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Real-time simulation of the nonlinear visco-elastic deformations of soft tissues

Abstract

Purpose

Mass-spring-damper (MSD) models are often used for real-time surgery simulation due to their fast response and fairly realistic deformation replication. An improved real time simulation model of soft tissue deformation due to a laparoscopic surgical indenter was developed and tested.

Method

The mechanical realization of conventional MSD models was improved using nonlinear springs and nodal dampers, while their high computational efficiency was maintained using an adapted implicit integration algorithm. New practical algorithms for model parameter tuning, collision detection, and simulation were incorporated.

Results

The model was able to replicate complex biological soft tissue mechanical properties under large deformations, i.e., the nonlinear and viscoelastic behaviors. The simulated response of the model after tuning of its parameters to the experimental data of a deer liver sample, closely tracked the reference data with high correlation and maximum relative differences of less than 5 and 10%, for the tuning and testing data sets respectively. Finally, implementation of the proposed model and algorithms in a graphical environment resulted in a real-time simulation with update rates of 150 Hz for interactive deformation and haptic manipulation, and 30 Hz for visual rendering.

Conclusion

The proposed real time simulation model of soft tissue deformation due to a laparoscopic surgical indenter was efficient, realistic, and accurate in ex vivo testing. This model is a suitable candidate for testing in vivo during laparoscopic surgery.

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References

  1. Basdogan C, Ho C-H, Srinivasan MA (2001) Virtual environments for medical training: graphical and haptic simulation of laparoscopic common bile duct exploration. IEEE ASME Trans Mechatron 6: 269–285

    Article  Google Scholar 

  2. Sederberg T, Parry S (1986) Free-form deformation of solid geometric models. ACM SIGGRAPH Comput Graph 20: 151–160

    Article  Google Scholar 

  3. Kass M, Witkin A, Terzopoulos D (1987) Snakes: active contour models. Int J Comput Vis 1: 321–332

    Article  Google Scholar 

  4. Terzopoulos D, Waters K (1990) Physically-based facial modeling, analysis, and animation. J Vis Comput Anim 1: 73–80

    Google Scholar 

  5. Gibson S, Samosky J, Mor A, Fyock C, Grimson E, Kanade T, Kikinis R, Lauer H, McKenzie N, Nakajima S (1997) Simulating arthroscopic knee surgery using volumetric object representations, real-time volume rendering and haptic feedback. In: Proceedings of the First Joint Conference CVRMed-MRCAS’97. Lecture Notes in Computer Science, vol 1205. Springer, Berlin, pp 369–378

  6. Gibson SFF (1997) 3D ChainMail: a fast algorithm for deforming volumetric objects, Symposium on Interactive 3D Graphics, ACM, Providence, Rhode Island, USA, pp 149–154

  7. De S, Kim J, Srinivasan MA (2001) Virtual surgery simulation using a collocation-based method of finite spheres. In: Bathe KJ (ed) Proceedings of the First MIT Conference on Computational Fluid and Solid Mechanics, Elsevier Science Ltd, pp 140–141

  8. Bro-Nielsen M (1998) Finite element modeling in surgery simulation. Proc IEEE 86: 490–503

    Article  Google Scholar 

  9. Monserrat C, Meier U, Alcaniz M, Chinesta F, Juan MC (2001) A new approach for the real-time simulation of tissue deformations in surgery simulation. Comput Methods Programs Biomed 64: 77–85

    PubMed  Article  CAS  Google Scholar 

  10. Bro-Nielsen M, Cotin S (1996) Real-time volumetric deformable models for surgery simulation using finite elements and condensation. Comput Graph Forum 15: 57–66

    Article  Google Scholar 

  11. Cotin S, Delingette H, Ayache N (1999) Real-time elastic deformations of soft tissues for surgery simulation. IEEE Trans Vis Comput Graph 5: 62–73

    Article  Google Scholar 

  12. Cotin S, Delingette H, Ayache N (2000) A hybrid elastic model for real-time cutting, deformations, and force feedback for surgery training and simulation. Visual Comput 16: 437–452

    Article  Google Scholar 

  13. Picinbono G, Delingette H, Ayache N (2001) Non-linear and anisotropic elastic soft tissue models for medical simulation. In: Proceeding ICRA 2001, IEEE International Conference on Robotics and Automation, vol 2. Seoul, Korea, 21–26, pp 1370–1375

