Skip to main content
SpringerLink
Log in

Soft tissue navigation for laparoscopic partial nephrectomy

  • Original Article
  • Published:
International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

Abstract

Purpose

Minimally invasive surgery of kidney cancer has become a standard therapy method for renal carcinomas. Due to improvements in diagnosis, carcinomas tend to be detected with a smaller size, which often allows for a tissue sparing, laparoscopic partial nephrectomy (LPN). Successful LPN requires a safe resection line inside the kidney, which spares most of healthy tissue, while assuring the complete tumor removal. This paper proposes an approach for a real-time visualization aid during LPN.

Methods

A surgical soft tissue navigation system for laparoscopic was designed, implemented and tested in vitro. The system enhances the surgeon’s perception to provide decision guidance directly before initiation of kidney resection. Preoperative planning, intraoperative imaging, and real-time image processing are incorporated in a system that can enhance an endoscope’s image by superimposing relevant medical information like tumor infiltrated tissue and risk structures. This system has a flexible design to facilitate its integration into surgical work flows. The system evaluation was divided into two parts: (1) a virtual evaluation environment, which allows for simulation of all involved system parameters; (2) in vitro surgeries were performed using a laparoscopic training unit to evaluate the overall robustness and accuracy of the navigation system with real data.

Results

The system was implemented and tested in vitro with favorable results. Real-time video recording of its operation was done to demonstrate the ability to simultaneously visualize the renal collecting system, major blood vessels, and abnormal lesion.

Conclusion

Laparoscopic partial nephrectomy can benefit from surgical computer assistance with preoperative planning, intraoperative imaging, and real time guidance integrated in a single system. The presented surgical navigation approach is suitable for testing in an intraoperative environment with human patients undergoing LPN.

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. Gesellschaft der epidemiologischen Krebsregister in Deutschland e. V., Krebs in Deutschland, Technical report, Robert-Koch-Institut (2006)

  2. Jayson M, Sanders H (1998) Increased incidence of serendipitously discovered renal cell carcinoma. Urology 51(2): 203–205

    Article  PubMed  CAS  Google Scholar 

  3. Williams SC, de la Rosette J, Landman J, Keeley F (2007) Cryoablation of small renal tumors. Eur Urol 5: 206–218

    Google Scholar 

  4. Thompson RH, Boorjian SA, Lohse CM, Leibovich BC, Kwon ED, Cheville JC, Blute ML (2007) Radical nephrectomy for pt1a renal masses may be associated with decreased overall survival compared with partial nephrectomy. J Urol 179: 468–473

    Article  Google Scholar 

  5. Janetschek G (2008) Editorial comment on: laparoscopic partial nephrectomy: the new standard of care?. Eur Urol 53(4): 742– 743

    Article  Google Scholar 

  6. Turna B, Aron M, Gill IS (2008) Expanding indications for laparoscopic partial nephrectomy. Urology

  7. Baumhauer M, Feuerstein M, Meinzer H-P, Rassweiler J (2008) Navigation in endoscopic soft tissue surgery: perspectives and limitations. J Endourol 22(4): 751–766

    Article  PubMed  Google Scholar 

  8. Shah RB, Bakshi N, Hafez KS, Wood DP, Kunju LP (2005) Image-guided biopsy in the evaluation of renal mass lesions in contemporary urological practice: indications, adequacy, clinical impact, and limitations of the pathological diagnosis. Hum Pathol 36(12): 1309–1315

    PubMed  Google Scholar 

  9. Somani BK, Nabi G, Thorpe P, N’Dow J, Swami S, McClinton S, Academic A, Group CUSA (2007) Image-guided biopsy-diagnosed renal cell carcinoma: critical appraisal of technique and long-term follow-up. Eur Urol 51(5):1289–1295; discussion 1296– 1297

    Google Scholar 

  10. Marescaux J, Rubino F, Arenas M, Mutter D, Soler L (2004) Augmented-reality-assisted laparoscopic adrenalectomy. JAMA 292(18): 2214–2215

    Article  PubMed  CAS  Google Scholar 

  11. Feuerstein M, Mussack T, Heining SM, Navab N (2008) Intra-operative laparoscope augmentation for port placement and resection planning in minimally invasive liver resection. IEEE Trans Med Imaging (to appear)

  12. Peters TM (2006) Image-guidance for surgical procedures. Phys Med Biol 51(14): R505–R540

    Article  PubMed  Google Scholar 

  13. Leroy A, Mozer P, Payan Y, Troccaz J (2007) Intensity-based registration of freehand 3d ultrasound and ct-scan images of the kidney. Int J Comput Assist Radiol Surg 2: 31–41

    Article  Google Scholar 

  14. Dillenseger J-L, Guillaume H, Patard J-J (2006) Spherical harmonics based intrasubject 3-d kidney modeling/registration technique applied on partial information. IEEE Trans Biomed Eng 53: 2185–2193

