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Virtual Laparoscopic Training System Based on VCH Model

  • Education & Training
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Abstract

Laparoscopy has been widely used to perform abdominal surgeries, as it is advantageous in that the patients experience lower post-surgical trauma, shorter convalescence, and less pain as compared to traditional surgery. Laparoscopic surgeries require precision; therefore, it is imperative to train surgeons to reduce the risk of operation. Laparoscopic simulators offer a highly realistic surgical environment by using virtual reality technology, and it can improve the training efficiency of laparoscopic surgery. This paper presents a virtual Laparoscopic surgery system. The proposed system utilizes the Visible Chinese Human (VCH) to construct the virtual models and simulates real-time deformation with both improved special mass-spring model and morph target animation. Meanwhile, an external device that integrates two five-degrees-of-freedom (5-DOF) manipulators was designed and made to interact with the virtual system. In addition, the proposed system provides a modular tool based on Unity3D to define the functions and features of instruments and organs, which could help users to build surgical training scenarios quickly. The proposed virtual laparoscopic training system offers two kinds of training mode, skills training and surgery training. In the skills training mode, the surgeons are mainly trained for basic operations, such as laparoscopic camera, needle, grasp, electric coagulation, and suturing. In the surgery-training mode, the surgeons can practice cholecystectomy and removal of hepatic cysts by guided or non-guided teaching.

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References

  1. Urbina, B., Coto, E., Rodríguez, O., and Miquilarena, R., Cerrolaza M a virtual system for laparoscopic surgery training. In, II Conferencia Internacional de Bioingeniería Computacional, 2005.

    Google Scholar 

  2. Heng, P.-A., Cheng, C.-Y., Wong, T.-T., Xu, Y., Chui, Y.-P., Chan, K.-M., and Tso, S.-K., A virtual-reality training system for knee arthroscopic surgery. Information Technology in Biomedicine, IEEE Transactions on. 8(2):217–227, 2004.

    Article  Google Scholar 

  3. Pan, J.J., Chang, J., Yang, X., Zhang, J.J., Qureshi, T., Howell, R., and Hickish, T., Graphic and haptic simulation system for virtual laparoscopic rectum surgery. The International Journal of Medical Robotics and Computer Assisted Surgery. 7(3):304–317, 2011.

    PubMed  Google Scholar 

  4. Kenney, P.A., Wszolek, M.F., Gould, J.J., Libertino, J.A., and Moinzadeh, A., Face, content, and construct validity of dV-trainer, a novel virtual reality simulator for robotic surgery. Urology. 73(6):1288–1292, 2009.

    Article  PubMed  Google Scholar 

  5. Lendvay, T.S., Casale, P., Sweet, R., and Peters, C., Initial validation of a virtual-reality robotic simulator. Journal of Robotic Surgery. 2(3):145–149, 2008. doi:10.1007/s11701-008-0099-1.

    Article  PubMed  Google Scholar 

  6. Bonrath, E.M., Weber, B.K., Fritz, M., Mees, S.T., Wolters, H.H., Senninger, N., and Rijcken, E., Laparoscopic simulation training: testing for skill acquisition and retention. Surgery. 152(1):12–20, 2012.

    Article  PubMed  Google Scholar 

  7. Ahlberg, G., Enochsson, L., Gallagher, A.G., Hedman, L., Hogman, C., McClusky III, D.A., Ramel, S., Smith, C.D., and Arvidsson, D., Proficiency-based virtual reality training significantly reduces the error rate for residents during their first 10 laparoscopic cholecystectomies. The American journal of surgery. 193(6):797–804, 2007.

    Article  PubMed  Google Scholar 

  8. Basdogan, C., Ho, C.-H., and Srinivasan, M.A., Virtual environments for medical training: graphical and haptic simulation of laparoscopic common bile duct exploration. Mechatronics, IEEE/ASME Transactions on. 6(3):269–285, 2001.

    Article  Google Scholar 

  9. Lamata, P., Gómez, E.J., Sánchez-Margallo, F.M., López, Ó., Monserrat, C., García, V., Alberola, C., Florido, M.Á.R., Ruiz, J., and Usón, J., SINERGIA laparoscopic virtual reality simulator: didactic design and technical development. Computer methods and programs in biomedicine. 85(3):273–283, 2007.

    Article  PubMed  Google Scholar 

  10. Delingette, H., Toward realistic soft-tissue modeling in medical simulation. Proceedings of the IEEE. 86(3):512–523, 1998.

    Article  Google Scholar 

  11. Sadraei E, Moazzen MH, Moghaddam MM, Sijani FS Real-time haptic simulation of soft tissue deformation. In: Robotics and Mechatronics (ICRoM), 2014 Second RSI/ISM International Conference on, 2014. IEEE, pp 053–058.

  12. Lombardo J-C, Cani M-P, Neyret F Real-time collision detection for virtual surgery. In: Computer Animation, 1999. Proceedings, 1999. IEEE, pp 82–90.

  13. Mi S-H, Hou Z-G, Yang F, Xie X-L, Bian G-B A collision response algorithm for 3D virtual reality minimally invasive surgery simulator. In: Control and Decision Conference (2014 CCDC), the 26th Chinese, 2014. IEEE, pp 4594–4599.

  14. Mimic http://www.mimicsimulation.com. Accessed 4 August 2015

  15. Lallas CD, Davis, Members of the Society of Urologic Robotic Surgeons JW, Robotic surgery training with commercially available simulation systems in 2011: a current review and practice pattern survey from the society of urologic robotic surgeons. Journal of Endourology. 26(3):283–293, 2012.

    Article  Google Scholar 

  16. RoSS. http://www.simulatedsurgicals.com/. Accessed 4 August 2015

  17. Seixas-Mikelus, S.A., Kesavadas, T., Srimathveeravalli, G., Chandrasekhar, R., Wilding, G.E., and Guru, K.A., Face validation of a novel robotic surgical simulator. Urology. 76(2):357–360, 2010.

    Article  PubMed  Google Scholar 

  18. SimSurgery. http://www.simsurgery.com/. Accessed 4 August 2015

  19. LI, A.A., Construction and visualization of high-resolution three-dimensional anatomical structure datasets for Chinese digital human. Chinese Science Bulletin. 53(12):1848–1854, 2008.

    Google Scholar 

  20. Tang, L., Chung, M.S., Liu, Q., and Shin, D.S., Advanced features of whole body sectioned images: virtual Chinese human. Clinical Anatomy. 23(5):523–529, 2010.

    Article  PubMed  Google Scholar 

  21. Normal mapping. https://en.wikipedia.org/wiki/Normal_mapping. Accessed 4 August 2015

  22. Morph target animation. https://en.wikipedia.org/wiki/Morph_target_animation. Accessed 4 August 2015

  23. Unity3D. http://unity3d.com/. Accessed 4 August 2015

  24. Lv, Z., Tek, A., Da Silva, F., Empereur-mot, C., Chavent, M., and Baaden, M., Game on, science-how video game technology may help biologists tackle visualization challenges. PloS one. 8(3):e57990, 2013.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

This work was supported by the National High-Tech Re-search and Development Program of China (863 Program: 2012AA02A606), the Program for New Century Excellent Talents in University (Grant No.NCET-10-0386).

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Authors and Affiliations

  1. Huazhong University of Science & Technology, Wuhan, Hubei, People’s Republic of China

    Jiangzhou Tang, Lang Xu, Longjun He, Songluan Guan, Xing Ming & Qian Liu

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  1. Jiangzhou Tang
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  2. Lang Xu
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  3. Longjun He
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  4. Songluan Guan
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  5. Xing Ming
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  6. Qian Liu
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Correspondence to Qian Liu.

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This article is part of the Topical Collection on Education and Training

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Tang, J., Xu, L., He, L. et al. Virtual Laparoscopic Training System Based on VCH Model. J Med Syst 41, 58 (2017). https://doi.org/10.1007/s10916-017-0702-y

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