Advertisement

Robot-Assisted Laparoscopic Ultrasound

  • Caitlin M. Schneider
  • Gregory W. DachsII
  • Christopher J. Hasser
  • Michael A. Choti
  • Simon P. DiMaio
  • Russell H. Taylor
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6135)

Abstract

Novel tools for existing robotic surgical systems present opportunities for exploring improved techniques in minimally invasive surgery. Specifically, intraoperative ultrasonography is a tool that is being used with increased frequency, yet has limitations with existing laparoscopic systems. The purpose of this study was to develop and to evaluate a new ultrasound system with the da Vinci ® Surgical System (Intuitive Surgical Inc., Sunnyvale CA) for laparoscopic visualization. The system consists of a prototype dexterous laparoscopic ultrasound instrument for use with the da Vinci surgical system, an integrated image display, and navigation tools. The system was evaluated by surgeons during pertinent activities, including phantom lesion detection and needle biopsy tasks, as well as in vivo porcine visualization and manipulation tasks. The system was found to be highly dexterous, clinically desirable, and advantageous over traditional laparoscopic systems. This device promises to improve performance of complex minimally-invasive surgical procedures.

Keywords

Augmented Reality Laparoscopic Partial Nephrectomy Laparoscopic Ultrasound Display Mode Vinci Surgical System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Patel, V.R., Palmer, K.J., Coughlin, G., Samavedi, S.: Robot-assisted laparoscopic radical prostatectomy: perioperative outcomes of 1500 cases. J. Endourol. 22, 2299–2305 (2008)CrossRefGoogle Scholar
  2. 2.
    Drouin, S.J., Vaessen, C., Hupertan, V., Comperat, E., Misrai, V., Haertig, A., Bitker, M.O., Chartier-Kastler, E., Richard, F., Roupret, M.: Comparison of mid-term carcinologic control obtained after open, laparoscopic, and robot-assisted radical prostatectomy for localized prostate cancer. World J. Urol. 27, 599–605 (2009)CrossRefGoogle Scholar
  3. 3.
    Ukimura, O., Nakamoto, M., Desai, M., Herts, B., Aron, M., Haber, G.-P., Kaouk, J., Miki, T., Sato, Y., Hashizume, M., Gill, I.: Augmented Reality Visualization During Laparoscopic Urologic Surgery: the Initial Clinical Experience. In: The 102nd American Urological Association (AUA 2007) Annual Meeting, Anaheim, p. V1052.(2007)Google Scholar
  4. 4.
    Su, L.-M., Vagvolgyi, B.P., Agarwal, R., Reiley, C.E., Taylor, R.H., Hager, G.D.: Augmented Reality During Robot-assisted Laparoscopic Partial Nephrectomy: Toward Real-Time 3D-CT to Stereoscopic Video Registration. Urology 73, 896–900 (2009)CrossRefGoogle Scholar
  5. 5.
    Wagner, C.R., Stylopoulos, N., Jackson, P.G., Howe, R.D.: The Benefit of Force Feedback in Surgery: Examination of Blunt Dissection. Presence: Teleoperators and Virtual Environments (2007)Google Scholar
  6. 6.
    Okamura, A.M.: Methods for Haptic Feedback in Teleoperated Robot-Assisted Surgery. Industrial Robot 31, 499–508 (2004)CrossRefGoogle Scholar
  7. 7.
    Kapoor, A., Taylor, R.: A Constrained Optimization Approach to Virtual Fixtures for Multi-Handed Tasks. In: IEEE International Conference on Robotics and Automation (ICRA), Pasadena, pp. 3401–3406 (2008)Google Scholar
  8. 8.
    Marayong, P., Bettini, A., Okamura, A.: Effect of Virtual Fixture Compliance on Human-Machine Cooperative Manipulation. In: EEE/RSJ International Conference on Intelligent Robots and Systems, pp. 1089–1095 (2002)Google Scholar
  9. 9.
