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Surgical Endoscopy

, Volume 28, Issue 3, pp 933–940 | Cite as

Real-time image guidance in laparoscopic liver surgery: first clinical experience with a guidance system based on intraoperative CT imaging

  • Hannes G. KenngottEmail author
  • Martin Wagner
  • Matthias Gondan
  • Felix Nickel
  • Marco Nolden
  • Andreas Fetzer
  • Jürgen Weitz
  • Lars Fischer
  • Stefanie Speidel
  • Hans-Peter Meinzer
  • Dittmar Böckler
  • Markus W. Büchler
  • Beat P. Müller-Stich
Article

Abstract

Background

Laparoscopic liver surgery is particularly challenging owing to restricted access, risk of bleeding, and lack of haptic feedback. Navigation systems have the potential to improve information on the exact position of intrahepatic tumors, and thus facilitate oncological resection. This study aims to evaluate the feasibility of a commercially available augmented reality (AR) guidance system employing intraoperative robotic C-arm cone-beam computed tomography (CBCT) for laparoscopic liver surgery.

Methods

A human liver-like phantom with 16 target fiducials was used to evaluate the Syngo iPilot® AR system. Subsequently, the system was used for the laparoscopic resection of a hepatocellular carcinoma in segment 7 of a 50-year-old male patient.

Results

In the phantom experiment, the AR system showed a mean target registration error of 0.96 ± 0.52 mm, with a maximum error of 2.49 mm. The patient successfully underwent the operation and showed no postoperative complications.

Conclusion

The use of intraoperative CBCT and AR for laparoscopic liver resection is feasible and could be considered an option for future liver surgery in complex cases.

Keywords

Navigation Liver surgery Liver resection Augmented reality Intraoperative imaging Computer assistance 

Notes

Acknowledgments

The authors thank Siemens AG, Healthcare Sector, for providing expert personnel during the evaluation to calibrate and operate the system during the intervention. In particular, we would like to thank Martin von Roden for his excellent contribution. Professor Böckler received a research grant and speaker honoraria from Siemens AG. Dr. Müller-Stich received reimbursements of travel expenses from Siemens AG, Erlangen, Germany. This research was supported by the Transregional Collaborative Research Centre (TCRC) ‘Cognition-Guided Surgery’ and the Research Training Group 1126 both funded by the DFG (German Research Foundation).

Disclosures

Drs. Kenngott, Wagner, Gondan, Nickel, Nolden, Fetzer, Weitz, Fischer, Meinzer and Büchler have no conflicts of interest or financial ties to disclose.

References

  1. 1.
    Jemal A, Bray F, Center MM, Ferlay J, Ward E, Forman D (2011) Global cancer statistics. CA Cancer J Clin 61(2):69–90PubMedCrossRefGoogle Scholar
  2. 2.
    Peterhans M, Oliveira T, Banz V, Candinas D, Weber S (2012) Computer-assisted liver surgery: clinical applications and technological trends. Crit Rev Biomed Eng 40(3):199–220PubMedCrossRefGoogle Scholar
  3. 3.
    Najmaei N, Mostafavi K, Shahbazi S, Azizian M (2012) Image-guided techniques in renal and hepatic interventions. Int J Med Robot. doi: 10.1002/rcs.1443 PubMedGoogle Scholar
  4. 4.
    Oliveira DA, Feitosa RQ, Correia MM (2011) sation of liver, its vessels and lesions from CT images for surgical planning. Biomed Eng Online 10:30PubMedCentralPubMedCrossRefGoogle Scholar
  5. 5.
    Nam WH, Kang DG, Lee D, Lee JY, Ra JB (2012) Automatic registration between 3D intra-operative ultrasound and pre-operative CT images of the liver based on robust edge matching. Phys Med Biol 57(1):69–91PubMedCrossRefGoogle Scholar
  6. 6.
    Zijlmans M, Langø T, Hofstad EF, Van Swol CFP, Rethy A (2012) Navigated laparoscopy—liver shift and deformation due to pneumoperitoneum in an animal model. Minim Invasive Ther Allied Technol 21(3):241–248PubMedCrossRefGoogle Scholar
  7. 7.
    Bussels B, Goethals L, Feron M, Bielen D, Dymarkowski S, Suetens P, Haustermans K (2003) Respiration-induced movement of the upper abdominal organs: a pitfall for the three-dimensional conformal radiation treatment of pancreatic cancer. Radiother Oncol 68(1):69–74PubMedCrossRefGoogle Scholar
  8. 8.
    Stoykov SA. Micro Dicom viewer. http://www.microdicom.com. Accessed June 2013
  9. 9.
    R Core Team (2012) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna. http://www.R-project.org. Accessed June 2013
  10. 10.
    Gumbs AA, Gayet B, Gagner M (2008) Laparoscopic liver resection: when to use the laparoscopic stapler device. HPB (Oxf) 10(4):296–303CrossRefGoogle Scholar
  11. 11.
    Nozaki T, Iida Y, Morii A, Fujiuchi Y, Fuse H (2012) Laparoscopic radical nephrectomy under near real-time three-dimensional surgical navigation with C-arm cone beam computed tomography. Surg Innov 19(3):263–267PubMedCrossRefGoogle Scholar
  12. 12.
    Nozaki T, Fujiuchi Y, Komiya A, Fuse H (2013) Efficacy of DynaCT for surgical navigation during complex laparoscopic surgery: an initial experience. Surg Endosc 27(3):903–909PubMedCrossRefGoogle Scholar
  13. 13.
    Rossitti S, Pfister M (2009) 3D road-mapping in the endovascular treatment of cerebral aneurysms and arteriovenous malformations. Interv Neuroradiol 15(3):283–290PubMedCentralPubMedGoogle Scholar
  14. 14.
    Ieiri S, Uemura M, Konishi K, Souzaki R, Nagao Y, Tsutsumi N, Akahoshi T, Ohuchida K, Ohdaira T, Tomikawa M, Zanoue K, Hashizume M, Taguchi T (2012) Augmented reality navigation system for laparoscopic splenectomy in children based on preoperative CT image using optical tracking device. Pediatr Surg Int 28(4):341–346PubMedCrossRefGoogle Scholar
  15. 15.
    Nicolau S, Soler L, Mutter D, Marescaux J (2011) Augmented reality in laparoscopic surgical oncology. Surg Oncol 20(3):189–201PubMedCrossRefGoogle Scholar
  16. 16.
    Shekhar R, Dandekar O, Bhat V, Philip M, Lei P, Godinez C, Sutton E, George I, Kavic S, Mezrich R, Park A (2010) Live augmented reality: a new visualization method for laparoscopic surgery using continuous volumetric computed tomography. Surg Endosc 24(8):1976–1985PubMedCrossRefGoogle Scholar
  17. 17.
    Vemuri AS, Wu JCH, Liu KC, Wu HS (2012) Deformable three-dimensional model architecture for interactive augmented reality in minimally invasive surgery. Surg Endosc 26(12):3655–3662PubMedCrossRefGoogle Scholar
  18. 18.
    Teber D, Guven S, Simpfendörfer T, Baumhauer M, Güven EO, Yencilek F, Gözen AS, Rassweiler J (2009) Augmented reality: a new tool to improve surgical accuracy during laparoscopic partial nephrectomy? Preliminary in vitro and in vivo results. Eur Urol 56(2):332–338PubMedCrossRefGoogle Scholar
  19. 19.
    Våpenstad C, Rethy A, Langø T, Selbekk T, Ystgaard B, Hernes TA, Marvik R (2010) Laparoscopic ultrasound: a survey of its current and future use, requirements, and integration with navigation technology. Surg Endosc 24(12):2944–2953PubMedCrossRefGoogle Scholar
  20. 20.
    Rassweiler MC, Ritter M, Michel MS, Häcker A (2013) Influence of endourological devices on 3D reconstruction image quality using the Uro Dyna-CT. World J Urol 31(5):1291–1295PubMedCrossRefGoogle Scholar
  21. 21.
    Bai M, Liu B, Mu H, Liu X, Jiang Y (2012) The comparison of radiation dose between C-arm flat-detector CT (DynaCT) and multi-slice CT (MSCT): a phantom study. Eur J Radiol 81(11):3577–3580. http://www.ncbi.nlm.nih.gov/pubmed/21963617 PubMedCrossRefGoogle Scholar
  22. 22.
    Kenngott HG, Wegner I, Neuhaus J, Nickel F, Fischer L, Gehrig T, Meinzer HP, Müller-Stich BP (2013) Magnetic tracking in the operation room using the da Vinci® telemanipulator is feasible. J Robot Surg 7(1):59–64PubMedCentralPubMedCrossRefGoogle Scholar
  23. 23.
    Kenngott HG, Neuhaus J, Müller-Stich BP, Wolf I, Vetter M, Meinzer HP, Köninger J, Büchler MW, Gutt CN (2008) Development of a navigation system for minimally invasive esophagectomy. Surg Endosc 22(8):1858–1865PubMedCrossRefGoogle Scholar
  24. 24.
    Koelblinger C, Schima W, Berger-Kulemann V, Wolf F, Plank C, Weber M, Lammer J (2013) C-arm CT during hepatic arteriography tumour-to-liver contrast: intraindividual comparison of three different contrast media application protocols. Eur Radiol 23(4):938–942PubMedCrossRefGoogle Scholar
  25. 25.
    Worm ES, Høyer M, Fledelius W, Nielsen JE, Larsen LP, Poulsen PR (2012) On-line use of three-dimensional marker trajectory estimation from cone-beam computed tomography projections for precise setup in radiotherapy for targets with respiratory motion. Int J Radiat Oncol Biol Phys 83(1):e145–e151PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Hannes G. Kenngott
    • 1
    Email author
  • Martin Wagner
    • 1
  • Matthias Gondan
    • 2
  • Felix Nickel
    • 1
  • Marco Nolden
    • 3
  • Andreas Fetzer
    • 3
  • Jürgen Weitz
    • 1
  • Lars Fischer
    • 1
  • Stefanie Speidel
    • 4
  • Hans-Peter Meinzer
    • 3
  • Dittmar Böckler
    • 5
  • Markus W. Büchler
    • 1
  • Beat P. Müller-Stich
    • 1
  1. 1.Department of SurgeryUniversity of HeidelbergHeidelbergGermany
  2. 2.Institute of Medical Biometry and InformaticsUniversity of HeidelbergHeidelbergGermany
  3. 3.Division of Medical and Biological InformaticsGerman Cancer Research CentreHeidelbergGermany
  4. 4.Institute for Anthropomatics IFAKarlsruhe Institute of Technology KITKarlsruheGermany
  5. 5.Department of Vascular and Endovascular SurgeryUniversity of HeidelbergHeidelbergGermany

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