  14. Picinbono G, Delingette H, Ayache N (2003) Non-linear anisotropic elasticity for real-time surgery simulation. Graph Models 65(5): 305–321

    Article  Google Scholar 

  15. Schwartz J-M, Denninger M, Rancourt D, Moisan C, Laurendeau D (2005) Modeling liver tissue properties using a non-linear visco-elastic model for surgery simulation. Med Image Anal 9: 103–112

    PubMed  Article  Google Scholar 

  16. Fung YC (1981) Biomechanics: mechanical properties of living tissues. Springer, New York, pp, pp 196–257

    Google Scholar 

  17. Basafa E, Farahmand F, Vossoughi G (2008) A non-linear mass-spring model for more realistic and efficient simulation of soft tissues surgery. Stud Health Technol Inform 132: 23–25

    PubMed  Google Scholar 

  18. Miller K, Chinzei K, Orssengo G, Bednarz P (2000) Mechanical properties of brain tissue in vivo: experiment and computer simulation. J Biomech 33(4): 1369–1376

    PubMed  Article  CAS  Google Scholar 

  19. Carter FJ, Frank TG, Davies PJ, Mclean D, Cuschieri A (2001) Measurements and modeling of the compliance of human and porcine organs. Med Image Anal 5(4): 231–236

    PubMed  Article  CAS  Google Scholar 

  20. Ottensmeyer MP, Kerdok AE, Howe RD, Dawson SL (2004) The effects of testing environment on the viscoelastic properties of Soft tissues. Lect Notes Comput Sci 3078: 9–18

    Article  Google Scholar 

  21. Kim J, Srinivasan MA (2005) Characterization of viscoelastic soft tissue properties from in vivo animal experiments and inverse FE parameter estimation. Lect Notes Comput Sci 3750: 599–606

    Article  Google Scholar 

  22. Tay BK, Kim J, Srinivasan MA (2006) In vivo mechanical behavior of intra-abdominal organs. IEEE Trans Biomed Eng 53(11): 2129–2138

    PubMed  Article  Google Scholar 

  23. Samur E, Sedef M, Basdogan C, Avtan L, Duzgun O (2007) A robotic indenter for minimally invasive measurement and characterization of soft tissue response. Med Image Anal 11(4): 361–373

    PubMed  Article  Google Scholar 

  24. Egorov V, Tsyuryupa S, Kanilo S, Kogit M, Sarvazyan A (2008) Soft tissue elastometer. Med Eng Phys 30: 206–212

    PubMed  Article  CAS  Google Scholar 

  25. Ahn B, Kim J (2009) Efficient soft tissue characterization under large deformations in medical simulations. Int J Precis Eng Manuf 10(4): 115–121

    Article  Google Scholar 

  26. Kauer M, Vuskovic V, Dual J, Szekely G, Bajka M (2002) Inverse finite element characterization of soft tissue. Med Image Anal 6(3): 275–287

    PubMed  Article  CAS  Google Scholar 

  27. Mazza E, Nava A, Hahnloser D, Jochum W, Bajka M (2007) The mechanical response of human liver and its relation to histology: An in vivo study. Med Image Anal 11: 663–672

    PubMed  Article  Google Scholar 

  28. Nasseri S, Bilston LE, Phan-Thien N (2002) Viscoelastic properties of pig kidney in shear, experimental results and modeling. Rheolgica Acta 41(1–2): 180–192

    Article  CAS  Google Scholar 

  29. Valtorta D, Mazza E (2005) Dynamic measurement of soft tissue viscoelastic properties with a torsional resonator device. Med Image Anal 9(5): 481–490

    PubMed  Article  Google Scholar 

  30. Sakuma I, Nishimura Y, Chui CK, Kobayashi E, Inada H, Chen X, Hisada T (2003) In vitro measurement of mechanical properties of liver tissue under compression and elongation using a new test piece holding method with surgical glue. Lect Notes Comput Sci 2673: 284–292

    Article  Google Scholar 

  31. Hu T, Desai JP (2003) Characterization of soft-tissue material properties: large deformation analysis. Lect Notes Comput Sci 3078: 28–37

    Article  Google Scholar 

  32. Rosen J, Brown JD, De S, Sinanan M, Hannaford B (2008) Biomechanical properties of abdominal organs in vivo and postmortem under compression loads. J Biomech Engin 130(2): 021020.1–021020.17

