Towards Interactive Planning of Coil Embolization in Brain Aneurysms

  • Jeremie Dequidt
  • Christian Duriez
  • Stephane Cotin
  • Erwan Kerrien
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5761)


Many vascular pathologies can now be treated in a minimally invasive way thanks to interventional radiology. Instead of open surgery, it allows to reach the lesion of the arteries with therapeutic devices through a catheter. As a particular case, intracranial aneurysms are treated by filling the localized widening of the artery with a set of coils to prevent a rupture due to the weakened arterial wall. Considering the location of the lesion, close to the brain, and its very small size, the procedure requires a combination of careful planning and excellent technical skills. An interactive and reliable simulation, adapted to the patient anatomy, would be an interesting tool for helping the interventional neuroradiologist plan and rehearse a coil embolization procedure. This paper describes an original method to perform interactive simulations of coil embolization and proposes a clinical metric to quantitatively measure how the first coil fills the aneurysm. The simulation relies on an accurate reconstruction of the aneurysm anatomy and a real-time model of the coil for which sliding and friction contacts are taken into account. Simulation results are compared to real embolization procedure and exhibit good adequacy.


Contact Force Beam Element Intracranial Aneurysm Detachable Coil Aneurysm Wall 
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.


  1. 1.
    Singha, V., Gressa, D., Higashidab, R., Dowdb, C., Halbachb, V., Johnston, S.: The learning curve for coil embolization of unruptured intracranial aneurysms. American Journal of Neuroradiology 23, 768–771 (2002)Google Scholar
  2. 2.
    Satoh, K., Ito, Y., Abe, H.: Measurement of volume ratio to predict coil compaction, on aneurysmal embolization. Interventional Radiology 1(4), 179–182 (1998)Google Scholar
  3. 3.
    Li, Z., Chui, C.-K., Cai, Y., Anderson, J.H., Nowinski, W.L.: Interactive catheter shape modeling in interventional radiology simulation. In: Niessen, W.J., Viergever, M.A. (eds.) MICCAI 2001. LNCS, vol. 2208, p. 457. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  4. 4.
    Hoefer, U., Langen, T., Nziki, J., Zeitler, F., Hesser, J., Mueller, U., Voelker, W., Maenner, R.: Cathi - catheter instruction system. In: Computer Assisted Radiology and Surgery (CARS), Paris, France, pp. 101–106 (2002)Google Scholar
  5. 5.
    Alderliesten, T.: Simulation of Minimally-Invasive Vascular Interventions for Training Purposes. PhD dissertation, Utrecht University (2004)Google Scholar
  6. 6.
    Cotin, S., Duriez, C., Lenoir, J., Neumann, P., Dawson, S.: New approaches to catheter navigation for interventional radiology simulation. In: Duncan, J.S., Gerig, G. (eds.) MICCAI 2005. LNCS, vol. 3750, pp. 534–542. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  7. 7.
    Dequidt, J., Lenoir, J., Cotin, S.: Interactive contacts resolution using smooth surface representation. In: Ayache, N., Ourselin, S., Maeder, A. (eds.) MICCAI 2007, Part II. LNCS, vol. 4792, pp. 850–857. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  8. 8.
    Laroche, D., Delorme, S., Anderson, T., Diraddo, R.: In-vivo validation of a stent implantation numerical model. In: Proc. Medicine Meets Virtual Reality Conference, Studies in Health Technology and Informatics., vol. 125, pp. 265–270 (2007)Google Scholar
  9. 9.
    Anxionnat, R., Bracard, S., Ducrocq, X., Trousset, Y., Launay, L., Kerrien, E.: Intracranial aneurysms: Clinical value of 3d digital subtraction Angiography in the Therapeutic Decision and Endovascular Treatment. Radiology (2001)Google Scholar
  10. 10.
    Lorensen, W., Cline, H.: Marching cubes: A high resolution 3d surface construction algorithm. In: Computer Graphics Proceedings, SIGGRAPH, vol. 21, pp. 163–169 (1987)Google Scholar
  11. 11.
    Lachaud, J.O., Montanvert, A.: Deformable meshes with automated topology changes for coarse-to-fine 3D surface extraction. Medical Image Analysis 3(2), 187–207 (1999)CrossRefGoogle Scholar
  12. 12.
    Dequidt, J., Marchal, M., Duriez, C., Kerrien, E., Cotin, S.: Interactive simulation of embolization coils: Modeling and experimental validation. In: Proceedings of MICCAI (2008)Google Scholar
  13. 13.
    Cloft, H.J., Joseph, G.J., Tong, F.C., Goldstein, J.H., Dion, J.E.: Use of three-dimensional guglielmi detachable coils in the treatment of wide-necked cerebral aneurysms. American Journal of Neuroradiology (1999)Google Scholar
  14. 14.
    Pauly, M., Pai, D., Leonidas, G.: Quasi-rigid objects in contact. In: Proceedings of ACM SIGGRAPH Symposium on Computer Animation, pp. 109–119 (2004)Google Scholar
  15. 15.
    Jourdan, F., Alart, P., Jean, M.: A gauss-seidel like algorithm to solve frictional contact problems. Comp. Meth. In: Appl. Mech. and Engin, 33–47 (1998)Google Scholar
  16. 16.
    Cloft, H.J., Joseph, G.J., Tong, F.C., Goldstein, J.H., Dion, J.E.: Use of three-dimensional guglielmi detachable coils in the treatment of wide-necked cerebral aneurysms. American Journal of NeuroRadiology, 1312–1314 (2000)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Jeremie Dequidt
    • 1
  • Christian Duriez
    • 1
  • Stephane Cotin
    • 1
  • Erwan Kerrien
    • 2
  1. 1.INRIA Lille Nord Europe - Alcove TeamVilleneuve d’AscqFrance
  2. 2.INRIA Nancy Grand Est - Magrit TeamVandoeuvre-lès-NancyFrance

Personalised recommendations