinkus, R., Lorenzen, M., Dargatz, M., Leussler, C., Rãűschmann, P., Adam, G.: MR elastography of the breast: preliminary clinical results. Rofo. 174(7), 830–834 (2002)

    Article  Google Scholar 

  24. Pathmanathan, P., Gavaghan, D.J., Whiteley, J.P., Chapman, S.J., Brady, J.M.: Predicting tumor location by modeling the deformation of the breast. IEEE Trans. Biomed. Eng. 55(10), 2471–2480 (2008)

    Article  Google Scholar 

  25. del Palomar, A.P., Calvo, B., Herrero, J., Lãşpez, J., Doblarãl’, M.: A finite element model to accurately predict real deformations of the breast. Med. Eng. Phys. 30(9), 1089–1097 (2008)

    Article  Google Scholar 

  26. Ramiao, N., Martins, P., Fernandes, A.A.: Biomechanical properties of breast tissue. In: ENBENG 2013, pp. 1–6 (2013)

    Google Scholar 

  27. Rueckert, D., Sonoda, L.I., Hayes, C., Hill, D.L., Leach, M.O., Hawkes, D.J.: Nonrigid registration using free-form deformations: application to breast MR images. IEEE Trans. Med. Imaging 18(8), 712–721 (1999)

    Article  Google Scholar 

  28. Samani, A., Bishop, J., Yaffe, M.J., Plewes, D.B.: Biomechanical 3-D finite element modeling of the human breast using MRI data. IEEE Trans. Med. Imaging 20(4), 271–279 (2001)

    Article  Google Scholar 

  29. Samani, A., Zubovits, J., Plewes, D.: Elastic moduli of normal and pathological human breast tissues: an inversion-technique-based investigation of 169 samples. Phys. Med. Biol. 52(6), 1565–1576 (2007)

    Article  Google Scholar 

  30. Seo, H., Cordier, F., Hong, K.: A breast modeler based on analysis of breast scans. Comput. Anima. Virtual Worlds 18(2), 141–151 (2007)

    Article  Google Scholar 

  31. Shih, T.C., Chen, J.H., Lium, D., Nie, K., Sun, L., Lin, M., Chang, D., Nalcioglu, O., Su, M.Y.: Computational simulation of breast compression based on segmented breast and fibroglandular tissues on magnetic resonance images. Phys. Med. Biol. 55(14), 4153–4168 (2010)

    Article  Google Scholar 

  32. Sotiras, A., Davatzikos, C., Paragios, N.: Deformable medical image registration: a survey. IEEE Trans. Med. Imaging 32(7), 1153–1190 (2013)

    Article  Google Scholar 

  33. Dose, S.J., Bader, M., Jenicke, L., Hemminger, G., JÃd’nicke, F., Avril, N.: Early prediction of response to chemotherapy in metastatic breast cancer using sequential 18F-FDG PET. J. Nucl. Med. 46(7), 1144–1150 (2005)

    Google Scholar 

  34. Tanner, C., Schnabel, J., Smith, A.C., Sonoda, L., Hill, D., Hawkes, D., Degenhard, A., Hayes, C., Leach, M., Hose, D.: The comparison of biomechanical breast models: initial results. In: ANSYSConvergence, Pittsburgh, PA, US, April 2002

    Google Scholar 

  35. Tanner, C., Hipwell, J.H., Hawkes, D.J., Szekely, G.: Breast shapes on real and simulated mammograms. Digit. Mammo. 6136, 540–547 (2010)

    Article  Google Scholar 

  36. Thanoon, D., Garbey, M., Kim, N., Bass, B.: A computational framework for breast surgery: application to breast conserving therapy. In: Computational Surgery and Dual Training, 5, pp. 249–266 (2009)

    Google Scholar 

  37. Wang, L., Filippatos, K., Friman, O., Hahn, H.K.: Fully automated segmentation of the pectoralis muscle boundary in breast MR images. In: Medical Imaging, Computer-Aided Diagnosis, p. 796309 (2011)

    Google Scholar 

  38. Wellman, P.S., Howe, R.D., Dalton, E., Kern, K.A.: Breast tissue stiffness in compression is correlated to histological diagnosis. J. Biomech. p. 4017745 (1999)

    Google Scholar 

  39. Wessel, C., Schnabel, J.A., Brady, M.: Towards a more realistic biomechanical modelling of breast malignant tumours. Phys. Med. Biol. 57(3), 631–648 (2012)

    Article  Google Scholar 

  40. Wessel, C., Schnabel, J.A., Brady, M.: Realistic biomechanical model of a cancerous breast for the registration of prone to supine deformations. EMBC 2013, 7249–7252 (2013)

    Google Scholar 

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Acknowledgements

This work was supported by the National Science Centre (NCN) under Grant No. 2011/03/B/ST6/04384 (AS), the Polish National Center of Research and Development grant no. STRATEGMED2/267398/4/NCBR/2015 (DB,KG) and the Institute of Automatic Control under Grant No. BKM/506/ RAU1/2016/t.7 (MDW).

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Authors and Affiliations

  1. Institute of Automatic Control, Silesian University of Technology, Akademicka 16, 44-100, Gliwice, Poland

    Marta Danch-Wierzchowska, Damian Borys & Andrzej Swierniak

  2. Department of PET Diagnostics, Maria Sklodowska-Curie Memorial Cancer Center and Institute of Oncology, Gliwice Branch, Wybrzeze AK 15, 44-100, Gliwice, Poland

    Kamil Gorczewski

Authors
  1. Marta Danch-Wierzchowska
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  2. Kamil Gorczewski
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  3. Damian Borys
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  4. Andrzej Swierniak
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Corresponding author

Correspondence to Marta Danch-Wierzchowska .

Editor information

Editors and Affiliations

  1. Faculty of Biomedical Engineering, Silesian University of Technology, Gliwice, Poland

    Marek Gzik

  2. Faculty of Biomedical Engineering, Silesian University of Technology, Zabrze, Poland

    Ewaryst Tkacz

  3. Faculty of Biomedical Engineering, Silesian University of Technology, Gliwice, Poland

    Zbigniew Paszenda

  4. Faculty of Biomedical Engineering, Silesian University of Technology, Gliwice, Poland

    Ewa Piętka

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Danch-Wierzchowska, M., Gorczewski, K., Borys, D., Swierniak, A. (2017). Trends in Biomechanical Finite Element Breast Deformation Modelling. In: Gzik, M., Tkacz, E., Paszenda, Z., Piętka, E. (eds) Innovations in Biomedical Engineering. Advances in Intelligent Systems and Computing, vol 526. Springer, Cham. https://doi.org/10.1007/978-3-319-47154-9_12

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  • DOI: https://doi.org/10.1007/978-3-319-47154-9_12

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  • Online ISBN: 978-3-319-47154-9

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