    Google Scholar 

  33. Lim YJ, Deo D, Singh TP, Jones DB, De S (2009) In situ measurement and modeling of biomechanical response of human cadaveric soft tissues for physics-based surgical simulation. Surg Endosc 23: 1298–1307

    PubMed  Article  Google Scholar 

  34. Kuhnapfel U, Cakmak HK, Maasz H (2000) Endoscopic surgery training using virtual reality and deformable tissue simulation. Comput Graph 24: 671–682

    Article  Google Scholar 

  35. Paloc C, Faraci A, Bello F (2006) Online remeshing for soft tissue simulation in surgical training. IEEE Comput Graph Appl 26: 24–34

    PubMed  Article  Google Scholar 

  36. Choi K-S, Sun H, Heng P-A (2004) An efficient and scalable deformable model for virtual reality-based medical applications. Artif Intell Med 32: 51–69

    PubMed  Article  Google Scholar 

  37. Teschner M, Girod S, Girod B (2001) Realistic modeling of elasto-mechanical properties of soft tissue and its evaluation. Int Congr Ser 1230: 51–56

    Article  Google Scholar 

  38. Thomson WT, Dahlen MD (1998) Theory of vibration with applications. Prentice-Hall, New Jersey

    Google Scholar 

  39. Tillier Y, Paccinia A, Durand-Revilleb M, Baya F, Chenot J-L (2003) Three-dimensional finite element modelling for soft tissues surgery. Int Congr Ser 1256: 349–355

    Article  Google Scholar 

  40. Joukhadar A, Garat F, Laugier C (1997) Parameter identification for dynamic simulation, IEEE International Conference on Robotics and Automation, IEEE, New Mexico, USA

  41. Deussen O, Kobbelt L, Tucke P (1995) Using simulated annealing to obtain good nodal approximations of deformable objects. In: Terzopoulos D, Thalmann D (eds) Eurographics workshop on computer animation and simulation. Springer, NewYork, pp 30–43

    Google Scholar 

  42. Louchet J, Provot X, Crochemore D (1995) Evolutionary identification of cloth animation models, Proceedings of the Eurographics Workshop on Computer Animation and Simulation, pp 44–54

  43. Laycock SD, Day AM (2005) Incorporating haptic feedbackfor the simulation of a deformable tool in a rigid scene. Comput Graph 29: 341–351

    Article  Google Scholar 

  44. Gregory AD, Lin MC, Gottschalk S, Taylor R (2000) Fast and accurate collision detection for haptic interaction using a three degree-of-freedom force-feedback device. Comput Geom 15: 69–89

    Article  Google Scholar 

  45. Zilles CB, Salisbury JK (1995) A constraint-based god-object method for haptic display, IEEE/RSJ International Conference on ntelligent Robots and Systems, Pittsburgh, PA, USA, pp 146–151

  46. Meier U, Lopez O, Monserrat C, Juan MC, Alcaniz M (2005) Real-time deformable models for surgery simulation: a survey. Comput Methods Programs Biomed 77: 183–197

    PubMed  Article  CAS  Google Scholar 

  47. Timoshenko S, Goodier JN (1951) Theory of elasticity. McGraw-Hill Book Company, New York, p, p 367

    Google Scholar 

  48. Astley OR, Hayward V (2000) Design constraints for haptic surgery simulation, IEEE International Conference on Robotics and Automation, San Francisco, CA, USA, pp 2446–2451

  49. Choi K-S, Sun H, Heng P-A, Zou J (2004) Deformable simulation using force propagation model with finite element optimization. Comput Graph 28: 559–668

    Article  Google Scholar 

  50. d’Aulignac D, Cavusoglu MC, Laugier C (1999) Modeling the dynamics of the human thigh for a realistic echographic simulator with force feedback. In: Proceedings of International Conference on Medical Image Computing Computer-Assisted Intervention. Lecture Notes in Computer Science, vol 1679. Springer, Berlin, pp 1191–1198

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Correspondence to Farzam Farahmand.

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Basafa, E., Farahmand, F. Real-time simulation of the nonlinear visco-elastic deformations of soft tissues. Int J CARS 6, 297–307 (2011). https://doi.org/10.1007/s11548-010-0508-6

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  • DOI: https://doi.org/10.1007/s11548-010-0508-6

Keywords

  • Soft tissue
  • Surgery simulation
  • Mass-spring models
  • Deformable modeling