    Park, S., Howe, R.D., Torchiana, D.F.: Virtual Fixtures for Robotic Cardiac Surgery. In: Niessen, W.J., Viergever, M.A. (eds.) MICCAI 2001. LNCS, vol. 2208. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  10. 10.
    Kazanzides, P., Hata, N., Ibanez, L.: Systems and Architectures for Computer Assisted Interventions (MICCAI 2008 Workshop) – Issue of Insight Journal, New York (2008)Google Scholar
  11. 11.
    Bosch, F., Ribes, J., Cléries, R., Díaz, M.: Epidemiology of hepatocellular carcinoma. Clin. Liver Dis. 9, 191–211 (2005)CrossRefGoogle Scholar
  12. 12.
    Kane, R.A.: Intraoperative Ultrasonography, History, Current State of the Art, and Future Directions. J. Ultrasound Med. 23, 1407–1420 (2004)MathSciNetGoogle Scholar
  13. 13.
    Zacherl, J., Scheuba, C., Imhof, M., Zacherl, M., Langle, F., Pokieser, P., Wrba, F., Wenzl, E., Muhlbacher, F., Jakesz, R., Steininger, R.: Current value of intraoperative sonography during surgery for hepatic neoplasms. World J. Surg. 26, 550–554 (2002)CrossRefGoogle Scholar
  14. 14.
    Fleming, I.N., Rivaz, H., Macura, K., Su, L.-M., Hamper, U., Lotan, T., Lagoda, G., Burnett, A., Taylor, R.H., Hager, G.D., Boctor, E.M.: Ultrasound elastography: enabling technology for image guided laparoscopic prostatectomy. In: SPIE Medical Imaging 2009: Visualization, Image-guided Procedures and Modeling, Orlando, Florida, vol. 7261, pp. 72612I–72612I-12 (2009)Google Scholar
  15. 15.
    Salcudean, S., Wen, X.u., Mahdavi, S., Moradi, M., Morris, J.W., Spadinger, I.: Ultrasound elastography – an image guidance tool for prostate brachytherapy. Brachytherapy 8, 125–126 (2009)CrossRefGoogle Scholar
  16. 16.
    Wood, T., Rose, D., Chung, M., Allegra, D., Foshag, L., Bilchik, A.: Radiofrequency ablation of 231 unre-sectable hepatic tumors: indications, limitations, and complications. Ann. Surg. Oncol. 7, 593–600 (2000)Google Scholar
  17. 17.
    Fenster, A., Downey, D.B., Cardinal, H.N.: Three-dimensional ultrasound imaging. Phys. Med. Biol. 46, R67–R99 (2001)Google Scholar
  18. 18.
    Cunha, D.d., Gravez, P., Leroy, C., Maillard, E., Jouan, J., Varley, P., Jones, M., Halliwell, M., Hawkes, D., Wells, P.N.T., Angelini, L.: The MIDSTEP System for Ultrasound guided Remote Telesurgery. In: IEEE EMBS, pp. 1266–1269 (1998)Google Scholar
  19. 19.
    Budde, R.P.J., Dessing, T.C., Meijer, R., Bakker, P.F.A., Borst, C., Gründeman, P.F.: Robot-assisted 13 MHz epicardial ultrasound for endoscopic quality assessment of coronary anastomoses. Interactive Cardiovascular and Thoracic Surgery 3 (2004)Google Scholar
  20. 20.
    Leven, J., Burschka, D., Kumar, R., Zhang, G., Blumenkranz, S.J., Dai, X., Awad, M., Hager, G., Marohn, M., Choti, M., Hasser, C., Taylor, R.H.: DaVinci Canvas: A Telerobotic Surgical System with Integrated, Robot-Assisted, Laparoscopic Ultrasound Capability. In: Duncan, J.S., Gerig, G. (eds.) MICCAI 2005. LNCS, vol. 3749, pp. 811–818. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  21. 21.
    Mansy, H.A., Grahe, J.R., Sandler, R.H.: Elastic properties of synthetic materials for soft tissue modeling. Phys. Med. Biol. 53, 2115–2130 (2008)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Caitlin M. Schneider
    • 1
  • Gregory W. DachsII
    • 1
  • Christopher J. Hasser
    • 1
  • Michael A. Choti
    • 1
  • Simon P. DiMaio
    • 1
  • Russell H. Taylor
    • 1
  1. 1.Department of Computer Science, Department of Surgery, Johns Hopkins Medicine, Intuitive Surgical Inc.Johns Hopkins University 

Personalised recommendations