    Article  PubMed  Google Scholar 

  15. Boettger T, Kunert T, Meinzer HP, Wolf I (2007) Application of a new segmentation tool based on interactive simplex meshes to cardiac images and pulmonary mri data. Acad Radiol 14(3): 319–329

    Article  Google Scholar 

  16. Benincasa AB, Galloway RL, Miga MI (2006) Feasibility study for image guided kidney surgery: assessment of required intraoperative surface for accurate physical to image space registrations, Master’s thesis, Vanderbilt University

  17. Welch G, Foxlin E (2002) Motion tracking: no silver bullet, but a respectable arsenal. IEEE Comput Graph Appl 22(6): 24–38

    Article  Google Scholar 

  18. Hartley R, Zisserman A (2003) Multiple View Geometry in Computer Vision, Cambridge University Press, 2000

  19. Canny J (1986) A computational approach to edge detection. IEEE Trans Pattern Anal Mach Intell (PAMI) 8: 679–698

    Article  Google Scholar 

  20. Yuen H, Princen J, Illingworth J (1990) Comparative study of hough transform methods for circle finding. Image Vis Comput 8: 71–77

    Article  Google Scholar 

  21. Rosenhahn B (2003) Pose estimation revisited, PhD thesis, Christian-Albrechts-UniversitSt Kiel

  22. Lu C-P, Hager GD, Mjolsness E (2000) Fast and globally convergent pose estimation from video images. IEEE Trans Pattern Anal Mach Intell (PAMI) 22: 610–622

    Article  Google Scholar 

  23. Stefansic JD, Herline AJ, Shyr Y, Chapman WC, Fitzpatrick JM, Dawant BM, Galloway RL (2000) Registration of physical space to laparoscopic image space for use in minimally invasive hepatic surgery. IEEE Trans Med Imaging 19(10): 1012–1023

    Article  PubMed  CAS  Google Scholar 

  24. Koppel D, Wang Y, Lee H (2004) Image-based rendering and modeling in video-endoscopy. In: IEEE international symposium on biomedical imaging: Nano to Macro

  25. Sauvee M, Poignet P, Triboulet J, Dombre E, Malis E, Demaria R (2006) 3D heart motion estimation using endoscopic monocular vision system. In: Sixth IFAC symposium on modeling and control in biomedical systems

  26. DeMenthon D, Davis L (1995) Model-based object pose in 25 lines of code. Int J Comput Vis 15: 123–141

    Article  Google Scholar 

  27. Lowe D (1991) Fitting parameterized three-dimensional models to images. IEEE Trans Pattern Anal Mach Intell (PAMI) 13(5): 441–450

    Article  Google Scholar 

  28. Araujo H, Carceroni R, Brown C (1998) A fully projective formulation to improve the accuracy of lowe’s pose-estimation algorithm. Comp Vis Image Underst 70(2): 227–238

    Article  Google Scholar 

  29. Baumhauer M, Simpfendoerfer T, Wolf I, Meinzer H-P (2007) Soft tissue navigation for laparoscopic prostatectomy: Evaluation of camera pose estimation for enhanced visualization. In: SPIE medical imaging

  30. Wolf I, Vetter M, Meinzer H-P (2005) The medical imaging interaction toolkit. Med Image Anal 9(6): 594–604

    Article  PubMed  Google Scholar 

  31. http://www.dkfz-heidelberg.de/de/mbi/videos/In-Vitro-Trials-DKFZ-Navigate d-Heminephrectomy.mpg

Download references

Author information

Authors and Affiliations

  1. German Cancer Research Center, Div. Medical and Biological Informatics, INF 280, 69120, Heidelberg, Germany

    M. Baumhauer, T. Simpfendörfer, H. -P. Meinzer & I. Wolf

  2. Department of General, Abdominal and Transplant Surgery, Ruprecht-Karls-University, INF 110, 69120, Heidelberg, Germany

    B. P. Müller-Stich & C. N. Gutt

  3. Department of Urology, Clinic Heilbronn, University of Heidelberg, 74078, Heilbronn, Germany

    D. Teber & J. Rassweiler

Authors
  1. M. Baumhauer
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. T. Simpfendörfer
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. B. P. Müller-Stich
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. D. Teber
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. C. N. Gutt
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. J. Rassweiler
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. H. -P. Meinzer
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. I. Wolf
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to M. Baumhauer or I. Wolf.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Baumhauer, M., Simpfendörfer, T., Müller-Stich, B.P. et al. Soft tissue navigation for laparoscopic partial nephrectomy. Int J CARS 3, 307–314 (2008). https://doi.org/10.1007/s11548-008-0216-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11548-008-0216-7

Keywords

Search

Navigation