Skip to main content
SpringerLink
Log in

Improving Endovascular Intraoperative Navigation with Real-Time Skeleton-Based Deformation of Virtual Vascular Structures

  • Conference paper
  • First Online:
Augmented Reality, Virtual Reality, and Computer Graphics (AVR 2016)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9769))

Abstract

Endovascular surgery requires acquisition of intraoperative X-ray images, exposing patient and surgical staff to a considerable dose of radiations. This disadvantage, and the difficulty in using bidimensional projective images, motivates the integration of endovascular navigators in the clinical practice. This paper presents a real-time vascular deformation system to enhance the standard static virtual environment usually used in endovascular navigation. Our approach is based on a skeleton representation of the virtual vessel, linked to the 3D vascular structure via vertex color masks applied on the target vascular branches. This method allows the usage of multiple partial skeletons, each with its own deformation function and linking strategy; so, we can model different kind of deformations due to several factors (e.g., heartbeat, breathing etc.). The system has been tested modeling the deformation of renal arteries due to patient breathing: showing a good visual realism, and ensuring the necessary updating frequency for real-time simulation.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Abi-Jaoudeh, N., Glossop, N., Dake, M., Pritchard, W.F., Chiesa, A., Dreher, M.R., Tang, T., Karanian, J.W., Wood, B.J.: Electromagnetic navigation for thoracic aortic stent-graft deployment: a pilot study in swine. J. Vasc. Interv. Radiol. 21(6), 888–895 (2010)

    Article  Google Scholar 

  2. Andersson, T., Söderman, M., Ruijters, D., Babic, D., Homan, R., Mielekamp, P.: 3D-multimodality roadmapping in interventional neuroradiology. MedicaMundi 53(2), 58–62 (2009)

    Google Scholar 

  3. Bartels, L.W., Bakker, C.J.G.: Endovascular interventional magnetic resonance imaging. Phys. Med. Biol. 48(14), R37–R64 (2003)

    Article  Google Scholar 

  4. Bock, M., Wacker, F.K.: MR-guided intravascular interventions: techniques and applications. J. Magn. Reson. Imaging 27(2), 326–338 (2008)

    Article  Google Scholar 

  5. Condino, S., Calabrò, E.M., Alberti, A., Parrini, S., Cioni, R., Berchiolli, R., Gesi, M., Ferrari, V., Ferrari, M.: Simultaneous tracking of catheters and guidewires: comparison to standard fluoroscopic guidance for arterial cannulation. Eur. J. Vasc. Endovasc. Surg. 47(1), 53–60 (2014)

    Article  Google Scholar 

  6. Condino, S., Ferrari, V., Freschi, C., Alberti, A., Berchiolli, R., Mosca, F., Ferrari, M.: Electromagnetic navigation platform for endovascular surgery: how to develop sensorized catheters and guidewires. Int. J. Med. Robot. Comput. Assist. Surg. 8(3), 300–310 (2012)

    Article  Google Scholar 

  7. Cornea, N.D., Silver, D., Yuan, X., Balasubramanian, R.: Computing hierarchical curve-skeletons of 3D objects. Vis. Comput. 21, 945–955 (2005)

    Article  Google Scholar 

  8. Draney, M.T., Zarins, C.K., Taylor, C.A.: Three-dimensional analysis of renal artery bending motion during respiration. J. Endovas. Ther. 12(3), 380–386 (2005)

    Article  Google Scholar 

  9. Ferrari, V., Cappelli, C., Megali, G., Pietrabissa, A.: An anatomy driven approach for generation of 3D models from multi-phase CT images. Int. J. Comput. Assist. Radiol. Surg. 3(1), S271–S273 (2008)

    Google Scholar 

  10. Ferrari, V., Carbone, M., Cappelli, C., Boni, L., Melfi, F., Ferrari, M., Mosca, F., Pietrabissa, A.: Value of multidetector computed tomography image segmentation for preoperative planning in general surgery. Surg. Endosc. 26(3), 616–626 (2012)

    Article  Google Scholar 

  11. King, A.P., Boubertakh, R., Rhode, K.S., Ma, Y.L., Chinchapatnam, P., Gao, G., Tangcharoen, T., Ginks, M.R., Cooklin, M., Gill, J.S., Hawkes, D.J., Razavi, R.S., Schaeffter, T.: A subject-specific technique for respiratory motion correction in image-guided cardiac catheterisation procedures. Med. Image Anal. 13(3), 419–431 (2009)

    Article  Google Scholar 

  12. Lujan, A.E., Larsen, E.W., Balter, J.M., Ten Haken, R.K.: A method for incorporating organ motion due to breathing into 3D dose calculations. Med. Phys. 26(5), 715–720 (1999)

