Model Predictive Control of a Medical Robotic System

  • Ivan BuzurovicEmail author
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 54)


One of the most challenging phases in interstitial brachytherapy is the placement of the needles. In these medical procedures, the needles are inserted inside the tissue to guide the positioning of the radioactive sources. The low dose-rate (LDR) radioactive sources are placed inside the tissue permanently, whereas a radioactive source in the high dose-rate (HDR) brachytherapy is temporarily placed in the desired positions so that the delivery of the prescription dose to the clinical targets can be achieved. Therefore, it is important to develop a robust and sophisticated tool that can perform the automatic needle placement with a high level of accuracy for different medical procedures and conditions. In this study, we propose a novel concept for the automatic needle insertion using a new miniature automated robotic system. The mathematical model of this system was derived, allowing the implementation of the model predictive control (MPC) that can be used to govern the mechanism. The purpose of this approach was to minimize the lateral components of the generalized reactive force which is responsible for the tissue displacement and, consequently, for the needle deflection.


Robotic system Model predictive control Needle insertion 


  1. 1.
    Buzurovic, I., Podder, T.K., Yu, Y.: Prediction control for brachytherapy robotic system. J. Robot. 1, 1–10 (2010)Google Scholar
  2. 2.
    Buzurovic, I., et al.: Real-time control strategy for collision avoidance and seed deposition in brachytherapy robotic system. Int. J. Comput. Assist. Radiol. Surg. 3, 30–34 (2008)CrossRefGoogle Scholar
  3. 3.
    Siebert, F.A., Hirt, M., Niehoff, P., Kovács, P.: Imaging of implant needles for real-time HDR-brachytherapy prostate treatment using biplane ultrasound transducers. Med. Phys. 36(8), 3406–3412 (2004)CrossRefGoogle Scholar
  4. 4.
    Abolhassani, N., Patel, R., Moallem, M.: Trajectory generation for robotic needle insertion in soft tissue. In: Proceedings of the 26th IEEE International Conference on Engineering in Medicine and Biology (EMBS), San Francisco CA, USA, pp. 2730–2733 (2004)Google Scholar
  5. 5.
    Alterovitz, R., Goldberg, K., Pouliot, J., Taschereau, R., Hsu, I.-C.: Sensorless planning for medical needle insertion procedures. In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, Las Vegas, NV, USA, pp. 3337–3343 (2003)Google Scholar
  6. 6.
    Chui, C.-K., Teoh, S.-H., Ong, C.-J., Anderson, J.H., Sakuma, I.: Integrative modeling of liver organ for simulation of flexible needle insertion. In: Proceedings of the 9th IEEE International Conference on Control, Automation, Robotics and Vision (ICARCV), Singapore, pp. 1–6 (2006)Google Scholar
  7. 7.
    Crouch, J.R., Schneider, C.M., Wainer, J., Okamura, A.M.: Velocity-dependent model for needle insertion in soft tissue. In: Proceedings of the 2005 Medical Image Computing and Computer-Assisted Intervention (MICCAI 2005), pp. 624–632 (2005)Google Scholar
  8. 8.
    DiMaio, S.P., Salcudean, S.E.: Needle insertion modeling and simulation. IEEE Trans. Robot. Autom. 19(5), 864–875 (2003)CrossRefGoogle Scholar
  9. 9.
    DiMaio, S.P., Salcudean, S.E.: Interactive simulation of needle insertion models. IEEE Trans. Biomed. Eng. 52(7), 1167–1179 (2005)CrossRefGoogle Scholar
  10. 10.
    Okamura, A.M., Simone, C., O’Leary, M.D.: Force modeling for needle insertion into soft tissue. IEEE Trans. Biomed. Eng. 51(10), 1707–1716 (2004)CrossRefGoogle Scholar
  11. 11.
    Wan, G., Wei, Z., Gardi, L., Downey, D.B., Downey, D.B., Fenster, A.: Brachytherapy needle deflection evaluation and correction. Med. Phys. 32(4), 902–909 (2005)CrossRefGoogle Scholar
  12. 12.
    Buzurovic, I., Tarun, K., Yu, Y.: Robotic systems for radiation therapy. In: Dutta, A. (ed.) Robotic Systems: Applications, Control and Programming, pp. 85–106. InTech, Rijeka (2012)Google Scholar
  13. 13.
    Fichtinger, G., Burdette, E.C., Tanacs, A., Patriciu, A., Mazilu, D., Whitcomb, L.L., et al.: Robotically assisted prostate brachytherapy with transrectal ultrasound guidance: phantom experiments. Brachytherapy 5, 14–26 (2006)CrossRefGoogle Scholar
  14. 14.
    Lin, A., Trejos, A.L., Patel, R.V., Malthaner, R.A.: Robot-assisted minimally invasive brachytherapy for lung cancer. Telesurgery 4, 35–52 (2008)Google Scholar
  15. 15.
    Meltsner, M.A., Ferrier, N.J., Thomadsen, B.R.: Observations on rotating needle insertions using a brachytherapy robot. Phys. Med. Biol. 52, 6027–6037 (2007)CrossRefGoogle Scholar
  16. 16.
    Moerland, M.A., Van den Bosch, M.R., Lagerburg, V., Battermann, J.J., Van Vulpen, M., Lagendijk, J.J.W.: An MRI scanner compatible implant robot for prostate brachytherapy. Brachytherapy 7(2), 100 (2008)CrossRefGoogle Scholar
  17. 17.
    Wei, Z., Wan, G., Gardi, L., Mills, G., Downey, D., Fenster, A.: Robot-assisted 3D-TRUS guided prostate brachytherapy: system integration and validation. Med. Phys. 31, 539–548 (2004)CrossRefGoogle Scholar
  18. 18.
    Buzurovic, I., Podder, T.K., Yan, K., Hu, Y., Valicenti, R., Dicker, A., Yu, Y.: Parameter optimization for brachytherapy robotic needle insertion and seed deposition. Med. Phys. 35(6), 2865 (2008)CrossRefGoogle Scholar
  19. 19.
    Buzurovic, I., Podder, T.K., Yu, Y.: Force prediction and tracking for image-guided robotic system using neural network approach. In: Proceedings of the IEEE Biomedical Circuits and Systems Conference (BioCAS), Baltimore MA, USA, pp. 41–44 (2008)Google Scholar
  20. 20.
    Buzurovic, I., Debeljkovic, D.: A Geometric approach to the investigation of the dynamics of constrained robotic systems. In: Proceedings of the IEEE International Symposium on Intelligent Systems and Informatics (SYSI), Subotica, Serbia, pp. 133–138 (2010)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Harvard Medical SchoolHarvard UniversityBostonUSA

Personalised recommendations