Skip to main content
SpringerLink
Log in

Real-Time Deformation Simulation of Kidney Surgery Based on Virtual Reality

  • Published:
Journal of Shanghai Jiaotong University (Science) Aims and scope Submit manuscript

Abstract

Virtual reality-based surgery simulation is becoming popular with the development of minimally invasive abdominal surgery, where deformable soft tissue is modelled and simulated. The mass-spring model (MSM) and finite element method (FEM) are common methods used in the simulation of soft tissue deformation. However, MSM has an issue concerning accuracy, while FEM has a problem with efficiency. To achieve higher accuracy and efficiency at the same time, we applied a co-rotational FEM in the simulation of a kidney with a tumour inside, achieving a real-time and accurate deformation simulation. In addition, we set a multi-model representation for mechanical simulation and visual rendering. The implicit Euler method and conjugate gradient method were adopted for setting and solving the linear system. For a realistic simulation of surgery, constraints outside the kidney and between the kidney and tumour were set with two series of mechanical properties for the two models. Experiments were conducted to validate the accuracy and real-time performance.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. ANTONIOU S A, ANTONIOU G A, ANTONIOU A I, et al. Past, present, and future of minimally invasive abdominal surgery [J]. Journal of the Society of Laparoendoscopic Surgeons, 2015, 19(3): e2015.00052.

    Article  Google Scholar 

  2. BERNHARDT S, NICOLAU S A, SOLER L, et al. The status of augmented reality in laparoscopic surgery as of 2016 [J]. Medical Image Analysis, 2017, 37: 66–90.

    Article  Google Scholar 

  3. DUAN Y P, HUANG W M, CHANG H B, et al. Volume preserved mass-spring model with novel constraints for soft tissue deformation [J]. IEEE Journal of Biomedical and Health Informatics, 2016, 20(1): 268–280.

    Article  Google Scholar 

  4. NEALEN A, MÜLLERM, KEISER R, et al. Physically based deformable models in computer graphics [J]. Computer Graphics Forum, 2006, 25(4): 809–836.

    Article  Google Scholar 

  5. ZIENKIEWICZ O C, TAYLOR R L, ZHU J Z. Field problems: A multidimensional finite element method [M]//The finite element method: Its basis and fundamentals. Amsterdam: Elsevier, 2013: 115–149.

    Chapter  Google Scholar 

  6. DE S, KIM J, LIM Y J, et al. The point collocation-based method of finite spheres (PCMFS) for real time surgery simulation [J]. Computers & Structures, 2005, 83(17/18): 1515–1525.

    Article  Google Scholar 

  7. FREUTEL M, SCHMIDT H, DÜRSELEN L, et al. Finite element modeling of soft tissues: Material models, tissue interaction and challenges [J]. Clinical Biomechanics, 2014, 29(4): 363–372.

    Article  Google Scholar 

  8. COURTECUISSE H, JUNG H, ALLARD J, et al. GPU-based real-time soft tissue deformation with cutting and haptic feedback [J]. Progress in Biophysics and Molecular Biology, 2010, 103(2/3): 159–168.

    Article  Google Scholar 

  9. COURTECUISSE H, ALLARD J, KERFRIDEN P, et al. Real-time simulation of contact and cutting of heterogeneous soft-tissues [J]. Medical Image Analysis, 2014, 18(2): 394–410.

    Article  Google Scholar 

  10. PLANTEFÈVE R, PETERLIK I, HAOUCHINE N, et al. Patient-specific biomechanical modeling for guidance during minimally-invasive hepatic surgery [J]. Annals of Biomedical Engineering, 2016, 44(1): 139–153.

    Article  Google Scholar 

  11. HELLER N, SATHIANATHEN N, KALAPARA A, et al. The KiTS19 challenge data: 300 kidney tumor cases with clinical context, CT semantic segmentations, and surgical outcomes [EB/OL]. [2020-12-02]. https://arxiv.org/pdf/1904.00445v2.pdf.

  12. NEWMAN T S, YI H. A survey of the marching cubes algorithm [J]. Computers & Graphics, 2006, 30(5): 854–879.

    Article  Google Scholar 

  13. GARLAND M, HECKBERT P S. Surface simplification using quadric error metrics [C]//Proceedings of the 24th Annual Conference on Computer Graphics and Interactive Techniques. New York: ACM Press, 1997: 209–216.

    Google Scholar 

  14. JU T, LOSASSO F, SCHAEFER S, et al. Dual contouring of hermite data [C]//Proceedings of the 29th Annual Conference on Computer Graphics and Interactive Techniques. New York: ACM Press, 2002: 339–346.

    Chapter  Google Scholar 

  15. NESME M, PAYAN Y, FAURE F. Efficient, physically plausible finite elements [EB/OL]. [2020-12-02]. https://hal.inria.fr/inria-00394480v1/document.

  16. FAURE F, DURIEZ C, DELINGETTE H, et al. SOFA: A multi-model framework for interactive physical simulation [M]//Soft tissue biomechanical modeling for computer assisted surgery. Berlin, Heidelberg: Springer, 2012: 283–321.

    Chapter  Google Scholar 

  17. BARAFF D, WITKIN A. Large steps in cloth simulation [C]//Proceedings of the 25th Annual Conference on Computer Graphics and Interactive Techniques. New York: ACM Press, 1998: 43–54.

    Google Scholar 

  18. SHEWCHUK J R. An introduction to the conjugate gradient method without the agonizing pain [R]. Schenley Park Pittsburgh, PA, USA: Carnegie Mellon University, 1994.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institute of Biomedical Manufacturing and Life Quality Engineering, State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China

    Mengjie Jing  (荆梦杰), Zhixin Cui  (崔志鑫), Hang Fu  (傅航) & Xiaojun Chen  (陈晓军)

  2. Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai, 200240, China

    Xiaojun Chen  (陈晓军)

Authors
  1. Mengjie Jing  (荆梦杰)
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Zhixin Cui  (崔志鑫)
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Hang Fu  (傅航)
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Xiaojun Chen  (陈晓军)
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Xiaojun Chen  (陈晓军).

Additional information

Foundation item: the National Key Research and Development Program of China (No. 2017YFB1302900), the National Natural Science Foundation of China (Nos. 81971709, M-0019, and 82011530141), the Foundation of Science and Technology Commission of Shanghai Municipality (Nos. 19510712200, and 20490740700), and the Shanghai Jiao Tong University Foundation on Medical and Technological Joint Science Research (Nos. ZH2018ZDA15, YG2019ZDA06, and ZH2018QNA23), and the 2020 Key Research Project of Xiamen Municipal Government (No. 3502Z20201030)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Jing, M., Cui, Z., Fu, H. et al. Real-Time Deformation Simulation of Kidney Surgery Based on Virtual Reality. J. Shanghai Jiaotong Univ. (Sci.) 26, 290–297 (2021). https://doi.org/10.1007/s12204-021-2295-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12204-021-2295-3

Key words

CLC number

Document code

Search

Navigation