    Article  Google Scholar 

  13. Parrini, S., Zhang, L., Condino, S., Ferrari, V., Caramella, D., Ferrari, M.: Automatic carotid centerline extraction from three-dimensional ultrasound doppler images. In: 36th Annual International Conference of the IEEE on Engineering in Medicine and Biology Society (EMBC 2014), pp. 5089–5092 (2014)

    Google Scholar 

  14. Pujol, S., Frerichs, K., Norbash, A., Kikinis, R., Westin, C.F.: Preliminary results of nonfluoroscopy-based 3D navigation for neurointerventional procedures. J. Vasc. Interv. Radiol. 18(2), 289–298 (2007)

    Article  Google Scholar 

  15. Pujol, S., Pecher, M., Magne, J.L., Cinquin, P.: A virtual reality based navigation system for endovascular surgery. Stud. Health Technol. Inform. 98, 310–312 (2004)

    Google Scholar 

  16. Saikus, C.E., Lederman, R.J.: Interventional cardiovascular magnetic resonance imaging: a new opportunity for image-guided interventions. JACC: Cardiovas. Imaging 2(11), 1321–1331 (2009)

    Google Scholar 

  17. Sidhu, R., Weir-McCall, J., Cochennec, F., Riga, C., DiMarco, A.N., Bicknell, C.D.: Evaluation of an electromagnetic 3D navigation system to facilitate endovascular tasks: a feasibility study. Eur. J. Vasc. Endovasc. Surg. 43(1), 22–29 (2012)

    Article  Google Scholar 

  18. Solomon, S.B., Dickfeld, T., Calkins, H.: Real-time cardiac catheter navigation on three-dimensional CT images. J. Interv. Cardiac Electrophysiol. 8, 27–36 (2003)

    Article  Google Scholar 

  19. Takemura, A., Suzuki, M., Sakamoto, K., Kitada, T., Iida, H., Okumura, Y., Harauchi, H.: Analysis of respiration-related movement of upper abdominal arteries: preliminary measurement for the development of a respiratory motion compensation technique of roadmap navigation. Radiolog. Phys. Technol. 1, 178–182 (2008)

    Article  Google Scholar 

  20. Yushkevich, P.A., Piven, J., Hazlett, H.C., Smith, R.G., Ho, S., Gee, J.C., Gerig, G.: User-guided 3D active contour segmentation of anatomical structures: significantly improved efficiency and reliability. NeuroImage 31(3), 1116–1128 (2006)

    Article  Google Scholar 

  21. Zhang, L., Parrini, S., Freschi, C., Ferrari, V., Condino, S., Ferrari, M., Caramella, D.: 3D ultrasound centerline tracking of abdominal vessels for endovascular navigation. Int. J. Comput. Assist. Radiol. Surg. 9(1), 127–135 (2014)

    Article  Google Scholar 

Download references

Acknowledgments

The research leading to these results has been partially supported by the scientific project LASER (electromagnetic guided in-situ laser fenestration of endovascular endoprosthesis, November 2014–November 2017) funded by the Italian Ministry of Health and Regione Toscana through the call “Ricerca Finalizzata 2011–2012”.

Author information

Authors and Affiliations

  1. Computer Science Department, Kettering University, Flint, MI, USA

    Giuseppe Turini

  2. Department of Translational Research on New Technologies in Medicine and Surgery, EndoCAS Center, University of Pisa, Pisa, Italy

    Giuseppe Turini, Sara Condino, Matteo Postorino, Vincenzo Ferrari & Mauro Ferrari

  3. Information Engineering Department, University of Pisa, Pisa, Italy

    Vincenzo Ferrari

Authors
  1. Giuseppe Turini
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sara Condino
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Matteo Postorino
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Vincenzo Ferrari
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Mauro Ferrari
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Giuseppe Turini .

Editor information

Editors and Affiliations

  1. University of Salento, Lecce, Italy

    Lucio Tommaso De Paolis

  2. University of Salento, Lecce, Italy

    Antonio Mongelli

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Turini, G., Condino, S., Postorino, M., Ferrari, V., Ferrari, M. (2016). Improving Endovascular Intraoperative Navigation with Real-Time Skeleton-Based Deformation of Virtual Vascular Structures. In: De Paolis, L., Mongelli, A. (eds) Augmented Reality, Virtual Reality, and Computer Graphics. AVR 2016. Lecture Notes in Computer Science(), vol 9769. Springer, Cham. https://doi.org/10.1007/978-3-319-40651-0_7

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-40651-0_7

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-40650-3

  • Online ISBN: 978-3-319-40651-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation